Journals in Mathematics and applied mathematics

Mathematical Social Sciences

ISSN: 0165-4896

The international, interdisciplinary journal Mathematical Social Sciences publishes original research articles, survey papers, short notes and book reviews. The journal emphasizes the unity of mathematical modelling in economics, psychology, political sciences, sociology and other social sciences.Topics of particular interest include the fundamental aspects of choice, information, and preferences (decision science) and of interaction (game theory and economic theory), the measurement of utility, welfare and inequality, the formal theories of justice and implementation, voting rules, cooperative games, fair division, cost allocation, bargaining, matching, social networks, and evolutionary and other dynamics models.Papers published by the journal are mathematically rigorous but no bounds, from above or from below, limits their technical level. All mathematical techniques may be used. The articles should be self-contained and readable by social scientists trained in mathematics.Benefits to authors We also provide many author benefits, such as free PDFs, a liberal copyright policy, special discounts on Elsevier publications and much more. Please click here for more information on our author services.Please see our Guide for Authors for information on article submission. If you require any further information or help, please visit our Support Center

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Mathematics and Computers in Simulation

ISSN: 0378-4754

Transactions of IMACSThe aim of the journal is to provide an international forum for the dissemination of up-to-date information in the fields of the mathematics and computers, in particular (but not exclusively) as they apply to the dynamics of systems, their simulation and scientific computation in general. Published material ranges from short, concise research papers to more general tutorial articles.Mathematics and Computers in Simulation, published monthly, is the official organ of IMACS, the International Association for Mathematics and Computers in Simulation (Formerly AICA). This Association, founded in 1955 and legally incorporated in 1956 is a member of FIACC (the Five International Associations Coordinating Committee), together with IFIP, IFAV, IFORS and IMEKO.Topics covered by the journal include mathematical tools in:•The foundations of systems modelling •Numerical analysis and the development of algorithms for simulationThey also include considerations about computer hardware for simulation and about special software and compilers. The journal also publishes articles concerned with specific applications of modelling and simulation in science and engineering, with relevant applied mathematics, the general philosophy of systems simulation, and their impact on disciplinary and interdisciplinary research.The journal includes a Book Review section -- and a "News on IMACS" section that contains a Calendar of future Conferences/Events and other information about the Association.

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Neural Networks

ISSN: 0893-6080

Neural Networks provides a forum for developing and nurturing an international community of scholars and practitioners who are interested in all aspects of neural networks, including deep learning and related approaches to artificial intelligence and machine learning. Neural Networks welcomes submissions that contribute to the full range of neural networks research, from cognitive modeling and computational neuroscience, through deep learning algorithms and mathematical analyses, to engineering and technological applications of systems that significantly use neural network concepts and learning techniques. This uniquely broad range facilitates the cross-fertilization of ideas between biological and technological studies, and helps to foster the development of the interdisciplinary community that is interested in biologically-inspire... artificial intelligence. Accordingly, the Neural Networks editorial board represents experts in fields including psychology, neurobiology, computer science, engineering, mathematics, and physics. On the other hand, neural networks should be central to submissions. The journal publishes articles, letters, and reviews/tutorials, as well as letters to the editor, editorials, and current events. Articles are published in one of five sections: learning systems, cognitive science, neuroscience, mathematical and computational analysis, engineering and applications.Neural Networks is the archival journal of three of the oldest and most prominent neural network societies: the International Neural Network Society (INNS), the Asia-Pacific Neural Network Society (APNNS), and the Japanese Neural Network Society (JNNS). A subscription to the journal is included with membership in each of these societies.Members of the societies listed as affiliated to the journal receive a 25% discount on Article Processing Charges when they publish an article in Neural Networks as an author - this will be detailed through the submission and production processes.INNS members receive additional support with a further 25% contribution from the INNS towards their open access article processing charges for accepted papers. If you are an INNS member, please submit this web form to receive reimbursement for 25% of your open access article processing charges. You will be asked to submit a PDF copy of your acceptance and production email, as well as a Wire Transfer Form.

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Next Research

ISSN: 3050-4759

Next Research is a peer-reviewed multidisciplinary journal, publishing research spanning all scientific technical and medical communities.The journal is part of the Next family, a new suite of multidisciplinary journals from Elsevier spanning all branches of science. Managed by our dedicated team of in-house Editors, Next Research offers authors speed, consistency, innovation, flexibility, and ease of submission.Next Research is an inclusive venue for scientifically accurate manuscripts that meet the ethical and scientific publishing standards. It publishes all research topics across the fields of health sciences, physical sciences, life sciences and social sciences. Next Research publishes experimental, computational, and theoretical work, in traditional formats such as Original Research Articles, Communications and Reviews, as well as novel formats and video content.The journal provides authors with rigorous peer review ensuring articles adhere to a high technical standard, with rapid decisions and a highly visible platform for scientists to share their research.We believe that all rigorous research should be shared.

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Nonlinear Analysis

ISSN: 0362-546X

An International Mathematical JournalNonlinear Analysis aims at publishing high-quality research papers broadly related to the analysis of partial differential equations and their applications. Submissions are encouraged in the areas of expertise of the editorial board.Benefits to authors We also provide many author benefits, such as free PDFs, a liberal copyright policy, special discounts on Elsevier publications and much more. Please click here for more information on our author services.Please see our Guide for Authors for information on article submission. If you require any further information or help, please visit our Support Center

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Nonlinear Analysis: Hybrid Systems

ISSN: 1751-570X

A journal of IFAC, the International Federation of Automatic ControlNonlinear Analysis: Hybrid Systems (NAHS) welcomes all original research papers on mathematical concepts, tools, and techniques from control theory, computer science, and applied mathematics for the modelling, analysis and design of hybrid dynamical systems, i.e., systems involving the interplay between discrete and continuous dynamic behaviors.Hybrid systems are ubiquitous in many branches of engineering and science as they can model broad ranges of dynamical systems. In particular, in cyber-physical systems, which integrate sensing, computation, control and communication (cyber) parts into physical objects and infrastructures, hybrid systems play an instrumental role. The description of the behavior of the cyber parts often calls for discrete models (automata, finite-state machines, switching logic, etc.), while the physical (thermal, mechanical, electrical, physical, biological) parts are well captured by continuous modelling formalisms (e.g., differential equations), thereby naturally resulting in hybrid system models such as (stochastic) hybrid automata, timed automata, switched systems, impulsive systems, jump-flow models, piecewise affine systems, non-smooth systems, etc. Also, many physical phenomena can often be well described by non-smooth or hybrid models, including mechanical systems with impacts and friction (walking robots), switched power converters and biological systems (e.g., firing neuron models).Hybrid systems can exhibit very rich dynamics and their analysis calls for new and strong theorical foundations to guarantee their stability, safety, functionality, and performance. The development of systematic methods for efficient and reliable design of hybrid systems is therefore a key challenge on the crossroads of control theory and computer science. It is currently of high interest to control engineers, computer scientists and mathematicians in research institutions as well as in many industrial sectors.Contribution... to Nonlinear Analysis: Hybrid Systems are invited in all areas pertaining to hybrid dynamical systems including: Modeling, modeling languages and specification;Analys... computability and complexity;Stochasti... hybrid systems;Impulsive systems;Formal verification and abstraction;Optimiza... and controller synthesis;Control over communication networks including self- and event-triggered control;Network Science and multi-agent systems;Fault diagnosis and fault-tolerant control;Simulation, implementation and tools;Safety, security, privacy, and resilience for cyber-physical systems;Planning and integrated control in dynamical systems.Contribution... on applications of hybrid dynamical systems methods are also encouraged. Fields of interest include: process and manufacturing industries, automotive and mobility systems, avionics, communication networks and networked control systems, energy and power systems, transportation networks, cyber-physical and embedded systems, (synthetic) biology and biomedical applications, life sciences, safety-critical systems, mobile and autonomous robotics, and other related areas.

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Nonlinear Analysis: Real World Applications

ISSN: 1468-1218

Nonlinear Analysis: Real World Applications welcomes all research articles of the highest quality with special emphasis on applying techniques of nonlinear analysis to model and to treat nonlinear phenomena with which nature confronts us. Coverage of applications includes any branch of science and technology such as solid and fluid mechanics, material science, mathematical biology and chemistry, control theory, and inverse problems.The aim of Nonlinear Analysis: Real World Applications is to publish articles which are predominantly devoted to employing methods and techniques from analysis, including partial differential equations, functional analysis, dynamical systems and evolution equations, calculus of variations, and bifurcations theory.Benefits to authors We also provide many author benefits, such as free PDFs, a liberal copyright policy, special discounts on Elsevier publications and much more. Please click here for more information on our author services.Two papers per year rule All the authors and co-authors cannot submit more than two papers to this journal (including coauthored papers) within a period of twelve (12) months. If you or one of your co-authors have already submitted two papers within a period of 12 months or less, your third submission (if any) will be returned to you.Rejection due to poor English Some papers with good mathematics have been rejected from this journal due to the poor level of English within the paper. It is the responsibility of the author to ensure that the English language used is correct before submitting their paper. For authors whose first language is not English, we highly recommend that you have it checked by a native English speaker or make use of an English editing service. Elsevier also offers this (at a cost) via our Webshop (English Language Editing ).Please see our Guide for Authors for more information on article submission. If you require any further information or help, please visit our Support Center

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Operations Research Letters

ISSN: 0167-6377

Operations Research Letters (ORL) is committed to the rapid review and fast publication of short articles on all aspects of operations research and analytics. ORL welcomes pure methodological papers and applied papers with firm methodological grounding. All articles are restricted to at most eight journal pages, with the option to relegate proofs and additional material to an online appendix. The main criteria for the papers to be published are quality, originality, relevance, and clarity. The journal's traditional strength is in methodology, including theory, modelling, algorithms, and computational studies. Please find below a full description of the areas covered by the journal.Area EditorsApproximation Algorithms for Combinatorial Optimization Problems Area Editor: Leah Epstein Associate Editors: M. Chrobak, K. Elbassioni, M. Feldman, J. Hurink, N. Olver, J. Sgall, J. Verschae The area covers all issues relevant to the development of efficient approximate solutions to computationally difficult problems. This includes worst case analysis or competitive analysis of approximation algorithms, and complexity results.Submissions can be articles consisting of theoretical work in the area, or articles combining significant theoretical contributions of mathematical flavor with computational investigations of heuristic approaches. Articles in the area of discrete optimization that do not belong to the scope of other areas may be submitted to this area as well.Computational Social Science Area Editor: Vianney Perchet Associate Editors: A. Drutsa, P. Mertikopoulos, R. Smorodinsky This area publishes papers focusing on data-driven procedures, either from a theoretical or an applied perspective, in operation research, games, economics and other social science. The scope includes: sample/computational complexity of mechanisms, learning in games/OR/social science, empirical solutions with AI algorithms (such as, but not limited to, deep learning techniques) of complex problems, etc. Continuous Optimization Area Editor: Hector Ramirez Associate Editors: M.F. Anjos, L.M. Briceno, D. Dadush, G. Eichfelder, D. Jiang, D. Orban, F. Schoen Papers in all fields of continuous optimization that are relevant to operations research are welcome. These areas include, but are not restricted to, linear programming, nonlinear programming (constrained or unconstrained, convex or nonconvex, smooth or nonsmooth, finite or infinite-dimensional... complementarity problems, variational inequalities, bilevel programming, and mathematical programs with equilibrium constraints. Financial Engineering Area Editor: Ning Cai Associate Editors: X. He, D. Mitchell Financial engineering utilizes methodologies of optimization, simulation, decision analysis and stochastic control to analyse the effectiveness and efficiency of financial markets. This area is interested in papers that innovate in terms of methods or that develop new models which guide financial practices. Examples include but are not limited to Fintech, financial networks, market microstructure, derivative pricing and hedging, credit and systemic risk, energy markets, portfolio selection. Game Theory Area Editor: Tristan Tomala Associate Editors: S. Beal, V. Ihele, D.W.K. Yeung, G. Zaccour This area publishes papers which use game theory to analyze operations research models or make theoretical contributions to the theory of games. The scope includes (but is not limited to): cooperative and non-cooperative games, dynamic games, mechanism and market design, algorithmic game theory, games on networks, games of incomplete information. Graphs & Networks Area Editor: Gianpaolo Oriolo Associate Editors: F. Bonomo, Y. Faenza, Z. Friggstad, L. Sanita The area seeks papers that apply, in original and insightful ways, discrete mathematics to advance the theory and practice of operations research, as well as those reporting theoretical or algorithmic advances for the area. Of particular, but not exclusive, interest are papers devoted to novel applications, telecommunications and transportation networks, graphs and web models and algorithms. Inventory and Supply Chain Optimization Area Editor: Sean Zhou Associate Editors: H. Abouee Mehrizi, A. Burnetas, X. Gong, Q. Li, J. Yang The area welcomes innovative papers focused on inventory control and supply management. Examples of topics include, but are not limited to, optimal sourcing, inventory and assortment selection, pricing and inventory optimization, capacity planning, multi-item/echelon systems, algorithms and bounds, near-optimal or asymptotic optimal solutions, and incentive design. Mixed Integer Optimization Area Editor: Marc Pfetsch Associate Editors: R. Fukasawa, L. Liberti, J.P. Vielma, G. Zambelli All submissions advancing the theory and practice of mixed integer (linear or nonlinear) programming like novel techniques and algorithmic approaches in convex relaxations, branch and cut, polyhedral combinatorics and theory driven heuristics are welcome. Case studies may be considered if they contribute to the general methodology. Operations Management Area Editor: Mahesh Nagarajan Associate Editors: L. Chu, Y. Ding, N. Golrezaei, T. Huh, R. Roet-Green, D. Saban, C. Shi, L. Zhu The OM department aims to publish short, focused high quality research in the area of operations management, broadly the field of operations research applied to management problems. We welcome papers that use a wide variety of methodologies, both descriptive as well as prescriptive in nature including optimization, applied probability, simulation, and game theory. Scheduling Area Editor: Marc Uetz Associate Editors: B. Moseley, E. Pesch, R. Van Stee We seek original and significant contributions to the analysis and solution of sequencing and scheduling problems. This includes structural and algorithmic results, in particular optimization, approximation and online algorithms, as well as game theoretic modeling. All results are welcome as long as the relevance of a problem and significance of the contribution is made compellingly clear. Stochastic Models and Data Science Area Editor: Henry LamAssociate Editors: H. Bastani, J. Dong, K. Murthy, I. Ryzhov, Y. Zhou The area seeks papers broadly on the interplay between operations research and machine learning and statistics where stochastic variability and uncertainty play a crucial role. The area values both papers that develop or utilize stochastic analysis and computation in data science problems, including but not limited to reinforcement learning, stochastic iterative algorithms for model estimation or training, probabilistic analysis of statistical and machine learning tools, sampling and Monte Carlo methods, and also papers that integrate learning or statistical techniques into stochastic modeling to enhance prediction or decision-making for a wide variety of systems. Stochastic Networks and Queues Area Editor: Harsha HonnappaAssociate Editors: E. Ozkan, W. Wang, Y. ZhaoThe area seeks papers that contribute to the modeling, analysis or innovative application of stochastic networks or queues. Work submitted should propose original models and develop novel analytical or computational methods more than incremental extensions. Examples of relevant application areas include but are not limited to supply chain management, manufacturing, financial engineering, healthcare, revenue management, service operations, telecommunications, sharing economy, online markets and public sector operations research. Application-oriented papers should demonstrate direct practical impact and have a strong methodological component as well.Stochastic Optimization and Machine Learning Area Editor: Angelos Georghiou Associate Editors: M. Bodur, M. Claus, E. Feinberg, P. Vayanos The Stochastic Optimization and Machine Learning area of Operations Research Letters solicits original articles that generate novel insights into problems that arise in optimization under uncertainty and in machine learning. The focus is broad and encompasses, among others, stochastic (dynamic) programming, (distributionally) robust optimization, data-driven optimization as well as the interface of machine learning with traditional areas of operations research. Successful submissions in this area are expected to make a clear and meaningful academic contribution, which may be through the study of new problems, models, solution techniques, performance analysis and convincing and reproducible numerical evaluations.

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Pattern Recognition

ISSN: 0031-3203

Pattern Recognition is a mature but exciting and fast developing field, which underpins developments in cognate fields such as computer vision, image processing, text and document analysis and neural networks. It is closely akin to machine learning, and also finds applications in fast emerging areas such as biometrics, bioinformatics, multimedia data analysis and most recently data science. The journal Pattern Recognition was established some 50 years ago, as the field emerged in the early years of computer science. Over the intervening years it has expanded considerably.The journal accepts papers making original contributions to the theory, methodology and application of pattern recognition in any area, provided that the context of the work is both clearly explained and grounded in the pattern recognition literature. Papers whos primary concern falls outside the pattern recognition domain and which report routine applications of it using existing or well known methods, should be directed elsewhere. The publication policy is to publish (1) new original articles that have been appropriately reviewed by competent scientific people, (2) reviews of developments in the field, and (3) pedagogical papers covering specific areas of interest in pattern recognition. Various special issues will be organized from time to time on current topics of interest to Pattern Recognition. Submitted papers should be single column, double spaced, no less than 20 and no more than 35 (40 for a review) pages long, with numbered pages.Benefits to authors We also provide many author benefits, such as free PDFs, a liberal copyright policy, special discounts on Elsevier publications and much more. Please click here for more information on our author services.Please see our Guide for Authors for information on article submission. If you require any further information or help, please visit our Support Center

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Pervasive and Mobile Computing

ISSN: 1574-1192

Special Issue Proposal Note PMCJ exclusively reviews Special Issue proposal forms submitted here through the designated submission system. Proposals submitted via any other means will not be considered for review. For more information on how to prepare and submit a SI proposal please check https://www.elsevier... and Scope As envisioned by Mark Weiser as early as 1991, pervasive computing systems and services have truly become integral to our daily lives. Tremendous advancements in a multitude of technologies ranging from personalized and embedded smart devices (e.g., smartphones, sensors, wearables, IoT) to ubiquitous connectivity through wireless mobile communications and cognitive networking infrastructures, to advanced computing techniques (including mobile edge/fog/cloud, data analytics and machine learning) and user-friendly middleware services and platforms have significantly contributed to the unprecedented advances in pervasive and mobile computing.Such cutting-edge pervasive technologies and paradigms have led to the convergence of cyber-physical-human systems with applications to smart environments (e.g., smart homes and cities, smart grid, smart transportation, smart health, smart agriculture) with the goal to improve human experience and quality of life without explicit awareness of the underlying communications and computing technologies. Additionally, the huge amount of (real-time) data collected via pervasive devices coupled with advanced data analytic, machine learning and AI (Artificial Intelligence) techniques for reliable prediction and decision-making are making breakthrough research in pervasive computing and applications, such as self-driving cars, predictive maintenance in the industry 4.0 environments, mobile recommendation systems, etc.The Pervasive and Mobile Computing Journal (PMC) is a high-impact, peer-reviewed technical journal that publishes high-quality scientific articles spanning theory and practice, and covering all aspects of pervasive and mobile computing and systems. Topics include, but not limited to: Pervasive Computing and Communications Architectures and ProtocolsPervasive, Mobile and Wearable Computing Systems and ServicesCyber-Physic... Systems and Cyber-Physical-Human SystemsSmart Systems and Applications (smart homes, smart cities, smart manufacturing, smart transportation, smart grid, smart health, smart agriculture, etc.)Human-centric Intelligent SystemsCognitive ComputingTrustworthy AI in Pervasive SystemsMachine Learning and Deep Learning in Pervasive and Mobile ComputingFederated, Distributed and Embedded learning, Learning at-the-edge in Pervasive SystemsLearning on Streaming Data and Continual Learning in Pervasive and Mobile SystemsBig Data and Data Analytics in Pervasive Computing SystemsInternet of Things and Social Internet of ThingsInternet of People and Internet of VehiclesEdge, Fog, Mobile Cloud and Opportunistic Computing in Pervasive and Mobile SystemsEnabling Pervasive Communication Technologies (e.g., wireless LANs, cellular, hybrid, ad hoc and cognitive networks)Wireless Sensors Networks and RFID TechnologiesUrban Sensing and Mobile CrowdsensingParticip... and Social SensingMachine-to-Ma... and Device-to-Device CommunicationsPositi... Localization and Tracking TechnologiesActivity Recognition and TrackingContext-awar... ComputingLocation-ba... Services and ApplicationsPervasiv... Service Creation, Composition, Discovery, Management, and DeliveryHuman User Interfaces and Interaction ModelsTrust, Reliability, Security, and Privacy in Pervasive and Mobile Computing SystemsPerformance Evaluation of Pervasive and Mobile Computing Systems

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Journals in Mathematics and applied mathematics

Mathematical Social Sciences

Mathematics and Computers in Simulation

Neural Networks

Next Research

Nonlinear Analysis

Nonlinear Analysis: Hybrid Systems

Nonlinear Analysis: Real World Applications

Operations Research Letters

Pattern Recognition

Pervasive and Mobile Computing

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