There is evidence about the international competitiveness of Small and Medium Enterprises having a close relationship with their absorptive capacity and internationalization networking, and for that reason, it is relevant to find out the main trends in this field of knowledge. The objective of this study is to provide a bibliometric analysis of the status of the existing research in the field to recognize main topics and help identify research gaps. This study was done through a review of 1,710 documents (...) published about this relationship from the Scopus and Web of Science databases, using as processing software application that employs two combinations of terms associated with Boolean operators. This was taken into account in order to optimize the accuracy of the search and to facilitate large data capture. The results show that these studies are in a period of high production and concentrated in a few countries and researchers’ networks in the United States, the People’s Republic of China, and some European countries. Moreover, the trend words used by researchers are those which link absorptive capacity with networking, open innovation, and firm performance. (shrink)

In this paper, we study the existence and uniqueness of solutions to implicit the coupled fractional differential system with the Katugampola–Caputo fractional derivative. Different fixed-point theorems are used to acquire the required results. Moreover, we derive some sufficient conditions to guarantee that the solutions to our considered system are Hyers–Ulam stable. We also provided an example that explains our results.

In this paper, the dynamics of Cournot duopoly game with a generalized bounded rationality is considered. The fractional bounded rationality of the Cournot duopoly game is introduced. The conditions of local stability analysis of equilibrium points of the game are derived. The effect of fractional marginal profit on the game is investigated. The complex dynamics behaviors of the game are discussed by numerical computation when parameters are varied.

The W/S test under neutrosophic statistics is proposed in this paper. The Monte Carlo simulation under the neutrosophic statistical interval method is proposed and applied to study the sensitivity of various neutrosophic statistical distributions. The power of test curves for neutrosophic distributions is presented. The efficiency of the proposed W/S test under neutrosophic statistics is compared with that of the W/S test under classical statistics. The proposed test is explained with the aid of an example.

The close relationship between collateral value and bank stability has led to a considerable need to a rapid and economical appraisal of real estate. The greater availability of information related to housing stock has prompted to the use of so-called big data and machine learning in the estimation of property prices. Although this methodology has already been applied to the real estate market to identify which variables influence dwelling prices, its use for estimating the price of properties is not so (...) frequent. The application of this methodology has become more sophisticated over time, from applying simple methods to using the so-called ensemble methods and, while the estimation capacity has improved, it has only been applied to specific geographical areas. The main contribution of this article lies in developing an application for the entire Spanish market that fully automatically provides the best model for each municipality. Real estate property prices in 433 municipalities are estimated from a sample of 790,631 dwellings, using different ensemble methods based on decision trees such as bagging, boosting, and random forest. The results for estimating the price of dwellings show a good performance of the techniques developed, in terms of the error measures, with the best results being achieved using the techniques of bagging and random forest. (shrink)

Many optimisation-based intrusion detection algorithms have been developed and are widely used for intrusion identification. This condition is attributed to the increasing number of audit data features and the decreasing performance of human-based smart intrusion detection systems regarding classification accuracy, false alarm rate, and classification time. Feature selection and classifier parameter tuning are important factors that affect the performance of any intrusion detection system. In this paper, an improved intrusion detection algorithm for multiclass classification was presented and discussed in detail. (...) The proposed method combined the improved teaching-learning-based optimisation algorithm, improved parallel JAYA algorithm, and support vector machine. ITLBO with supervised machine learning technique was used for feature subset selection. The selection of the least number of features without causing an effect on the result accuracy in FSS is a multiobjective optimisation problem. This work proposes ITLBO as an FSS mechanism, and its algorithm-specific, parameterless concept was explored. IPJAYA in this study was used to update the C and gamma parameters of the support vector machine. Several experiments were performed on the prominent intrusion ML dataset, where significant enhancements were observed with the suggested ITLBO-IPJAYA-SVM algorithm compared with the classical TLBO and JAYA algorithms. (shrink)

The research focuses on a sample of 26 Italian real estate asset management companies —whose asset management is totally linked to real estate funds—that considers a period of six years. Using some variables extrapolated from the internal accountability of each SGR, the analysis investigates possible relationships between them to verify the presence or absence of economies of scale of Italian real estate management companies by multivariate regressions. The results show that there is no single model for profit maximization and cost (...) minimization, but all depends on the business model that each SGR decides to adopt. (shrink)

Medical image segmentation is a key technology for image guidance. Therefore, the advantages and disadvantages of image segmentation play an important role in image-guided surgery. Traditional machine learning methods have achieved certain beneficial effects in medical image segmentation, but they have problems such as low classification accuracy and poor robustness. Deep learning theory has good generalizability and feature extraction ability, which provides a new idea for solving medical image segmentation problems. However, deep learning has problems in terms of its application (...) to medical image segmentation: one is that the deep learning network structure cannot be constructed according to medical image characteristics; the other is that the generalizability y of the deep learning model is weak. To address these issues, this paper first adapts a neural network to medical image features by adding cross-layer connections to a traditional convolutional neural network. In addition, an optimized convolutional neural network model is established. The optimized convolutional neural network model can segment medical images using the features of two scales simultaneously. At the same time, to solve the generalizability problem of the deep learning model, an adaptive distribution function is designed according to the position of the hidden layer, and then the activation probability of each layer of neurons is set. This enhances the generalizability of the dropout model, and an adaptive dropout model is proposed. This model better addresses the problem of the weak generalizability of deep learning models. Based on the above ideas, this paper proposes a medical image segmentation algorithm based on an optimized convolutional neural network with adaptive dropout depth calculation. An ultrasonic tomographic image and lumbar CT medical image were separately segmented by the method of this paper. The experimental results show that not only are the segmentation effects of the proposed method improved compared with those of the traditional machine learning and other deep learning methods but also the method has a high adaptive segmentation ability for various medical images. The research work in this paper provides a new perspective for research on medical image segmentation. (shrink)

A new test of independence under neutrosophic statistics for testing the association between two criteria of classification is presented in this paper. The necessary contingency tables for the neutrosophic population and the neutrosophic sample are presented. The test statistic of the proposed test is introduced under neutrosophic statistics. A real example from education is selected to explain the proposed test. From the real example, it is concluded that the proposed test of independence is more informative, flexible, and suitable to be (...) applied under uncertainty as compared to the existing test under classical statistics. (shrink)

Degradations frequently occur in archive films that symbolize the historical and cultural heritage of a nation. In this study, the problem of detection blotches commonly encountered in archive films is handled. Here, a block-based blotch detection method is proposed based on a visual saliency map. The visual saliency map reveals prominent areas in an input frame and thus enables more accurate results in the blotch detection. A simple and effective visual saliency map method is taken into consideration in order to (...) reduce computational complexity for the detection phase. After the visual saliency maps of the given frames are obtained, blotch regions are estimated by considered spatiotemporal patches—without the requirement for motion estimation—around the saliency pixels, which are subjected to a prethresholding process. Experimental results show that the proposed block-based blotch detection method provides a significant advantage with reducing false alarm rates over HOG feature, LBP feature, and regions-matching methods presented in recent years. (shrink)

This study aims to stabilize the unwanted fluctuation of buildings as mechanical structures subjected to earth excitation as the noise. In this study, the ground motion is considered as a Wiener process, in which the governing stochastic differential equations have been presented in the form of Ito equation. To stabilize the vibration of the system, the ATMD system is considered and located on the upmost story of the building. A sliding mode controller has been utilized to control the ATMD system, (...) which is a robust controller in the presence of uncertainty. For this purpose, the design of a sliding mode controller for the general dynamic system with Lipschitz nonlinearity and considering the Ito relations has been accomplished. The mentioned design has been implemented considering the presence of the Weiner process and existence of uncertainty in the structure and actuator. Then, the obtained general control law has been generalized to control the ATMD system. The results show that the designed controller is effective to reduce the effect of the unwanted impused vibrations on the building. (shrink)

Industrial robots have a great impact on increasing the productivity and reducing the time of the manufacturing process. To serve this purpose, in the past decade, many researchers have concentrated to optimize robotic models utilizing artificial intelligence techniques. Gimbal joints because of their adjustable mechanical advantages have been investigated as a replacement for traditional revolute joints, especially when they are supposed to have tiny motions. In this research, the genetic algorithm, a well-known evolutionary technique, has been adopted to find optimal (...) parameters of the gimbal joints. Since adopting the GA is a time-consuming process, an artificial neural network architecture has been proposed to model the behavior of the GA. The result shows that the proposed ANN model can be used instead of the complex and time-consuming GA in the process of finding the optimal parameters of the gimbal joint. (shrink)

Our purpose is to present the notions of a β-Λ-set and a β-V-sets in topological space. We discuss the basic properties of β-Λ-sets and β-V-sets. Also, the achievement of the topology defined by these families of sets is obtained. Finally, these results are applied to the case of X,τ which is the digital n-space Zn,Kn.

Hydraulic drive mode enables legged robots to have excellent characteristics, such as greater power-to-weight ratios, higher load capacities, and faster response speeds than other robots. Nowadays, highly integrated valve-controlled cylinder, called the hydraulic drive unit, is employed to drive the joints of these robots. However, there are some common problems in the HDU resulted from hydraulic systems, such as strong nonlinearity, asymmetry dynamic characteristics between positive and negative moving directions of the piston rod, and time-varying parameters. It is difficult to (...) obtain the desired control performance by just using classical control methods such as the traditional PID control. In this paper, a position controller that combines fuzzy terminal sliding mode control and time delay estimation is proposed, in which FTSMC adopts a compound reaching law which combines the tangent function and the exponential reaching law. Moreover, the fuzzy control is introduced to adjust the parameters of the reaching law in real time to improve the adaptability of FTSMC. Based on FTSMC, the external uncertain disturbance of the HDU position control system is estimated by TDE, which ensures the simplicity of system modeling and the normal application of FTSMC. Finally, the control effects of the controller combining FTSMC and TDE are verified on the HDU performance test platform and the load simulation experiment platform. The experimental results show that the proposed controller greatly improves the system position control performance and has a strong disturbance rejection ability and a good adaptability under different working conditions. The above research results can provide an important reference and experimental basis for the inner loop of compliance control of legged robots. (shrink)

The analysis of network robustness tackles the problem of studying how a complex network behaves under adverse scenarios, such as failures or attacks. In particular, the analysis of interdependent networks’ robustness focuses on the specific case of the robustness of interacting networks and their emerging behaviors. This survey systematically reviews literature of frameworks that analyze the robustness of interdependent networks published between 2005 and 2017. This review shows that there exists a broad range of interdependent network models, robustness metrics, and (...) studies that can be used to understand the behaviour of different systems under failure or attack. Regarding models, we found that there is a focus on systems where a node in one layer interacts with exactly one node at another layer. In studies, we observed a focus on the network percolation. While among the metrics, we observed a focus on measures that count network elements. Finally, for the networks used to test the frameworks, we found that the focus was on synthetic models, rather than analysis of real network systems. This review suggests opportunities in network research, such as the study of robustness on interdependent networks with multiple interactions and/or spatially embedded networks, and the use of interdependent network models in realistic network scenarios. (shrink)

Control of unsafe behaviors has always been a difficult point in Coal Mine Safety Management. To study the regular pattern of behavior propagations in CMSM, a series of evolutionary dynamical system models are established by the delay and impulsive differential equations. The threshold constraints and impulse responses in the models can accurately correspond to the actual inspection and supervision measures in safety management. Through the simulation analysis and comparison of the system stability, it can be concluded that some proper settings (...) of the TCs and impulse responses bring satisfactory evolutionary stability. Based on the main results of this study, we put forward some decision-making suggestions on the control points and control strategies of unsafe behaviors in safety management. (shrink)

Constrained clustering is intended to improve accuracy and personalization based on the constraints expressed by an Oracle. In this paper, a new constrained clustering algorithm is proposed and some of the informative data pairs are selected during an iterative process. Then, they are presented to the Oracle and their relation is answered with “Must-link or Cannot-link.” In each iteration, first, the support vector machine is utilized based on the label produced by the current clustering. According to the distance of each (...) document from the hyperplane, the distance matrix is created. Also, based on cosine similarity of word2vector of each document, the similarity matrix is created. Two types of probability are calculated and they are smoothed for belonging to neighborhoods. Neighborhoods form the samples that are labeled by Oracle, to be in the same cluster. Finally, at the end of each iteration, the data with a greater level of uncertainty is selected for questioning the oracle. In order to evaluate, the proposed method is compared with famous state-of-the-art methods based on two criteria and over a standard dataset. The result demonstrates an increased accuracy and stability of the obtained result with fewer questions. (shrink)

In this article, some new nonlinear fractional partial differential equations -dimensional breaking soliton equations; and the space-time fractional order SRLW equation) have been considered, in which the treatment of these equations in the diverse applications are described. Also, the fractional derivatives in the sense of β-derivative are defined. Some fractional PDEs will convert to consider ordinary differential equations with the help of transformation β-derivative. These equations are analyzed utilizing an integration scheme, namely, the rational exp−Ωη-expansion method. Different kinds of traveling (...) wave solutions such as solitary, topological, dark soliton, periodic, kink, and rational are obtained as a by product of this scheme. Finally, the existence of the solutions for the constraint conditions is also shown. The outcome indicates that some fractional PDEs are used as a growing finding in the engineering sciences, mathematical physics, and so on. (shrink)

This research investigates the notion of builders’ on-site engagement to physically build architectural interventions based on their demands, spatial requirements, and collaborative improvisation enhanced with the principles of uniqueness and bespoke solutions which are previously explored in computational models. The paper compares and discusses two physical installations as proto-architectural assemblies testing two different designs and building approaches: the top-down predefined designers’ scenario contrary to bottom-up unpredictable improvisation. It encompasses a building strategy based on the discrete precut components assembled by builders (...) themselves in situ. The paper evaluates both strategies in a qualitative observation and comparison defining advantages and limitations of the top-down design strategy in comparison with the decentralised bottom-up building system built by the builders themselves. As such, it outlines the position of a designer within the bottom-up building processes on-site. The paper argues that improvisation and builders’ direct engagement on-site lead to solutions that better reflect human needs and low-tech building principles incorporated can deliver unpredictable but convenient spatial scenarios. (shrink)

Real-world complex systems inevitably suffer from perturbations. When some system components break down and trigger cascading failures on a system, the system will be out of control. In order to assess the tolerance of complex systems to perturbations, an effective way is to model a system as a network composed of nodes and edges and then carry out network robustness analysis. Percolation theories have proven as one of the most effective ways for assessing the robustness of complex systems. However, existing (...) percolation theories are mainly for multilayer or interdependent networked systems, while little attention is paid to complex systems that are modeled as multipartite networks. This paper fills this void by establishing the percolation theories for multipartite networked systems under random failures. To achieve this goal, this paper first establishes two network models to describe how cascading failures propagate on multipartite networks subject to random node failures. Afterward, this paper adopts the largest connected component concept to quantify the networks’ robustness. Finally, this paper develops the corresponding percolation theories based on the developed network models. Simulations on computer-generated multipartite networks demonstrate that the proposed percolation theories coincide quite well with the simulations. (shrink)

Topological index is a mathematical coding of the molecular graphs that predicts the physicochemical, biological, toxicological, and structural properties of the chemical compounds that are directly associated with the molecular graphs. The Zagreb connection indices are one of the TIs of the molecular graphs depending upon the connection number appeared in 1972 to compute the total electron energy of the alternant hydrocarbons. But after that, for a long period, these are not studied by researchers. Recently, Ali and Trinajstic Mol. Inform. (...) 372018,1−7 restudied the Zagreb connection indices and reported that the Zagreb connection indices comparatively to the classical Zagreb indices provide the better absolute value of the correlation coefficient for the thirteen physicochemical properties of the octane isomers. In this paper, we compute the general results in the form of exact formulae & upper bounds of the second Zagreb connection index and modified first Zagreb connection index for the resultant graphs which are obtained by applying operations of corona, Cartesian, and lexicographic product. At the end, some applications of the obtained results for particular chemical structures such as alkanes, cycloalkanes, linear polynomial chain, carbon nanotubes, fence, and closed fence are presented. In addition, a comparison between exact and computed values of the aforesaid Zagreb indices is also included. (shrink)

Wireless sensor networks are widely used in many fields, such as medical and health care, military monitoring, target tracking, and people’s life, because of their advantages of convenient deployment, low cost, and good concealment. However, due to the low battery capacity of sensor nodes and environmental changes, the energy consumption of nodes is serious and the accuracy of data collection is low. In the data collection method of multiple random paths, due to the uneven geographical distribution between nodes and the (...) influence of the environment, it is easy to cause the communication between nodes to be blocked and the construction of random paths to fail. This paper proposes an efficient data collection algorithm for this problem. The algorithm is improved on the basis of the random node selection algorithm. This method can effectively avoid the failure of random path node selection and improve the node selection of random path in wireless sensor networks. Then, the sensor network in the dynamic environment is analyzed based on the static environment. An efficient data collection algorithm based on the position prediction of extreme learning machines is proposed. This method uses extreme learning machine methods to perform trajectory prediction for nodes in a dynamic environment. (shrink)

Effective teamwork in an initially leaderless group requires a high level of collective leadership emerging from dynamic interactions among group members. Leader emergence is a crucial topic in collective leadership, yet it is challenging to investigate as the problem context is typically highly complex and dynamic. Here, we explore leadership emergence and leadership perception by means of computational simulations whose assumptions and parameters were informed by empirical research and human-subject experiments. Our agent-based model describes the process of group planning. Each (...) agent is assigned with three key attributes: talkativeness, intelligence, and credibility. An agent can propose a suggestion to modify the group plan as a speaker or respond and evaluate others’ suggestions and leadership as a listener. Simulation results suggested that agents with high values of talkativeness, intelligence, and credibility tended to be perceived as leaders by their peers. Results also showed that talkativeness may be the most significant and instantaneous predictor for leader emergence of the three investigated attributes: talkativeness, intelligence, and credibility. In terms of group performance, smaller groups may outperform larger groups regarding their problem-solving ability in the beginning, but their performance tends to be of no significant difference in a long run. These results match the empirical literature and offer a mechanistic, operationalized description of the collective leadership processes. (shrink)

Time-varying output formation control problems for high-order time-invariant swarm systems are studied with nonlinear uncertainties and directed network topology in this paper. A robust controller which consists of a nominal controller and a robust compensator is applied to achieve formation control. The nominal controller based on the output feedback is designed to achieve desired time-varying formation properties for the nominal system. And the robust compensator based on the robust signal compensator technology is constructed to restrain nonlinear uncertainties. The time-varying formation (...) problem is transformed into the stability problem. And the formation errors can be arbitrarily small with expected convergence rate. Numerical examples are provided to illustrate the effectiveness of the proposed strategy. (shrink)

Most multiobjective particle swarm optimizers often face the challenges of keeping diversity and achieving convergence on tackling many-objective optimization problems, as they usually use the nondominated sorting method or decomposition-based method to select the local or best particles, which is not so effective in high-dimensional objective space. To better solve MaOPs, this paper presents a novel angular-guided particle swarm optimizer. A novel velocity update strategy is designed in AGPSO, which aims to enhance the search intensity around the particles selected based (...) on their angular distances. Using an external archive, the local best particles are selected from the surrounding particles with the best convergence, while the global best particles are chosen from the top 20% particles with the better convergence among the entire particle swarm. Moreover, an angular-guided archive update strategy is proposed in AGPSO, which maintains a consistent population with balanceable convergence and diversity. To evaluate the performance of AGPSO, the WFG and MaF test suites with 5 to 10 objectives are adopted. The experimental results indicate that AGPSO shows the superior performance over four current MOPSOs and four competitive evolutionary algorithms, when solving most of the test problems used. (shrink)

By constructing an evolutionary game model of green dairy industry chain from the perspective of green sustainable development, this paper analyzed the evolution process of strategy selection of dairy farmers and dairy enterprises under the supervision of the government. The study found the following. In the absence of supervision, even if the initial cooperation willingness of dairy farmers and dairy enterprises is strong, once the additional cost of their input of “green production” is less than the additional benefit, they will (...) eventually choose noncooperative strategy. In the case of government supervision, when the government punishment or subsidy is not strong enough, the strategic choice of dairy farmers and dairy enterprises will fluctuate repeatedly, and the game equilibrium cannot be reached. However, when the government punishments and subsidies are strong enough, dairy farmers and dairy enterprises will choose to cooperate in their own interests. At this time, government subsidies have a greater impact on the evolution of bilateral cooperation than government punishments. The reduction of green production cost can promote the formation of the green dairy industry chain, which is conducive to the green dairy industry chain system to achieve an ideal equilibrium state. (shrink)

The global asymptotic behavior of solutions in a cross-diffusive predator-prey model with cannibalism is studied in this paper. Firstly, the local stability of nonnegative equilibria for the weakly coupled reaction-diffusion model and strongly coupled cross-diffusion model is discussed. It is shown that the equilibria have the same stability properties for the corresponding ODE model and semilinear reaction-diffusion model, but under suitable conditions on reaction coefficients, cross-diffusion-driven Turing instability occurs. Secondly, the uniform boundedness and the global existence of solutions for the (...) model with SKT-type cross-diffusion are investigated when the space dimension is one. Finally, the global stability of the positive equilibrium is established by constructing a Lyapunov function. The result indicates that, under certain conditions on reaction coefficients, the model has no nonconstant positive steady state if the diffusion matrix is positive definite and the self-diffusion coefficients are large enough. (shrink)

Given the importance of users in medical innovation, positive user participation can boost the cooperative innovation process within the medical supply chain. A stochastic differential model based on user feedback is proposed to study the relationship between user feedback and the medical supply chain. The stability and sensitivity of the medical supply chain is analysed through different parameters. The results show that the effect of patient feedback and suggestions from hospitals on the innovation level of medical services and medical products (...) is positive, such that the impact of the innovation level of medical services on users and the effect of patient feedback are positively related to marginal profits and that cooperative innovation is beneficial for medical product and service innovation and the improvement of demand and profits. (shrink)

In the past decades, the booming growth of housing markets in China triggers the urgent need to explore how the rapid urban spatial expansion, large-scale urban infrastructural development, and fast-changing urban planning determine the housing price changes and spatial differentiation. It is of great significance to promote the existing governing policy and mechanism of housing market and the reform of real-estate system. At the level of city, an empirical analysis is implemented with the traditional econometric models of regressive analysis and (...) GIS-based spatial autocorrelation models, focusing in examining and characterizing the spatial homogeneity and nonstationarity of housing prices in Guangzhou, China. There are 141 neigborhoods in Guangzhou identified as the independent individuals, and their values of the average annual housing prices in are clarified as the dependent variables in regressing analysis models used in this paper. Simultaneously, the factors including geographical location, transportation accessibility, commercial service intensity, and public service intensity are identified as independent variables in the context of urban development and planning. The integration and comparative analysis of multiple linear regression models, spatial autocorrelation models, and geographically weighted regressing models are implemented, focusing on exploring the influencing factors of house prices, especially characterizing the spatial heterogeneity and nonstationarity of housing prices oriented towards the spatial differences of urban spatial development, infrastructure layout, land use, and planning. This has the potential to enrich the current approaches to the complex quantitative analysis modelling of housing prices. Particularly, it is favorable to examine and characterize what and how to determine the spatial homogeneity and nonstationarity of housing prices oriented towards a microscale geospatial perspective. Therefore, this study should be significant to drive essential changes to develop a more efficient, sustainable, and competitive real-estate system at the level of city, especially for the emerging and dynamic housing markets in the megacities in China. (shrink)

With the explosion of data traffic, mobile edge computing has emerged to solve the problem of high time delay and energy consumption. In order to cope with a large number of computing tasks, the deployment of edge servers is increasingly intensive. Thus, server service areas overlap. We focus on mobile users in overlapping service areas and study the problem of computation offloading for these users. In this paper, we consider a multiuser offloading scenario with intensive deployment of edge servers. In (...) addition, we divide the offloading process into two stages, namely, data transmission and computation execution, in which channel interference and resource preemption are considered, respectively. We apply the noncooperative game method to model and prove the existence of Nash equilibrium. The real-time update computation offloading algorithm is proposed to obtain equilibrium offloading strategies. Due to the high complexity of the RUCO algorithm, the multiuser probabilistic offloading decision algorithm is proposed to improve this problem. We evaluate the performance of the MPOD algorithm through experiments. The experimental results show that the MPOD algorithm can converge after a limited number of iterations and can obtain the offloading strategy with lower cost. (shrink)

Resource support between individuals is of particular importance in controlling or mitigating epidemic spreading, especially during pandemics. However, there remains the question of how we can protect ourselves from being infected while helping others by donating resources in fighting against the epidemic. To answer the question, we propose a novel resource allocation model by considering the awareness of self-protection of individuals. In the model, a tuning parameter is introduced to quantify the reaction strength of individuals when they are aware of (...) the disease. And then, a coupled model of resource allocation and disease spreading is proposed to study the impact of self-awareness on resource allocation and its impact on the dynamics of epidemic spreading. Through theoretical analysis and extensive Monte Carlo simulations, we find that in the stationary state, the system converges to two states: the whole healthy or the completely infected, which indicates an abrupt increase in the prevalence when there is a shortage of resources. More importantly, we find that too cautious and too selfless for the people during the outbreak of an epidemic are both not suitable for disease control. Through extensive simulations, we locate the optimal point, at which there is a maximum value of the epidemic threshold, and an outbreak can be delayed to the greatest extent. At last, we study further the effects of the network structure on the coupled dynamics. We find that the degree heterogeneity promotes the outbreak of disease, and the network structure does not alter the optimal phenomenon in behavior response. Based on the results of this study, a constructive suggestion is that in the face of a global pandemic, individuals or countries should strengthen mutual support and cooperation while doing their own prevention to suppress the epidemic optimally. (shrink)

The uncertainty of the engineering system increases with the growing complexity of the engineering system; therefore, the tolerance to the uncertainty is essential. In the design phase, the output performance should reach the design criterion, even under large variations of design parameters. The tolerance to design parameter variations may be measured by the size of a solution space in which the output performance is guaranteed to deliver the required performance. In order to decouple dimensions, a maximum solution hyperbox, expressed by (...) intervals with respect to each design parameter, is sought. The proposed approach combines the metaheuristic algorithm with the DIRECT algorithm where the former is used to seek the maximum size of hyperbox, and the latter is used as a checking technique that guarantees the obtained hyperbox is indeed a solution hyperbox. There are three advantages of the proposed approach. First, it is a global search and has a considerable high possibility to produce the globally maximum solution hyperbox. Second, it can be used for both analytically known and black-box performance functions. Third, it guarantees that any point selected within the obtained hyperbox satisfies the performance criterion as long as the performance function is continuous. Furthermore, the proposed approach is illustrated by numerical examples and real examples of complex systems. Results show that the proposed approach outperforms the GHZ and CES-IA methods in the literature. (shrink)

In the financial market, information and investment behaviors disseminate in investor social networks, and different contagion patterns may cause diverse investment trends. Prior studies have investigated the impact of investor social networks, but few have considered community structure. In this paper, we study the impact of the community structure of investor social networks on the diffusion of internet investment products. A two-stage diffusion model is proposed, and the clustering coefficient and modularity of an investor social network are considered. The results (...) show that both modularity and the clustering coefficient have an impact on the diffusion velocity and scale and that the impact is most evident at the stage of explosive growth. The negative influence of a large modularity can be hardly mitigated by adjusting other factors. Furthermore, a decrease in modularity and an increase in the clustering coefficient can better facilitate diffusion when the temporary investment rate is high and can partly offset the negative impact of information discarding and divestment. (shrink)

The existing convergence control guidance laws are designed via the Lyapunov asymptotic stability theory or finite-time stability theory. However, guidance law based on the Lyapunov asymptotic stability theory would lead the states to zero only as time approaches infinity, which is imperfect theory. The convergence time for guidance laws based on finite-time stable theory is dependent on the initial states. A fixed-time convergent guidance law with impact angle control is proposed in this paper. The proposed guidance law consists of two (...) parts. One is the heading error angle shaping term, and the other is the bias term to achieve the desired impact angle. The guidance command is continuous during the engagement without utilizing the switching logics. Unlike the existing guidance law in the literature, the fixed-time stability theory is utilized to ensure the impact angle error to converge to zero before the interception. Furthermore, the convergence rate is merely related to control parameters. Simulations are carried out to illustrate the effectiveness of the proposed guidance law. (shrink)

This paper studies the multiconsensus problem of multiagent networks based on sampled data information via the pulse-modulated intermittent control which is a general control framework unifying impulsive control, intermittent control, and sampling control. Two kinds of multiconsensus, including stationary multiconsensus and dynamic multiconsensus of multiagent networks, are taken into consideration in such control framework. Based on the eigenvalue analysis and algebraic graph theory, some necessary and sufficient conditions on the feedback gains and the control period are established to ensure the (...) multiconsensus. Finally, several simulation results are included to show the theoretical results. (shrink)

Consider a dynamic task allocation problem, where tasks are unknowingly distributed over an environment. This paper considers each task comprising two sequential subtasks: detection and completion, where each subtask can only be carried out by a certain type of agent. We address this problem using a novel nature-inspired approach called “hunter and gatherer.” The proposed method employs two complementary teams of agents: one agile in detecting and another skillful in completing the tasks. To minimize the collective cost of task accomplishments (...) in a distributed manner, a game-theoretic solution is introduced to couple agents from complementary teams. We utilize market-based negotiation models to develop incentive-based decision-making algorithms relying on innovative notions of “certainty and uncertainty profit margins.” The simulation results demonstrate that employing two complementary teams of hunters and gatherers can effectually improve the number of tasks completed by agents compared to conventional methods, while the collective cost of accomplishments is minimized. In addition, the stability and efficacy of the proposed solutions are studied using Nash equilibrium analysis and statistical analysis, respectively. It is also numerically shown that the proposed solutions function fairly; that is, for each type of agent, the overall workload is distributed equally. (shrink)

In this paper, a heterogeneous diffusive prey-predator system is first proposed and then studied analytically and numerically. Some sufficient conditions are derived, including permanence and extinction of system and the boundedness of the solution. The existence of periodic solution and its stability are discussed as well. Furthermore, numerical results indicate that both the spatial heterogeneity and the time-periodic environment can influence the permanence and extinction of the system directly. Our numerical results are consistent with the analytical analysis.

Interactions in microservice systems are complex due to three dimensions: numerous asynchronous interactions, the diversity of asynchronous communication, and unbounded buffers. Analyzing such complex interactions is challenging. In this paper, we propose an approach for interaction analysis using model checking techniques, which is supported by the Process Analysis Toolkit tool. First, we use Labeled Transition Systems to model interaction behaviors in microservice systems as sequences of send actions under synchronous and asynchronous communications. Second, we introduce a notion of correctness called (...) “interaction soundness” which is considered as a minimal requirement for microservice systems. Third, we propose an encoding of LTSs into the CSP# process algebra for automatic verification of the property interaction soundness. The experimental results show that our approach can automatically and effectively identify interaction faults in microservice systems. (shrink)

To provide a basic guidance for the selection of nozzle layout, a mathematical model of the impingement depth for helical gears under oil jet lubrication is established. Furthermore, computational fluid dynamics methods are adopted to validate the effectiveness and accuracy of the derived impingement model. Firstly, the distribution characteristics of the oil volume fraction and oil-gas pressure in meshing area were obtained in flow field simulation. Meanwhile, the influence of spray angle, jet velocity, and gear ratio on lubrication effect was (...) obtained. Then, the transient temperature field of the tooth surface was simulated by the method of thermal-fluid coupling analysis, and the lowest temperature distribution and the corresponding oil jet velocity were determined. Finally, experiments on the temperature characteristics measured by an infrared thermal imager of helical gears with different nozzle parameters were carried out in a gear test rig. The simulation results of transient temperature field are in good agreement with those obtained by experiments, and it indicates that the thermal-fluid coupling analysis method is correct and feasible to predict the temperature field of the helical gear pair under oil injection jet lubrication. (shrink)

Nonlinear dynamic models are widely used for characterizing processes that govern complex biological pathway systems. Over the past decade, validation and further development of these models became possible due to data collected via high-throughput experiments using methods from molecular biology. While these data are very beneficial, they are typically incomplete and noisy, which renders the inference of parameter values for complex dynamic models challenging. Fortunately, many biological systems have embedded linear mathematical features, which may be exploited, thereby improving fits and (...) leading to better convergence of optimization algorithms. In this paper, we explore options of inference for dynamic models using a novel method of separable nonlinear least-squares optimization and compare its performance to the traditional nonlinear least-squares method. The numerical results from extensive simulations suggest that the proposed approach is at least as accurate as the traditional nonlinear least-squares, but usually superior, while also enjoying a substantial reduction in computational time. (shrink)

An understanding of the intracommunity trade is essential for the agents involved in the fresh tomato market. The purpose of this paper is to analyze the interdependent relationships between exporting and importing countries within the European Union for a specific product such as fresh tomatoes and thus understand which have been the key countries in three specific years. The methodology used to study the interrelationships of trade flows in the countries of the European Union is that of triangulation by means (...) of the Leontief input-output model. Artificial intelligence techniques are used to process and triangulate the data based on pathfinding techniques using a cost function. The triangulation results have created a hierarchy of countries. This type of methodology has not been applied to the field of foreign trade. The results show that Netherlands and Spain are key countries in intracommunity trade as they have a strong impact both with regard to their exports and their imports and are fundamental when analyzing the growth of specific sectors and how they are able to stimulate the economies of other countries. (shrink)

In this paper, we use the fixed-point index and nonnegative matrices to study the existence of positive solutions for a system of Hadamard-type fractional differential equations with semipositone nonlinearities.

Conservative chaotic systems have potentials in engineering application because of their superiority over the dissipative systems in terms of ergodicity and integer dimension. In this paper, five-dimension Euler equations are constructed by integrating two of sub-Euler equations, which are contributory to the exploration of higher-dimensional systems. These Euler equations compose the conservative parts from their antisymmetric structure, which have been proved to be both Hamiltonian and Casimir energy conservative. Furthermore, a family of Hamiltonian conservative hyperchaotic systems are proposed by breaking (...) the conservation of Casimir energy. The numerical analysis shows that the system displays some interesting behaviors, such as the coexistence of quasi-periodic, chaotic, and hyperchaotic behaviors. Adaptive synchronization method is used to realize the hyperchaos synchronization. Finally, the system passed the NIST tests successfully. Field programmable gate array platform is used to implement the proposed Hamiltonian conservative hyperchaos. (shrink)

Since the conservative chaotic system has no general attractors, conservative chaotic flows are more suitable for the chaos-based secure communication than the chaotic attractors. In this paper, two Hamiltonian conservative chaotic systems are constructed based on the 4D Euler equations and a proposed construction method. These two new systems are investigated by equilibrium points, dynamical evolution map, Hamilton energy, and Casimir energy. They look similar, but it is found that one can be explained using Casimir power and another cannot be (...) explained in terms of the mechanism of chaos. Furthermore, a pseudorandom signal generator is developed based on these proposed systems, which are tested based on NIST tests and implemented by using the field programmable gate array technique. (shrink)

The diffusion of green agricultural production under intensive management pattern is an interactive process of strategy comparison and learning on complex networks among traditional farmers and new agricultural operation entities. Based on the theory of evolutionary game and complex networks, we construct evolutionary game models on the scale-free networks to simulate the evolution process of green agricultural production under the market mechanism and the government guidance mechanism, respectively. The comparison analysis results in different scenarios show that the stable state of (...) the green agricultural production network is determined by interactions among the subjects. Detailed experimental results indicate that the double-score system under government guidance mechanism has a significant effect on the diffusion of the green agricultural production, of which the extra reward or penalty obtained from government is crucial. Besides, the diffusion of the green agricultural production under the market mechanism is mostly affected by the net profit of green agricultural production. These results are of great significance for increasing efficiency of government’s incentive and promoting the initiatives of traditional farmers and new agricultural operation entities in the green agricultural production. (shrink)

This paper investigates access link control and resource allocation for the device-to-device communication in the fifth generation cellular networks. The optimization objective of this problem is to maximize the number of admitted D2D links and minimize the total power consumption of D2D links under the condition of meeting the minimum transmission rate requirements of D2D links and common cellular links. This problem is a two-stage nondeterministic polynomial problem, the solving process of which is very complex. So, we transform it into (...) a one-stage optimization problem. According to the monotonicity of objective function and constraint conditions, a monotone optimization problem is established, which is solved by reverse polyblock approximation algorithm. In order to reduce the complexity of this algorithm, a solution algorithm based on iterative convex optimization is proposed. Simulation results show that both algorithms can maximize the number of admitted D2D links and minimize the total power consumption of D2D links. The proposed two algorithms are better than the energy efficiency optimization algorithm. (shrink)

In this work, we present an approach to design a multistable system with one-directional, two-directional, and three-directional hidden multiscroll attractor by defining a vector field on ℝ3 with an even number of equilibria. The design of multistable systems with hidden attractors remains a challenging task. Current design approaches are not as flexible as those that focus on self-excited attractors. To facilitate a design of hidden multiscroll attractors, we propose an approach that is based on the existence of self-excited double-scroll attractors (...) and switching surfaces whose relationship with the local manifolds associated to the equilibria lead to the appearance of the hidden attractor. The multistable systems produced by the approach could be explored for potential applications in cryptography, since the number of attractors can be increased by design in multiple directions while preserving the hidden attractor allowing a bigger key space. (shrink)

After the financial crisis triggered by the subprime mortgage crisis in the United States in 2008, many scholars believed that the unstable transmission of shadow banking business in the banking system is the main factor causing financial turmoil. This paper proposes a dynamic complex interbank network system model with shadow banking in which the dynamic complex interbank network system differs from the traditional banking network and is formed by the interrelated business between shadow banks and commercial banks to explore the (...) effect of shadow banking on the systemic risk. The results show that the existence of shadow banking will increase the systemic risk, accelerate the speed of bankruptcy of banks, reduce the survival ratio of banks, and increase the strength of central bank assistance. The smaller the number of shadow banks in the system, the higher the degree of credit connection among commercial banks and the smaller the systemic risk. (shrink)

Humor refers to the quality of being amusing. With the development of artificial intelligence, humor recognition is attracting a lot of research attention. Although phonetics and ambiguity have been introduced by previous studies, existing recognition methods still lack suitable feature design for neural networks. In this paper, we illustrate that phonetics structure and ambiguity associated with confusing words need to be learned for their own representations via the neural network. Then, we propose the Phonetics and Ambiguity Comprehension Gated Attention network (...) to learn phonetic structures and semantic representation for humor recognition. The PACGA model can well represent phonetic information and semantic information with ambiguous words, which is of great benefit to humor recognition. Experimental results on two public datasets demonstrate the effectiveness of our model. (shrink)

A distributed fuzzy adaptive control with similar parameters is constructed for a class of heterogeneous multiagent systems. Unlike many existing works, the dimensions of each multiagent dynamic system are considered to be nonidentical in this paper. Firstly, similar properties for different dimensions of multiagent systems are introduced, and some similar parameters among multiagent systems are also proposed. Secondly, a distributed fuzzy adaptive control on the basis of similar parameters is designed for the consensus of leader-follower multiagent systems. Following the graph (...) theory and Lyapunov stability approach, it is concluded that UUB of all signals in the closed-loop system can be guaranteed, and the consensus tacking error converges to a small compact zero set. Finally, a simulation example with different dimensions is provided to illustrate the effectiveness of the proposed method. (shrink)

An SIS propagation model with the nonlinear rewiring rate on an adaptive network is considered. It is found by bifurcation analysis that the model has the complex behaviors which include the transcritical bifurcation, saddle-node bifurcation, Hopf bifurcation, and Bogdanov–Takens bifurcation. Especially, a bifurcation curve with “S” shape emerges due to the nonlinear rewiring rate, which leads to multiple equilibria and twice saddle-node bifurcations. Numerical simulations show that the model admits a homoclinic bifurcation and a saddle-node bifurcation of the limit cycle.

The University of Texas at Dallas has proposed 24 top journals covering all areas related to management. UTD24 are currently the most authoritative management journals. Institutions or research scholars who have published papers in these journals are considered to have a high academic level. This study uses the paper quality published by an institution in the UTD24 journals to indicate the research quality of this institution and takes the papers published by Chinese Business School in the UTD24 journals from 2000 (...) to 2018 as the research object. By analyzing the staged evolution process and the research hotspot of international research collaboration network of Chinese Business School, this paper summarizes and analyzes the factors that influence the quality of papers published by Chinese Business School in UTD24 journals: degree centrality of an institution, betweenness centrality of an institution, the degree of attention of an institution, the degree of novelty of an institution, and the number of countries cooperating with the institution. This paper divides paper quality into two parts: the total number of papers and citations per paper of an institution. Among them, degree centrality and betweenness centrality of the institution have a significant positive impact on the total number of papers of the institution. The degree of attention and the number of countries cooperating with the institution have a significant positive impact on citations per paper, and the degree of novelty has a significant negative impact on citations per paper. (shrink)

The disk dynamo system, which is capable of chaotic behaviours, is obtained experimentally from two disk dynamos connected together. It models the geomagnetic field and is used to explain the reversals in its polarity. Actually, the parameters of the chaotic systems exhibit random fluctuation to a greater or lesser extent, which can carefully describe the disturbance made by environmental noise. The global dynamics of the chaotic disk dynamo system with random fluctuating parameters are concerned, and some new results are presented. (...) Based on the generalized Lyapunov function, the globally attractive and positive invariant set is given, including a two-dimensional parabolic ultimate boundary and a four-dimensional ellipsoidal ultimate boundary. Furthermore, a set of sufficient conditions is derived for all solutions of the stochastic disk dynamo system being global convergent to the equilibrium point. Finally, numerical simulations are presented for verification. (shrink)

The rapid developments in sensor technology and mobile devices bring a flourish of social images, and large-scale social images have attracted increasing attention to researchers. Existing approaches generally rely on recognizing object instances individually with geo-tags, visual patterns, etc. However, the social image represents a web of interconnected relations; these relations between entities carry semantic meaning and help a viewer differentiate between instances of a substance. This article forms the perspective of the spatial relationship to exploring the joint learning of (...) social images. Precisely, the model consists of three parts: a module for deep semantic understanding of images based on residual network ; a deep semantic analysis module of text beyond traditional word bag methods; a joint reasoning module from which the text weights obtained using image features on self-attention and a novel tree-based clustering algorithm. The experimental results demonstrate the effectiveness of using Flickr30k and Microsoft COCO datasets. Meanwhile, our method considers spatial relations while matching. (shrink)

Personalized recommender systems, as effective approaches for alleviating information overload, have received substantial attention in the last decade. Learning effective latent factors plays the most important role in recommendation methods. Several recent works extracted latent factors from user-generated content such as ratings and reviews and suffered from the sparsity problem and the unbalanced distribution problem. To tackle these problems, we enrich the latent representations by incorporating user-generated content and item raw content. Deep neural networks have emerged as very appealing in (...) learning effective representations in many applications. In this paper, we propose a novel deep neural architecture named DeepFusion to jointly learn user and item representations from numerical ratings, textual reviews, and item metadata. In this framework, we utilize multiple types of deep neural networks that are best suited for each type of heterogeneous inputs and introduce an extra layer to obtain the joint representations for users and items. Experiments conducted on the Amazon product data demonstrate that our approach outperforms multiple state-of-the-art baselines. We provide further insight into the design selections and hyperparameters of our recommendation method. In addition, we further explore the relative importance of various item metadata information on improving the rating prediction performance towards personalized product recommendation, which is extremely valuable for feature extraction in practice. (shrink)

For the optimal design of electromagnetic devices, it is the most time consuming to obtain the training samples from full wave electromagnetic simulation software, including HFSS, CST, and IE3D. Traditional machine learning methods usually use only labeled samples or unlabeled samples, but in practical problems, labeled samples and unlabeled samples coexist, and the acquisition cost of labeled samples is relatively high. This paper proposes a semisupervised learning Gaussian Process, which combines unlabeled samples to improve the accuracy of the GP model (...) and reduce the number of labeled training samples required. The proposed GP model consists two parts: initial training and self-training. In the process of initial training, a small number of labeled samples obtained by full wave electromagnetic simulation are used for training the initial GP model. Afterwards, the trained GP model is copied to another GP model in the process of self-training, and then the two GP models will update after crosstraining with different unlabeled samples. Using the same test samples for testing and updating, a model with a smaller error will replace another. Repeat the self-training process until a predefined stopping criterion is met. Four different benchmark functions and resonant frequency modeling problems of three different microstrip antennas are used to evaluate the effectiveness of the GP model. The results show that the proposed GP model has a good fitting effectiveness on benchmark functions. For microstrip antennas resonant frequency modeling problems, in the case of using the same labeled samples, its predictive ability is better than that of the traditional supervised GP model. (shrink)

In this paper, we study the existence and nonexistence of solutions to fractional elliptic equations with the Hardy potential −Δsu−λu/x2s=ur−1+δgu,in Ω,ux>0,in Ω,ux=0,in ℝN∖Ω, where Ω⊂ℝN is a bounded Lipschitz domain with 0∈Ω, −Δs is a fractional Laplace operator, s∈0,1, N>2s, δ is a positive number, 2

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This paper investigates the observer-based structural balance control for a class of complex dynamical networks. Generally speaking, a complete complex dynamical network is composed of two coupled subsystems, which are called node subsystem and connection relationship subsystem, respectively. Similar to synchronization and stabilization of networks, the structural balance is another phenomenon of networks and determined by the state of connection relationships. However, it is not feasible to design the controller for the CS directly because the states of the connection relationships (...) are difficult to be measured accurately in practical applications. In order to solve this problem, a state observer for the CS has been designed. Thus, the structural balance controller in the CS can be directly designed by using the estimation information of the state observer. Then, with the help of the Lyapunov stability theory, it is proved that the CS can asymptotically track a given structural balance matrix under the influence of the observer-based controller. Finally, the results derived from this paper are demonstrated by performing a numerical example. (shrink)

In this paper, a new data-driven learning method is investigated based on the dynamical data of the system. A regularized regression wavelet approach is proposed to optimize the learning result for the system fault. Based on the optimizing results, a fault tolerant stability scheme is given. Then, the efficiency of the proposed technique is verified by a vertical take-off and landing aircraft stability example.

This paper investigates both the time-varying formation and multiple time-varying formation tracking problems of networked heterogeneous robotic systems with parameter uncertainties and external disturbances in the task space. Each robot inside can be either redundant or nonredundant. Several novel estimator-based hierarchical cooperative algorithms are designed to achieve both the tracking task and the possible preset subtasks for redundant robots. Besides, the designed estimator algorithms guarantee that each robot can obtain the accurate information of their corresponding leaders. By employing Lyapunov stability (...) and input-to-state stability, sufficient conditions on the asymptotic stability of the error closed-loop system are derived. Finally, two simulation examples are presented to verify the effectiveness of the proposed algorithms. (shrink)

To analyze whether information sharing in the institutional investors plays the role of a market stabilizer or risk booster, this paper constructs the institutional investor information network employing the common holding stocks of the mutual funds as links. The information linkages between two funds with large positions in the same stock are hypothesized to be connected to each other. Then, we use the information sharing efficiency in the fund networks to study the effects of information transmission on stock market extreme (...) risk and financial systemic risk. Especially, the speed of information diffusion in the network is characterized by the topology structures based on social network theory. Empirical research studies find that the Chinese fund information network exhibits small-world characteristics, which reflects rapid speed of information diffusion. Seen from the idiosyncratic risk of volatility, information sharing of institutional investors can improve the behavior consistency of fund managers, thus increasing the stock volatility via herd effects. Besides, it can be concluded that institutional investor information sharing can reduce the extreme risk by promoting the comprehensiveness of information flow and the market pricing efficiency of stocks, thereby reducing the degree of financial systemic risk. The obtained conclusions provide suggestions for decision-making of institutional investors. It can help the regulators to pay attention to the herd effects so as to control systemic risk. (shrink)

In this paper, by using subsuper solutions method, we study the existence of weak positive solutions for a new class of p,q Laplacian nonlinear elliptic system in bounded domains, when ax, bx,αx, and βx are sign-changing functions that maybe negative near the boundary, without assuming sign conditions on f0,g0,h0, and γ0.

In this paper, the time-fractional Fujimoto–Watanabe equation is investigated using the Riemann–Liouville fractional derivative. Symmetry groups and similarity reductions are obtained by virtue of the Lie symmetry analysis approach. Meanwhile, the time-fractional Fujimoto–Watanabe equation is transformed into three kinds of reduced equations and the third of which is based on Erdélyi–Kober fractional integro-differential operators. Furthermore, the conservation laws are also acquired by Ibragimov’s theory.

The Internet has become an important carrier of information. Its data contain abundant information about hot events, user relations and attitudes, and so on. Many enterprises use high-impact Internet users to promote products, so it is very important to understand the mechanism of information transmission. Mining social network data can help people analyze the complex and changing relationships between users. The traditional method for doing this is to analyze information such as common interests and common friends, but this data cannot (...) truly describe the degree of intimacy between users. What really connects different users on the Internet is the delivery of information. The algorithm proposed in this paper considers the dynamic characteristics of information transmission, finds maximum transmission paths from information transmission results, and finally calculates the intimacy degrees between users according to all the maximum information transmission paths within a certain period. (shrink)

The trajectory tracking task of a magnetic levitation system connected to a beam mechanism is solved by means of a nested saturation control with a feedforward term. The flatness property of the system allows to use the nested saturation control technique and the feedforward control to stabilize the output tracking error around the equilibrium. The closed-loop error dynamics is proven to be locally exponentially stable. Numerical simulations prove the effectiveness of the proposal.

The convenience of transportation brings the diversity of individuals’ travelling modes; in this paper, we present an improved epidemic diffusion model in a multilayer metapopulation network. Firstly, we construct the metapopulation network with different travelling ways, and then, the epidemic spreading threshold is calculated by means of the mean-field method. Taking the periodicity of individuals’ travelling into account, we further explore the epidemic diffusion model with individuals’ periodic travelling and deduce the epidemic spreading threshold using the Perron–Frobenius theorem. Our results (...) show that if all individuals in each area decide to move, the epidemic threshold can be effectively raised while each individual chooses an unbiased region to arrive. In addition, with the increase of individuals’ mobility rate or regional heterogeneous infection coefficient, the fluctuation range of the density of infected becomes larger, while the fluctuation period is almost unchanged. However, the change of individuals’ periodic motion could cause the change of the fluctuation period of infected density. We try to provide a new perspective for the research of metapopulation. (shrink)

The equipment scheduling and propagation characteristics of vibration wave from vibratory roller ⟶ filling material nonlinear systems with multistability are the core problems of subgrade intelligent construction technology, and the logistics scheduling of the equipment is directly related to the construction efficiency. Aiming at the shortages, one typical subgrade located at the Gu’an station of Beijing-Xiong’an city railway is selected to research and finish the field tests; some findings are shown as follows: first, some valuable suggestions about the logistics scheduling (...) of intelligent equipment are proposed, which can break the barriers between the organizations and improve construction efficiency; second, when the vibration wave propagates from the vibratory roller ⟶ surface of filling material ⟶ different buried depths of filling material, the peak acceleration of vibration wave gradually decreases and is hyperbolic distribution approximately. At the same time, the sensitive of attenuation is shown as follows: Z 0.9), and the concrete functional relationship among different amplitudes of harmonics can be summarized as y = Ae−BX; fourth, the vibration energy is mainly concentrated near 10–30 Hz in the vibratory roller, but when the vibration wave propagates from vibratory roller⟶filling material, the vibration energy gradually decreases with the increase in depth, and the marginal spectrum gradually changes from one peak to two peaks, that is, 30–50 Hz and 50–100 Hz; fifth, the vibration energy in the vibrational wheel is distributed averagely in the compaction process, and the effective compaction time is two seconds, which will be helpful for revealing the propagation characteristics of vibration wave, optimizing the compaction quality control models and providing some support for the development of intelligent compaction theory of railway subgrade. (shrink)

This paper examines approximation-based fixed-time adaptive tracking control for a class of uncertain nonlinear pure-feedback systems. Novel virtual and actual controllers are designed that resolve the meaninglessness of virtual and actual controllers at the origin and in the negative domain, and the sufficient condition for the system to have semiglobal fixed-time stability is also provided. Radial basis function neural networks are introduced to approximate unknown functions for solving the fixed-time control problem of unknown nonlinear pure-feedback systems, and the mean value (...) theorem is used to solve the problem of nonaffine structure in nonlinear pure-feedback systems. The controllers designed in this paper ensure that all signals in the closed-loop system are semiglobally uniform and ultimately bounded in a fixed time. Two simulation results show that appropriate design parameters can limit the tracking error within a region of the origin in a fixed time. (shrink)

In this paper, we propose a family of heavy tailed distributions, by incorporating a trigonometric function called the arcsine exponentiated-X family of distributions. Based on the proposed approach, a three-parameter extension of the Weibull distribution called the arcsine exponentiated-Weibull distribution is studied in detail. Maximum likelihood is used to estimate the model parameters, and its performance is evaluated by two simulation studies. Actuarial measures including Value at Risk and Tail Value at Risk are derived for the ASE-W distribution. Furthermore, a (...) numerical study of these measures is conducted proving that the proposed ASE-W distribution has a heavier tail than the baseline Weibull distribution. These actuarial measures are also estimated from insurance claims real data for the ASE-W and other competing distributions. The usefulness and flexibility of the proposed model is proved by analyzing a real-life heavy tailed insurance claims data. We construct a modified chi-squared goodness-of-fit test based on the Nikulin–Rao–Robson statistic to verify the validity of the proposed ASE-W model. The modified test shows that the ASE-W model can be used as a good candidate for analyzing heavy tailed insurance claims data. (shrink)

In order to comprehensively study and identify the electromagnetic torque difference among the single static air-gap eccentricity fault, the single stator interturn short circuit fault, and the combined fault composed of these two, this article investigates the EMT ripple properties due to the mentioned three faults. Different from other studies, this paper considers not only the effect of the single fault types but also the impact of the single fault combinations on the EMT ripple characteristics. Detailed EMT expressions for each (...) fault are firstly derived on the basis of the magnetic flux density analysis. Then, finite element calculation and experimental study on a CS-5 prototype generator with two poles at 3000 rpm, which is specifically designed and manufactured ourselves, are carried out to validate the analysis result. It is found that the three faults will induce different ripple components in EMT. The combined faults have the most intensive impact sensitivity on the EMT ripples, while the single SAGE fault ranks the last in the impact effect. (shrink)

In this paper, we solve the problem of position regulation in a magnetic levitation system that is fed by a DC/DC Buck power electronic converter as a power amplifier. We present a formal asymptotic stability proof. Although this result is local, the merit of our proposal relies on the fact that this is the first time that such a control problem is solved for a magnetic levitation system, a nonlinear electromechanical plant. In this respect, we stress that most works in (...) the literature on control of electromechanical systems actuated by power electronic converters are devoted to control brushed DC motors which are well known to have a linear model. Furthermore, despite the plant that we control in the present paper is complex, our control law is simple. It is composed by four nested loops driven by one sliding mode controller, two proportional-integral controllers, and a nonlinear proportional-integral-derivative position controller. Each one of these loops is devoted to control each one of the subsystems that compose the plant: electric current through the converter inductor, voltage at the converter capacitor, electric current through the electromagnet, and position of the ball. Thus, our proposal is consistent with the simple and intuitive idea of controlling each subsystem of the plant in order to render robust the control scheme. We stress that such a solution is complicated to derive using other control approaches such as differential flatness or backstepping. In this respect, our proposal relies on a novel passivity-based approach which, by exploiting the natural energy exchange between the mechanical and electrical dynamics, renders possible the design of a control scheme with the above cited features. (shrink)

In this paper, we consider the nonlinear inverse-time heat problem with a conformable derivative concerning the time variable. This problem is severely ill posed. A new method on the modified integral equation based on two regularization parameters is proposed to regularize this problem. Numerical results are presented to illustrate the efficiency of the proposed method.

This article considers how the Japanese ports interact with the ports of China and along the 21st century Maritime Silk Road while they are embedded in the global port network, especially in the context of China’s Belt and Road Initiative. At a port level, it primarily uses connectivity analysis to analyze the port relations and significances in the maritime network. In contrast, at the network level, it applies the methods from network sciences to analyze the significances of these maritime networks (...) and the interactions among the maritime networks of Japan, China, and MSR. This article extracts a large-scale maritime network from ports and vessels’ profiles and data of vessels’ Automatic Identification System. It then examines the relations among the networks after defining the maritime networks, network generation schemes, and port network analysis tools. Based on the analysis results and findings, this study draws some implications for regional ports and shipping development and the global supply network. (shrink)

In this paper, a new 4D memristor-based chaotic system is constructed by using a smooth flux-controlled memristor to replace a resistor in the realization circuit of a 3D chaotic system. Compared with general chaotic systems, the chaotic system can generate coexisting infinitely many attractors. The proposed chaotic system not only possesses heterogeneous multistability but also possesses homogenous multistability. When the parameters of system are fixed, the chaotic system only generates two kinds of chaotic attractors with different positions in a very (...) large range of initial values. Different from other chaotic systems with continuous bifurcation diagrams, this system has discrete bifurcation diagrams when the initial values change. In addition, this paper reveals the relationship between the symmetry of coexisting attractors and the symmetry of initial values in the system. The dynamic behaviors of the new system are analyzed by equilibrium point and stability, bifurcation diagrams, Lyapunov exponents, and phase orbit diagrams. Finally, the chaotic attractors are captured through circuit simulation, which verifies numerical simulation. (shrink)

The shipping industry is developing towards intelligence rapidly. An accurate and fast method for ship image/video detection and classification is of great significance for not only the port management, but also the safe driving of Unmanned Surface Vehicle. Thus, this paper makes a self-built dataset for the ship image/video detection and classification, and its method based on an improved regressive deep convolutional neural network is presented. This method promotes the regressive convolutional neural network from four aspects. First, the feature extraction (...) layer is lightweighted by referring to YOLOv2. Second, a new feature pyramid network layer is designed by improving its structure in YOLOv3. Third, a proper frame and scale suitable for ships are designed with a clustering algorithm to reduced 60% anchors. Last, the activation function is verified and optimized. Then, the detecting experiment on 7 types of ships shows that the proposed method has advantage compared with the YOLO series networks and other intelligent methods. This method can solve the problem of low recognition rate and real-time performance for ship image/video detection and classification with a small dataset. On the testing-set, the final mAP is 0.9209, the Recall is 0.9818, the AIOU is 0.7991, and the FPS is 78–80 in video detection. Thus, this method provides a highly accurate and real-time ship detection method for the intelligent port management and visual processing of the USV. In addition, the proposed regressive deep convolutional network also has a better comprehensive performance than that of YOLOv2/v3. (shrink)

Based on the integer-order memristive system that can generate two-scroll, three-scroll, and four-scroll chaotic attractors, in this paper, we found other phenomena that two kinds of three-scroll chaotic attractors coexist in this system with different initial conditions. Furthermore, we proposed a coexisting fractional-order system based on the three-scroll chaotic attractors system, in which the three-scroll or four-scroll chaotic attractors emerged with different fractional-orders q. Meanwhile, with fractional-order q=0.965 and different initial conditions, coexistence of two kinds of three-scroll and four-scroll chaotic (...) attractors is found simultaneously. Finally, we discussed controlling chaos for the fractional-order memristive chaotic system. (shrink)

With the development of science and technology, products are being updated more and more quickly. Therefore, the diffusion of product information can make people better choose products. It is very meaningful to study the competition and diffusion of multiple product information. In this paper, the dual product information diffusion model with preference was proposed based on the mean-field equation in complex networks. The dynamic of the model was analyzed by the analysis of Markov chains. According to the Monte Carlo simulation (...) mechanism, the critical threshold of product information was obtained. The accuracy of the theory and model results is verified by computer simulation, and the scenarios in which the two products information are mutually promoted and mutually suppressed are simulated. (shrink)

The design of a swarm optimization-based fractional control for engineering application is an active research topic in the optimization analysis. This work offers the analysis, design, and simulation of a new neural network- based nonlinear fractional control structure. With suitable arrangements of the hidden layer neurons using nonlinear and linear activation functions in the hidden and output layers, respectively, and with appropriate connection weights between different hidden layer neurons, a new class of nonlinear neural fractional-order proportional integral derivative controller is (...) proposed and designed. It is obtained by approximating the fractional derivative and integral actions of the FOPID controller and applied to the motion control of nonholonomic differential drive mobile robot. The proposed NNFOPID controller’s parameters consist of derivative, integral, and proportional gains in addition to fractional integral and fractional derivative orders. The tuning of these parameters makes the design of such a controller much more difficult than the classical PID one. To tackle this problem, a new swarm optimization algorithm, namely, MAPSO-EFFO algorithm, has been proposed by hybridization of the modified adaptive particle swarm optimization and the enhanced fruit fly optimization to tune the parameters of the NNFOPID controller. Firstly, we developed a modified adaptive particle swarm optimization algorithm by adding an initial run phase with a massive number of particles. Secondly, the conventional fruit fly optimization algorithm has been modified by increasing the randomness in the initialization values of the algorithm to cover wider searching space and then implementing a variable searching radius during the update phase by starting with a large radius which decreases gradually during the searching phase. The tuning of the parameters of the proposed NNFOPID controller is carried out by reducing the MS error of 0.000059, whereas the MSE of the nonlinear neural system is equivalent to 0.00079. The NNFOPID controller also decreased control signals that drive DDMR motors by approximately 45 percent compared to NNPID and thus reduced energy consumption in circular trajectories. The numerical simulations revealed the excellent performance of the designed NNFOPID controller by comparing its performance with that of nonlinear neural controllers on the trajectory tracking of the DDMR with different trajectories as study cases. (shrink)

The eccentric connectivity polynomial of a connected graph G=VG,EG is described as ξcG,y=∑a∈VGdegGayecGa, where ecGa and degGa represent the eccentricity and the degree of the vertex a, respectively. The eccentric connectivity index can also be acquired from ξcG,y by taking its first derivatives at y=1. The ECI has been widely used for analyzing both the boiling point and melting point for chemical compounds and medicinal drugs in QSPR/QSAR studies. As the extension of ECI, the ECP also performs a pivotal role (...) in pharmaceutical science and chemical engineering. Graph products conveniently play an important role in many combinatorial applications, graph decompositions, pure mathematics, and applied mathematics. In this article, we work out the ECP of ℱ-sum of graphs. Moreover, we derive the explicit expressions of ECP for well-known graph products such as generalized hierarchical, cluster, and corona products of graphs. We also apply these outcomes to deduce the ECP of some classes of chemical graphs. (shrink)

In this paper, we propose a dynamic territorializing approach for the problem of distributing tasks among a group of robots. We consider the scenario in which a task comprises two subtasks—detection and completion; two complementary teams of agents, hunters and gatherers, are assigned for the subtasks. Hunters are assigned with the task of exploring the environment, i.e., detection, whereas gatherers are assigned with the latter subtask. To minimize the workload among the gatherers, the proposed algorithm utilizes the center of mass (...) of the known targets to form territories among the gatherers. The concept of center of mass has been adopted because it simplifies the task of territorial optimization and allows the system to dynamically adapt to changes in the environment by adjusting the assigned partitions as more targets are discovered. In addition, we present a game-theoretic analysis to justify the agents’ reasoning mechanism to stay within their territory while completing the tasks. Moreover, simulation results are presented to analyze the performance of the proposed algorithm. First, we investigate how the performance of the proposed algorithm varies as the frequency of territorializing is varied. Then, we examine how the density of the tasks affects the performance of the algorithm. Finally, the effectiveness of the proposed algorithm is verified by comparing its performance against an alternative approach. (shrink)

Multispectral image classification has long been the domain of static learning with nonstationary input data assumption. The prevalence of Industrial Revolution 4.0 has led to the emergence to perform real-time analysis in an online learning scenario. Due to the complexities in online and time-series multispectral image analysis, there is a high occurrence probability in variations of spectral bands from an input stream, which deteriorates the classification performance or makes them ineffective. To highlight this critical issue, firstly, this study formulates the (...) problem of new spectral band arrival as virtual concept drift. Secondly, an adaptive convolutional neural network ensemble framework is proposed and evaluated for a new spectral band adaptation. The adaptive CNN ensemble framework consists of five modules, including dynamic ensemble classifier module. DEC uses the weighted voting ensemble approach using multiple optimized CNN instances. DEC module can increase dynamically after new spectral band arrival. The proposed ensemble approach in the DEC module contributes the diversity to the ensemble system in the simple yet effective manner. The results have shown the effectiveness and proven the diversity of the proposed framework to adapt the new spectral band during online image classification. Moreover, the extensive training dataset, proper regularization, optimized hyperparameters, and more appropriate CNN architecture significantly contributed to retaining the performance accuracy. (shrink)

Road networks serve as the backbone of cities, shaping urban structure as well as providing the critical function of transport for people, goods, and services. The design and management of resilient road infrastructure, therefore, is essential for building a sustainable city. Road networks grow and evolve over time, such that their topology shifts from an initially planned state to the one that emerges from self-organization and urban growth. In this work, we use a dual mapping approach to compare the topological (...) features of road networks in 25 districts in Seoul, South Korea. By using average node degree as an indicator of the level of self-organization, we present that multiple topological variables including power-law exponent gradually shift as a network grows. By testing static error and attack tolerance of these networks, we also show that the gradual shift in topology also has an important implication in network resilience. We suggest a new method, inspired by Lorenz curve, for quantifying network vulnerability. This modified Lorenz curve enables calculating the relative impact of intensive attacks to random failures and shows that a more self-organized road network tends to become more vulnerable to selective attacks. (shrink)

The Foot-mounted Inertial Pedestrian-Positioning System based on the Micro-Inertial Measurement Unit is a good choice for the forest fire fighters when the Global Navigation Satellite System is unavailable. Zero Velocity Update provides a solution for reducing cumulative positioning errors caused by the integral calculation of the inertial navigation. However, the performance of ZUPT is highly affected by the low accuracy and high noise of the MIMU. The accuracy of conventional ZUPT for attitude alignment is reduced by the zero offset of (...) acceleration and the drift of a gyroscope during the standing phase. An initial alignment algorithm based on Adaptive Gradient Descent Algorithm is proposed. In the stepping phase, the extended Kalman filter is often used to correct attitude and position in track estimation. However, the measurement noise of the EKF is influenced by the high-frequency acceleration and angular velocity. Thus, the accuracy of the attitude and position will decrease. A double-constrained extended Kalman filtering is proposed. An adaptive parameter positively correlated with the acceleration and angular velocity is set, and the measurement noise in the DEKF is adaptively adjusted. The performance of the proposed method is verified by implementing the pedestrian test trajectory using MPU-9150 MIMU manufactured by InvenSense. The results show that the attitude error of the AGDA is 33.82% less than that of the conventional GDA. The attitude error of DEKF is 21.70% less than that of the conventional EKF. The experimental results verify the effectiveness and applicability of the proposed method. (shrink)

The vulnerability of network information systems has attracted considerable research attention in various domains including financial networks, transportation networks, and infrastructure systems. To comprehensively investigate the network vulnerability, well-designed attack strategies are necessary. However, it is difficult to formulate a global attack strategy as the complete information of the network is usually unavailable. To overcome this limitation, this paper proposes a novel prediction algorithm named Linkboost, which, by predicting the hidden edges of the network, can complement the seemingly missing but (...) potentially existing connections of the network with limited information. The key aspect of this algorithm is that it can deal with the imbalanced class distribution present in the network data. The proposed approach was tested on several types of networks, and the experimental results indicated that the proposed algorithm can successfully enhance the destruction rate of the network even with incomplete information. Furthermore, when the proportion of the missing information is relatively small, the proposed attack strategy relying on the high degree nodes performs even better than that with complete information. This finding suggests that the nodes important to the network structure and connectivity can be more easily identified by the links added by Linkboost. Therefore, the use of Linkboost can provide useful insight into the operation guidance and design of a more effective attack strategy. (shrink)

A Planetary Gear Train can be used in series-parallel transmission to redistribute powers. Selectable one-way clutches, compared with traditional friction clutches, can simplify controls and diversify patterns especially for hybrid transmissions. In this paper, a nonlinear torsional model of a power-split PGT coupled with three SOWCs is proposed. Piecewise nonlinearities of SOWCs as well as clearance, time-varying mesh stiffness, and synthetic transmission error of the PGT are considered. With a specified group of comprehensive evaluation indices, influences of piecewise nonlinearities of (...) SOWCs are explored. Simulation results show that the piecewise nonlinearities of SOWCs can diminish collision range and reduce resonances of the PGT. Further research studies on parameter configurations of each SOWC reveal that of the three SOWCs, stiffness and radius of the SOWC connected to the sun gear of the PGT are dominant factors. Large stiffness and effective radius of the SOWC render the PGT fall into chaos on lower meshing frequencies; however, enormous impact vibrations occur to the SOWC if it gets too soft. Additionally, the increase of the damping ratio of the SOWC connected to sun gear can distinctly reduce the vibration and maximum dynamic load of the system on the entire working range. (shrink)

In this paper, we introduce the definitions of d¯-shadowing property, d¯-shadowing property, topological ergodicity, and strong ergodicity of iterated function systems IFSf0,f1. Then, we show the following: 1 if IFSf0,f1 has the d¯-shadowing property, then ℱk has the d¯-shadowing property for any k∈Z+; 2 if ℱk has the d¯-shadowing property for some k∈Z+, then IFSf0,f1 has the d¯-shadowing property ; 3 if IFSf0,f1 has the d¯-shadowing property or d¯-shadowing property, and f0 or f1 is surjective, then IFSf0,f1 is chain mixing; (...) 4 let f0,f1 be open maps. For IFSf0,f1 with the d¯-shadowing property, if A⊂X is dense in X, and s is a minimal point of f0 or f1 for any s∈A, then IFSf0,f1 is strongly ergodic, and hence, ℱk is strongly ergodic; and 5 for IFSf0,f1 with the average shadowing property, if S⊂X is dense in X, and s is a quasi-weakly almost periodic point of f0 or f1 for any s∈S, then IFSf0,f1 is ergodic. (shrink)

A Mixed Logic Dynamic model and control method based on mode selection are proposed for the Buck convertor. In establishing the hybrid system model, the factors such as the inductor current are neglected, and the Model Predictive Control is used to switch the most favorable working state of the control target. Since the modeling process ignores the inductance and current, it is necessary to convert the optimization prediction control resulting to avoid the problem that the model is inconsistent with the (...) control object. The method proposed in this paper uses fewer auxiliary logic variables and mixed logic variables in the modeling process, simplifying the model and improving the solution speed. This method can not only make the Buck converter work in the Continuous Current Mode but also work in the Discontinuous Current Mode, extending the adjustment range of the Buck converter. The simulation results show that the proposed method has a better control performance than the traditional MLD model. (shrink)

Real-world complex systems always interact with each other, which causes these systems to collapse in an avalanche or cascading manner in the case of random failures or malicious attacks. The robustness of multilayer networks has attracted great interest, where the modeling and theoretical studies of which always rely on the concept of multilayer networks and percolation methods. A straightforward and tacit assumption is that the interdependence across network layers is strong, which means that a node will fail entirely with the (...) removal of all links if one of its interdependent nodes in other network layers fails. However, this oversimplification cannot describe the general form of interactions across the network layers in a real-world multilayer system. In this paper, we reveal the nature of the avalanche disintegration of general multilayer networks with arbitrary interdependency strength across network layers. Specifically, we identify that the avalanche process of the whole system can essentially be decomposed into two microscopic cascading dynamics in terms of the propagation direction of the failures: depth penetration and scope extension. In the process of depth penetration, the failures propagate from layer to layer, where the greater the number of failed nodes is, the greater is the destructive power that will emerge in an interdependency group. In the process of scope extension, failures propagate with the removal of connections in each network layer. Under the synergy of the two processes, we find that the percolation transition of the system can be discontinuous or continuous with changes in the interdependency strength across network layers, which means that a sudden system-wide collapse can be avoided by controlling the interdependency strength across network layers. Our work not only reveals the microscopic mechanism of global collapse in multilayer infrastructure systems but also provides stimulating ideas on intervention programs and approaches for cascade failures. (shrink)

In this research, we use the double-delayed feedback control method in order to control chaos in a finance system. Taking delays as parameters, the dynamic behavior of the system is investigated. Firstly, we study the local stability of equilibrium and the existence of local Hopf bifurcations. It can find that the delays can make chaos disappear and generate a stable equilibrium or periodic solution, which means the effectiveness of DDFC method. By using the normal form theory and center manifold argument, (...) one derives the explicit algorithm for determining the properties of bifurcation. In addition, we also apply some mathematical methods to show the stability changes of the financial system in two parameters’ τ1,τ2 plane. Finally, we give some numerical simulations by Matlab Microsoft to show the validity of theoretical analyses. (shrink)

Symmetry is an important property found in a large number of nonlinear systems. The study of chaotic systems with symmetry is well documented. However, the literature is unfortunately very poor concerning the dynamics of such systems when their symmetry is altered or broken. In this paper, we investigate the dynamics of a simple jerk system with hyperbolic tangent nonlinearity whose symmetry is broken by adding a constant term modeling an external excitation force. We demonstrate that the modified system experiences several (...) unusual and striking nonlinear phenomena including coexisting bifurcation branches, hysteretic dynamics, coexisting asymmetric bubbles, critical transitions, and multiple coexisting asymmetric attractors for some suitable ranges of system parameters. These features are highlighted by exploiting common nonlinear analysis tools such as graphs of largest Lyapunov exponent, bifurcation diagrams, phase portraits, and basins of attraction. The control of multistability is investigated by using the method of linear augmentation. We demonstrate that the multistable system can be converted to a monostable state by smoothly adjusting the coupling parameter. The theoretical results are confirmed by performing a series of PSpice simulations based on an electronic analogue of the system. (shrink)

In this paper, a new so-called iterative Laplace transform method is implemented to investigate the solution of certain important population models of noninteger order. The iterative procedure is combined effectively with Laplace transformation to develop the suggested methodology. The Caputo operator is applied to express the noninteger derivative of fractional order. The series form solution is obtained having components of convergent behavior toward the exact solution. For justification and verification of the present method, some illustrative examples are discussed. The closed (...) contact is observed between the obtained and exact solutions. Moreover, the suggested method has a small volume of calculations; therefore, it can be applied to handle the solutions of various problems with fractional-order derivatives. (shrink)

The connectivity of a network contains information about the relationships between nodes, which can denote interactions, associations, or dependencies. We show that this information can be analyzed by measuring the uncertainty contained in paths along nodes and links in a network. Specifically, we derive from first principles a measure known as effective information and describe its behavior in common network models. Networks with higher effective information contain more information in the relationships between nodes. We show how subgraphs of nodes can (...) be grouped into macronodes, reducing the size of a network while increasing its effective information. We find that informative higher scales are common in simulated and real networks across biological, social, informational, and technological domains. These results show that the emergence of higher scales in networks can be directly assessed and that these higher scales offer a way to create certainty out of uncertainty. (shrink)

This paper proposes a new no-equilibrium chaotic system that has the ability to yield infinitely many coexisting hidden attractors. Dynamic behaviors of the system with respect to the parameters and initial conditions are numerically studied. It shows that the system has chaotic, quasiperiodic, and periodic motions for different parameters and coexists with a large number of hidden attractors for different initial conditions. The circuit and microcontroller implementations of the system are given for illustrating its physical meaning. Also, the synchronization conditions (...) of the system are established based on the adaptive control method. (shrink)

After a theory of morphogenesis in chemical cells was introduced in the 1950s, much attention had been devoted to the numerical solution of reaction-diffusion partial differential equations. The Crank–Nicolson method has been a common second-order time-stepping procedure. However, the CN method may introduce spurious oscillations for nonsmooth data unless the time step size is sufficiently small. This article studies a nonoscillatory second-order time-stepping procedure for RD equations, called a variable-θmethod, as a perturbation of the CN method. In each time level, (...) the new method detects points of potential oscillations to implicitly resolve the solution there. The proposed time-stepping procedure is nonoscillatory and of a second-order temporal accuracy. Various examples are given to show effectiveness of the method. The article also performs a sensitivity analysis for the numerical solution of biological pattern forming models to conclude that the numerical solution is much more sensitive to the spatial mesh resolution than the temporal one. As the spatial resolution becomes higher for an improved accuracy, the CN method may produce spurious oscillations, while the proposed method results in stable solutions. (shrink)

A large number of clinical observations have showed that metabolites are involved in a variety of important human diseases in the recent years. Nonetheless, the inherent noise and incompleteness in the existing biological datasets are tough factors which limit the prediction accuracy of current computational methods. To solve this problem, in this paper, a prediction method, IBNPLNSMDA, is proposed which uses the improved bipartite network projection method to predict latent metabolite-disease associations based on linear neighborhood similarity. Specifically, liner neighborhood similarity (...) matrix about metabolites is reconstructed according to the new feature which is gained by the known metabolite-disease associations and relevant integrated similarities. The improved bipartite network projection method is adopted to infer the potential associations between metabolites and diseases. At last, IBNPLNSMDA achieves a reliable performance in LOOCV outperforming the compared methods. In addition, in case studies of four common human diseases, simulation results confirm the utility of our method in discovering latent metabolite-disease pairs. Thus, we believe that IBNPLNSMDA could serve as a reliable computational tool for metabolite-disease associations prediction. (shrink)

Today’s remarkable challenge of maritime transportation industry is the detrimental contamination generation from fossil fuels. To tackle such a challenge and reduce the contribution into air pollution, different power solutions have been considered; among others, hybrid energy-based solutions are powering many ferry boats. This paper introduces an energy management strategy for a hybrid energy system of a ferry boat with the goal to optimize the performance and reduce the operation cost. HES considered for the ferry boat consists of different devices (...) such as proton exchange membrane fuel cell, LI-ION battery bank, and cold ironing. PEMFC systems are appropriate to employ as they are not polluting. The battery bank compensates for the abrupt variations of the load as the fuel cell has a slow dynamic against sudden changes of the load. Also, CI systems can improve the reduction of the expenses of energy management, during hours where the ferry boat is located at the harbor. To study the performance, cost and the pollution contribution CO2, NOX, SOX of the proposed hybrid energy management strategy, we compare it against three various types of HEM from the state-of-the-art and also available rule-based methods in the literature. The analysis results show a high applicability of the proposed HES. All results in this paper have been obtained in the MATLAB software environment. (shrink)

The phytoplankton-fish model for catching fish with impulsive feedback control is established in this paper. Firstly, the Poincaré map for the phytoplankton-fish model is defined, and the properties of monotonicity, continuity, differentiability, and fixed point of Poincaré map are analyzed. In particular, the continuous and discontinuous properties of Poincaré map under different conditions are discussed. Secondly, we conduct the analysis of the necessary and sufficient conditions for the existence, uniqueness, and global stability of the order-1 periodic solution of the phytoplankton-fish (...) model and obtain the sufficient conditions for the existence of the order-kk≥2 periodic solution of the system. Numerical simulation shows the correctness of our results which show that phytoplankton and fish with the impulsive feedback control can live stably under certain conditions, and the results have certain reference value for the dynamic change of phytoplankton in aquatic ecosystems. (shrink)

Data envelopment analysis has proven to be a powerful technique for assessing the relative performance of a set of homogeneous decision-making units. A critical feature of conventional DEA approaches is that only one or several sets of optimal virtual weights are used to aggregate the ratio performance efficiencies, and thus, the efficiency scores might be too extreme or even unrealistic. Alternatively, this paper aims at developing a new performance dominance probability approach and applying it to analyze the banking operations in (...) China. Towards that purpose, we first propose an extended eco-inefficiency model based on the DEA methodology to address banking activities and their possible relative performances. Since the eco-inefficiency will be obtained using a set of optimal weights, we further build a performance dominance structure by considering all sets of feasible weights from a data-driven perspective. Then, we develop two pairwise eco-inefficiency dominance concepts and propose the inefficiency dominance probability model. Finally, we illustrate the eco-inefficiency dominance probability approach with 32 Chinese listed banks from 2014 to 2018 to demonstrate the usefulness and efficacy of the proposed method. (shrink)

Additive eigenvalue problem appears in ergodic optimal control or the homogenization of Hamilton–Jacobi equations. It has wide applications in several fields including computer science and then attracts the attention. In this paper, we consider the Poisson equations with the prescribed contact angle boundary condition and finally derive the existence and the uniqueness of the solution to the additive problem of the Laplace operator with the prescribed contact angle boundary condition.

Innovation subsidy is of great significance to promoting enterprise innovation development. However, in recent years, the frequent occurrence of R&D subsidy deception in China has greatly reduced effectiveness of innovation. From the perspective of the strategic choice motivation of the innovation subject, this paper constructs a multiplayer stochastic evolutionary game model. The influence of each variable on the subject strategy adoption is analyzed by simulation. There are two important findings in this paper. First, the paper confirms that there is an (...) optimal boundary for the high subsidies received by enterprises and academic institutions, and the “subsidy boundary” is solved through the model. Second, this paper analyzes the effectiveness of the regulation of each variable through simulation and provides management and policy implications. (shrink)

This paper studies the problem of leader-following synchronization for complex networks subject to delayed impulsive disturbances, where two kinds of time delays considered exist in internal complex networks and impulsive disturbances. Some delay-dependent sufficient criteria are derived in terms of linear matrix inequalities by using the delayed impulsive differential inequality method. Moreover, a feedback controller is designed to realize desired synchronization via the established LMIs. Our proposed results show that the requirements of impulse intervals and impulse sizes are dropped, and (...) delayed impulses and large scale impulses are allowed to coexist. Finally, some examples are given to show the effectiveness of the obtained results. (shrink)

The real-time and high-continuity requirements of the edge computing network gain more and more attention because of its active defence problem, that is, a data-driven complex problem. Due to the dual constraints of the hybrid feature of edge computing networks and the uncertainty of new attack features, implementing active defence measures such as detection, evasion, trap, and control is essential for the security protection of edge computing networks with high real-time and continuity requirements. The basic idea of safe active defence (...) is to make the defence gain more significant than the attack loss. To encounter the new attacks with uncertain features introduced by the ubiquitous transmission network in the edge computing network, this paper investigates the attack behaviour and presents an attack-defence mechanism based on game theory. Based on the idea of dynamic intrusion detection, we utilize the game theory in the field of edge computing network and suggest a data-driven mimicry intrusion detection game model-based technique called GLIDE. The game income of participants and utility computing methods under different deployment strategies are analysed in detail. According to the proof analysis of the Nash equilibrium condition in the model, the contradictory dynamic game relationship is described. Therefore, the optimal deployment strategy of the multiredundancy edge computing terminal intrusion detection service in the edge computing network is obtained by solving the game balance point. The detection probability of the edge computing network for network attacks is improved, and the cost of intrusion detection of the edge computing network is reduced. (shrink)

A reverse recycling supply chain consisting of two recyclers is established in this paper, which takes into account the fact that the recyclers will consider the issue of fair concern in pricing. The paper discusses the local stability of the Nash equilibrium point in this price game model showing that the fair concern factors will reduce the stable area of the system. The paper also discusses the impacts of the sensitivity of the recovery price and the price cross coefficient on (...) the stable area of the system. Through the method of system simulation and use of some indicators, such as the singular attractor, bifurcation diagram, attraction domain, power spectrum, and maximum Lyapunov exponent, the characteristics of the system at different times will be illustrated. (shrink)

This paper puts forward a class of ratio-dependent Leslie predator-prey models. Firstly, a neutral delay predator-prey model with ratio dependence and impulse control is established and the existence of positive periodic solutions is proved by the coincidence degree theory. Secondly, a stochastic disturbance Leslie model of Smith growth is obtained when the interference of white noise is taken into consideration and the impact of delay is ignored. Applying Ito^’s formula, we get the conditions of system persistence and extinction. Finally we (...) verify the correctness of theoretical analysis with numerical simulations. (shrink)

In this study, hybrid state-action-reward-state-action and Q-learning algorithms are applied to different stages of an upper confidence bound applied to tree search for Tibetan Jiu chess. Q-learning is also used to update all the nodes on the search path when each game ends. A learning strategy that uses SARSAλ and Q-learning algorithms combining domain knowledge for a feedback function for layout and battle stages is proposed. An improved deep neural network based on ResNet18 is used for self-play training. Experimental results (...) show that hybrid online and offline reinforcement learning with a deep neural network can improve the game program’s learning efficiency and understanding ability for Tibetan Jiu chess. (shrink)

In view of the particularity and high risk of coal mining industry, the decision-making behavior of multiple agents inside the coal-mine enterprise plays a very important role in ensuring the safety and sustainable development of coal mining industry. The existing literature studies on coal-mine safety production focus mainly on statically analyzing the game among the external entities such as the government, the enterprises themselves, and the employees inside the enterprise from a macro perspective,are short of research on revealing the dynamic (...) interactions among the actors directly involved in the coal-mine accidents and also on proposals for effective interactions that will lead to improved safety outcomes. Therefore, this paper explores the use of evolutionary game theory to describe the interactions among the stakeholders in China’s coal-mine safety production system, which includes the organization, the first-line miners, and the first-line managers. Moreover, the paper also explores dynamic simulations of the evolutionary game model to analyze the stability of stakeholder interactions and to identify equilibrium solutions. The simulation results show that when certain conditions are met, the decision-making behavior of the organization, miners, and managers can evolve into the unique ideal steady state. In addition, the strategy portfolio with a relatively high initial proportion of three agents converges more quickly to an ideal state than a relatively low strategy portfolio. Moreover, the stable state and equilibrium values are not affected by the initial value changes. Finally, we find that the combination of positive incentive policies and strict penalties policies can make the evolutionary game system converge to desired stability faster. The application of the evolutionary game and numerical simulation when simulating the multiplayer game process of coal-mine safety production is an effective way, which provides a more effective solution to the safety and sustainable development of coal mining industry. (shrink)

This paper concerns robust stabilization of nonlinear fractional order interconnected systems. Based on uncertain fractional order Takagi–Sugeno fuzzy model and the fractional order extension of lyapunov direct method, a parallel distributed compensate controller is designed to asymptotically stabilize the fractional order interconnected systems. Then, a sufficient condition is given in the format of linear matrix inequalities. Simulation example is given to validate the effectiveness of the approach.

We show the effect of investor anxiety on momentum in the Chinese stock market. In this market dominated by retail investors, we examine the momentum profits in 900 types of daily testing periods. We find prevalent price reversals in the long formation and holding periods in the Chinese A-share market. Compared to Goyal and Wahal, Wang and Xie, and Kang et al. who found no momentum, our novel finding from a daily basis is that the A-share market presents price momentum (...) within the short formation and holding periods. We first test the momentum profits under different strengths of anxiety in the A-share market. The stocks held by the least anxious investors elicit the strongest price momentum, whereas the stocks held by the most anxious investors encounter much weaker price momentum in the A-share market. According to our empirical outcomes, the A-share market overall exhibits higher anxiety and weaker momentum, whereas the B-share market embodies milder anxiety and stronger momentum. From the results of single market and cross-market comparisons, the intrinsic anxiety of retail investors is an essential factor stimulating the Chinese stock market to be prone to price reversals. (shrink)

Two types of coupled different dimensional delayed reaction-diffusion neural network models without and with parametric uncertainties are analyzed in this paper. On the one hand, passivity and synchronization of the raised network model with certain parameters are studied through exploiting some inequality techniques and Lyapunov stability theory, and some adequate conditions are established. On the other hand, the problems of robust passivity and robust synchronization of CDDDRDNNs with parameter uncertainties are solved. Finally, two numerical examples are given to testify the (...) effectiveness of the derived passivity and synchronization conditions. (shrink)

Cultural assets preserve the traces of people’s life history around the world. With an understanding of the historical context and meaning of cultural assets, people would cherish their value and then adopt appropriate cultural resource preservation strategies. Human rights as the universal value refer to the inalienable and basic rights of human beings. This article uses the National Cultural Assets Network to query Taiwan’s human rights-themed cultural assets, and I apply the spatial information technology of the DocuSky digital humanities academic (...) research platform to draw the maps with GIS and visualization tools. Also, I apply spatial information to the academic research of human rights-themed cultural assets, aiming to deepen local cultural identity and unveiling that human studies influence spatial practice. Tourism is an important experience economy. Based on the value of Taiwan’s human rights-themed cultural assets, I plan to guide the human rights journey in Taipei to share Taiwan’s experience of happiness with the world, as well. (shrink)

In this paper, a nonsingular fast terminal adaptive neurosliding mode control for spacecraft formation flying systems is investigated. First, a supertwisting disturbance observer is employed to estimate external disturbances in the system. Second, a fast nonsingular terminal sliding mode control law is proposed to guarantee the tracking errors of the spacecraft formation converge to zero in finite time. Third, for the unknown parts in the spacecraft formation flying dynamics, we proposed an adaptive neurosliding mode control law to compensate them. The (...) proposed sliding mode control laws not only achieve the formation but also alleviate the effect of the chattering. Finally, simulations are used to demonstrate the effectiveness of the proposed control laws. (shrink)

Recently, algebraic characterization of multiagent controllability through its topology has been widely concerned by the systems and control community. The controllability of leader-follower networked multiagent systems under the framework of generic linear dynamics is firstly discussed via λ-matrix. Some new algebra-theoretic necessary and/or sufficient conditions of the controllability for generic linear multiagent systems are established. Moreover, the controllable conditions for multiagent networks with special topological graphs through λ-matrix are presented.

The group controllability of continuous-time multiagent systems with multiple leaders is considered in this paper, where the entire group is compartmentalized into a few subgroups. The group controllability concept of continuous-time MASs with multiple leaders is put forward, and the group controllability criteria are obtained for switching and fixed topologies, respectively. Finally, the numerical simulations are given to prove the validity of the theoretical results.

This paper focuses on the stability problems of continuous linear systems with two additive time-varying delay components. Firstly, an effective and simple Lyapunov–Krasovskii functional is established, which not only takes adequate information of delay components and their upper bounds into consideration but also establishes a simpler form to decrease the computational complexity. Secondly, an improved delay-dependent stability criterion together with its corollary is obtained by employing the generalized free-weighting-matrix-based inequality and some other techniques to calculate the derivative of the constructed (...) LKF, which will further reduce the introduced estimation error and make the criteria less conservative. Lastly, a numerical example is presented to illustrate the less conservatism and lower computational complexity of the derived results. (shrink)

Nowadays, scholar recommender systems often recommend academic papers based on users’ personalized retrieval demands. Typically, a recommender system analyzes the keywords typed by a user and then returns his or her preferred papers, in an efficient and economic manner. In practice, one paper often contains partial keywords that a user is interested in. Therefore, the recommender system needs to return the user a set of papers that collectively covers all the queried keywords. However, existing recommender systems only use the exact (...) keyword matching technique for recommendation decisions, while neglecting the correlation relationships among different papers. As a consequence, it may output a set of papers from multiple disciplines that are different from the user’s real research field. In view of this shortcoming, we propose a keyword-driven and popularity-aware paper recommendation approach based on an undirected paper citation graph, named PRkeyword+pop. At last, we conduct large-scale experiments on the real-life Hep-Th dataset to further demonstrate the usefulness and feasibility of PRkeyword+pop. Experimental results prove the advantages of PRkeyword+pop in searching for a set of satisfactory papers compared with other competitive approaches. (shrink)

Let Γ be a simple connected undirected graph with vertex set VΓ and edge set EΓ. The metric dimension of a graph Γ is the least number of vertices in a set with the property that the list of distances from any vertex to those in the set uniquely identifies that vertex. For an ordered subset W=w1,w2,…,wk of vertices in a graph Γ and a vertex v of Γ, the metric representation of v with respect to W is the k-vector (...) rvW=dv,w1,dv,w2,…,dv,wk. If every pair of distinct vertices of Γ have different metric representations, then the ordered set W is called a resolving set of Γ. It is known that the problem of computing this invariant is NP-hard. In this paper, we consider the problem of determining the cardinality ψΓ of minimal doubly resolving sets of Γ and the strong metric dimension for the jellyfish graph JFGn,m and the cocktail party graph CPk+1. (shrink)

In this paper, a fully discretized finite difference scheme is derived for two-dimensional wave equation with damped Neumann boundary condition. By discrete energy method, the proposed difference scheme is proven to be of second-order convergence and of unconditional stability with respect to both initial conditions and right-hand term in a proper discretized L2 norm. The theoretical result is verified by a numerical experiment.

In this paper, a multi-unmanned underwater vehicle cooperative dynamic maneuver decision-making algorithm is proposed based on the combination of game theory and intuitionistic fuzzy sets. Underwater environments with weak connectivity, underwater noise, and dynamic uncertainties are fully considered through intuitionistic fuzzy sets, which solves one of the main problems in making decisions underwater. Subsequently, the intuitionistic fuzzy multiattribute evaluation of a UUV maneuver strategy is conducted, and the intuitionistic fuzzy payment matrix of the cooperative dynamic maneuver game is obtained. Thereafter, (...) the Nash equilibrium condition is proposed to satisfy the intuitionistic fuzzy total order, and the Nash equilibrium maneuver decision-making model under a dynamic underwater environment is established. Meanwhile, the modified particle swarm optimization method is presented to solve the established problem and find the optimal strategy. Finally, an example is used to verify the superiority of the proposed cooperative dynamic maneuver decision-making algorithm. (shrink)

The conjugate gradient method is very effective in solving large-scale unconstrained optimal problems. In this paper, on the basis of the conjugate parameter of the conjugate descent method and the second inequality in the strong Wolfe line search, two new conjugate parameters are devised. Using the strong Wolfe line search to obtain the step lengths, two modified conjugate gradient methods are proposed for general unconstrained optimization. Under the standard assumptions, the two presented methods are proved to be sufficient descent and (...) globally convergent. Finally, preliminary numerical results are reported to show that the proposed methods are promising. (shrink)

In this paper, the fractional order models are used to study the propagation of ion-acoustic waves in ultrarelativistic plasmas in nonplanar geometry. Firstly, according to the control equations, -dimensional cylindrical Kadomtsev–Petviashvili equation and 2D cylindrical-modified Kadomtsev–Petviashvili equation are derived by using multiscale analysis and reduced perturbation methods. Secondly, using the semi-inverse method and the fractional variation principle, the abovementioned equations are derived the time-space fractional equations. Furthermore, based on the fractional order transformation, the 1-decay mode solution of the TSF-CKP equation (...) is obtained by using the simplified homogeneous balance method, and using the generalized hyperbolic-function method, the exact analytic solution of TSF-CMKP equation is obtained. Finally, the effects of the phase speed λ, electron number density and the fractional order α,β,ω on the propagation of ion-acoustic waves in ultrarelativistic plasmas are analyzed. (shrink)

Data stream classification becomes a promising prediction work with relevance to many practical environments. However, under the environment of concept drift and noise, the research of data stream classification faces lots of challenges. Hence, a new incremental ensemble model is presented for classifying nonstationary data streams with noise. Our approach integrates three strategies: incremental learning to monitor and adapt to concept drift; ensemble learning to improve model stability; and a microclustering procedure that distinguishes drift from noise and predicts the labels (...) of incoming instances via majority vote. Experiments with two synthetic datasets designed to test for both gradual and abrupt drift show that our method provides more accurate classification in nonstationary data streams with noise than the two popular baselines. (shrink)

Exact periodic and localized solutions of a nonlocal Mel′nikov equation are derived by the Hirota bilinear method. Many conventional nonlocal operators involve integration over a spatial or temporal domain. However, the present class of nonlocal equations depends on properties at selected far field points which result in a potential satisfying parity time symmetry. The present system of nonlocal partial differential equations consists of two dependent variables in two spatial dimensions and time, where the dependent variables physically represent a wave packet (...) and an auxiliary scalar field. The periodic solutions may take the forms of breathers and line solitons. The localized solutions can include propagating lumps and rogue waves. These nonsingular solutions are obtained by appropriate choice of parameters in the Hirota expansion. Doubly periodic solutions are also computed with elliptic and theta functions. In sharp contrast with the local Mel′nikov equation, the auxiliary scalar field in the present set of solutions can attain complex values. Through a coordinate transformation, the governing equation can reduce to the Schrödinger–Boussinesq system. (shrink)

The complex systems with edge computing require a huge amount of multifeature data to extract appropriate insights for their decision making, so it is important to find a feasible feature selection method to improve the computational efficiency and save the resource consumption. In this paper, a quantum-based feature selection algorithm for the multiclassification problem, namely, QReliefF, is proposed, which can effectively reduce the complexity of algorithm and improve its computational efficiency. First, all features of each sample are encoded into a (...) quantum state by performing operations CMP and Ry, and then the amplitude estimation is applied to calculate the similarity between any two quantum states. According to the similarities, the Grover–Long method is utilized to find the nearest k neighbor samples, and then the weight vector is updated. After a certain number of iterations through the above process, the desired features can be selected with regards to the final weight vector and the threshold τ. Compared with the classical ReliefF algorithm, our algorithm reduces the complexity of similarity calculation from O to O, the complexity of finding the nearest neighbor from O to OM, and resource consumption from O to O. Meanwhile, compared with the quantum Relief algorithm, our algorithm is superior in finding the nearest neighbor, reducing the complexity from O to OM. Finally, in order to verify the feasibility of our algorithm, a simulation experiment based on Rigetti with a simple example is performed. (shrink)

In this paper, a new fractional-order discrete noninvertible map of cubic type is presented. Firstly, the stability of the equilibrium points for the map is examined. Secondly, the dynamics of the map with two different initial conditions is studied by numerical simulation when a parameter or a derivative order is varied. A series of attractors are displayed in various forms of periodic and chaotic ones. Furthermore, bifurcations with the simultaneous variation of both a parameter and the order are also analyzed (...) in the three-dimensional space. Interior crises are found in the map as a parameter or an order varies. Thirdly, based on the stability theory of fractional-order discrete maps, a stabilization controller is proposed to control the chaos of the map and the asymptotic convergence of the state variables is determined. Finally, the synchronization between the proposed map and a fractional-order discrete Loren map is investigated. Numerical simulations are used to verify the effectiveness of the designed synchronization controllers. (shrink)

The problem of almost disturbance decoupling is addressed for fractional-order nonlinear systems. A new definition for the norm is proposed to describe the effect of disturbances on the output tracking error for fractional-order systems. Based on the Lyapunov stability theory and the backstepping design method, a tracking controller is constructed to make the output tracking error converge to zero without external disturbances and to attenuate the effect of disturbances on the tracking error at zero initial conditions. In order to validate (...) these theoretical results, a numerical example and two practical examples are given. (shrink)

In this paper, we investigate the finite-time synchronization control for a class of nonlinear coupled multiweighted complex networks with Markovian switching and time-varying delay analytically and quantitatively. The value of this study lies in four aspects: First, it designs the finite-time synchronization controller to make the NCMWCNs with Markovian switching and time-varying delay achieve global synchronization in finite time. Second, it derives two kinds of finite-time estimation approaches by analyzing the impact of the nonlinearity of nonlinear coupled function on synchronization (...) dynamics and synchronization convergence time. Third, it presents the relationship between Markovian switching parameters and synchronization problems of subsystems and the overall system. Fourth, it provides some numerical examples to demonstrate the effectiveness of the theoretical results. (shrink)

Affected by the Internet, computer, information technology, etc., building a smart city has become a key task of socialist construction work. The smart city has always regarded green and low-carbon development as one of the goals, and the carbon emissions of the auto parts industry cannot be ignored, so we should carry out energy conservation and emission reduction. With the rapid development of the domestic auto parts industry, the number of car ownership has increased dramatically, producing more and more CO2 (...) and waste. Facing the pressure of resources, energy, and environment, the effective and circular operation of the auto parts supply chain under the low-carbon transformation is not only a great challenge, but also a development opportunity. Under the background of carbon emission, this paper establishes a decision-making optimization model of the low-carbon supply chain of auto parts based on carbon emission responsibility sharing and resource sharing. This paper analyzes the optimal decision-making behavior and interaction of suppliers, producers, physical retailers, online retailers, demand markets, and recyclers in the auto parts industry, constructs the economic and environmental objective functions of low-carbon supply chain management, applies variational inequality to analyze the optimal conditions of the whole low-carbon supply chain system, and finally carries out simulation calculation. The research shows that the upstream and downstream auto parts enterprises based on low-carbon competition and cooperation can effectively manage the carbon footprint of the whole supply chain through the sharing of responsibilities and resources among enterprises, so as to reduce the overall carbon emissions of the supply chain system. (shrink)

To deal with coordination problem of a supply chain consisting of two competitive suppliers and a dominant retailer, considering these factors such as cooperation effort degrees and competition on the supply chain members, we establish a two-stage model considering cooperation effort degrees and competition of the suppliers from the perspectives of decentralized decision and centralized decision and exploit it to discuss the optional decisions and explore the impact of cooperation effort degrees on the profits of supply chain members. Then, we (...) use a group negotiation model to establish a coordination mechanism. The results reveal that the decision variables and overall profit of the supply chain of suppliers and retailers under centralized decisions are better than those under the decentralized decisions. Besides, the degree of competition and price sensitivity have positive and negative effects on the efforts of suppliers and retailers, respectively. Meanwhile, the degree of cooperation between suppliers and retailers affects the profits of supply chain members and the whole supply chain in different degrees. Finally, the proposed value-added profit distribution mechanism can effectively deal with conflict problem and guarantee supply chain members and supply chain to maximize their profits and adopt the centralized decision. (shrink)

The stabilization problem of the complex chaotic system is investigated in this paper. First, a systematic method is proposed, by which a given complex chaotic system can be transformed into its equivalent real chaotic system. Then, both simple and physical controller is designed for the corresponding real chaotic system by the dynamic feedback control method, thereby the controller for the original complex chaotic system is obtained. Especially, for some complex system, the controller is obtained by the linear feedback control method. (...) Finally, two illustrative examples with numerical simulations are used to verify the validity and effectiveness of the theoretical results. (shrink)

Corporate social responsibility has a significant impact on the operation of enterprises. This study analyzes the production and coordination decisions of closed-loop supply chain by establishing two assumptions of endogenous and exogenous CSR. The results reveal that, for ordinary consumers, CSR is quantified as the parameter of consumer surplus, which has an impact on the patent licensing fee, revenue-sharing ratio, and so on, and which not only increases the sales quantity in CLSC but also creates more value for the manufacturer (...) and the retailer. Considering endogenous CSR, the study found that the manufacturer’s CSR level and the manufacturer’s and the retailer’s profits both increase with the proportion of CSR-sensitive consumers. In the endogenous model, the manufacturer sets a higher wholesale price and lower patent licensing fee than in the exogenous model. Perfect coordination in the two models can be achieved by setting a revenue-sharing ratio related to wholesale price and patent licensing fee. In practice, improving the social responsibility consciousness of consumers and raising enterprises’ CSR level can achieve a win-win situation for revenues and social welfare. (shrink)

The stability problem of networked control system with cyberattacks and processing delay is considered under an event-triggered scheme. An improved distributed event-triggered mechanism is proposed, which optimizes the performance of system dynamics and decreases the network transmission load simultaneously. By means of Bessel–Legendre inequality method and constructing an active Lyapunov–Krasovskii functional, a series of larger upper bounds of delay are obtained corresponding to the order of N. It is worth mentioning that the upper bound increases with N, which means that (...) the conservatism of the stability criterion lowers. Finally, a distributed event-triggered controller is designed. The validity of the results is verified by numerical examples. (shrink)

Flexibility is an important indicator to consider the uncertain information processing ability of the supply chain comprehensively. It is a powerful way to improve the efficiency and quality of supply chain operation by evaluating the level of supply chain flexibility effectively. The traditional method is used to decompose the supply chain flexibility evaluation indicators from the perspective of system structure or cost saving, but these indicators cannot truly describe the dynamics of the supply chain operation. Otherwise, supply chain flexibility evaluation (...) is a typical multiobjective evaluation; there are some incompatibilities between these flexible evaluation indicators, and the common evaluation methods are difficult to deal with such contradictions. In this paper, the dynamic characteristics of supply chain operation are considered, and the evaluation system of supply chain flexibility is designed from the perspective of operation efficiency. The matter-element analysis theory is used to create the comprehensive appraisal model of supply chain flexibility. The matter-element matrix solves the uncertainty and incompatibility of the evaluated factors used to assess supply chain flexibility. The paper evaluates the performance of four autoservice companies and concludes that the evaluation grades of the four companies are in line with the reality, indicating that the evaluation system and the method are effective and credible. (shrink)

A weight least squares algorithm is developed for rational models with outliers in this paper. Different weights are assigned for each cost function, and by calculating the derivatives of these cost functions, the parameter estimates can be estimated. Compared with the traditional least squares algorithm, the proposed algorithm can remove the bad effect caused by the outliers, thus has more accurate parameter estimates. A simulation example is proposed to validate the effectiveness of the proposed algorithm.

In this work, we are pleased to investigate multiple positive solutions for a system of Caputo fractional p-Laplacian boundary value problems, and we also provide an example for illustrating our main results.

This paper presents an active fault-tolerant method to mitigate sensor failures in multimotor synchronous control. First, inspired by the construction of the coupling matrix in complex network synchronous output, a consistent matrix is designed based on structural redundancy in synchronous control. This consistent matrix has two advantages: one is that it can reflect different sensor output similarities and the other one is that it can detect, locate, and estimate the sensor fault. Then, the fault information is integrated into the design (...) of tolerance control with an improved mean feedback mechanism. The proposed method is suitable for both single and multiple fault situations, and its effectiveness is finally verified by both MATLAB simulation and the ABB semiphysical experimental platform. (shrink)

In the field of ophthalmology, diabetic retinopathy is a major cause of blindness. DR is based on retinal lesions including exudate. Exudates have been found to be one of the signs and serious DR anomalies, so the proper detection of these lesions and the treatment should be done immediately to prevent loss of vision. In this paper, pretrained convolutional neural network- based framework has been proposed for the detection of exudate. Recently, deep CNNs were individually applied to solve the specific (...) problems. But, pretrained CNN models with transfer learning can utilize the previous knowledge to solve the other related problems. In the proposed approach, initially data preprocessing is performed for standardization of exudate patches. Furthermore, region of interest localization is used to localize the features of exudates, and then transfer learning is performed for feature extraction using pretrained CNN models. Moreover, the fused features from fully connected layers are fed into the softmax classifier for exudate classification. The performance of proposed framework has been analyzed using two well-known publicly available databases such as e-Ophtha and DIARETDB1. The experimental results demonstrate that the proposed pretrained CNN-based framework outperforms the existing techniques for the detection of exudates. (shrink)

Are nearby places described by related words? In this article, we transfer this research question in the field of lexical encoding of geographic information onto the level of intertextuality. To this end, we explore Volunteered Geographic Information to model texts addressing places at the level of cities or regions with the help of so-called topic networks. This is done to examine how language encodes and networks geographic information on the aboutness level of texts. Our hypothesis is that the networked thematizations (...) of places are similar, regardless of their distances and the underlying communities of authors. To investigate this, we introduce Multiplex Topic Networks, which we automatically derive from Linguistic Multilayer Networks as a novel model, especially of thematic networking in text corpora. Our study shows a Zipfian organization of the thematic universe in which geographical places are located in online communication. We interpret this finding in the context of cognitive maps, a notion which we extend by so-called thematic maps. According to our interpretation of this finding, the organization of thematic maps as part of cognitive maps results from a tendency of authors to generate shareable content that ensures the continued existence of the underlying media. We test our hypothesis by example of special wikis and extracts of Wikipedia. In this way, we come to the conclusion that geographical places, whether close to each other or not, are located in neighboring semantic places that span similar subnetworks in the topic universe. (shrink)

In this paper, we focus on the interaction solutions of a -dimensional Vakhnenko equation. By using Hirota’s transformation combined with the three-wave method and with symbolic computation, some interaction solutions which include interaction solutions between exponential and trigonometric functions and interaction solutions between exponential and trigonometric and hyperbolic functions are presented.

In this paper, a nonlinear viscoelastic Kirchhoff equation in a bounded domain with a time-varying delay term and logarithmic nonlinearity in the weakly nonlinear internal feedback is considered, where the global and local existence of solutions in suitable Sobolev spaces by means of the energy method combined with Faedo-Galerkin procedure is proved with respect to the condition of the weight of the delay term in the feedback and the weight of the term without delay and the speed of delay. Furthermore, (...) a general stability estimate using some properties of convex functions is given. These results extend and improve many results in the literature. (shrink)

This paper deals with the global existence of solutions in a bounded domain for nonlinear viscoelastic Kirchhoff system with a time varying delay by using the energy and Faedo–Galerkin method with respect to the delay term weight condition in the feedback and the delay speed. Furthermore, by using some convex functions properties, we prove a uniform stability estimate.

In this work, a novel hyperjerk system, with hyperbolic sine function as the only nonlinear term, is proposed, as a modification of a hyperjerk system proposed by Leutcho et al. First, a dynamical analysis on the system is performed and interesting phenomena concerning chaos theory, such as route to chaos, antimonotonicity, crisis, and coexisting attractors, are studied. For this reason, the system’s bifurcation diagrams with respect to different parameter values are plotted and its Lyapunov exponents are computed. Afterwards, the synchronization (...) of the system is considered, using active control. The proposed system is then applied, as a chaotic generator, to the problem of chaotic path planning, using a combination of sampling and a modulo tactic technique. (shrink)

Potential damages to existing tunnels represent a major concern for constructing deep excavations in urban areas. The uncertainty of subsurface conditions and the nonlinear interactions between multiple agents make the prediction of the response of tunnel induced by adjacent excavations a rather difficult and complex task. This paper proposes an initiative to solve this problem by using process-based modelling, where information generated from the interaction processes between soils, structures, and excavation activities is utilized to gradually reduce uncertainty related to soil (...) properties and to learn the interaction patterns through machine learning techniques. To illustrate such a concept, this paper presents a simple process-based model consisting of artificial neural network module, inverse modelling module, and mechanistic module. The ANN module is trained to learn and recognize the patterns of the complex interactions between excavation deformations, its geometries and support structures, and soil properties. The inverse modelling module enables a gradual reduction of uncertainty associated with soil characterizations by accumulating field observations during the construction processes. Based on the inputs provided by the former two modules, the mechanistic module computes the response of tunnel. The effectiveness of the proposed process-based model is evaluated against high-fidelity numerical simulations and field measurements. These evaluations suggest that the strategy of combining artificial intelligence techniques with information generated during interaction processes can represent a promising approach to solve complex engineering problems in conventional industries. (shrink)

In this paper, we propose a new approximation method, which differs from the traditional differential transform method in calculating the coefficients of Taylor polynomials. Numerical examples are presented to illustrate the efficiency and reliability of our own method. Namely, two Sturm–Liouville problems are solved by the present α-parameterized differential transform method, and the obtained results are compared with those obtained by the classical DTM and by the analytical method. The result reveals that α-parameterized differential transform method is a simple and (...) effective numerical algorithm. (shrink)

In this paper, Daftardar–Jeffery Polynomials are introduced in the Optimal Homotopy Asymptotic Method for solution of a coupled system of nonlinear partial differential equations. The coupled nonlinear KdV system is taken as test example. The results obtained by the proposed method are compared with the multistage Optimal Homotopy Asymptotic Method. The results show the efficiency and consistency of the proposed method over the Optimal Homotopy Asymptotic Method. In addition, accuracy of the proposed method can be improved by taking higher order (...) approximations. (shrink)

In this paper, we propose the disturbance observer-based continuous finite-time sliding mode controller for input-affine nonlinear systems in which additive matched and mismatched disturbances exist. The objective is to show the robustness and disturbance attenuation performance of the closed-loop system with the proposed DOBCSMC subjected to general classes of matched and mismatched disturbances. The proposed DOBCSMC consists of three main features: the nonlinear finite-time disturbance observer to obtain a fast and accurate estimation of matched and mismatched disturbances, the nonlinear sliding (...) surface to ensure high precision in the steady-state phase of the controlled output, and the continuous supertwisting algorithm to guarantee finite-time convergence of the controlled output and reduce the chattering under the effect of matched and mismatched disturbances. It should be noted that the existing approaches cannot handle time-varying mismatched disturbances and/or cannot guarantee faster finite-time stability of the controlled output. We prove that the closed-loop system with the DOBCSMC guarantees both finite-time reachability to the sliding surface and finite-time stability of the controlled output to the origin. Various simulations are performed to demonstrate the effectiveness of the proposed DOBCSMC. In particular, the simulation results show that the DOBCSMC guarantees faster convergence of the closed-loop system to the origin, higher precision of the controlled output, and better robustness performance against various classes of matched and mismatched disturbances, compared with the existing approaches. (shrink)

The process of predicting water quality over a catchment area is complex due to the inherently nonlinear interactions between the water quality parameters and their temporal and spatial variability. The empirical, conceptual, and physical distributed models for the simulation of hydrological interactions may not adequately represent the nonlinear dynamics in the process of water quality prediction, especially in watersheds with scarce water quality monitoring networks. To overcome the lack of data in water quality monitoring and prediction, this paper presents an (...) approach based on the feedforward neural network model for the simulation and prediction of dissolved oxygen in the Nyando River basin in Kenya. To understand the influence of the contributing factors to the DO variations, the model considered the inputs from the available water quality parameters including discharge, electrical conductivity, pH, turbidity, temperature, total phosphates, and total nitrates as the basin land-use and land-cover percentages. The performance of the FNN model is compared with the multiple linear regression model. For both FNN and MLR models, the use of the eight water quality parameters yielded the best DO prediction results with respective Pearson correlation coefficient R values of 0.8546 and 0.6199. In the model optimization, EC, TP, TN, pH, and temperature were most significant contributing water quality parameters with 85.5% in DO prediction. For both models, LULC gave the best results with successful prediction of DO at nearly 98% degree of accuracy, with the combination of LULC and the water quality parameters presenting the same degree of accuracy for both FNN and MLR models. (shrink)

The dynamics of protection processes has been a fundamental challenge in systemic risk analysis. The conceptual principle and methodological techniques behind the mechanisms involved have been harder to grasp than researchers understood them to be. In this paper, we show how to construct a large variety of behaviors by applying a simple algorithm to networked agents, which could, conceivably, offer a straightforward way out of the complexity. The model starts with the probability that systemic risk spreads. Even in a very (...) random social structure, the propagation of risk is guaranteed by an arbitrary network property of a set of elements. Despite intensive systemic risk, the potential of the absence of failure could also be driven when there has been a strong investment in protection through a heuristically evolved protection level. It is very interesting to discover that many applications are still seeking the mechanisms through which networked individuals build many of these protection processes or mechanisms based on fitness due to evolutionary drift. At the same time, this approach could be useful for researchers and those who need to use protection dynamics to guard against systemic risk under intrinsic randomness in artificial circumstances. (shrink)

Mobile users typically have a series of complex tasks consisting of time-constrained workflows and concurrent workflows that need to be processed. However, these tasks cannot be performed directly locally due to resource limitations of the mobile terminal, especially for battery life. Fortunately, mobile edge computing has been recognized as a promising technology which brings abundant resource at the edge of mobile network enabling mobile devices to overcome the resource and capacity constraints. However, edge servers, such as cloudlets, are heterogeneous and (...) have limited resources. Thus, it is important to make an appropriate offloading strategy to maximize the utility of each cloudlet. In view of this, the time consumption and energy consumption of mobile devices and resource utilization of cloudlets have been taken into consideration in this study. Firstly, a multiconstraint workflow mode has been established, and then a multiobjective optimization mode is formulated. Technically, an improved optimization algorithm is proposed to address this mode based on Nondominated Sorting Genetic Algorithm II. Both extensive experimental evaluations and detailed theoretical analysis are conducted to show that the proposed method is effective and efficiency. (shrink)

Considering the fuel consumption and soil compaction, optimization of the performance of tractors is crucial for modern agricultural practices. The tractive performance is influenced by many factors, making it difficult to be modeled. In this work, the traction force and tractive efficiency of a low-power tractor, as affected by soil coefficient, vertical load, horizontal deformation, soil compaction, and soil moisture, were studied. The optimal work of a tractor is a compromise between the maximum traction force and the maximum tractive efficiency. (...) Optimizing these factors is complex and requires accurate models. To this end, the performances of soft computing approaches, including neural networks, genetic algorithms, and adaptive network fuzzy inference system, were evaluated. The optimal performance was realized by neural networks trained by backpropagation as well as backpropagation combined with a genetic algorithm, with a coefficient of determination of 0.955 for the traction force and 0.954 for the tractive efficiency. Based on models with the best accuracy, a sensitivity analysis was performed. The results showed that the traction performance is mainly influenced by the soil type; nevertheless, the vertical load and soil moisture also exhibited a relatively strong influence. (shrink)

The Nocturnal Frontal Lobe Epilepsy is a form of epilepsy in which seizures occur predominantly during sleep. In other forms of epilepsy, the commonly used clinical approach mainly involves manual inspection of encephalography signals, a laborious and time-consuming process which often requires the contribution of more than one experienced neurologist. In the last decades, numerous approaches to automate this detection have been proposed and, more recently, machine learning has shown very promising performance. In this paper, an original Convolutional Neural Network (...) architecture is proposed to develop patient-specific seizure detection models for three patients affected by NFLE. The performances, in terms of accuracy, sensitivity, and specificity, exceed by several percentage points those in the most recent literature. The capability of the patient-specific models has been also tested to compare the obtained seizure onset times with those provided by the neurologists, with encouraging results. Moreover, the same CNN architecture has been used to develop a cross-patient seizure detection system, resorting to the transfer-learning paradigm. Starting from a patient-specific model, few data from a new patient are enough to customize his model. This contribution aims to alleviate the task of neurologists, who may have a robust indication to corroborate their clinical conclusions. (shrink)

The paper, focusing on the context of Public Administration, addresses the effects of monetary incentives in employees’ performance. In the Italian PA, the monetary incentives are distributed according to the D.L.150/09 which is based on the rank order tournament. The paper investigates if this mechanism has positive and sustainable impacts on the employees’ performance in the short, middle, and long term. The employees’ performance has been modeled as a function of ability and motivation. The results of the computational experiments show (...) a positive impact of the monetary incentives, distributed according to merit criteria, on the employees’ performance in the short, middle, and long term. (shrink)

In this study, a closed-loop brain stimulation control system scheme for epilepsy seizure abatement is designed by brain-machine interface technique. In the controller design process, the practical parametric uncertainties involving cerebral blood flow, glucose metabolism, blood oxygen level dependence, and electromagnetic disturbances in signal control are considered. An appropriate transformation is introduced to express the system in regular form for design and analysis. Then, sufficient conditions are developed such that the sliding motion is asymptotically stable. Combining Caputo fractional order definition (...) and neural network, a finite time fractional order sliding mode controller is designed to guarantee reachability of the sliding mode. The stability and reachability analysis of the closed-loop tracking control system gives the guideline of parameter selection, and simulation results based on comprehensive comparisons are carried out to demonstrate the effectiveness of proposed approach. (shrink)

The performance level of a multistate system can vary among different values rather than only two states. To improve the reliability of MSSs, a maintenance strategy has been adopted to satisfy customer demand, and reliability modeling of MSS with preventive maintenance and customer demand is proposed. According to the regular degradation and random failure at each state, based on the Markov random process, the proposed MSS with preventive maintenance can be modeled to satisfy the customer demand in a specific state. (...) This model can also be adapted to compute other reliability indices. Based on this model, the effect of different preventive maintenance actions on the reliability indices can be analyzed and further compared. Two numerical examples have been illustrated to show the validity of the proposed model. The reliability model presented in this study can be used to assess the type of MSS and help reliability engineers to compare different maintenance actions quantitatively and make optimal decisions. (shrink)

Two important tasks in multiattribute group decision-making are to describe the attribute values and to generate a ranking of all alternatives. A superior tool for the first task is linguistic interval-valued intuitionistic fuzzy number, and an effective tool for the second task is aggregation operator. To date, nearly ten AOs of LIVIFNs have been presented. Each AO has its own features and can work well in its specific context. But there is not yet an AO of LIVIFNs that can offer (...) desirable generality and flexibility in aggregating attribute values and capturing attribute interrelationships and concurrently reduce the influence of unreasonable attribute values. To this end, a linguistic interval-valued intuitionistic fuzzy Archimedean power Muirhead mean operator and its weighted form, which have such capabilities, are presented in this paper. Firstly, the generalised expressions of the AOs are established by a combination of the Muirhead mean operator and the power average operator under the Archimedean T-norm and T-conorm operations of LIVIFNs. Then the properties of the AOs are explored and proved, their specific expressions are constructed, and the special cases of the specific expressions are discussed. After that, a new method for solving the MAGDM problems based on LIVIFNs is designed on the basis of the weighted AO. Finally, the designed method is illustrated via a practical example, and the presented AOs are evaluated via experiments and comparisons. (shrink)

In recent years, streaming music platforms have become very popular mainly due to the huge number of songs these systems make available to users. This enormous availability means that recommendation mechanisms that help users to select the music they like need to be incorporated. However, developing reliable recommender systems in the music field involves dealing with many problems, some of which are generic and widely studied in the literature while others are specific to this application domain and are therefore less (...) well-known. This work is focused on two important issues that have not received much attention: managing gray-sheep users and obtaining implicit ratings. The first one is usually addressed by resorting to content information that is often difficult to obtain. The other drawback is related to the sparsity problem that arises when there are obstacles to gather explicit ratings. In this work, the referred shortcomings are addressed by means of a recommendation approach based on the users’ streaming sessions. The method is aimed at managing the well-known power-law probability distribution representing the listening behavior of users. This proposal improves the recommendation reliability of collaborative filtering methods while reducing the complexity of the procedures used so far to deal with the gray-sheep problem. (shrink)

We provide an agent-based model to explain the emergence of collective opinions not based on feedback between different opinions, but based on emotional interactions between agents. The driving variable is the emotional state of agents, characterized by their valence, quantifying the emotion from unpleasant to pleasant, and their arousal, quantifying the degree of activity associated with the emotion. Both determine their emotional expression, from which collective emotional information is generated. This information feeds back on the dynamics of emotional states and (...) individual opinions in a nonlinear manner. We derive the critical conditions for emotional interactions to obtain either consensus or polarization of opinions. Stochastic agent-based simulations and formal analyses of the model explain our results. Possible ways to validate the model are discussed. (shrink)

The dynamic characteristics of an offshore wind turbine with tripod suction buckets are investigated through finite element analysis and full-scale experiments. In finite element analysis, an integrated framework is suggested to create a simple yet accurate high fidelity model. The integrated framework accounts for not only the strain dependency of the soil but also for all dynamics in the seabed, including those of the soil, suction bucket skirt, and cap. Hence, the model accurately describes the coupling effect of translational and (...) rotational motions of the seabed. The prediction results are compared to the experimental results obtained via full-scale testing in four stages during construction and in several operational conditions. The comparison shows that the stiffness of the suction bucket cap and strain dependency of the soil play a significant role in predicting natural frequency, suggesting that these two factors should be considered in finite element analysis for the accurate prediction of dynamic responses of an offshore wind conversion system. Moreover, dynamic analysis of the strain and acceleration measured during operational conditions shows that strain is more robust than acceleration with regard to the characterization of the overall dynamics of an offshore wind conversion system because the natural frequency of an offshore wind turbine is very low. It can be inferred that the measurement of strain is a more effective way to monitor the long-term evolution of dynamic characteristics. The suggested integrated framework and measurement campaign are useful not only to avoid conservatism that may incur additional costs during load calculation and design phases but also to establish an intelligent operation and maintenance strategy with a novel sensing technique. (shrink)

For the preparation of orthopedic shoes, it is necessary to design boot-trees, where pathological abnormalities of club feet are taken into account as much as possible. For the normal functioning of the club foot, we have to develop such an internal shape of special-purpose footwear, which is comfortable for the patient. This paper describes the methods and issues of the 3D design for constructing the geometric shapes of the main cross sections of the orthopedic boot-tree. In the research process, the (...) authors’ team of this article relied mainly on the patient database, containing the anthropometric, strain-gauge, and pedographic data on club and pathological feet. To construct the shapes of the main cross sections of the orthopedic boot-tree, we have used the integral curves to the suitable second-order differential equations. By means of a computer program, we executed turning and connection of sections of the obtained curves, on the basis of which we have the shapes of transverse-vertical cross sections of the orthopedic boot-tree. This paper also describes the main longitudinal-vertical section and the print of the orthopedic boot-tree in 3D format. By using a program of 3D design, a skeleton of the orthopedic boot-tree was constructed in the spatial format. (shrink)

This paper investigates the problem of quantized dissipative observer-based output feedback control of Markovian descriptor jump systems with unavailable states, appearing networked-induced delay. The descriptor systems are presented as Markovian jump systems which give a more realistic presentation for a variety of nonlinear dynamical systems than conventional state-space representation. To accomplish the objective, a uniform framework is employed to design the delayed Markov observer-based controller and event-triggered scheme. Additionally, we provided the ℋ∞ and ℒ2-ℒ∞ and dissipative performance indices which are (...) robust against the disturbances with time-varying delays. Moreover, a novel Lyapunov–Krasovskii functional is considered to guarantee the closed loop for stochastic stability analysis of the Markovian descriptor jump system. The solvability of Lyapunov–Krasovskii functional results in the formation of linear matrix inequalities. The controller and observer gains can be obtained by solving the linear matrix inequalities. Simulations are performed to validate the proposed scheme. (shrink)

The Benjamin–Ono equation is a useful model to describe the long internal gravity waves in deep stratified fluids. In this paper, the nonlocal Alice–Bob Benjamin–Ono system is induced via the parity and time-reversal symmetry reduction. By introducing an extended Bäcklund transformation, the symmetry-breaking soliton, breather, and lump solutions for this system are obtained through the derived Hirota bilinear form. By taking suitable constants in the involved ansatz functions, abundant fascinating symmetry-breaking structures of the related explicit solutions are shown.

Based on the principal-agent theory, we give a theoretical interpretation on evolution of the complex partnerships between the online SCF providers in China. First, we describe the principal-agent relationships and analyze the optimal profit-sharing contracts between the banks and the B2B platforms. Then, from a dual perspective of leadership transfer and absolute benefit change, we explain the behavioral choices of the banks in the cooperation. Results show that, at the initial stage of growth of the platforms’ abilities to rate online (...) borrowers, the leadership and the absolute benefit of the banks will suffer a “double decline,” which explains why the leading banks in China “divorced” the B2B platforms during 2011 to 2013. However, as the platforms’ rating abilities grow to “maturity,” the absolute benefit of the banks will finally exceed its original level, and then the rational banks would cooperate with the platforms again even at the expense of losing a portion of their leadership, which answers why the banks in China have come back to “remarry” the B2B platforms since 2014. (shrink)

An integrated pest management prey-predator model with ratio-dependent and impulsive feedback control is investigated in this paper. Firstly, we determine the Poincaré map which is defined on the phase set and discuss its main properties including monotonicity, continuity, and discontinuity. Secondly, the existence and stability of the boundary order-one periodic solution are proved by the method of Poincaré map. According to the Poincaré map and related differential equation theory, the conditions of the existence and global stability of the order-one periodic (...) solution are obtained when ΦyA yA. Furthermore, we prove the existence of the order-kk≥2 periodic solution under certain conditions. Finally, we verify the main results by numerical simulation. (shrink)

An examination was performed on whether director interlocks enabled the adoption of a dividend policy for the benefit of the parent company in the ownership structure. Specifically, the study investigated the dependence of the impact of the central position in the board network on the probability of dividend payment. Based on sample of firms listed on Polish capital market, it was observed that the more central the company’s position in the interlocking directorate network, the more likely it is to pay (...) dividends to a subsidiary. This effect is related to the eigenvector centrality. The results obtained suggest that corporate financial policy can be spread across firms through the board network. (shrink)

Visceral leishmaniasis, known as kala-azar, is a serious parasitic disease. After malaria, VL is the second largest parasitic killer. This paper focuses on the VL transmission around sandflies, dogs, and people. Kashgar is located on the southwestern edge of Xinjiang, where kala-azar parasite infection occurs every year. According to the cases reported in the Kashgar Prefecture from 2004 to 2016, we proposed a dynamic model based on these three populations. The SEIR model was established for human population, the SI model (...) was established for sandfly population, and the SI model was established for dog population. We fitted the model to cumulative cases from 2004 to 2016 for the epidemic in Kashgar and predicted that the cumulative incidence of kala-azar in Kashgar would continue to increase, but its growth rate would gradually slow down, which means that the number of cases would gradually decrease every year. We also estimated the basic reproduction number R0 = 1.76. The sensitivity analysis shows that the mutual infection between sandfly and dog contributes the most to the basic reproduction number, while the transmission proportion of sandfly to the susceptible person and the mutual infection between sandfly and dog contribute the most to the number of leishmaniasis human cases. Therefore, according to the sensitivity analysis results, reducing the contact between sandflies and dogs is an effective way to reduce kala-azar. (shrink)

In order to solve the problems of traffic object detection, fuzzification, and simplification in real traffic environment, an automatic detection and classification algorithm for roads, vehicles, and pedestrians with multiple traffic objects under the same framework is proposed. We construct the final V view through a considerate U-V view method, which determines the location of the horizon and the initial contour of the road. Road detection results are obtained through error label reclassification, omitting point reassignment, and so an. We propose (...) a peripheral envelope algorithm to determine sources of vehicles and pedestrians on the road. The initial segmentation results are determined by the regional growth of the source point through the minimum neighbor similarity algorithm. Vehicle detection results on the road are confirmed by combining disparity and color energy minimum algorithms with the object window aspect ratio threshold method. A method of multifeature fusion is presented to obtain the pedestrian target area, and the pedestrian detection results on the road are accurately segmented by combining the disparity neighbor similarity and the minimum energy algorithm. The algorithm is tested in three datasets of Enpeda, KITTI, and Daimler; then, the corresponding results prove the efficiency and accuracy of the proposed approach. Meanwhile, the real-time analysis of the algorithm is performed, and the average time efficiency is 13 pfs, which can realize the real-time performance of the detection process. (shrink)

The provinces of Jiangsu, Anhui, Jiangxi, and Zhejiang and the city of Shanghai in the lower reaches of the Yangtze River forming a concentrated distribution area of developed cities and rich villages in China are so called “the four provinces and one city,” which have experienced rapid and typical urban-rural development. By drawing on the perspective of allometric growth, this paper conducts fundamental analysis and multifractal analysis of 52 prefecture-level cities in four provinces and one city in the lower reaches (...) of the Yangtze River. Fundamental analysis shows that there are different patterns of allometric growth in various areas of the region, as well as the emergence of diffusion in fundamental activities and of polarisation in advanced activities. Multifractal analysis also shows that the comprehensive regional development is dominated by large- and medium-sized cities, but various fields have different fractal spectrums and form six interrelated urban-rural integration modes. The multiple spatial dissymmetry disclosed in the analysis also shows that each field had its own allometric growth features during the regional development. This paper adopts the fitting function and the relevant parameters of the fractal dimension to quantify the evolution in particular fields. Analysis shows that the developments in prefecture-level cities are different and represent the regional evolution status; the urban-rural development in metropolises and small- and medium-sized cities is nonmainstream. (shrink)

This paper studies the control of a class of 3D chaotic systems with uncertain parameters and external disturbances. A new method which is referred as the analytical solution approach is firstly proposed for constructing Lyapunov function. Then, for suppressing the trajectories of the 3D chaotic system to its equilibrium point 00,0,0, a novel fast convergence controller containing parameter λ which determines the convergence rate of the system is presented. By using the designed Lyapunov function, the stability of the closed-loop system (...) is proved via the Lyapunov stability theorem. Computer simulations are employed to a new chaotic system to illustrate the effectiveness of the theoretical results. (shrink)

In capable person governing agricultural cooperatives, the internal governance is essential for cooperatives to achieve sustainable development. As an important mechanism of cooperative internal governance, relational governance is the focus of the current research in the field of cooperative internal governance. Based on the theory of organizational justice, relational embeddedness theory, and relational governance theory, this paper constructs the relationship between interactive justice, relational embeddedness, and governance performance based on fuzzy cognitive map and discusses the influence mechanism of interactive justice (...) on relational governance performance. Taking 245 members of 18 agricultural cooperatives as samples, this paper makes an empirical test by using the machine learning method. Through the analysis of the data, we find that interactive justice has a significant positive impact on the governance performance. Relational embeddedness also has a significant positive impact on the governance performance. And relational embeddedness plays an intermediary role in the positive impact of interactive justice on governance performance. To some extent, the research results broaden the relationship between interactive justice and relational governance performance and provide useful reference for cooperatives to strengthen internal governance and achieve sustainable growth. (shrink)

Based on the theory of acoustic waves, a circular surface radiator model is introduced as a basis for constructing a knowledge transfer model for a knowledge alliance. The three main variables in the model are chosen to be the number of enterprises in knowledge alliance, the frequency of knowledge transfer, and the relationship distances between the knowledge bodies. The internal mechanism of knowledge transfer in a knowledge alliance is studied, and the direct relationships among the internal influencing factors are explored. (...) The results show that the number of enterprises in knowledge alliance, knowledge transfer frequency, and knowledge transfer effect are positively correlated. The “Rayleigh distance” in the knowledge field is the appropriate relationship distance measure for assessing knowledge transfer within the alliance. The Rayleigh distance is highly correlated with the number of enterprises in knowledge alliance and knowledge transfer frequency. Moreover, the number of enterprises in knowledge alliance and knowledge transfer frequency are interrelated. (shrink)

As both ticks and hosts may carry one or more pathogens, the phenomenon of coinfection of multiple tick-borne diseases becomes highly relevant and plays a key role in tick-borne disease transmission. In this paper, we propose a coinfection model involving two tick-borne diseases in a tick-host population and calculate the basic reproduction numbers at the disease-free equilibrium and two boundary equilibria. To explore the impact of coinfection, we also derive the invasion reproduction numbers which indicate the potential of a pathogen (...) to persist when another pathogen already exists in tick and host populations. Then, we obtain the global stability of the system at the disease-free equilibrium and the boundary equilibrium, respectively, and further demonstrate the existence conditions for uniform persistence of the two diseases. The final numerical simulations mainly verify the theoretical results of coinfection. (shrink)

Identifying important nodes in complex networks is essential in disease transmission control, network attack protection, and valuable information detection. Many evaluation indicators, such as degree centrality, betweenness centrality, and closeness centrality, have been proposed to identify important nodes. Some researchers assign different weight to different indicator and combine them together to obtain the final evaluation results. However, the weight is usually subjectively assigned based on the researcher’s experience, which may lead to inaccurate results. In this paper, we propose an entropy-based (...) self-adaptive node importance evaluation method to evaluate node importance objectively. Firstly, based on complex network theory, we select four indicators to reflect different characteristics of the network structure. Secondly, we calculate the weights of different indicators based on information entropy theory. Finally, based on aforesaid steps, the node importance is obtained by weighted average method. The experimental results show that our method performs better than the existing methods. (shrink)

Video-based moving vehicle detection and tracking is an important prerequisite for vehicle counting under complex transportation environments. However, in the complex natural scene, the conventional optical flow method cannot accurately detect the boundary of the moving vehicle due to the generation of the shadow. In addition, traditional vehicle tracking algorithms are often occluded by trees, buildings, etc., and particle filters are also susceptible to particle degradation. To solve this problem, this paper proposes a kind of moving vehicle detection and tracking (...) based on the optical flow method and immune particle filter algorithm. The proposed method firstly uses the optical flow method to roughly detect the moving vehicle and then uses the shadow detection algorithm based on the HSV color space to mark the shadow position after threshold segmentation and further combines the region-labeling algorithm to realize the shadow removal and accurately detect the moving vehicle. Improved affinity calculation and mutation function of antibody are proposed to make the particle filter algorithm have certain adaptivity and robustness to scene interference. Experiments are carried out in complex traffic scenes with shadow and occlusion interference. The experimental results show that the proposed algorithm can well solve the interference of shadow and occlusion and realize accurate detection and robust tracking of moving vehicles under complex transportation environments, which has the potentiality to be processed on a cloud computing platform. (shrink)

This paper investigated the global synchronization of fractional-order memristive neural networks. To deal with the effect of reaction-diffusion and time delay, fractional partial and comparison theorem are introduced. Based on the set value mapping theory and Filippov solution, the activation function is extended to discontinuous case. Adaptive controllers with a compensator are designed owing to the existence of unknown parameters, with the help of Gronwall–Bellman inequality. Numerical simulation examples demonstrate the availability of the theoretical results.

In this paper, event-triggered leader-following consensus of general linear multiagent systems under both fixed topology and switching topologies is studied. First, centralised and decentralised event-triggered control strategies based on neighbors’ state estimation are proposed under fixed topology, in which the controller is only updated at the time of triggering. Obviously, compared with the continuous time control algorithms, the event-triggered control strategies can reduce the communication frequency among agents effectively. Meanwhile, event-triggering conditions are derived for systems to achieve consensus by using (...) the Lyapunov stability theory and model transformation method. Then, the theoretical results obtained under the fixed topology are extended to the switching topologies, and the sufficient conditions for the system to achieve leader-following consensus under the switching topologies are given. However, different from fixed topology, the control input of each agent is updated both at event-triggering and topology switching time. Finally, Zeno behaviors can be excluded by proving that the minimum triggering interval of each agent is strictly positive, and the effectiveness of the event-triggered protocol is verified by simulation experiments. (shrink)

In this article, the diffraction of the electromagnetic wave by the building with two rooms is considered. The rooms have doors and windows with lossy dielectric walls. The electromagnetic properties of the building as an opened coupled resonator system are investigated at different source locations and several frequencies including 5G band. The problem is solved by using the Method of Auxiliary Sources. The near electric field distributions are calculated and analyzed.

This paper investigates the hybrid-driven mechanism problem for Markov jump system, where both channel quantization and network-induced delay based on uncertain network are considered. Firstly, comparing with the traditional event-triggered scheme, a hybrid-driven mechanism is employed in networked control systems for the finite capacity of communication bandwidth resources and system performance in equilibrium. Then, the quantization technology is applied in the communication channel from sensor-to-controller and controller-to-actuator. The application of BCQ is for further investigation that mitigate data packet transmission rate. (...) Thirdly, Markov jump system is modeled for the hybrid-driven mechanism and network-induced delay. By constructing the Lyapunov–Krasovskii function, a sufficient condition is derived as the stability criterion, and the controller is designed in which the nonlinear term is rewritten for simplifying the calculation. Finally, two simulation examples are provided to demonstrate the effectiveness of the proposed approach. (shrink)

In this paper, the approximation property of the linear combinations of Baskakov operators is investigated by using a Jacobi weight function. Moreover, both the positive and inverse theorems for the weighted simultaneous approximation of the linear combinations of Baskakov operators are proved.

In this paper, we investigate single-strain and multistrain viral infection models with general incidence function and density-dependent diffusion subject to the homogeneous Neumann boundary conditions. For the single-strain viral infection model, by using the linearization method and constructing appropriate Lyapunov functionals, we obtain that the global threshold dynamics of the model is determined by the reproductive numbers for viral infection ℛ0. For the multistrain viral infection model, we have discussed the competitive exclusion problem. If the reproduction number ℛi for strain (...) i is maximal and larger than one, the steady state Ei corresponding to the strain i is globally stable. Thus, competitive exclusion happens and all other strains die out except strain i. Meanwhile, we can prove that the single-strain and multistrain viral infection models are well posed. Furthermore, numerical simulations are also carried out to illustrate the theoretical results, which is seldom seen in the relevant known literatures. (shrink)

Due to the current unstable travel performance and poor driving maneuverability of rice combine harvester crawler chassis with high load in the rice field, the driver’s standard sitting posture model was developed by analyzing the handling of the crawler chassis driving control panel. Based on this model, the joystick length and cab manipulation space layout were designed. The Finite Element Software was used to develop the loading and restraining model of the chassis frame, and then the structural characteristics and bearing (...) capacity of the crawler chassis were analyzed. The high-bearing running stability and the rationality of operating force of the joystick of rice combine harvester crawler chassis designed in this paper through experiments were verified by experiments. The results showed that when the crawler chassis of rice combine harvester bears a load of 3.5 t, the driving speed is relatively stable in the three speed ranges of 1 m/s, 1.5 m/s, and 2 m/s, and the maximum variance of driving speed variation is 5.022 × 10−4. The actual average operating force of each operating lever on the crawler chassis ranges from 30.36 to 42.71 N, and the operating force of each operating lever is suitable for 95% of Chinese adult male operators. The research results provide a good method and reference for the future development of the crawler chassis structure of rice combine harvester. (shrink)

In this paper, we investigate the impact of a periodically evolving domain on the dynamics of the diffusive West Nile virus. A reaction-diffusion model on a periodically and isotropically evolving domain which describes the transmission of the West Nile virus is proposed. In addition to the classical basic reproduction number, the spatial-temporal basic reproduction number depending on the periodic evolution rate is introduced and its properties are discussed. Under some conditions, we explore the long-time behavior of the virus. The virus (...) will go extinct if the spatial-temporal basic reproduction number is less than or equal to one. The persistence of the virus happens if the spatial-temporal basic reproduction number is greater than one. We consider special case when the periodic evolution rate is equivalent to one to better understand the impact of the periodic evolution rate on the persistence or extinction of the virus. Some numerical simulations are performed in order to illustrate our analytical results. Our theoretical analysis and numerical simulations show that the periodic change of the habitat range plays an important role in the West Nile virus transmission, in particular, the increase of periodic evolution rate has positive effect on the spread of the virus. (shrink)

In this paper, an effective method to determine an initial searching point of the network reconfiguration problem for power loss reduction is proposed for improving the efficiency of the continuous genetic algorithm to the NR problem. The idea of the method is to close each initial open switch in turn and solve power flow for the distribution system with the presence of a closed loop to choose a switch with the smallest current in the closed loop for opening. If the (...) radial topology constraint of the distribution system is satisfied, the switch opened is considered as a control variable of the ISP. Then, ISP is attached to the initial population of CGA. The calculated results from the different distribution systems show that the proposed CGA using ISP could reach the optimal radial topology with better successful rate and obtained solution quality than the method based on CGA using the initial population generated randomly and the method based on CGA using the initial radial configuration attached to the initial population. As a result, CGA using ISP can be a favorable method for finding a more effective radial topology in operating distribution systems. (shrink)

This paper is concerned with the delay-dependent stability of systems with distributed time-varying delays. The novelty relies on the use of some new inequalities which are less conservative than some existing inequalities. A less conservative stability criterion is obtained by constructing some new augmented Lyapunov–Krasovskii functionals, which are given in terms of linear matrix inequalities. The effectiveness of the presented criterion is demonstrated by two numerical examples.

In order to study the transmission of rabies epidemics in vampire bats, we propose a mathematical model for vampire bat rabies virus. A threshold R0 is identified which determines the outcome of the disease. If R0 1, the endemic equilibrium is globally asymptotically stable with certain conditions. Through the numerical simulation, the correctness of the theoretical results is verified. We carry out the sensitivity analysis of the parameters which provide a theoretical basis for preventing and controlling the transmission of bat (...) rabies. (shrink)

This paper proposes a chaotic stochastic fractal search algorithm method to solve the reconfiguration problem for minimizing the power loss and improving the voltage profile in distribution systems. The proposed method is a metaheuristic method developed for overcoming the weaknesses of the conventional SFSA with two processes of diffuse and update. In the first process, new points will be created from the initial points by the Gaussian walk. For the second one, SFSA will update better positions for the particles obtained (...) in the diffusion process. In addition, this study has also integrated the chaos theory to improve the SFSA diffusion process as well as increase the rate of convergence and the ability to find the optimal solution. The effectiveness of the proposed CSFSA has been verified on the 33-bus, 84-bus, 119-bus, and 136-bus distribution systems. The obtained results from the test cases by CSFSA have been verified to those from other natural methods in the literature. The result comparison has indicated that the proposed method is more effective than many other methods for the test systems in terms of power loss reduction and voltage profile improvement. Therefore, the proposed CSFSA can be a very promising potential method for solving the reconfiguration problem in distribution systems. (shrink)

One of the most important threats to today’s civilization is terrorism. Terrorism not only disturbs the law and order situations in a society but also affects the quality of lives of humans and makes them suppressed physically and emotionally and deprives them of enjoying life. The more the civilizations have advanced, the more the people are working towards exploring different mechanisms to protect the mankind from terrorism. Different techniques have been used as counterterrorism to protect the lives of individuals in (...) society and to improve the quality of life in general. Machine learning methods have been recently explored to develop techniques for counterterrorism based on artificial intelligence. Since deep learning has recently gained more popularity in machine learning domain, in this paper, these techniques are explored to understand the behavior of terrorist activities. Five different models based on deep neural network are created to understand the behavior of terrorist activities such as is the attack going to be successful or not? Or whether the attack is going to be suicide or not? Or what type of weapon is going to be used in the attack? Or what type of attack is going to be carried out? Or what region is going to be attacked? The models are implemented in single-layer neural network, five-layer DNN, and three traditional machine learning algorithms, i.e., logistic regression, SVM, and Naïve Bayes. The performance of the DNN is compared with NN and the three machine learning algorithms, and it is demonstrated that the performance in DNN is more than 95% in terms of accuracy, precision, recall, and F1-Score, while ANN and traditional machine learning algorithms have achieved a maximum of 83% accuracy. This concludes that DNN is a suitable model to be used for predicting the behavior of terrorist activities. Our experiments also demonstrate that the dataset for terrorist activities is big data; therefore, a DNN is a suitable model to process big data and understand the underlying patterns in the dataset. (shrink)

Lump-type wave solution of the Bogoyavlenskii–Kadomtsev–Petviashvili equation is constructed by using the bilinear structure and Hermitian quadratic form. The dynamical behaviors of lump-type wave solution are investigated and presented analytically and graphically. Furthermore, we discuss the interaction between a lump-type wave and a kink wave solution. Absorb-emit interaction between two kinds of solitary wave solutions is shown. This kind of interaction solution can be regarded as a lump-type wave which propagates on the kink wave background.

During the mining of deep mineral resources, the rock is in the complex mechanical environment of high crustal stress and blasting excavation unloading, and the improved SHPB test system is used to carry out frequent impact disturbance test of deep rock in the process of unloading high static stress. Firstly, the general characteristics of dynamic stress-strain curve envelope of the whole process trend can be divided into four stages: the stable development stage of micro cracks, the non-stable development stage of (...) micro cracks, the fatigue damage stage, and the fatigue failure stage. Then, the damage variables of the rock are defined by continuous factors, strain equivalence principle and statistical damage theory, which are based on the whole deformation characteristics of rock during the test. And the derived damage variable equation of rock in the damage process is proved to be reasonable, and the damage constitutive model of rock under frequent disturbances in the process of unloading high static stress is established by the combined model method. Finally, the rationality of constitutive equation is verified by test data, which shows that the dynamic stress-strain curve envelope is in good consistency with the theoretical curve of constitutive equation. (shrink)

M-eigenvalues of fourth-order partially symmetric tensors play important roles in the nonlinear elastic material analysis and the entanglement problem of quantum physics. In this paper, we introduce M-identity tensor and establish two M-eigenvalue inclusion intervals with n parameters for fourth-order partially symmetric tensors, which are sharper than some existing results. Numerical examples are proposed to verify the efficiency of the obtained results. As applications, we provide some checkable sufficient conditions for the positive definiteness and establish bound estimations for the M-spectral (...) radius of fourth-order partially symmetric nonnegative tensors. (shrink)

The problem of unmeasured parameters estimation for distributed control systems is studied in this paper. The Takagi–Sugeno fuzzy model which can appropriate any nonlinear systems is employed, and based on the model, an observer-based fuzzy H∞ filter which has robustness against time-delay, external noise, and system uncertainties is designed. The sufficient condition for the existence of the desired filter is derived in terms of linear matrix inequalities solutions. Moreover, the underdetermined estimation problem in which the number of sensors available is (...) typically less than the number of state variables to be estimated is specifically addressed. A systematic method is proposed to produce a model tuning parameter vector of appropriate dimension for the estimation of the filter, and the optimal transformation matrix is selected via iterative solution to minimize the estimated error. Finally, a simulation example for turbofan aeroengine is given to illustrate the effectiveness of the proposed method, and the estimated error is less than 2.5%. (shrink)

Deep learning-based visual odometry systems have shown promising performance compared with geometric-based visual odometry systems. In this paper, we propose a new framework of deep neural network, named Deep Siamese convolutional neural network, and design a DL-based monocular VO relying on DSCNN. The proposed DSCNN-VO not only considers positive order information of image sequence but also focuses on the reverse order information. It employs supervised data-driven training without relying on any modules in traditional visual odometry algorithm to make the DSCNN (...) to learn the geometry information between consecutive images and estimate a six-DoF pose and recover trajectory using a monocular camera. After the DSCNN is trained, the output of DSCNN-VO is a relative pose. Then, trajectory is recovered by translating the relative pose to the absolute pose. Finally, compared with other DL-based VO systems, we demonstrate the proposed DSCNN-VO achieve a more accurate performance in terms of pose estimation and trajectory recovering through experiments. Meanwhile, we discuss the loss function of DSCNN and find a best scale factor to balance the translation error and rotation error. (shrink)

Optimising the allocation of population, land, and capital production resources is crucial for promoting an efficient urbanisation and solving the urban land financial problem. This study uses a panel threshold model to identify the response boundary of urban construction land use efficiency to government debt level for 51 postfinancial crisis Chinese coastal cities. The results indicate that the threshold of economic development level and provincial gross domestic product are 2.67 and 5.17, respectively. In cities with relatively backward economic development, an (...) expansion of the government debt scale hinders the improvement of the utilisation efficiency of construction land. Also, the threshold value of the government’s accumulated debt level threshold is 15.83%. When cities fall below the government accumulated debt level threshold. This study’s findings can provide a reference for a sustainable promotion of new urbanisation in both China and in other countries to avoid the risk of land urbanisation. (shrink)

We investigate a reduced generalized -dimensional shallow water wave equation, which can be used to describe the nonlinear dynamic behavior in physics. By employing Bell’s polynomials, the bilinear form of the equation is derived in a very natural way. Based on Hirota’s bilinear method, the expression of N-soliton wave solutions is derived. By using the resulting N-soliton expression and reasonable constraining parameters, we concisely construct the high-order breather solutions, which have periodicity in x,y-plane. By taking a long-wave limit of the (...) breather solutions, we have obtained the high-order lump solutions and derived the moving path of lumps. Moreover, we provide the hybrid solutions which mean different types of combinations in lump and line wave. In order to better understand these solutions, the dynamic phenomena of the above breather solutions, lump solutions, and hybrid solutions are demonstrated by some figures. (shrink)

This paper is concerned with a reaction-diffusion heroin model in a bound domain. The objective of this paper is to explore the threshold dynamics based on threshold parameter and basic reproduction number ℜ0, and it is proved that if ℜ0 1, heroin spread is uniformly persistent and there exists a positive heroin-spread steady state. We also obtain that the explicit formula of ℜ0 and global attractiveness of constant positive steady state when all parameters are positive constants. Our simulation results reveal (...) that compared to the homogeneous setting, the spatial heterogeneity has essential impacts on increasing the risk of heroin spread. (shrink)

Light detection and ranging is commonly used to create high-resolution maps; however, the efficiency and convergence of parameter estimation are difficult. To address this issue, we evaluated the structural characteristics of received LiDAR signals by decomposing them into Gaussian functions and applied the variable projection algorithm of the separable nonlinear least-squares problem to the process of waveform fitting. First, using a variable projection algorithm, we separated the linear and nonlinear parameters in the Gaussian function model; the linear parameters are expressed (...) with nonlinear parameters by the function. Thereafter, the optimal estimation of the characteristic parameters of the Gaussian function components was transformed into a least-squares problem only comprising nonlinear parameters. Finally, the Levenberg–Marquardt algorithm was used to solve these nonlinear parameters, whereas the linear parameters were calculated simultaneously in each iteration, and the estimation results satisfying the nonlinear least-square criterion were obtained. Five groups of waveform decomposition simulation data and ICESat/GLAS satellite LiDAR waveform data were used for the parameter estimation experiments. During the experiments, for the same accuracy, the separable nonlinear least-squares optimization method required fewer iterations and lesser calculation time than the traditional method of not separating parameters; the maximum number of iterations was reached before the traditional method converged to the optimal estimate. The method of separating variables only required 14 iterations to obtain the optimal estimate, reducing the computational time from 1128 s to 130 s. Therefore, the application of the separable nonlinear least-squares problem can improve the calculation efficiency and convergence speed of the parameter solution process. It can also provide a new method for parameter estimation in the Gaussian model for LiDAR waveform decomposition. (shrink)

The supervised learning-based recommendation models, whose infrastructures are sufficient training samples with high quality, have been widely applied in many domains. In the era of big data with the explosive growth of data volume, training samples should be labelled timely and accurately to guarantee the excellent recommendation performance of supervised learning-based models. Machine annotation cannot complete the tasks of labelling training samples with high quality because of limited machine intelligence. Although expert annotation can achieve a high accuracy, it requires a (...) long time as well as more resources. As a new way of human intelligence to participate in machine computing, crowdsourcing annotation makes up for shortages of machine annotation and expert annotation. Therefore, in this paper, we utilize crowdsourcing annotation to label training samples. First, a suitable crowdsourcing mechanism is designed to create crowdsourcing annotation-based tasks for training sample labelling, and then two entropy-based ground truth inference algorithms are proposed to achieve quality improvement of noise labels provided by the crowd. In addition, the descending and random order manners in crowdsourcing annotation-based tasks are also explored. The experimental results demonstrate that crowdsourcing annotation significantly improves the performance of machine annotation. Among the ground truth inference algorithms, both HILED and HILI improve the performance of baselines; meanwhile, HILED performs better than HILI. (shrink)