Journal Guide

Computational Mathematics and Modeling focuses on important Russian contributions to computational mathematics that are useful to the applied scientist or engineer. This quarterly publication presents timely research articles by scientists from Moscow State University, an institution recognized worldwide for influential contributions to this subject. Numerical analysis, control theory, and the interplay of modeling and computational mathematics are among the featured topics.

Computational Mechanics reports original research in computational mechanics of enduring scholarly value. It focuses on areas that involve and enrich the rational application of mechanics, mathematics, and numerical methods in the practice of modern engineering. The journal investigates theoretical and computational methods and their rational applications. Areas covered include solid and structural mechanics, multi-body system dynamics, constitutive modeling, inelastic and finite deformation response, and structural control. The journal also covers fluid mechanics and fluid-structure interactions, biomechanics, free-surface and two-fluid flows, aerodynamics, fracture mechanics and structural integrity, multi-scale mechanics, particle and meshfree methods, transport phenomena, and heat transfer. Lastly, the journal publishes modern variational methods in mechanics in general.

CMFT is an international mathematics journal which publishes carefully selected original research papers in complex analysis (in a broad sense), and on applications or computational methods related to complex analysis. Survey articles of high standard and current interest can be considered for publication as well. Contributed papers should be written in English (exceptions in rare cases are tolerated), and in a lucid, expository style. Papers should not exceed 30 printed pages.

This journal publishes research on the analysis and development of computational algorithms and modeling technology for optimization. It examines algorithms either for general classes of optimization problems or for more specific applied problems, stochastic algorithms as well as deterministic algorithms. Computational Optimization and Applications covers a wide range of topics in optimization, including: large scale optimization, unconstrained optimization, constrained optimization, nondifferentiable optimization, combinatorial optimization, stochastic optimization, multiobjective optimization, and network optimization. It also covers linear programming, complexity theory, automatic differentiation, approximations and error analysis, parametric programming and sensitivity analysis, management science, and more. This peer-reviewed journal features both research and tutorial papers that provide theoretical analysis, along with carefully designed computational experiments.Officially cited as: Comput Optim Appl

Social networks, Social computing, Mathematics of social networks, Computational aspects of social networks, Therory of social computing

Computational Statistics (CompStat) is an international journal that fosters the publication of applications and methodological research in the field of computational statistics. The journal provides a forum for computer scientists, mathematicians, and statisticians working in a variety of areas in statistics, including biometrics, econometrics, data analysis, graphics, simulation, algorithms, knowledge-based systems, and Bayesian computing. CompStat papers emphasize the contribution to and influence of computing on statistics and vice versa. The journal also publishes hardware, software, and package reports as well as book reviews.Officially cited as: Comput Stat

Computational Statistics & Data Analysis (CSDA), the official journal of the International Association of Statistical Computing (IASC), is an international journal dedicated to the dissemination of methodological research and applications in the areas of computational statistics and data analysis. The journal consists of three refereed sections, and a fourth section dedicated to news on statistical computing. The refereed sections are divided into the following subject areas:I) Computational Statistics - Manuscripts dealing with: 1) the explicit impact of computers on statistical methodology (e.g., Bayesian computing, bioinformatics, computational econometrics, computer graphics, computer intensive inferential methods, data exploration, data mining, expert systems, heuristics, knowledge based systems, machine learning, neural networks, numerical and optimization methods, parallel computing, statistical databases, statistical systems), and 2) the development, evaluation and validation of statistical software and algorithms. Software and algorithms can be submitted with manuscripts and will be stored together with the online article.II) Statistical Methodology for Data Analysis - Manuscripts dealing with novel and original data analytical strategies and methodologies applied in biostatistics (design and analytic methods for clinical trials, epidemiological studies, statistical genetics, or genetic/environmental interactions), chemometrics, classification, data exploration, density estimation, design of experiments, econometrics, environmetrics, education, image analysis, marketing, model free data exploration, pattern recognition, psychometrics, statistical physics, image processing, robust procedures.Statistical methodology includes, but not limited to: bootstrapping, classification techniques, clinical trials, data exploration, density estimation, design of experiments, pattern recognition/image analysis, parametric and nonparametric methods, statistical genetics, Bayesian modeling, outlier detection, robust procedures, cross-validation, functional data, fuzzy statistical analysis, mixture models, model selection and assessment, nonlinear models, partial least squares, latent variable models, structural equation models, supervised learning, signal extraction and filtering, time-series modelling, longitudinal analysis, multilevel analysis and quality control.III) Special Applications - Manuscripts at the interface of statistics and computing (e.g., comparison of statistical methodologies, computer-assisted instruction for statistics, simulation experiments). Advanced statistical analysis with real applications (economics, social sciences, marketing, psychometrics, chemometrics, signal processing, finance, medical statistics, environmentrics, statistical physics).

Computational & Applied Mathematics began to be published in 1981. This journal was conceived as the main scientific publication of SBMAC (Brazilian Society of Computational and Applied Mathematics).   The objective of the journal is the publication of original research in Applied and Computational Mathematics, with interfaces in Physics, Engineering, Chemistry, Biology, Operations Research, Statistics, Social Sciences and Economy. The journal has the usual quality standards of scientific international journals and we aim high level of contributions in terms of originality, depth and relevance. CAM is currently reviewed in Mathematical Reviews and Institute of Scientific Information (Webofscience).  

Computational & Mathematical Organization Theory has been accepted for Social Sciences Citation Index, Science Citation Index Expanded, and Current Contents/Social & Behavioral Sciences, and will first appear with an Impact Factor in the Journal Citation Reports 2010, published in 2011. Computational & Mathematical Organization Theory provides an international forum for interdisciplinary research that combines computation, organizations and society. The goal is to advance the state of science in formal reasoning, analysis, and system building drawing on and encouraging advances in areas at the confluence of social networks, artificial intelligence, complexity, machine learning, sociology, business, political science, economics, and operations research. The papers in this journal will lead to the development of newtheories that explain and predict the behaviour of complex adaptive systems, new computational models and technologies that are responsible to society, business, policy, and law, new methods for inte

The journal Computer Aided Geometric Design is for researchers, scholars, and software developers dealing with mathematical and computational methods for the description of geometric objects as they arise in areas ranging from CAD/CAM to robotics and scientific visualization. The journal publishes original research papers, survey papers and with quick editorial decisions short communications of at most 3 pages. The primary objects of interest are curves, surfaces, and volumes such as splines (NURBS), meshes, subdivision surfaces as well as algorithms to generate, analyze, and manipulate them. This journal will report on new developments in CAGD and its applications, including but not restricted to the following:Mathematical and Geometric FoundationsCurve, Surface, and Volume generationCAGD applications in Numerical Analysis, Computational Geometry, Computer Graphics, or Computer VisionIndustrial, medical, and scientific applicationsThe aim is to collect and disseminate information on computer aided design in one journal. To provide the user community with methods and algorithms for representing curves and surfaces. To illustrate computer aided geometric design by means of interesting applications. To combine curve and surface methods with computer graphics. To explain scientific phenomena by means of computer graphics. To concentrate on the interaction between theory and application. To expose unsolved problems of the practice. To develop new methods in computer aided geometry.Benefits to authorsWe 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 pages: http://support.elsevier.com

The development of computer methods for the solution of scientific and engineering problems governed by the laws of mechanics was one of the great scientific and engineering achievements of the second half of the 20th century, with a profound impact on science and technology. This is accomplished through advanced mathematical modeling and numerical solutions reflecting a combination of concepts, methods and principles that are often interdisciplinary in nature and span several areas of mechanics, mathematics, computer science and other scientific disciplines as well.Computer Methods in Applied Mechanics and Engineering was founded over three decades ago, providing a platform for the publication of papers in this important field of science and engineering. The range of appropriate contributions is very wide. It covers any type of computational method for the simulation of complex physical problems leading to the analysis and design of engineering products and systems. This includes theoretical development and rational applications of mathematical models, variational formulations, and numerical algorithms related to finite element, boundary element, finite difference, finite volume, and meshless discretization methods in the following fields of computational science and engineering:• Solid and structural mechanics• Fluid mechanics• Mechanics of materials• Heat transfer• Dynamics• Geomechanics• Acoustics• Biomechanics• Nanomechanics• Molecular dynamics• Quantum mechanics• Electromagnetics,and also includes virtual design, multiscale phenomena, from nanoscale to macroscale, multiphysics problems, parallel computing, optimization, probabilistic and stochastic approaches.CMAME publishes original papers at the forefront of modern research describing significant developments of computational methods in solving problems of applied mechanics and engineering.

Computer Science Review intends to fulfil a need in the Computer Science community by publishing research surveys and expository overviews in computer science and related fields. The reviews are aimed at a general computer science audience seeking a full and expert overview of the latest in computer science research.The journal will publish research surveys and expository overviews in computer science. Articles from other fields are welcome, as long as their content is relevant to computer science.Articles should be of sufficient scientific interest and help to advance the fundamental understanding of ongoing research, applied or theoretical, for a general computer science audience. The treatment of each topic should be more than a catalogue of known results. Emphasis should be on clarity and originality of presentation and each survey should add insight to the topic under review.A survey may typically contain the following elements:Introduction (including motivation and historical remarks)Outline of the SurveyBasic concepts, examples and results (with sketches of the proofs)Comments on the relevance of the results, relations to other results and applicationsOpen problemsCritical review of the relevant literatureComprehensive bibliographyAuthors should give a clear and well-balanced treatment of their subject. Expanded versions of primary research papers are generally not acceptable. The optimal length for a paper is considered to be approximately 30 printed pages or about 20,000 words, including tables and diagrams.

Computer Speech & Language publishes reports of original research related to the recognition, understanding, production, coding and mining of speech and language.The speech and language sciences have a long history, but it is only relatively recently that large-scale implementation of and experimentation with complex models of speech and language processing has become feasible. Such research is often carried out somewhat separately by practitioners of artificial intelligence, computer science, electronic engineering, information retrieval, linguistics, phonetics, or psychology.The journal provides a focus for this work, and encourages an interdisciplinary approach to speech and language research and technology. Thus contributions from all of the related fields are welcomed in the form of reports of theoretical or experimental studies, tutorials, reviews, and brief correspondence pertaining to models and their implementation, or reports of fundamental research leading to the improvement of such models.Research Areas IncludeAlgorithms and models for speech recognition and synthesisNatural language processing for speech understanding and generationStatistical computational linguisticsComputational models of discourse and dialogueInformation retrieval, extraction and summarizationSpeaker and language recognitionComputational models of speech production and perceptionSignal processing for speech analysis, enhancement and transformationEvaluation of human and computer system performanceBenefits to authorsWe 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 pages: http://support.elsevier.com