Journal Guide

Machine Learning: Engineering is a multidisciplinary open access journal dedicated to the application of machine learning (ML), artificial intelligence (AI) and data-driven computational methods across all areas of engineering. The journal also publishes research that presents methodological, theoretical, or conceptual advances in machine learning and AI with applications to engineering.

Machine Learning: Health is a multidisciplinary open access journal dedicated to the application of machine learning, artificial intelligence (AI) and data-driven computational methods across healthcare and the medical, biological, clinical, and health sciences. The journal also publishes research that presents methodological, theoretical, or conceptual advances in machine learning and AI with applications to medicine and health sciences.

Machine Translation publishes original research papers on all aspects of MT, including (but not restricted to): - Statistical MT - Example-Based MT - Rule-Based MT - Hybrid MT - Spoken Language Translation - Discriminative MT - Evaluation in MT - MT Applications - Computer-Assisted Translation - Multilingual Corpus Resources - Tools for translators - The role of technology in translator training - MT and language teaching In addition, Machine Translation welcomes papers with a multilingual aspect from other areas of Computational Linguistics and Language Engineering, including: - text composition and generation - information retrieval - natural language interfaces - dialogue systems - message understanding systems - discourse phenomena - text mining - knowledge engineering - contrastive linguistics - morphology, syntax, semantics, pragmatics - computer-aided language instruction and learning - software localization and internationalization Machine Translation regularly focuses on issues of special interest, features a regular Book Review section, and welcomes other contributions of interest to the wide readership of the journal.

Sponsored by the International Association for Pattern Recognition, this journal publishes high-quality, technical contributions in machine vision research and development. Machine Vision and Applications features coverage of all applications and engineering aspects of image-related computing, including original contributions dealing with scientific, commercial, industrial, military, and biomedical applications of machine vision. The journal places particular emphasis on the engineering and technology aspects of image processing and computer vision. It includes coverage of the following aspects of machine vision applications: algorithms, architectures, VLSI implementations, AI techniques and expert systems for machine vision, front-END sensing, multidimensional and multisensor machine vision, real-time techniques, image databases, virtual reality and visualization.

Machines (ISSN 2075-1702) is an international, peer-reviewed journal on machinery and engineering. It publishes research articles, reviews, short communications and letters. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. Full experimental and/or methodical details must be provided. There are, in addition, unique features of this journal: manuscripts regarding research proposals and research ideas will be particularly welcomed electronic files or software regarding the full details of the calculation and experimental procedure - if unable to be published in a normal way - can be deposited as supplementary material

Materials Advances is an international, gold open access journal, publishing high-quality research across the breadth of materials science. The journal accepts experimental or theoretical studies that report new understanding, applications, properties and synthesis of materials, building on and complementing the materials content already published across the Royal Society of Chemistry journal portfolio. Submissions are handled by our high profile associate editors, all of whom also look after submissions to Journal of Materials Chemistry A, B & C. The Materials Advances publishing experience comes with the reputation, standards, commitment and expertise you would expect from an RSC journal, plus the visibility boost that comes from being open access and part of the Journal of Materials Chemistry family.

Materials Discovery aims to promote all aspects of the emerging field of Materials Informatics and the scope includes, but is not limited to, the use of informatics or data intensive experiments and computations as applied to:

• the discovery and design of new materials and/or microstructures;
• advancing knowledge and theoretical understanding of materials processes and /or mechanisms governing materials behavior;
• understanding the nature of data collection and generation in both experimental and computational studies; and
• methods to aid the analysis and interpretation of data and databases.

We encourage submission of articles where the fundamental issues underlying topics of data measurement, quantification and uncertainty are linked to the interpretation of materials science phenomena and characterization.

Materials Discovery publishes full-length articles, perspective and review articles. The journal supports the open data movement, and is part of the Open Data Pilot (http://www.elsevier.com/about/research-data/open-data) and encourages authors to make their data available through a repository, and facilitate re-use by making use of the open access journal Data-in-Brief (http://www.journals.elsevier.com/data-in-brief/), for a reduced fee if submitted directly through Materials Discovery.

This journal is jointly sponsored by Gesellschaft fuer Operations Research (The German OR Society) and the Nederlands Genootschap voor Besliskunde (The Dutch OR Society). It features contributions to mathematics, statistics, and computer science that have special relevance to operations research. The journal publishes theoretical and applied papers with substantial mathematical interest in the areas of mathematical programming, continuous and discrete and combinatorial optimization, stochastic models, Markov decision processes and stochastic programming, dynamic programming, control theory, game theory, graphs and networks, queueing systems, inventory and reliability. The journal also covers mathematical methods and applications in economics, business administration, finance, and engineering. In addition, Mathematical Methods of Operations Research includes a special section devoted to review papers on mathematical methods and models in interesting fields of operations research and related optimization theory

This is the official journal of the Mathematical Optimization Society. It publishes original articles dealing with every aspect of mathematical programming: everything of direct or indirect use concerning the problem of optimizing a function of many variables, often subject to a set of constraints. This involves theoretical and computational issues as well as application studies. Mathematical Programming consists of two series: Series A publishes original research articles, expositions and surveys, and reports on computational experimentation and new or innovative practical applications as well as short communications dealing with the above. Each issue of Series B focuses on a single subject, selected to respond to the current interests of the mathematical programming community and has one or more guest-editors, who need not be members of the editorial board. An issue may be a collection of original articles, a single research monograph or a selection of papers from an appropriate conference.

Mathematical Programming Computation (MPC) publishes original research articles covering computational issues in mathematical programming. Articles report on innovative software, comparative tests, modeling environments, libraries of data, and/or applications. A main feature of the journal is the inclusion of accompanying software and data with submitted manuscripts. The journal's review process includes the evaluation and testing of the accompanying software. Where possible, the review will aim for verification of reported computational results. Topics covered in MPC include linear programming, convex optimization, nonlinear optimization, stochastic optimization, robust optimization, integer programming, combinatorial optimization, global optimization, network algorithms, and modeling languages.

Mathematical and Computer Modelling provides a medium of exchange for the diverse disciplines utilizing mathematical or computer modelling as either a theoretical or working tool. Equal attention is given to the mechanics, methodology and theory of modelling with an attempt to advocate either mathematical or computer modelling, or a combination of the two, in an integrative form. While the unifying aspect of the journal is its adherence to quantitative models, it seeks diversity by being concerned with a variety of disciplines, including engineering, biological, medical, environmental, social, behavioural and other sciences. Both theoretical and applied works which employ mathematical or computer modelling will be considered for publication. Papers dealing with experiments shall be considered when the results are presented as an integral part of the modelling process.

The analysis and improvement of performance in complex systems, the adaptation of plants to new demands or conditions, and the design of 'optimal' systems are a few of the challenges confronting engineers and systems scientists today. In many cases solutions to problems in areas such as these may be found through the use of appropriate mathematical models. The dynamic case, whether continuous time, discrete time of discrete-event, deterministic or stochastic, presents special challenges, and derivation of an appropriate solution depends strongly on the proper initial formulation of the goals and constraints. Increasingly this demands an interdisciplinary approach to modelling. Models can take the form of sets of equations, graphs or nets, or some combination of elements such as these. The derivation, combination, simplification and validation of models and sub-models are the main topics of Mathematical and Computer Modelling of Dynamical Systems, which provides an international forum for the presentation of new ideas in modelling and for the exchange of experience and knowledge through descriptions of specific applications. Original work will be published as regular papers or short notes dealing with a range of topics including the following:Processes and methods for model formulation, identification, development, reduction and validation etc. (including guidelines and check lists)Automation of modelling and software aid for modellingThe relationship between computational/simulation methods, the underlying mathematical formulation and real-world modelling problemsQualitative modelling including fuzzy and iterative approaches to modellingModular modelling (especially applied to interdisciplinary fields such as mechatronic or controlled environmental systems)Learning networks in modellingUncertainties in modellingThe relationship between the modelling approach and problem solutionsComparisons of methods for modelling, model reduction and model validationeffects of modelling errors on overall performance of engineering system (e.g. relationship between modelling and control design)Applications in the field of engineering systemsApplications in other fields (such as environmental systems, biotechnology etc.) provided the methods or ideas presented are relevant in a number of areas or are of interest from a theoretical point of viewCase studies allowing a comparison of ideas or methods Consequently, computer simulation and description of mathematical methods and/or algorithms are restricted to the field of modelling and to the consequences of modelling. Only the most important facts about the latter should be discussed but not all the details of modelling languages or about mathematical methods and/or algorithms which is used to solve the task for which the (simulation) model was created. Modelling of the task including the modelling of the dynamic system, of restrictions, of goals etc. and the implications of the model used on solution and on solution methods are of primary interest.Therefore, papers dealing with applications are accepted only when the purpose of the model, the assumptions (explicit and implicit) made in its development and the precise process of model validation are discussed carefully. Authors are requested to concentrate an those aspects which are of interest to a large community of engineers and scientists and to organize the paper so that it is stimulating and easily readable for engineers and scientists working in a wide range of application areas. Further, a manuscript should be self-contained without being lengthy i.e. its contents should be able to be understood by readers that are not experts in that specific area of application and without consulting many articles in the literature.INCREASED 2009 5-year Impact Factor: 0.623169; 2010 Thomson Reuters, 2009 Journal Citation Reports174;ReadershipEngineers - especially electrical and control engineers, aerospace engineers, mechanical engineers, marine and offshore engineers, chemical engineers, safe engineers and civil engineers, mathematicians and computer scientists who are involved with applications of mathematical and computer modelling in the physical sciences, in biology, in medicine, in ecology and in other fields such as economics. All published research articles in this journal have undergone rigorous peer review, based on initial editor screening and anonymous refereeing by independent expert referees.DisclaimerTaylor & Francis makes every effort to ensure the accuracy of all the information (the 8220;Content8221;) contained in its publications. However, Taylor & Francis and its agents and licensors make no representations or warranties whatsoever as to the accuracy, completeness or suitability for any purpose of the Content and disclaim all such representations and warranties whether express or implied to the maximum extent permitted by law. Any views expressed in this publication are the views of the authors and are not the views of Taylor & Francis.

The 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.