Journal Guide

Optimization Methods and Software publishes refereed papers on the latest developments in the theory and realization of optimization methods, with particular emphasis on the interface between software development and algorithm design. Topics include: * Theory, implementation and performance evaluation of algorithms and computer codes for linear, nonlinear, discrete, stochastic optimization and optimal control. This includes in particular conic, semi-definite, mixed integer, network, non-smooth, multi-objective and global optimization by deterministic or nondeterministic algorithms. * Algorithms and software for complementarity, variational inequalities and equilibrium problems, and also for solving inverse problems, systems of nonlinear equations and the numerical study of parameter dependent operators. * Various aspects of efficient and user-friendly implementations: e.g. automatic differentiation, massively parallel optimization, distributed computing, on-line algorithms, error sensitivity and validity analysis, problem scaling, stopping criteria and symbolic numeric interfaces. * Theoretical studies with a clear potential for applicability, as well as successful applications of optimization methods and software in specific areas such as engineering, machine learning, data mining, economics, finance, biology, or medicine. All published research articles in this journal have undergone rigorous peer review, based on initial editor screening and anonymous refereeing by independent expert referees. Disclaimer Taylor & Francis makes every effort to ensure the accuracy of all the information (the 'Content') 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.

This journal promotes the application of optimization methods in the engineering sciences. This includes facilitating the development of advanced optimization methods for direct or indirect use in engineering. The journal provides a forum in which engineers obtain information about recent advances of optimization sciences, and researchers in mathematical optimization learn about the needs of engineering sciences and successful applications of optimization methods. It closes the gap between optimization theory and the practice of engineering. Optimization and Engineering presents all optimization methods of relevance to applications in engineering sciences: deterministic and stochastic, continuous, mixed integer and discrete, when they are relevant to applications in engineering sciences. It also highlights successful applications of optimization in various areas and contains a special section for readers without a strong background in the field, which offers material aimed at educating potential users of opti

This journal presents original research concerning the theory and applications of ordered sets. It covers all theoretical aspects of the subject, with emphasis on research in algebra and lattice theory, combinatorics and set systems, directed and undirected graphs, computational and discrete geometry, theoretical computer science, and the theory of sets and relational structures. In addition, Order presents applications of order-theoretic methods in these mathematical areas and in more algorithmically oriented research in computing and operations research. It offers coverage that is broadly representative of the best research on ordered structures and their applications. Given the wide scope of the journal, prospective authors are asked to identify a member [or members] of the editorial board whose research interests are closest to the contents of the submission. This helps to ensure both that submissions fit the journal's scope and that the review process begins efficiently.

PLoS Computational Biology features works of exceptional significance that further our understanding of living systems at all scales—from molecules and cells, to patient populations and ecosystems—through the application of computational methods. Readers include life and computational scientists, who can take the important findings presented here to the next level of discovery.Research articles that primarily describe new methods and offer only limited biological insight will be considered only in those exceptional instances in which the method is expected to significantly impact the field of computational biology, typically making substantial breakthroughs in areas of demonstrated importance. Research articles modeling aspects of biological systems should demonstrate both scientific novelty and profound new biological insights. Research articles describing improved or routine methods, models, software, and databases will not be considered by PLoS Computational Biology, and may be more appropriate for PLoS ONE.Generally, reliability and significance of biological discovery are validated and enriched by experimental studies. Experimental validation is not required for publication, however, nor does experimental validation of a modest biological discovery render a manuscript suitable for PLoS Computational Biology.For all submissions, authors must clearly provide detail, data, and software to ensure readers' ability to reproduce the models, methods, and results.Authors unsure of whether their work is within the scope of the journal should submit a presubmission inquiry.

The first academic journal for serious investigators of teleoperators and virtual environments, Presence is filled with stimulating material applicable to these advanced electromechanical and computer devices.Incorporating perspectives from physics to philosophy, Presence appeals to a wide audience - particularly mechanical and electrical engineers concerned with teleoperators; those interested in virtual environments, including computer scientists, high-tech artists, and media people; and psychologists involved in the study of human-machine interfaces and sensorimotor/cognitive behavior.

Parallel Computing is an international journal presenting the practical use of parallel computer systems, including high performance architecture, system software, programming systems and tools, and applications. Within this context the journal covers all aspects of high-end parallel computing.Parallel Computing features original research work, tutorial and review articles as well as novel or illustrative accounts of application experience with (and techniques for) the use of parallel computers. Contributions can cover:• System software for parallel computer systems including programming languages (new languages as well as compilation techniques), operating systems (including middleware), and resource management (scheduling and load-balancing).• Enabling software including debuggers, performance tools, and system and numeric libraries.• General hardware (architecture) concepts, new technologies enabling the realization of such new concepts, and details of commercially available systems• Software engineering and productivity as it relates to parallel computing• Application or tool case studies demonstrating novel ways to achieve parallelism• Performance measurement results on state-of-the-art systems• Approaches to effectively utilize large-scale parallel computing including new algorithms or algorithm analysis with demonstrated relevance to real applications using existing or next generation parallel computer architectures.• Parallel I/O systems both hardware and software• Networking technology for support of high-speed computing demonstrating the impact of high-speed computation on parallel applicationsBenefits 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

Parallel Processing Letters (PPL) aims to rapidly disseminate results on a worldwide basis in the field of parallel processing in the form of short papers. It fills the need for an information vehicle which can convey recent achievements and further the exchange of scientific information in the field. This journal has a wide scope and topics covered include:

This journal presents original research that describes novel pattern analysis techniques as well as industrial and medical applications. It details new technology and methods for pattern recognition and analysis in applied domains, including computer vision and image processing, speech analysis, robotics, multimedia, document analysis, character recognition, knowledge engineering for pattern recognition, fractal analysis, and intelligent control. Pattern Analysis and Applications (PAA) also examines the use of advanced methods, including statistical techniques, neural networks, genetic algorithms, fuzzy pattern recognition, machine learning, and hardware implementations which are either relevant to the development of pattern analysis as a research area or detail novel pattern analysis applications. The journal contains case-studies as well as reviews on benchmarks, evaluations of tools, and important research activities at international centers of excellence.

Pattern Recognition is the official journal of the Pattern Recognition Society. The Society was formed to fill a need for information exchange among research workers in the pattern recognition field. Up to now, we ''pattern-recognitionophiles'' have been tagging along in computer science, information theory, optical processing techniques, and other miscellaneous fields. Because this work in pattern recognition presently appears in widely spread articles and as isolated lectures in conferences in many diverse areas, the purpose of the journal Pattern Recognition is to give all of us an opportunity to get together in one place to publish our work. The journal will thereby expedite communication among research scientists interested in pattern recognition.We consider pattern recognition in the broad sense, and we assume that the journal will be read by people with a common interest in pattern recognition but from many diverse backgrounds. These include biometrics, target recognition, biological taxonomy, meteorology, space science, classification methods, character recognition, image processing, industrial applications, neural computing, and many others.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.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

Pattern Recognition Letters aims at rapid publication of concise articles of a broad interest in pattern recognition.Subject areas include all the current fields of interest represented by the Technical Committees of the International Association of Pattern Recognition, and other developing themes involving learning and recognition. Examples include:• Statistical, structural, syntactic pattern recognition;• Neural networks, machine learning, data mining;• Discrete geometry, algebraic, graph-based techniques for pattern recognition;• Signal analysis, image coding and processing, shape and texture analysis;• Computer vision, robotics, remote sensing;• Document processing, text and graphics recognition, digital libraries;• Speech recognition, music analysis, multimedia systems;• Natural language analysis, information retrieval;• Biometrics, biomedical pattern analysis and information systems;• Scientific, engineering, social and economical applications of pattern recognition;• Special hardware architectures, software packages for pattern recognition.We invite contributions as research reports or commentaries.Research reports should be concise summaries of methodological inventions and findings, with strong potential of wide applications.Alternatively, they can describe significant and novel applications of an established technique that are of high reference value to the same application area and other similar areas.Commentaries can be lecture notes, subject reviews, reports on a conference, or debates on critical issues that are of wide interests.To serve the interests of a diverse readership, the introduction should provide a concise summary of the background of the work in an accepted terminology in pattern recognition, state the unique contributions, and discuss broader impacts of the work outside the immediate subject area. All contributions are reviewed on the basis of scientific merits and breadth of potential interests.

Pattern Recognition and Image Analysis: Advances in Mathematical Theory and Applications is a per reviewed international journal featuring top papers in pattern recognition, image recognition, analysis, understanding, and processing. Emphasis is laid on rapid publishing of concise articles covering theory, methodology, and applications. Major topics include mathematical theory of pattern recognition and image analysis, raw data representation, computer vision, image mining, processing and understanding, machine learning, computer graphics, forecasting, data and knowledge bases, data mining, neural nets, artificial intelligence, software, specialized computer architectures, applications, and related areas.

Peer-to-Peer Networking and Applications disseminates state-of-the-art research and development results to facilitate effective deployment of P2P networking and applications. The journal brings together and fosters interaction among academic and industrial communities to promote further research that leads to new P2P applications and services. This journal not only addresses research topics related to networking and communications theory, but also considers the standardization, economic, and engineering aspects of P2P technologies and their impact on software engineering, computer engineering, networked communication, and security. It includes papers addressing system, application, and service issues. Peer-to-Peer Networking and Applications publishes original research papers, tutorials, reviews, case studies, and correspondences from the research, development, and standardization communities.

Perceptionis a scholarly journal reporting experimental results and theoretical ideas ranging over the fields of human. animal. and machine perception. Topics covered include physiological mechanisms and clinical neurological disturbances; psychological data on pattern and object perception in animals and man; the role of experience in developing perception; skills. such as driving and flying; effects of culture on perception and aesthetics; errors. illusions. and perceptual phenomena occurring in controlled conditions. with emphasis on their theoretical significance; cognitive experiments and theories relating knowledge to perception; development of categories and generalisations; strategies for interpreting sensory patterns in terms of objects by organisms and machines; special problems associated with perception of pictures and symbols; verbal and nonverbal skills; reading; philosophical implications of experiments and theories of perception for epistemology. aesthetics. and art.

Performance Evaluation functions as a leading journal in the area of modeling, measurement, and evaluation of performance aspects of computing and communication systems. As such, it aims to present a balanced and complete view of the entire Performance Evaluation profession. Hence, the journal is interested in papers that focus on one or more of the following dimensions:Define new performance evaluation tools, including measurement and monitoring tools as well as modeling and analytic techniquesProvide new insights into the performance of computing and communication systemsIntroduce new application areas where performance evaluation tools can play an important role and creative new uses for performance evaluation tools.More specifically, common application areas of interest include the performance of:Resource allocation and control methods and algorithms (e.g. routing and flow control in networks, bandwidth allocation, processor scheduling, memory management)System architecture, design and implementationCognitive radioVANETsSocial networks and mediaEnergy efficient ICTEnergy harvestingData centersData centric networksSystem reliabilitySystem tuning and capacity planningWireless and sensor networksAutonomic and self-organizing systemsEmbedded systemsNetwork scienceFurther, common performance evaluation tools of interest include:queueing theoryscheduling theorysimulation methodsdata analysismeasurement techniques (e.g. software and hardware monitors) and workload characterizationstochastic geometrylarge deviationsmean-field theorygame theory and equilibrium analysisNote that the above lists are not all inclusive or restrictive and submissions with creative applications of performance evaluation tools outside of those above and/or applications outside of those above are also welcome.A variety of types of submissions are possible, including: original work, tutorials & surveys, news items and short communications.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