The indispensability argument seeks to establish the existence of mathematical objects. The success of the indispensability argument turns on finding cases of genuine extra- mathematical explanation. In this paper, I identify a new case of extra- mathematical explanation, involving the search patterns of fully-aquatic marine predators. I go on to use this case to predict the prevalence of extra- mathematical explanation in science.

Objective: A deep understanding of the relationship between a scarce drug's dose and clinical response is necessary to appropriately distribute a supply-constrained drug along these lines. Summary of key data: The vast majority of drug development and repurposing during the COVID-19 pandemic – an event that has made clear the ever-present scarcity in healthcare systems –has been ignorant of scarcity and dose optimisation's ability to help address it. Conclusions: Future pandemic clinical trials systems should obtain dose optimisation data, as these (...) appear necessary to enable appropriate scarce resource allocation according to societal values. (shrink)

Endeavours of politicians, representatives of law enforcement institutions and courts to create simplified, accelerated and less human and time resources requiring legal procedures in criminal cases prompted the authors of this article to assess the possibilities to develop the written form of procedure in Lithuania. The goal of the authors of this article is to assess the origin and goals of the written form of procedure, as well as to define the main rules and points for discussions on the possibilities (...) to develop the written form of procedure in the Lithuanian criminal procedural law. The conclusion is drawn in this article to the effect that written form of procedure is seen as a condition for simplifying and accelerating the legal process, and choosing this form of procedure is not considered as denying or restraining the expectations of participants of criminal procedure towards a fair trial. The analysis provides the basis for the authors to make a conclusion on the appropriate limits of applying written or oral procedures for hearing criminal cases: Oral procedure must be guaranteed in cases where questions of criminal liability and personal guilt are solved at the first instance court hearings; Oral procedure usually has to be guaranteed in cases where during the procedure at the first instance court hearing the questions of criminal liability and personal guilt are solved, although oral procedure may be limited and the procedure may be conducted in written form if new evidence are not investigated and there is no doubt for deciding whether oral procedure is better for understanding the case; Oral procedure need not be guaranteed only in cases where questions of application of the law are solved and if oral procedure was guaranteed during the procedure at the court of first instance; Written procedure may guarantee the right to a fair trial, where the participants of the procedure are allowed to provide various explanations and written documents or a person is allowed to ask for an oral court hearing. (shrink)

The standard approach to solve prediction tasks is to apply inductive methods such as, e.g., the straight rule. Such methods are proven to be access-optimal in specific prediction settings, but not in all. Within the optimality-approach of meta-induction, success-based weighted prediction methods are proven to be access-optimal in all possible continuous prediction settings. However, meta-induction fails to be access-optimal in so-called demonic discrete prediction environments where the predicted value is inversely correlated with the true outcome. In this paper the problem (...) of discrete prediction environments is addressed by embedding them into a synchronised prediction setting. In such a setting the task consists in providing a discrete and a continuous prediction. It is shown that synchronisation constraints exclude the possibility of demonic environments. (shrink)

Applying causal methods to fields such as healthcare, marketing, and economics receives increasing interest. In particular, optimising the individual-treatment-effect – often referred to as uplift modelling – has peaked in areas such as precision medicine and targeted advertising. While existing techniques have proven useful in many settings, they suffer vividly in a dynamic environment. To address this issue, we propose a novel optimisation target that is easily incorporated in bandit algorithms. Incorporating this target creates a causal model which we name (...) an uplifted contextual multi-armed bandit. Experiments on real and simulated data show the proposed method to effectively improve upon the state-of-the-art. All our code is made available online at https://github.com/vub-dl/u-cmab. (shrink)

ABSTRACTIn this article I pursue the implications of the statement that constitutional rights are – as Alexy’s principles theory argues – optimisation requirements, and show that they are not. I ar...

Plastic waste is a significant environmental problem for almost all countries; therefore, protecting the environment from the problem is crucial. The most sensible solution to these problems is substituting the natural aggregates with substantial plastic waste in various building materials. This study aimed to optimise the mixed design ratio of cement brick containing plastic waste as aggregate replacement. Plastic cement brick mixtures were prepared by the incorporation of four different types of plastic waste such as polyethylene terephthalate (PET), high-density polyethylene, (...) low-density polyethylene and polypropylene into cement bricks with different cement contents (150, 300 and 450 g) and plastic replacement percentages (0, 3 and 6%). Compressive strength and water absorption of the plastic cement bricks were analysed using a statistical model through the response surface methodology. It revealed the optimum cement brick mixed design is C3-1% PET with the compressive strength of 27.50 MPa and water absorption of 1.16%. The optimised plastic cement brick also satisfied the general ASTM C62-17 requirements for building bricks despite the higher porosity observed by the scanning electron microscopy. The results from Fourier transform infrared spectroscopy analysis also showed that the addition of the plastic waste into cement brick was unlikely to modify the chemical compound within the cement brick mixtures. Thus, the proposed mathematical model can predict the required hardened properties of plastic cement bricks and could lead to greater utilisation of plastic waste in building materials. (shrink)

This paper examines three approaches to the relationship between our moral reasons to bear costs for others’ sake before and beyond the call of duty. Symmetry holds that you are required to optimise your beneficial sacrifices even when they are genuinely supererogatory. If you are required to bear a cost C for the sake of a benefit B, when they are the only costs and benefits at stake, you are also conditionally required to bear an additional cost C, for the (...) sake of an additional benefit B, when enough other costs and benefits are at stake that both of your alternatives are presumptively supererogatory. Disconnection rejects the requirement to optimise when your options are presumptively supererogatory and maintains that you have an entirely free hand to choose as you will among them. Asymmetry holds that when acting beyond the call of duty you are entitled to a measure of additional freedom compared to when you are not taking on supererogatory costs—you can prioritise your own well-being and reasons to a greater degree—but places constraints on the options that you may permissibly choose. We defend a version of Asymmetry and explore its implications for recent debates on charitable giving. (shrink)

Almaatouq et al. propose an integrative experiment design space combined with large samples for scientific advancement. We argue recent innovative designs combining closed-loop experiment designs and Bayesian optimisation allow for integrative experiments at an individual level during a single session, circumventing the necessity for large samples. This method can be applied across disciplines, including developmental and clinical research.

In the metabolic control theory, the control coefficient is a key parameter in quantifying the sensitivity of the flux towards an infinitesimal variation of enzyme activity. This concept does not apply just as it is for variations of enzyme concentrations whenever there is spatial, energy or resources limitations in the cell. Due to constraint on total enzyme concentration, the variation of concentration of any given enzyme may affect the concentrations of other enzymes. To take into account these correlations between enzyme (...) concentrations, we propose the concept of "combined response coefficient". Its definition is similar to that of the control coefficient, but its mathematical expression is different. Its range of variation is from – + 1, the null value corresponding to optimum enzyme concentration, i.e. to concentrations that maximise the flux, and the negative values to concentrations beyond the optimum value. A summation property could be derived using a simple weighting of the combined response coefficients, the sum of the weighed coefficient being 0. (shrink)

Central to the argument of ‘Biodefense and the Production of Knowledge: Rethinking the Problem’ are claims that the vast majority of ethical debate about biodefense research to date has focused on the dual use problem, and the focus of ethical discussion of dual-use research has been on the need to strike ‘a proper balance of only two dominant values: biosecurity and “open science”’ —the idea being that ‘under current conditions other values can and ought to be ignored because the stakes (...) are so high’.1With regard to , Buchanan and Kelley's main point is that policy making regarding biodefense and dual use should be seen as an ‘optimisation problem’—the aim should be to achieve the greater good of society, where all relevant values are taken into account, rather than limiting attention to just two values—security and open science—in particular. While, as other commentators have argued, it is questionable whether these authors have provided an accurate account of ethical discussion of biodefense and dual use to date, in this brief commentary my purpose is to argue that the values of security and open science should themselves be seen as proxies for other values and that solution to …. (shrink)

This article examines soldier performance optimisation, enhancement, and augmentation across the three dimensions of physical performance, cognitive performance, and socio-cultural understanding. Optimisation refers to combatants attaining their maximum biological potential. Enhancement refers to combatants achieving a level of performance beyond their biological potential through drugs, surgical procedures, or even gene editing. Augmentation refers to a blending of organic and biomechatronic body parts such as electronic or mechanical implants, prosthetics, and brain–machine interfaces. This article identifies that soldier optimisation is a necessity (...) to protect individual combatants and to give them the ability to make legal and morally justifiable decisions in battle. While enhancement and augmentation of military personnel can lead to accelerated and more destructive warfare, it can also be argued that there is an ethical and moral responsibility to provide combatants the best opportunity for survivability, and that better functioning, less fatigued, and better informed military personnel can make better decisions in battle. There is also a moral responsibility of the state for the combatants themselves, and short-term military success must be balanced against the short- and long-term health and wellbeing of the personnel. This article concludes that it is both the intent and the degree that decide the acceptability. (shrink)

The concept of performance has gradually become established in health policies. Presented as necessary and positive, it is often reduced to efficiency, which results in policies and management styles aimed at optimisation. While they are supposed to guarantee the sustainability of our healthcare systems, these practices have made them fragile. Insights from the life sciences help us understand why. Indeed, biologists observe that living beings do not prioritise optimisation but robustness. To cope with fluctuations, a robust organisation operates with redundancies, (...) apparent waste, heterogeneity, organised fluctuations, slowness, and hesitation. It functions sub‐optimally. This article offers a theoretical reflection and management directions for more robust healthcare systems. (shrink)

This study suggests a new approach to EEG data classification by exploring the idea of using evolutionary computation to both select useful discriminative EEG features and optimise the topology of Artificial Neural Networks. An evolutionary algorithm is applied to select the most informative features from an initial set of 2550 EEG statistical features. Optimisation of a Multilayer Perceptron is performed with an evolutionary approach before classification to estimate the best hyperparameters of the network. Deep learning and tuning with Long Short-Term (...) Memory are also explored, and Adaptive Boosting of the two types of models is tested for each problem. Three experiments are provided for comparison using different classifiers: one for attention state classification, one for emotional sentiment classification, and a third experiment in which the goal is to guess the number a subject is thinking of. The obtained results show that an Adaptive Boosted LSTM can achieve an accuracy of 84.44%, 97.06%, and 9.94% on the attentional, emotional, and number datasets, respectively. An evolutionary-optimised MLP achieves results close to the Adaptive Boosted LSTM for the two first experiments and significantly higher for the number-guessing experiment with an Adaptive Boosted DEvo MLP reaching 31.35%, while being significantly quicker to train and classify. In particular, the accuracy of the nonboosted DEvo MLP was of 79.81%, 96.11%, and 27.07% in the same benchmarks. Two datasets for the experiments were gathered using a Muse EEG headband with four electrodes corresponding to TP9, AF7, AF8, and TP10 locations of the international EEG placement standard. The EEG MindBigData digits dataset was gathered from the TP9, FP1, FP2, and TP10 locations. (shrink)

In times of rapid technological progress, transhumanism, which strives for radical technological transformations of the human being, spreads its ideas with great publicity and media impact. Although these ideas are directed towards the future, they influence how we understand humans, bodies, and technology today. T his article exam­ ines the anthropology of transhumanism and investigates the extent to which it offers approaches for the contemporary anthropology of body optimisation. T he article comes to the conclusion that the understanding of the (...) human being in transhumanism is prob­ lematic in many respects and therefore not suitable for the further development of a contemporary philosophical anthropology. Nevertheless, corrective perspectives for an anthropology of contemporary body optimisation can be derived from these problems. (shrink)

Previous research studies of traffic networks are mainly based on planar networks and less considered the influence of multilayer networks, which illustrate and represent different appropriate urban traffic modes. Development of rail and road networks is inseparable from the development of a prosperous urban area; thus, research on multilayer networks has scientific potential and fulfils a real need. In this paper, a framework of complex network based integrated multilayer urban growth and optimisation model is proposed, to analyse the complex relationships (...) between the traffic network structure, the population growth, and the urban land-use. The innovation of this paper is the combination of the traffic complex multilayer networks and the “Four Step Model”. With the multiobjective, multilayer network coevolution and optimisation model, a more efficient traffic network layout was generated based on different land-use, population density, and travel speed scenarios. Then, this paper has proved that the proposed CNIMUGOM can save the traffic network construction investment, reduce the travel cost, make the urban traffic network more efficient, and decrease the total traffic flow amount. This research has connected the recent complex multilayer network related study and traditional urban economic model based study. The findings of the study afford to improve the current land-use and traffic integrated models and can provide traffic network planning suggestions for urban agglomeration development. (shrink)

The permanent struggle for optimisation can be seen as one of the most significant cultural principles of contemporary Western societies: the demand for improved performance and efficiency as well as the pursuit of self-improvement are con-sidered necessary in order to keep pace with an accelerated, competitive modern-ity. This affects not only work and education, but also family life, parent–child relationships and intimate relationships in respect to the body and the self, in regard to the public as well as the private (...) realm. Bringing together contributions from renowned scholars from the fields of sociology, psychology and psycho-analysis, this book explores the impacts of optimisation on culture and psyche, examining the contradictions and limitations of optimisation, in conjunction with the effects of social transformations on individuals and shifts in regard to the meaning of ‘pathology’ and ‘normality’. (shrink)

The IPAP Schizophrenia Algorithm was originally designed in the form of a flow chart to help physicians optimise the treatment of schizophrenic patients. We examined the current version from the perspective of recent work on terminologies and ontologies thereby drawing on the resources of Basic Formal Ontology, and this with the objective to make the algorithm appropriate for Semantic Web applications. We found that Basic Formal Ontology is a rich enough theory to represent all the entities involved and that applying (...) the theory to the IPAP schizophrenia algorithm results in a representation that can be used by software agents to perform monitoring and control in a referent tracking environment. (shrink)

Definition of the problemThe article addresses the relationship between reproduction, time and the good life. Services offered by reproductive medicine and conceptions of the good life in time influence each other reciprocally. This interaction is characterised by implicit and explicit normative settings and expectations of appropriate temporality.ArgumentsWe first discuss the significance of time for the life course and for parenthood from a sociological and social psychological perspective. Reproductive medicine can increase the options for becoming a parent and thus for life-time (...) autonomy. However, in the context of societal imperatives for optimisation and efficiency, it can also have opposite effects and increase heteronomy. Overall, this leads to changed forms of adaptation and self-determination, new dilemmas and ambivalences in the temporal optimisation of parenthood.ConclusionsAgainst this background, we explain how the ethics of reproductive medicine could benefit from interdisciplinary research that focuses on life in its temporal course. (shrink)

In a series of recent publications, Gigerenzer and his collaborators have attempted to derive new norms of rationality from their psychological research in the Centre for Adaptive Behaviour and Cognition (ABC). Specifically, they have claimed that there are good reasons to replace the norms traditionally used to assess rational behaviour, which rest on the ideal of optimisation. Their proposal has considerable importance, as it has been laid out as a revision of the normative framework accepted in the social, behavioural, and (...) cognitive sciences. Still, whereas the ABC scholars present their approach as diametrically opposed to the framework of optimisation—two incompatible takes on the problem of defining rational behaviour—this paper argues that it is not entirely clear whether this is the case. I introduce a distinction between different kinds of reflection upon norms of rationality that has been neglected by ABC scholars, and provide reasons to think that the departure from the traditional framework might be less radical than ABC scholars suppose. (shrink)

The relations between rationality and optimization have been widely discussed in the wake of Herbert Simon's work, with the common conclusion that the rationality concept does not imply the optimization principle. The paper is partly concerned with adding evidence for this view, but its main, more challenging objective is to question the converse implication from optimization to rationality, which is accepted even by bounded rationality theorists. We discuss three topics in succession: (1) rationally defensible cyclical choices, (2) (...) the revealed preference theory of optimization, and (3) the infinite regress of optimization. We conclude that (1) and (2) provide evidence only for the weak thesis that rationality does not imply optimization. But (3) is seen to deliver a significant argument for the strong thesis that optimization does not imply rationality. (shrink)

A considerable number of areas of bioscience, including gene and drug discovery, metabolic engineering for the biotechnological improvement of organisms, and the processes of natural and directed evolution, are best viewed in terms of a ‘landscape’ representing a large search space of possible solutions or experiments populated by a considerably smaller number of actual solutions that then emerge. This is what makes these problems ‘hard’, but as such these are to be seen as combinatorial optimisation problems that are best attacked (...) by heuristic methods known from that field. Such landscapes, which may also represent or include multiple objectives, are effectively modelled in silico, with modern active learning algorithms such as those based on Darwinian evolution providing guidance, using existing knowledge, as to what is the ‘best’ experiment to do next. An awareness, and the application, of these methods can thereby enhance the scientific discovery process considerably. This analysis fits comfortably with an emerging epistemology that sees scientific reasoning, the search for solutions, and scientific discovery as Bayesian processes. (shrink)

Merging logic and mathematics in deductive inference-an innovative, cutting-edge approach. Optimization methods for logical inference? Absolutely, say Vijay Chandru and John Hooker, two major contributors to this rapidly expanding field. And even though "solving logical inference problems with optimization methods may seem a bit like eating sauerkraut with chopsticks... it is the mathematical structure of a problem that determines whether an optimization model can help solve it, not the context in which the problem occurs." Presenting powerful, proven (...) optimization techniques for logic inference problems, Chandru and Hooker show how optimization models can be used not only to solve problems in artificial intelligence and mathematical programming, but also have tremendous application in complex systems in general. They survey most of the recent research from the past decade in logic/optimization interfaces, incorporate some of their own results, and emphasize the types of logic most receptive to optimization methods-propositional logic, first order predicate logic, probabilistic and related logics, logics that combine evidence such as Dempster-Shafer theory, rule systems with confidence factors, and constraint logic programming systems. Requiring no background in logic and clearly explaining all topics from the ground up, Optimization Methods for Logical Inference is an invaluable guide for scientists and students in diverse fields, including operations research, computer science, artificial intelligence, decision support systems, and engineering. (shrink)

Mental representations have continuous as well as discrete, combinatorial properties. For example, while predominantly discrete, phonological representations also vary continuously; this is reflected by gradient effects in instrumental studies of speech production. Can an integrated theoretical framework address both aspects of structure? The framework we introduce here, Gradient Symbol Processing, characterizes the emergence of grammatical macrostructure from the Parallel Distributed Processing microstructure (McClelland, Rumelhart, & The PDP Research Group, 1986) of language processing. The mental representations that emerge, Distributed Symbol Systems, (...) have both combinatorial and gradient structure. They are processed through Subsymbolic Optimization–Quantization, in which an optimization process favoring representations that satisfy well-formedness constraints operates in parallel with a distributed quantization process favoring discrete symbolic structures. We apply a particular instantiation of this framework, λ-Diffusion Theory, to phonological production. Simulations of the resulting model suggest that Gradient Symbol Processing offers a way to unify accounts of grammatical competence with both discrete and continuous patterns in language performance. (shrink)

This article argues that evolutionary models based on selection validate, under appropriate conditions, the relevance of optimality as an explanatory mechanism in rational choice theory. The reason is that these frameworks share the mechanism that drives the results, namely, optimization, even if they situate it at different levels. The consequences of our argument are twofold. First, it resolves the tension between those predictions of rational choice theory that are accurate and the evidence showing that individuals seldom optimize. Second, it (...) relativizes the explanatory import of rationality without diminishing the role of optimization as a mechanism. (shrink)

Within educational science and communication science, the concepts of scientific literacy and effectiveness of science communication have been intensely debated in relation to the free types of education, but the research did not focus on the specificity of their target (the general public) in relation to the specificity of their object (science). In general, research maintained an exclusively externalist view for these concepts and associated them with the complexity and diversity of teaching science and less with the epistemic dimension of (...) science communication as a transfer of understandable knowledge in particular conditions. This prospected research advances an internalist view on these concepts, aiming to answer the question of whether science communication (with a conceptual meaning that embeds understanding, message, and goal) to the general public is possible and in what form, within an epistemological theoretical framework. (shrink)

With the increasing number of electric vehicles, the charging demand of EVs has brought many new research hotspots, i.e., charging path planning and charging pricing strategy of the charging stations. In this paper, an integrated framework is proposed for multiobjective EV path planning with varied charging pricing strategies, considering the driving distance, total time consumption, energy consumption, charging fee such factors, while the charging pricing strategy is designed based on the objectives of maximizing the total revenues of the charging stations (...) and balancing the profits of the charging stations. First, the energy consumption model of EVs, the M/M/S queuing model of charging stations, and the charging model of charging piles are established. A novel charging path planning algorithm is proposed based on bidirectional Martins’ algorithm, which can assist EV users to select charging stations and plan charging paths. Then, a particle swarm optimization algorithm is applied to solve the optimal solution of charging station pricing designation. Finally, the method proposed in the paper is simulated on the street map of Shenzhen to verify the efficacy of the multiobjective charging path planning for EVs and the feasibility of the charging pricing strategy. (shrink)

The conventional community sports facility allocation methods have high minimum costs, and a new community sports facility allocation performance optimization method is designed based on a linear programming model in order to reduce the performance capital investment. The standardized community sports facility allocation performance objective function is established, and a pairwise model is built to divide the feasible and optimal solutions, and the feasible solutions and their constraints are found out. Establish a community sports facility configuration performance optimization (...) model, delineate the boundaries of the optimal solution by bifurcation, and set the feasible domain of the performance optimization model. The performance optimization algorithm is designed to improve the speed of community sports facility allocation performance optimization. In the experiment, the method is compared with data-driven method, digital management method, and evolutionary game algorithm, which requires less capital investment in spring, autumn, and winter than digital management method and evolutionary game algorithm, and the minimum capital investment in summer is less than the other three methods. From the above experimental data, it is clear that the performance optimization method has the smallest minimum capital investment and achieves the purpose of reducing the input cost. (shrink)

River water pollution by wastewater can cause significant negative impact on the aquatic sustainability. Hence, accurate modeling of this complicated system and its cost-effective treatment and reuse decision is very important because this optimization process is related to economic expenditure, societal health, and environmental deterioration. In order to optimize this complex system, we may consider three treatment or reuse options such as microscreening filtration, nitrification, and fertilization-oriented irrigation on top of two existing options such as settling and biological oxidation. (...) The objective of this environmental optimization is to minimize the economic expenditure of life cycle costs while satisfying the public health standard in terms of groundwater quality and the environmental standard in terms of river water quality. Particularly, this study improves existing optimization model by pinpointing the critical deficit location of dissolved oxygen sag curve by using analytic differentiation. Also, the proposed formulation considers more practical constraints such as maximal size of irrigation area and minimal amount of filtration treatment process. The results obtained by using an evolutionary algorithm, named a parameter-setting-free harmony search algorithm, show that the proposed model successfully finds optimal solutions while conveniently locating the critical deficit point. (shrink)

Scientific reasoning represents complex argumentation patterns that eventually lead to scientific discoveries. Social epistemology of science provides a perspective on the scientific community as a whole and on its collective knowledge acquisition. Different techniques have been employed with the goal of maximization of scientific knowledge on the group level. These techniques include formal models and computer simulations of scientific reasoning and interaction. Still, these models have tested mainly abstract hypothetical scenarios. The present thesis instead presents data-driven approaches in social epistemology (...) of science. A data-driven approach requires data collection and curation for its further usage, which can include creating empirically calibrated models and simulations of scientific inquiry, performing statistical analyses, or employing data- mining techniques and other procedures. -/- We present and analyze in detail three co-authored research projects on which the thesis’ author was engaged during her PhD. The first project sought to identify optimal team composition in high energy physics laboratories using data-mining techniques. The results of this project are published in (Perović et al. 2016), and indicate that projects with smaller numbers of teams and team members outperform bigger ones. In the second project, we attempted to determine whether there is an epistemic saturation point in experimentation in high energy physics. The initial results from this project are published in (Sikimić et al. 2018). In the thesis, we expand on this topic by using computer simulations to test for biases that could induce scientists to invest in projects beyond their epistemic saturation point. Finally, in previous examples of data-driven analyses, citations are used as a measure of epistemic efficiency of projects in high energy physics. In order to additionally justify and analyze the usage of this parameter in their data-driven research, in the third project Perović & Sikimić (2019) analyzed and compared inductive patterns in experimental physics and biology with the reliability of citation records in these fields. They conclude that while citations are a relatively reliable measure of efficiency in high energy physics research, the same does not hold for the majority of research in experimental biology. -/- Additionally, contributions of the author that are for the first time published in this theses are: (a) an empirically calibrated model of scientific interaction of research groups in biology, (b) a case study of irregular argumentation patterns in some pathogen discoveries, and (c) an introductory discussion of the benefits and limitations of data- driven approaches to the social epistemology of science. Using computer simulations of an empirically calibrated model, we demonstrate that having several levels of hierarchy and division into smaller research sub-teams is epistemically beneficial for researchers in experimental biology. We also show that argumentation analysis in biology represents a good starting point for further data-driven analyses in the field. Finally, we conclude that a data-driven approach is informative and useful for science policy, but requires careful considerations about data collection, curation, and interpretation. (shrink)

This article presents a simple derivation of optimization models for reaction networks leading to a generalized form of the mass-action law, and compares the formal structure of Minimum Information Divergence, Quadratic Programming and Kirchhoff type network models. These optimization models are used in related articles to develop and illustrate the operation of ontology alignment algorithms and to discuss closely connected issues concerning the epistemological and statistical significance of sharp or precise hypotheses in empirical science.

This paper examines the explanatory distinctness of wiring optimization models in neuroscience. Wiring optimization models aim to represent the organizational features of neural and brain systems as optimal (or near-optimal) solutions to wiring optimization problems. My claim is that that wiring optimization models provide design explanations. In particular, they support ideal interventions on the decision variables of the relevant design problem and assess the impact of such interventions on the viability of the target system.

The paper deals with the problems in the electric power industry, do not allow us to ensure a sufficient level of competitiveness of the industry and each individual subject of the electric power industry, the threatens national security, in particular, the economic security of the state, and creates barriers to maintaining the sustainable development of territories. It is proposed to use the economic and mathematical modeling allowed us to determine the high importance of human resources in the final results of (...) the electric power company, which makes it possible to consider the optimization of investment funds from the position of strengthening the focus of management processes in the field of personnel development. (shrink)

This paper introduces the basic principle and application process of simulated annealing algorithm and improves the simulated annealing algorithm so that it can converge faster to get the new parameters of cultural and creative product design and make it more in line with the reality of engineering optimization. In the cultural creative industry, it is necessary to use the creatorʼs creativity and technology to derive and develop the original cultural resources with the help of various materialization means, to refine (...) the abstract and profound contents of cultural resources to make them more visualized, and to produce products with both spiritual and economic values through the multiple development and utilization of their intellectual property contents. By studying the feasibility analysis of the cultural and creative design, the design positioning of the cultural and creative products is determined. In this article, we use the simulated annealing method to simulate and analyse the condition values in the design process of cultural creative products. As the Internet era progresses, people have more diversified requirements for cultural and creative products, and they need to have innovative ideas to follow the trend, so the design of cultural and creative products can spread culture through different design expressions and media. As one of the important pillar industries for future development, cultural and creative products are characterized by a wide range of styles and practicality, which meet the aesthetic needs and fashion trends of modern people. (shrink)

Wheels are the key components of a train, and the shape of the wheel flange should be maintained to ensure the security of train operations. As a method to maintain the shape at the cost of the diameter size, reprofiling has significant impacts on the lifecycle of a train. A wheel model is built in this paper based on the analysis of the wheel wear features and datasets from Taiyuan locomotives. With the decision variables T i, T i ′, which (...) describe the reprofiling strategy, we formulate a multiobjective optimization problem simultaneously minimizing the reprofiling numbers and maximizing the serving years. To find the solutions of the multiobjective model, the NSGA-II is extended with an alteration of the crowding distance calculation and genetic operators. The improved NSGA-II performs better than other approaches. Meanwhile, outstanding solutions with longer servicing years and less reprofiling are listed in this paper. Our study reveals the relationship between the diameter, flange thickness, and their individual attrition rates and proposes a wear model, multiobjective model, and improved NSGA-II. Compared with existing reprofiling strategies, the strategy recommended in our work can significantly increase the lifecycle of the wheel coupled with a low repair frequency. (shrink)

This study is to explore the optimization of the adaptive genetic algorithm in the backpropagation neural network, so as to expand the application of the BPNN model in nonlinear issues. Traffic flow prediction is undertaken as a research case to analyse the performance of the optimized BPNN. Firstly, the advantages and disadvantages of the BPNN and genetic algorithm are analyzed based on their working principles, and the AGA is improved and optimized. Secondly, the optimized AGA is applied to optimize (...) the standard BPNN, and the optimized algorithm is named as OAGA-BPNN. Finally, three different cases are proposed based on the actual scenario of traffic flow prediction to analyse the optimized algorithm on the matrix laboratory platform by simulation. The results show that the average error distribution of the GA-BPNN algorithm is about 1% with small fluctuation range, better calculation accuracy, and generalization performance in contrast to the BPNN. The average output error of the AGA-BPNN fluctuates around 0 and remains in a relatively stable range as a whole in contrast to that of GA-BPNN; the maximum fitness level keeps increasing during the evolution process but approaches the average value in later process, so the population diversity is hard to be guaranteed. The output error of the OAGA-BPNN fluctuates little compared with that of AGA-BPNN, and its maximum fitness continues to increase in the evolution process with guaranteed population diversity. In short, the OAGA-BPNN algorithm can achieve the best performance in terms of calculation accuracy, generalization performance, and population evolution. (shrink)

With the rapid development of China’s social economy and the improvement of the level of urbanization, urban transportation has also been greatly developed. With the booming development of the internet and the sharing economy industry, shared bicycles have emerged as the times requirement. Shared bicycles are a new type of urban transportation without piles. As a green way of travel, shared bicycles have the advantages of convenience, fashion, green, and environmental protection. However, many problems have also arisen in the use (...) of shared bicycles, such as man-made damage to the vehicle, the expiration of the service life of the vehicle, etc. These problems are unavoidable, and the occurrence of these failure problems will also cause serious harm to the use of shared bicycles. This article aims to study the path optimization of shared bicycles considering the recovery of faulty vehicles during dispatching. Based on the K-means spatial data clustering algorithm, a path optimization experiment of shared bicycle recycling scheduling considering the recycling of faulty vehicles is carried out. The experiment concluded that the shared bicycle recycling scheduling path based on K-means clustering planning significantly reduces the total time spent and the total cost of performing recycling scheduling tasks. Among them, the unit price of recycling and dispatching of each faulty shared bicycle has dropped by 4.1 yuan compared with the market unit price. The conclusion shows that the shared bicycle recycling scheduling path considering faulty vehicle recycling based on K-means clustering algorithm has been greatly optimized. (shrink)

The introduction of multiple intelligence theory into sports professional football teaching is a requirement of educational innovation, which helps to expand and play the multiple functions of football, and can effectively improve the comprehensive quality of football professional science. Under the perspective of multiple intelligence theory, college sports professional football teaching will focus on the all-round development of students, actively cultivate students’ multiple intelligence, and reflect the democratization, individualization, and diversification of teaching in the process of educational concept innovation. This (...) article explains the origin and characteristics of the particle swarm optimization algorithm and discusses the application status of the PSO algorithm in detail. We introduced the standard PSO algorithm, including mathematical forms, iteration steps, and flowcharts. In addition, it also specifically describes the proposed new PSO improved algorithm, including the food chain strategy and reproduction strategy, as well as the implementation of the algorithm. Through analysis, it is concluded that the implementation and implementation of relevant systems is the guarantee for the sustained and sound development of campus football. The amount of football lessons is insufficient, and the classroom teaching effect is not ideal. Physical education teachers are acceptable, but the football professional knowledge training of physical education teachers needs to be strengthened. The selection and setting of the teaching content of football lessons lack systematic, scientific, and adaptable, and the teaching methods and teaching model concepts are backward. In the process of football teaching, teachers ignored the evaluation and assessment of students’ nonphysical and nonintellectual factors, and campus football activities did not achieve the expected goals. (shrink)