Introduction -- Direct algorithms of decompositions of matrices by non-orthogonal transformations -- Direct algorithms of decompositions of matrices by orthogonal transformations -- Direct algorithms of solution of linear equations -- Iterative algorithms of solution of linear equations -- Direct algorithms of solution of eigenvalue problem -- Iterative algorithms of solution of eigenvalue problem -- Algorithms of solution of singular value decomposition.

Brain structural covariance network can delineate the brain synchronized alterations in a long-range time period. It has been used in the research of cognition or neuropsychiatric disorders. Recently, causal analysis of structural covariance network, winner-take-all and cortex–subcortex covariance network, and modulation analysis of structural covariance network have expended the technology breadth of SCN. However, the lack of user-friendly software limited the further application of SCN for the research. In this work, we developed the graphical user interface toolkit of brain structural (...) covariance connectivity based on MATLAB platform. The software contained the analysis of SCN, CaSCN, MOD-SCN, and WTA-CSSCN. Also, the group comparison and result-showing modules were included in the software. Furthermore, a simple showing of demo dataset was presented in the work. We hope that the toolkit could help the researchers, especially clinical researchers, to do the brain covariance connectivity analysis in further work more easily. (shrink)

La pandemia de Covid-19 cambió la forma de manejar los laboratorios de ingeniería. Para el último trimestre del año 2020, se estableció como un objetivo académico el desarrollo de prácticas del Laboratorio de Procesos virtuales involucrando a estudiantes de pregrado de Ingeniería Química de la Universidad Metropolitana, utilizando la plataforma de programación y cálculo numérico Matlab aplicando la metodología de estudio Aprendizaje Basado en Proyectos. La respuesta de los estudiantes indicó que la experiencia adquirida les genera confianza en su (...) uso, mejor comprensión de las ventajas y desventajas involucradas y a futuro un beneficio competitivo en la industria. (shrink)

Se presenta las aplicaciones desarrollas para virtualizar el laboratorio de fluidos y transferencias de la Universidad Metropolitana. El objetivo es permitir a los estudiantes realizar las prácticas de laboratorio de manera online. Se desarrolló una aplicación de cada práctica utilizando MATLAB App Designer. Los estudiantes lograron hacer cada práctica virtual manipulando en tiempo real las variables correspondientes y obtener los resultados con el cual realizar los informes. Estas aplicaciones fueron empleadas para dictar la asignatura de manera virtual, obteniendo buena (...) aceptación por parte de los estudiantes, los cuales sintieron cada práctica interactiva y de utilidad para su proceso de aprendizaje. (shrink)

The Shodagor of Matlab, Bangladesh, are a seminomadic community of people who live and work on small wooden boats, within the extensive system of rivers and canals that traverse the country. This unique ecology places particular constraints on family and economic life and leads to Shodagor parents employing one of four distinct strategies to balance childcare and provisioning needs. The purpose of this paper is to understand the conditions that lead a family to choose one strategy over another by (...) testing predictions about socioecological factors that impact the sexual division of labor, including a family’s stage in the domestic cycle, aspects of the local ecology, and the availability of alloparents. Results show that although each factor has an impact on the division of labor individually, a confluence of these factors best explains within-group, between-family differences in how mothers and fathers divide subsistence and childcare labor. These factors also interact in particular ways for Shodagor families, and it appears that families choose their economic strategies based on the constellation of constraints that they face. The results of these analyses have implications for theory regarding the sexual division of labor across cultures and inform how Shodagor family economic and parenting strategies should be contextualized in future studies. (shrink)

How should we measure metacognitive sensitivity, i.e. the efficacy with which observers’ confidence ratings discriminate between their own correct and incorrect stimulus classifications? We argue that currently available methods are inadequate because they are influenced by factors such as response bias and type 1 sensitivity . Extending the signal detection theory approach of Galvin, Podd, Drga, and Whitmore , we propose a method of measuring type 2 sensitivity that is free from these confounds. We call our measure meta-d′, which reflects (...) how much information, in signal-to-noise units, is available for metacognition. Applying this novel method in a 2-interval forced choice visual task, we found that subjects’ metacognitive sensitivity was close to, but significantly below, optimality. We discuss the theoretical implications of these findings, as well as related computational issues of the method. We also provide free Matlab code for implementing the analysis. (shrink)

It will be settled out for the open problem of designing an r-order finite-time state observer for reaction-diffusion genetic regulatory networks with time-varying delays. By assuming the Dirichlet boundary conditions, aiming to estimate the mRNA and protein concentrations via available network measurements. Firstly, sufficient F-T stability conditions for the filtering error system have been investigated via constructing an appropriate Lyapunov–Krasovskii functional and using several integral inequalities and convex technique simultaneously. These conditions are delay-dependent and reaction-diffusion-dependent and can be checked by (...) MATLAB toolbox. Furthermore, a method is proposed to design an r-order F-T state observer, and the explicit expressions of observer gains are given. Finally, a numerical example is presented to illustrate the effectiveness of the proposed method. (shrink)

In a digital communication environment, information security is mandatory. Three essential parameters used in the design process of a steganography algorithm are Payload, security, and fidelity. However, several methods are implemented in information hiding, such as Least Significant Bit (LBS), Discrete Wavelet Transform, Masking, and Discrete Cosine Transform. The paper aims to investigate novel steganography techniques based on agent technology. It proposes a Framework of Steganography based on agent for secret communication using LSB. The most common image steganography databases are (...) explored for training and testing. The methodology in this work is based on the statistical properties of the developed agent software using Matlab. The experiment design is based on six statistical feature measures, including Histogram, Mean, Standard deviation, Entropy, Variance and Energy. For steganography, an Ensemble classifier is used to test two scenarios: embedding a single language message and inserting bilingual messages. ROC Curve represents the evaluation metrics. The result shows that the designed agent-based system with 50% training/testing sample set and 0.2 Payload can pick out the best cover image for the provided hidden message size to avoid visual artifact. (shrink)

The Bubonic Plague outbreak that wormed its way through San Francisco’s Chinatown in 1900 tells a story of prejudice guiding health policy, resulting in enormous suffering for much of its Chinese population. This article seeks to discuss the potential for hidden “prejudice” should Artificial Intelligence (AI) gain a dominant foothold in healthcare systems. Using a toy model, this piece explores potential future outcomes, should AI continue to develop without bound. Where potential dangers may lurk will be discussed, so that the (...) full benefits AI has to offer can be reaped whilst avoiding the pitfalls. The model is produced using the computer programming language MATLAB and offers visual representations of potential outcomes. Interwoven with these potential outcomes are numerous historical models for problems caused by prejudice and recent issues in AI systems, from police prediction and facial recognition software to recruitment tools. Therefore, this research’s novel angle, of using historical precedents to model and discuss potential futures, offers a unique contribution. (shrink)

: The corpus of fatwa named as Bostānu Shaqā’iq al-Nuʿmān, recorded in the Veliyuddin Efendi section under the number 1414 at Beyazıd State Library. It has been ignored so far. Because of its name, it may be thought that it is a part of Tashkoprulüzāde’s book Shaḳā’iḳ-i Nuʿmāniyya, but it is a nuqullu fatwa collection of Babakūshī ʿAbdurrahmān Efendi. In the famous Shaqā’iq appendix Atā’ī, which gives information about the biography of Abdurrahmān Efendi does not mention the book with this (...) name. Abdurrahman Efendi who was from a family in Plovdiv region worked in different positions in Istanbul and Edirne. Then, he was appointed as a mufti to Kefe, Crimea. He died in 983/1576. There is no information about his scholarly identity in ‛Aṭā‛ī except being the intern of Abū l-Suʿūd Efendi. In this essay, first of all, the place of Babakūshī in Ottoman Islamic Law tradition will be determined, and the features of the manuscripts and some notes on the postscript will be studied. In assessment section, especially because of the notes on the manuscripts, it has to be studied in terms of Islamic Law literature and its place should be figured out in fatwa literature. Summary: Nuqullu Fatwa collections that included citations were the books that were created for people to have access to the ruling on legal issues of scholars who were appointed as Muslim judges or muftis together with their sources and background. Although there are several studies in the literature about fatwa collections with citations Babakūshī ʿAbd al-Raḥmān Efendi's book titled Bostânu Shaqā'iḳ al-Nuʿmān was not included in the literature. ‛Aṭā‛ī provides information about the life of Babakūshī Abdurrahman Efendi. Atâ'î explains that he climbed the stairs with the help of Baba Efendi and joined the special group of people with aptitude at the level of apprenticeship. Then he raised also to the level of being the intern of Abū l-Suʿūd Efendi. Later, Babakūshī ʿAbd al-Raḥmān started to teach. He taught as a teacher for three years in Istanbul and then became the Mufti of Kefe replacing Molla Akmal al-Dīn. Molla Ekmeleddin, who was better known as Ekmel Efendi, just like ʿAbd al-Raḥmān Efendi, was an apprentice of Abū l-Suʿūd Efendi and would later be transferred to Cyprus after the island was conquered. According to Aṭā‛ī, ʿAbd al-Raḥmān Efendi remained in that position which he was appointed as Ṣahn teacher until his death and died in Zilqāda 983/February 1576. The highest position that Babakūshī took among the religious scholars organization in the Ottoman Empire was being the Mufti of Kefe. As stated by ‛Aṭā‛ī, he was appointed as the Mufti of Kefe with the title of Ṣahn teacher. Instead of giving information about his teachers, ‛Aṭā‛ī mostly concentrated on Baba Efendi who was one of his relatives. Therefore we do not have information about his mentors/teachers. We can say that he belonged to the Ottoman school of scholars since he was an apprentice of Abū l-Suʿūd Efendi. The copy which is the subject matter of this study is registered as Veliyüddin Efendi with number 1414 at Bāyezıd State Library. According to our research, the copy which has 237 sheets is the only copy of the book. From the expressions of Babakūshī in the preface, it is concluded that the book was written close to his death. There are several notes written with different pens as footnotes of the book. Here, four of them which are considered to be more important will be identified.First: Notes written with the same pen as the main text. These are generally citations from books such as Tatarkhāniyye, Hidāya, ‛İnâya, Kashf al-Asrâr Sharḥu Manār.Second: are 'maṭlabs' i.e. important matters. Third: are relatively inelaborate notes. These were written by someone who we thought was not a copyist/calligrapher when compared with the general style of the book. Fourth: Warning notes which included some questions. These are generally in Turkish. The preface of the book, provides sufficient information about who the author was and the nature of the book. ʿAbd al-Raḥmān Efendi, with the intention of writing a collection, started to research taking into account imams' and shaykhs' nāsikh and mensūkh and he also considered sheikhs' explanations about what was definite and what needed caution and taqwa in practice. He recorded that this search lasted for 3 years and he referred especially to Fatāwa-yi Qādikhān and Fatāwa-yı Tatarkhāniyya within this period and additionally reviewed and studied Islamic Law books that he found in the Ottoman Empire. He described that he divided these into chapters and inserted subject matters in the footnotes. Then he described how he gave the title, Bostānu Shaqā'iḳ al-Nuʿmān to the book emphasizing especially bostan.This could be seen in the expression, Masīratan li'l-Qudāt. No reference was made to Shaqā'iḳ al-Nuʿmān in the title of the book. Probably he had his intentions due to the famous book titled Şeḳ' āiḳ-i Nuʿmaniye and his pupils). In the chapter which started with Fasl right after the preface the author said that fatwa would be issued based on the opinions of three imams, namely Abū Ḥanīfa, Abu Yūsuf and Imām Muhammed that their madhap was followed and their good morals were observed. Then, it was stated that the Mufti could issue fatwas according to the opinions of first, Abū Ḥanīfa, then Abu Yūsuf and finally Imam Muḥammed. It was also stated that if he could not find their opinions and had himself muctehid, he could give his ictihad. The Fatwa collection, Bostān, is an important work among the 16th century Ottoman books since it is an important scholar's book who had witnessed Islamic knowledge in the central Ottoman Empire and Crimean region. (shrink)

Neuroimaging is critical in the diagnosis and treatment of brain cancers; however, the first detection of tumors is a challenge. Detection techniques like image segmentation are heavily reliant on the segmented image’s resolution. Magnetic resonance imaging tumor segmentation has emerged as a new study area in the medical imaging field. This spongy and delicate mass of tissue is the brain. Stable conditions allow for patterns to enter and interact with each other. To put it simply, a tumor is a mass (...) of tissue that has grown unchecked by the natural mechanisms that keep it under control. When cells divide uncontrollably, they create a cancerous tumor. Brain tumors can be detected and segmented using a variety of methods. A new method for detecting brain tumors using MRI images is presented in this research. An innovative Woelfel filter is used for enhancement, and morphological segmentation approaches combined with anisotropic diffusion are used for segmentation. Segmentation of brain tumors can be accomplished using thresholding and morphological techniques, which are both effective. The tumor will be located and identified using morphological image processing. Image denoising refers to the process of removing artefacts such as noise and aliasing from digital images. Here MATLAB programming language is utilised as it incorporates all the toolboxes required for the application involved in the work. (shrink)

This fifth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics, and is available in open-access. The collected contributions of this volume have either been published or presented after disseminating the fourth volume in 2015 in international conferences, seminars, workshops and journals, or they are new. The contributions of each part of this volume are chronologically ordered. First Part of this book presents some (...) theoretical advances on DSmT, dealing mainly with modified Proportional Conflict Redistribution Rules (PCR) of combination with degree of intersection, coarsening techniques, interval calculus for PCR thanks to set inversion via interval analysis (SIVIA), rough set classifiers, canonical decomposition of dichotomous belief functions, fast PCR fusion, fast inter-criteria analysis with PCR, and improved PCR5 and PCR6 rules preserving the (quasi-)neutrality of (quasi-)vacuous belief assignment in the fusion of sources of evidence with their Matlab codes. Because more applications of DSmT have emerged in the past years since the apparition of the fourth book of DSmT in 2015, the second part of this volume is about selected applications of DSmT mainly in building change detection, object recognition, quality of data association in tracking, perception in robotics, risk assessment for torrent protection and multi-criteria decision-making, multi-modal image fusion, coarsening techniques, recommender system, levee characterization and assessment, human heading perception, trust assessment, robotics, biometrics, failure detection, GPS systems, inter-criteria analysis, group decision, human activity recognition, storm prediction, data association for autonomous vehicles, identification of maritime vessels, fusion of support vector machines (SVM), Silx-Furtif RUST code library for information fusion including PCR rules, and network for ship classification. Finally, the third part presents interesting contributions related to belief functions in general published or presented along the years since 2015. These contributions are related with decision-making under uncertainty, belief approximations, probability transformations, new distances between belief functions, non-classical multi-criteria decision-making problems with belief functions, generalization of Bayes theorem, image processing, data association, entropy and cross-entropy measures, fuzzy evidence numbers, negator of belief mass, human activity recognition, information fusion for breast cancer therapy, imbalanced data classification, and hybrid techniques mixing deep learning with belief functions as well. (shrink)

The vehicle suspension system is represented by a complex group of components which connect the wheels to the frame or body. Its primary function is to reduce or absorb various vehicle vibrations generated by road disturbances, providing comfort and safety for passengers. Most modern vehicles have independent, active, or semiactive front and rear suspensions which allow the use of electronic actuation. For this reason, automotive engineers conduct research on the active suspension model to determine the most suitable control algorithm. Three (...) active suspension models are intensely used within simulations: the quarter-car, the half-car, and the full-car models. This paper proposes an adaptive harmonic control for a half-car active suspension system. The mathematical model of the suspension system is implemented in the MATLAB/Simulink environment. The control approach is tested via simulation, and several comparisons with the classical proportional-integral controller are provided. The simulation results show that the controller behaves quite similarly on the half-car model as it did on a quarter-car model. Additionally, an improvement to the harmonic control algorithm has been accomplished. (shrink)

In this paper, we have considered a dynamical model of Chlamydia disease with varying total population size, bilinear incidence rate and pulse vaccination strategy. We have defined two positive numbers $$R_{0}$$ R 0 and $$R_{1}$$ R 1. It is proved that there exists an infection-free periodic solution which is globally attractive if $$R_{0} 1.$$ R 1 > 1. The important mathematical findings for the dynamical behaviour of the Chlamydia disease model are also numerically verified using MATLAB. Finally epidemiological implications (...) of our analytical findings are addressed critically. (shrink)

Introduction: A general trend in the psychological literature suggests that guilt contributes to morality more than shame does. Unlike shame-prone individuals, guilt-prone individuals internalize the causality of negative events, attribute responsibility in the first person, and engage in responsible behavior. However, it is not known how guilt- and shame-proneness interact with the attribution of responsibility to others. -/- Methods: In two Web-based experiments, participants reported their attributions of moral culpability (i.e., responsibility, causality, punishment and decision-making) about morally ambiguous acts of (...) killing in different conditions. In Study 1 the vignettes were presented in the 1st person, while in Study 2 in the 3rd person. To test proneness to guilt and shame, we utilized the GASP scale, which differentiates between the affective and behavioral components of each emotion. Statistical analyses were performed in Matlab and R. -/- Results: We found that guilt- and shame-proneness were associated with the severity of attributions in both the first and the third person, but the effect was strong only in the guilt case (both subtypes) and shame-affect case, and not in the shame-behavior case. We call this the Moralizing Effect. -/- Discussion: We wonder whether our finding that guilt-prone people tend to attribute a higher degree of culpability to others is really consistent with the view that guilt motivates people to choose the “moral paths in life”. This echoes views about the harmful aspects of guilt, which have been expressed historically in philosophy, for example, by Friedrich Nietzsche. (shrink)

This paper studies the state of charge estimation of supercapacitors and lithium batteries in the hybrid energy storage system of electric vehicles. According to the energy storage principle of the electric vehicle composite energy storage system, the circuit models of supercapacitors and lithium batteries were established, respectively, and the model parameters were identified online using the recursive least square method and Kalman filtering algorithm. Then, the online estimation of SOC was completed based on the Kalman filtering algorithm and unscented Kalman (...) filtering algorithm. Finally, the experimental platform for SOC estimation was built and Matlab was used for calculation and analysis. The experimental results showed that the SOC estimation results reached a high accuracy, and the variation range of estimation error was [−0.94%, 0.34%]. For lithium batteries, the recursive least square method is combined with the 2RC model to obtain the optimal result, and the estimation error is within the range of [−1.16%, 0.85%] in the case of comprehensive weighing accuracy and calculation amount. Moreover, the system has excellent robustness and high reliability. (shrink)

Fractal art graphics are the product of the fusion of mathematics and art, relying on the computing power of a computer to iteratively calculate mathematical formulas and present the results in a graphical rendering. The selection of the initial value of the first iteration has a greater impact on the final calculation result. If the initial value of the iteration is not selected properly, the iteration will not converge or will converge to the wrong result, which will affect the accuracy (...) of the fractal art graphic design. Aiming at this problem, this paper proposes an improved optimization method for selecting the initial value of the Gauss-Newton iteration method. Through the area division method of the system composed of the sensor array, the effective initial value of iterative calculation is selected in the corresponding area for subsequent iterative calculation. Using the special skeleton structure of Newton’s iterative graphics, such as infinitely finely inlaid chain-like, scattered-point-like composition, combined with the use of graphic secondary design methods, we conduct fractal art graphics design research with special texture effects. On this basis, the Newton iterative graphics are processed by dithering and MATLAB-based mathematical morphology to obtain graphics and then processed with the help of weaving CAD to directly form fractal art graphics with special texture effects. Design experiments with the help of electronic Jacquard machines proved that it is feasible to transform special texture effects based on Newton's iterative graphic design into Jacquard fractal art graphics. (shrink)

Computational intelligence techniques are being investigated as an extension of the traditional fault diagnosis methods. This article presents, for the first time, a scheme for fault detection and isolation via artificial neural networks and fuzzy logic. It deals with the sensor fault of a three-link selective compliance assembly robot arm robot. A second scheme is proposed for fault detection and accommodation via analytical redundancy, and it deals with the sensor fault of a three-link SCARA robot. These proposed FDI approaches are (...) implemented on Matlab/simulink software and tested under several types of faults. The results show the importance of this process. Then, the sensor faults are detected and isolated successfully. Also, the actuator faults are detected and a fault tolerance strategy is used for reconfigurable control using a sliding-mode observer. (shrink)

Tradition wireless sensor networks transmit data by single or multiple hops. However, some sensor nodes close to a static base station forward data more frequently than others, which results in the problem of energy holes and makes networks fragile. One promising solution is to use a mobile node as a mobile sink, which is especially useful in energy-constrained networks. In these applications, the tour planning of MS is a key to guarantee the network performance. In this paper, a novel strategy (...) is proposed to reduce the latency of mobile data gathering in a WSN while the routing strategies and tour planning of MS are jointly optimized. First, the issue of network coverage is discussed before the appropriate number of clusters being calculated. A dynamic clustering scheme is then developed where a virtual cluster center is defined as the MS sojourn for data collection. Afterwards, a tour planning of MS based on prediction is proposed subject to minimizing the traveling distance to collect data. The proposed method is simulated in a MATLAB platform to show the overall performance of the developed system. Furthermore, the physical tests on a test rig are also carried out where a small WSN based on an unmanned aerial vehicle is developed in our laboratory. The test results validate the feasibility and effectiveness of the method proposed. (shrink)

We show that the conventional first-order algorithm of unification can be simulated by finite artificial neural networks with one layer of neurons. In these unification neural networks, the unification algorithm is performed by error-correction learning. Each time-step of adaptation of the network corresponds to a single iteration of the unification algorithm. We present this result together with the library of learning functions and examples fully formalised in MATLAB Neural Network Toolbox.

In this paper, a fresh method is offered regarding training of particular neural networks. This technique is a combination of the adaptive genetic (AG) and cuckoo search (CS) algorithms, called the AGCS method. The intention of training a particular artificial neural network (ANN) is to obtain the finest weight load. With this protocol, a particular weight is taken into account as feedback, which is optimized by means of the hybrid AGCS protocol. In the beginning, a collection of weights is initialized (...) and the similar miscalculation is discovered. Finally, during training of an ANN, we can easily overcome the training complications involving ANNs and also gain the finest overall performance with training of the ANN. We have implemented the proposed system in MATLAB, and the overall accuracy is about 93%, which is much better than that of the genetic algorithm (86%) and CS (88%) algorithm. (shrink)

In the traditional case, the uncertainty of the ambient temperature measured by the experiential distributed sensor is considered. In this paper, a model based on the moving least square method in the fusion algorithm is proposed to study the optimal monitoring point of the sensor in the greenhouse and determine the most suitable installation position of the sensor in the greenhouse to improve the control effect of the temperature control device of the system. MATLAB simulation software is used to (...) simulate each working condition of the greenhouse. Temperature data measured at 15 locations in the greenhouse were used to evaluate all possible combinations of monitoring locations and to estimate the optimal location for indoor temperature sensors. Compared with the traditional method, the error is reduced to 0.373, and the data are more accurate. (shrink)

Excessive use of social media is a developing concern in the twenty-first century. This issue needs to be addressed before it has any more significant consequences than what we are currently experiencing. As a preventive technique, advertisements and awareness-raising campaigns about the detrimental impact of digital technologies are used. The application of novel mathematical techniques and terminologies in this field of study will have significant potential to enhance healthy living by preventing certain ailments. This is the most compelling justification for (...) conducting a new study with the most up-to-date techniques at our disposal. This study investigates clear and concise transmission in order to generate a deterministic mathematical model of social media addiction S M A using the fractal-fractional derivative operator. Also, the analysis of the S M A model in terms of the invariant domain, the existence of a positive invariant solution, and equilibria assumptions are stated in a detailed manner. Besides that, the basic reproduction number ℝ 0 < 1 is computed, demonstrating that the proposed methodology is more efficacious. The Atangana-Baleanu FF differential operators are recently defined in FF differential operators that are applied to characterize the S M A model’s mathematical algorithm. We investigated the numerical behaviour of the S M A in three ways: changing the fractional-order α as well as the fractal-dimension ℘ ; changing α while keeping ℘ constant; and changing ℘ while keeping α constant. Our examined visualizations and simulation studies using MATLAB for the numerical modelling of the aforementioned system showed that the novel developed Atangana-Baleanu FF differential operators produce remarkable results when compared to the classical frame. (shrink)

This paper introduces a novel method to control the operation of the active suspension system. In this research, a quarter-dynamic model is used to simulate the vehicle’s vibrations. Besides, the sliding mode-PID-integrated algorithm with five state variables is proposed to be used. This is a completely original and novel algorithm. The process of establishing the control algorithm is clearly described. The simulation is performed by the MATLAB software. The results of the paper have shown the advantages of the sliding (...) mode-PID algorithm used in this research. Accordingly, the displacement and acceleration of the sprung mass were significantly reduced when this algorithm was used. The maximum and average values of the displacement of the sprung mass are only 1.31% and 1.29%, respectively, compared with the situation of the vehicle using a passive suspension. Similarly, the value of the acceleration is 6.98% and 2.94%, respectively. In addition, the phenomenon of “chattering” has also been significantly reduced when using this controller. In the future, some more complex algorithms can be proposed. (shrink)

In this paper, we first define the vector product in Minkowski space $\mathbb{R}_{4}^{7}$, which is identified with the space of spatial split-octonions. Next, we derive the $G_{2}-$ frame formulae for a seven dimensional Minkowski curve by using the spatial split-octonions and the vector product. We show that Frenet–Serret formulas are satisfied for a spatial split octonionic curve. We obtain the congruence of two spatial split octonionic curves and give relationship between the $G_{2}-$ frame and Frenet–Serret frame. Furthermore, we present the (...) Frenet–Serret frame with split octonions in $\mathbb{R}_{4}^{8}$. Finally, we give illustrative examples with Matlab codes. (shrink)

In this work, our aim is to investigate the impact of a non-Kolmogorov predator-prey-subsidy model incorporating nonlinear prey refuge and the effect of fear with Holling type II functional response. The model arises from the study of a biological system involving arctic foxes, lemmings, and seal carcasses. The positivity and asymptotically uniform boundedness of the solutions of the system have been derived. Analytically, we have studied the criteria for the feasibility and stability of different equilibrium points. In addition, we have (...) derived sufficient conditions for the existence of local bifurcations of codimension 1. It is also observed that there is some time lag between the time of perceiving predator signals through vocal cues and the reduction of prey’s birth rate. So, we have analyzed the dynamical behaviour of the delayed predator-prey-subsidy model. Numerical computations have been performed using MATLAB to validate all the analytical findings. Numerically, it has been observed that the predator, prey, and subsidy can always exist at a nonzero subsidy input rate. But, at a high subsidy input rate, the prey population cannot persist and the predator population has a huge growth due to the availability of food sources. (shrink)

A new edge detection technique based on the texture feature coding method is proposed. The TFCM is a texture analysis scheme that is generally used in texture-based image segmentation and classification applications. The TFCM transforms an input image into a texture feature image whose pixel values represent the texture information of the pixel in the original image. Then, on the basis of the transformed image, several features are calculated as texture descriptors. In this article, the TFCM is employed differently to (...) construct an edge detector. In particular, the texture feature number of the TFCM is considered. In other words, the TFN image is used for subsequent processes. After obtaining the TFN image, a simple thresholding scheme is employed for obtaining the coarse edge image. Finally, an edge-thinning procedure is used to obtain the tuned edges. We conducted several experiments on a variety of images and compared the results with the popular existing methods such as the Sobel, Prewitt, Canny, and Canny–Deriche edge detectors. The obtained results were evaluated quantitatively with the Figure of Merit criterion. The experimental results demonstrated that our proposed method improved the edge detection performance greatly. We further implemented the proposed edge detector with a hardware system. To this end, a field programmable gate array chip was used. The related simulations were carried out with the MATLAB Simulink tool. Both software and hardware implementations demonstrated the efficiency of the proposed edge detector. (shrink)

In recent years, the important and fast growth in the development and demand of multimedia products is contributing to an insufficiency in the bandwidth of devices and network storage memory. Consequently, the theory of data compression becomes more significant for reducing data redundancy in order to allow more transfer and storage of data. In this context, this paper addresses the problem of lossy image compression. Indeed, this new proposed method is based on the block singular value decomposition (SVD) power method (...) that overcomes the disadvantages of MATLAB’s SVD function in order to make a lossy image compression. The experimental results show that the proposed algorithm has better compression performance compared with the existing compression algorithms that use MATLAB’s SVD function. In addition, the proposed approach is simple in terms of implementation and can provide different degrees of error resilience, which gives, in a short execution time, a better image compression. (shrink)

The losses in the radial distribution system are inevitable which needs to be minimized for the proper transmission of power to the end customers. This problem can be solved by the allocation of capacitor banks at proper locations with appropriate sizing. These allocations need an efficient approach for the performance enhancement of RDS. In this paper, several metaheuristic techniques such as particle swarm optimization, Harmony search, Bat, Cuckoo, and Grey-wolf algorithms are employed to find the size of capacitor banks. Loss (...) sensitivity analysis is considered for the indication of candidate buses where a capacitor has to be installed to reduce the total system losses and ultimately increase efficiency. Cost-effectiveness, power loss minimization, and voltage enhancement can be determined and compared for these 5 techniques and are implemented on the IEEE-34 bus system to illustrate the efficacy of each of them. The results show the advantages and drawbacks of the techniques separately. The simulations are carried out in MATLAB. (shrink)

The temporal structure of behavior contains a rich source of information about its dynamic organization, origins, and development. Today, advances in sensing and data storage allow researchers to collect multiple dimensions of behavioral data at a fine temporal scale both in and out of the laboratory, leading to the curation of massive multimodal corpora of behavior. However, along with these new opportunities come new challenges. Theories are often underspecified as to the exact nature of these unfolding interactions, and psychologists have (...) limited ready-to-use methods and training for quantifying structures and patterns in behavioral time series. In this paper, we will introduce four techniques to interpret and analyze high-density multi-modal behavior data, namely, to: (1) visualize the raw time series, (2) describe the overall distributional structure of temporal events (Burstiness calculation), (3) characterize the nonlinear dynamics over multiple timescales with Chromatic and Anisotropic Cross-Recurrence Quantification Analysis (CRQA), (4) and quantify the directional relations among a set of interdependent multimodal behavioral variables with Granger Causality. Each technique is introduced in a module with conceptual background, sample data drawn from empirical studies and ready-to-use Matlab scripts. The code modules showcase each technique’s application with detailed documentation to allow more advanced users to adapt them to their own datasets. Additionally, to make our modules more accessible to beginner programmers, we provide a “Programming Basics” module that introduces common functions for working with behavioral timeseries data in Matlab. Together, the materials provide a practical introduction to a range of analyses that psychologists can use to discover temporal structure in high-density behavioral data. (shrink)

At present, the motion control algorithms of lower limb exoskeleton robots have errors in tracking the desired trajectory of human hip and knee joints, which leads to poor follow-up performance of the human-machine system. Therefore, an iterative learning control algorithm is proposed to track the desired trajectory of human hip and knee joints. In this paper, the experimental platform of lower limb exoskeleton rehabilitation robot is built, and the control system software and hardware design and robot prototype function test are (...) carried out. On this basis, a series of experiments are carried out to verify the rationality of the robot structure and the feasibility of the control method. Firstly, the dynamic model of the lower limb exoskeleton robot is established based on the structure analysis of the human lower limb; secondly, the servo control model of the lower limb exoskeleton robot is established based on the iterative learning control algorithm; finally, the exponential gain closed-loop system is designed by using MATLAB software. The relationship between convergence speed and spectral radius is analyzed, and the expected trajectory of hip joint and knee joint is obtained. The simulation results show that the algorithm can effectively improve the gait tracking accuracy of the lower limb exoskeleton robot and improve the follow-up performance of the human-machine system. (shrink)

The renin-angiotensin system (RAS) is critical in sodium and blood pressure (BP) regulation, and in cardiovascular-renal (CVR) diseases and therapeutics. As a contribution to SAPHIR project, we present a realistic computer model of renin production and circulating RAS, integrated into Guyton’s circulatory model ( GCM ). Juxtaglomerular apparatus, JGA , and Plasma modules were implemented in C ++/M2SL (Multi-formalism Multi-resolution Simulation Library) for fusion with GCM . Matlab © optimization toolboxes were used for parameter identification. In JGA , renin (...) production and granular cells recruitment (GCR) are controlled by perfusion pressure (PP), macula densa (MD), angiotensin II (Ang II), and renal sympathetic activity (RSNA). In Plasma , renin and ACE (angiotensin-converting enzyme) activities are integrated to yield Ang I and II. Model vs. data deviation is given as normalized root mean squared error (nRMSE; n points). Identification: JGA and Plasma parameters were identified against selected experimental data. After fusion with GCM : (1) GCR parameters were identified against Laragh’s PRA-natriuresis nomogram; (2) Renin production parameters were identified against two sets of data ([renin] transients vs. ACE or renin inhibition). Finally, GCR parameters were re-identified vs. Laragh’s nomogram (nRMSE 8%, n = 9). Validation: (1) model BP, PRA and [Ang II] are within reported ranges, and respond physiologically to sodium intake; (2) short-term Ang II infusion induces reported rise in BP and PRA. The modeled circulating RAS, in interaction with an integrated CVR, exhibits a realistic response to BP control maneuvers. This construction will allow for modelling hypertensive and CVR patients, including salt-sensitivity, polymorphisms, and pharmacotherapeutics. (shrink)

Demodulating harmful nodes and diminishing the energy waste in sensor nodes can prolong the lifespan of wireless sensor networks. In this study, a genetic algorithm and an adaptive neuro fuzzy inference system were used to diminish the energy waste of sensors. Weighted trust evaluation was applied to search for harmful nodes in the network to prolong the lifespan of WSNs. A low-energy adaptive clustering hierarchy method was used to analyze the results. It was discovered that searching for harmful nodes with (...) GA-ANFIS using weighted trust evaluation significantly increased the lifespan of WSNs. For evaluation of the proposed method we used the mean of energy of all sensors against of the round, data packets received in base station, minimum energy versus rounds and number of alive sensors versus rounds. Also, in this paper we compared the proposed method results with LEACH, LEACH-DT, Random, SIF and GA-Fuzzy methods. As results the proposed method has high life time than other methods. A representation of the overall system was implemented using MATLAB software. (shrink)

This book attempts to marry truth-conditional semantics with cognitive linguistics in the church of computational neuroscience. To this end, it examines the truth-conditional meanings of coordinators, quantifiers, and collective predicates as neurophysiological phenomena that are amenable to a neurocomputational analysis. Drawing inspiration from work on visual processing, and especially the simple/complex cell distinction in early vision (V1), we claim that a similar two-layer architecture is sufficient to learn the truth-conditional meanings of the logical coordinators and logical quantifiers. As a prerequisite, (...) much discussion is given over to what a neurologically plausible representation of the meanings of these items would look like. We eventually settle on a representation in terms of correlation, so that, for instance, the semantic input to the universal operators (e.g. and, all)is represented as maximally correlated, while the semantic input to the universal negative operators (e.g. nor, no)is represented as maximally anticorrelated. On the basis this representation, the hypothesis can be offered that the function of the logical operators is to extract an invariant feature from natural situations, that of degree of correlation between parts of the situation. This result sets up an elegant formal analogy to recent models of visual processing, which argue that the function of early vision is to reduce the redundancy inherent in natural images. Computational simulations are designed in which the logical operators are learned by associating their phonological form with some degree of correlation in the inputs, so that the overall function of the system is as a simple kind of pattern recognition. Several learning rules are assayed, especially those of the Hebbian sort, which are the ones with the most neurological support. Learning vector quantization (LVQ) is shown to be a perspicuous and efficient means of learning the patterns that are of interest. We draw a formal parallelism between the initial, competitive layer of LVQ and the simple cell layer in V1, and between the final, linear layer of LVQ and the complex cell layer in V1, in that the initial layers are both selective, while the final layers both generalize. It is also shown how the representations argued for can be used to draw the traditionally-recognized inferences arising from coordination and quantification, and why the inference of subalternacy breaks down for collective predicates. Finally, the analogies between early vision and the logical operators allow us to advance the claim of cognitive linguistics that language is not processed by proprietary algorithms, but rather by algorithms that are general to the entire brain. Thus in the debate between objectivist and experiential metaphysics, this book falls squarely into the camp of the latter. Yet it does so by means of a rigorous formal, mathematical, and neurological exposition – in contradiction of the experiential claim that formal analysis has no place in the understanding of cognition. To make our own counter-claim as explicit as possible, we present a sketch of the LVQ structure in terms of mereotopology, in which the initial layer of the network performs topological operations, while the final layer performs mereological operations. The book is meant to be self-contained, in the sense that it does not assume any prior knowledge of any of the many areas that are touched upon. It therefore contains mini-summaries of biological visual processing, especially the retinocortical and ventral /what?/ parvocellular pathways computational models of neural signaling, and in particular the reduction of the Hodgkin-Huxley equations to the connectionist and integrate-and-fire neurons Hebbian learning rules and the elaboration of learning vector quantization the linguistic pathway in the left hemisphere memory and the hippocampus truth-conditional vs. image-schematic semantics objectivist vs. experiential metaphysics and mereotopology. All of the simulations are implemented in MATLAB, and the code is available from the book’s website. • The discovery of several algorithmic similarities between visison and semantics. • The support of all of this by means of simulations, and the packaging of all of this in a coherent theoretical framework. (shrink)

It is of practical significance to introduce the Internet of Things technology into the financial service industry and find the driving factors and mechanisms of financial innovation to accelerate the promotion of financial innovation. This article starts from the perspective of banks and other supply chain financial institutions, takes mainstream trading products in the commodity trading market as the research object, uses the LA-VAR model, and fully considers the market price fluctuations and liquidity factors of supply chain financial inventory products. (...) It analyzes the theoretical basis of the continuous innovation of rural financial products. On the basis of analyzing the basic characteristics and types of rural financial product innovation, we explore the connotation of sustainable innovation of rural financial products, clarify the evaluation criteria, and lay a theoretical foundation for continuous dynamic evaluation. Based on technical innovation evaluation theoretical models such as Schumpeter’s innovation model, technical specifications-technological track model, and NR relationship model market, we analyze the innovation elements of rural financial products from the external and internal aspects of innovation and discuss the relationship between the factors. The interaction mechanism of rural financial products has established a dynamic mechanism model for the continuous innovation of rural financial products. A fuzzy comprehensive evaluation was made on the continuous innovation power of financial service industry products in a certain area. Using a combination of remote surveys and on-site visits, a questionnaire survey was conducted on financial service industry institutions in a certain region’s financial system. Each survey object was required to conduct 120 × 1067 index comparisons and use the data after processing the arithmetic average Matlab carries out the objective processing of programming. The results show that the LA-VAR model with liquidity indicators can measure the liquidity risk well and more comprehensively evaluate the risk of the inventory pledge financing model. According to the index weights determined by AHP, the development of the financial service industry will be promoted in a targeted manner from the internal construction of financial institutions and the optimization of the external innovation environment. (shrink)

Through the analysis of emotional tendency in online public opinion, governments and enterprises can stabilize people’s emotion more effectively and maintain social stability. The problem studied in this paper is how to analyze the emotional tendency of online public opinion efficiently, and finally, this paper chooses deep learning algorithm to perform fast analysis of emotional tendency of online public opinion. This paper briefly introduced the structure of the basic model used for emotional tendency analysis of online public opinion and the (...) convolutional neural network model used for text emotion classification. Then, the CNN model was improved by long short-term memory. A simulation experiment was carried out on MATLAB for the improved text emotion classification model to verify the influence of activation function type on the improved model and the performance difference between the improved model and support vector machine and traditional CNN models. The results showed that the improved classification model that adopted the sigmoid activation function had higher accuracy and was less affected by language than the relu and tanh activation functions; the improved classification model had the highest accuracy, recall rate, and F-value in classifying emotional tendency of web texts, followed by the traditional CNN model and the SVM model. (shrink)

Music is an abstract art form that uses sound as its means of expression. It has deeply affected our lives. This paper proposes a method for extracting segment features from nonmultiple cluster music files. We divide each piece of music into multiple segments and extract the features of each segment. The specific process includes nonmultiple cluster music file note extraction, main melody extraction, segment division, and segment feature extraction. The segment feature is extracted from a segment of a piece of (...) music, contains the main melody and accompaniment information of the segment, and can reflect the sequence relationship of the notes. This paper proposes a performance style conversion network based on recurrent neural network and convolutional neural network. The bidirectional recurrent neural network based on Gated Recurrent Unit is used to extract different styles of note feature vector sequences, and the extracted note feature vector sequence is used to predict the intensity of a specific style, and the intensity changes of different styles of nonmultiple cluster music are better learned. Through the comparison, the multiclassification strategy of “one-to-the-rest” is selected, and the fuzzy recurrent neural network is applied to the shortcomings of the unrecognizable area. Finally, according to the feature extraction method and the principle of the classifier algorithm studied in this paper, a music style classification system is implemented in the MATLAB environment. Experimental simulation shows that this system can effectively classify music performance styles. (shrink)

The aim of this article was to discuss the modeling and control method of quadrotor unmanned aerial vehicle. In the process of modeling, mechanism modeling and experimental testing are combined, especially the motor and propeller are modeled in detail. Through the understanding of the body structure and flight principle of the quadrotor UAV, the Newton–Euler method is used to analyze the dynamics of the quadrotor UAV, and the mathematical model of the UAV is established under the small angle rotation. Process (...) identifier is used to control it. First, the attitude angle of the model is controlled by PID, and based on this, the speed in each direction is controlled by PID. Then, the PID control of the four rotor aircraft with the center of gravity offset is simulated by MATLAB. The results show that the pitch angle and roll angle can be controlled by 5 degrees together without center of gravity deviation, and the PID can effectively control the control quantity and achieve the desired effect in a short time. Classical BP algorithm, classical GA-BP algorithm, and improved GA-BP algorithm were trained, respectively, with a total of 150 sets of training data, training function uses Levenberg-Marquardt, and performance function uses mean squared error. In the background of the same noise, the improved GA-BP algorithm has the highest detection rate, classical GA-BP algorithm is the second, and classical BP algorithm is the worst. The simulation results show that the PID control law can effectively control the attitude angle and speed of the rotor UAV in the case of center of gravity deviation. (shrink)