Journal Guide

Mechatronics is the synergistic combination of precision mechanical engineering, electronic control and systems thinking in the design of products and manufacturing processes. It relates to the design of systems, devices and products aimed at achieving an optimal balance between basic mechanical structure and its overall control. The purpose of this journal is to provide rapid publication of topical papers featuring practical developments in mechatronics. It will cover a wide range of application areas including consumer product design, instrumentation, manufacturing methods, computer integration and process and device control, and will attract a readership from across the industrial and academic research spectrum. Particular importance will be attached to aspects of innovation in mechatronics design philosophy which illustrate the benefits obtainable by an a priori integration of functionality with embedded microprocessor control. A major item will be the design of machines, devices and systems possessing a degree of computer based intelligence. The journal seeks to publish research progress in this field with an emphasis on the applied rather than the theoretical. It will also serve the dual role of bringing greater recognition to this important area of engineering.Mechatronics publishes the following types of papers:• Regular Articles should describe original research of high quality in the field of Mechatronics.• Review Articles will generally be specially commissioned, however, suggestions for topics and authors are welcomed by the Editor-in-Chief.•Technical Notes provide rapid publication of important new contributions.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

Medical Image Analysis provides a forum for the dissemination of new research results in the field of medical and biological image analysis, with special emphasis on efforts related to the applications of computer vision, virtual reality and robotics to biomedical imaging problems. The journal publishes the highest quality, original papers that contribute to the basic science of processing, analysing and utilizing medical and biological images for these purposes. The journal is interested in approaches that utilize biomedical image datasets at all spatial scales, ranging from molecular/cellular imaging to tissue/organ imaging. While not limited to these alone, the typical biomedical image datasets of interest include those acquired from:Magnetic resonanceUltrasoundComputed tomographyNuclear medicineX-rayOptical and Confocal MicroscopyVideo and range data imagesThe types of papers accepted include those that cover the development and implementation of algorithms and strategies based on the use of various models (geometrical, statistical, physical, functional, etc.) to solve the following types of problems, using biomedical image datasets: representation of pictorial data, visualization, feature extraction, segmentation, inter-study and inter-subject registration, longitudinal / temporal studies, image-guided surgery and intervention, texture, shape and motion measurements, spectral analysis, digital anatomical atlases, statistical shape analysis, computational anatomy (modelling normal anatomy and its variations), computational physiology (modelling organs and living systems for image analysis, simulation and training), virtual and augmented reality for therapy planning and guidance, telemedicine with medical images, telepresence in medicine, telesurgery and image-guided medical robots, etc.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

Memetic Computing features articles on high quality research in hybrid metaheuristics (including evolutionary hybrids) for optimization, control and design in continuous and discrete optimization domains. It goes beyond current search methodologies towards innovative research on the emergence of cultural artifacts such as game, trade and negotiation strategies and, more generally, rules of behavior as they apply to, for example, robotic, multi-agent and artificial life systems. Memetic Computing is an avenue for the latest results in natural computation, artificial intelligence, machine learning, operational research and natural sciences, which are combined in novel ways so as to transcend the intrinsic limitations of a single discipline. Potential authors are invited to submit original research articles for publication consideration at any time. Reviews and short research communications are also welcomed. Further information on submission, format, lengths and style files is available through the journal website. All manuscripts should be submitted electronically using the Online Submission system. We aim to achieve a typical turnaround time of not more than 3 months for the review process. Some (but not all) of the topics covered by Memetic Computing are: Algorithmic Intelligence in Optimisation, Control and Design Hybrid (Parallel) Metaheuristics such as Tabu Search, Path relinking, Scatter Search, GRASP methods, Iterated Local Search, Simulated annealing, Variable Neighborhood Search, Evolutionary Algorithms, Learning Classifier Systems, Memetic Algorithms, Cultural Algorithms, etc. Approximate and exact algorithms for Combinatorial and Continuous Optimisation Integer and Linear Programming Ant Colony Computing Self-organisation, Self-Assembly, Self-Generation, Self-Healing of artificial systems Swarm Intelligence<, /LI> Neural networks Evolutionary Dynamics Memetic Theory Artificial Cultures in multi-agent systems, webbots and robots. Landscape Analysis Methodological aspects of experimental computing. Search based Software Engineering Genetic Programming Constraint Optimisation Representation and encoding studies Real-world applications Machine learning and Data Mining Multiobjective optimisation Artificial immune systems

Microprocessors and Microsystems: Embedded Hardware Design (MICPRO) is a journal covering all design and architectural aspects related to embedded systems hardware. It includes different embedded system hardware platforms ranging from custom hardware via reconfigurable systems and application specific processors to general purpose embedded processors. Special emphasis is put on novel complex embedded architectures, such as systems on chip (SoC), systems on a programmable/reconfigurable chip (SoPC) and multi-processors on a chip (MPoC) as well as their communication methods, such as network-on-chip (NoC).Design automation of such systems including methodologies, techniques and tools for their design as well as novel designs of hardware components fall within the scope of this journal. Novel applications that use embedded systems are also central in this journal. While software is not a part of this journal hardware/software co-design methods that consider interplay between software and hardware components with emphasis on hardware are also relevant here.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

Affiliated with the Society for Machines and Mentality, the journal Minds and Machines fosters a tradition of criticism within the AI and philosophical communities on problems and issues of common concern. Its scope explicitly encompasses philosophical aspects of computer science. The journal affords an international forum for the discussion and debate of important and controversial issues concerning significant developments within its areas of editorial focus. It features special issues devoted to specific topics, critical responses to previously published pieces, and review essays discussing current problem situations.

Multidimensional Systems and Signal Processing publishes research and selective surveys papers ranging from the fundamentals to important new findings. The journal responds to and provides a solution to the widely scattered nature of publications in this area, offering unity of theme, reduced duplication of effort, and greatly enhanced communication among researchers and practitioners in the field.A partial list of topics addressed in the journal includes multidimensional control systems design and implementation;  multidimensional stability and realization theory; prediction and filtering of multidimensional processes; Spatial-temporal signal processing; multidimensional filters and filter-banks; array signal processing; and applications of multidimensional systems and signal processing to areas such as healthcare and 3-D imaging techniques.

Natural Computing refers to computational processes observed in nature, and human-designed computing inspired by nature. When complex natural phenomena are analyzed in terms of computational processes, our understanding of both nature and the essence of computation is enhanced. Characteristic for human-designed computing inspired by nature is the metaphorical use of concepts, principles and mechanisms underlying natural systems. Natural computing includes evolutionary algorithms, neural networks, molecular computing and quantum computing. The journal Natural Computing provides a forum for discovery in natural computing, offering links among researchers and insight into trends in an emerging specialty. The journal reports on theory, experiments, and applications, and covers natural computing from a very broad perspective, including use of algorithms to consider evolution as a computational process, and neural networks in light of computational trends in brain research. Now indexed in ISI.

The Journal provides a forum for integrating theoretical and experimental findings in computational neuroscience across relevant interdisciplinary boundaries. Rapidly accumulating empirical data in the neurobiological, psychological and cognitive domains provide important constraints for new theoretical models. The Journal aims to present such theoretical results, and make them accessible to neurobiologists, psychologists and cognitive scientists. Read More: http://informahealthcare.com/page/net/Description.

Networks and Spatial Economics (NETS) is devoted to the mathematical and numerical study of economic activities facilitated by human infrastructure. The range of topics is broadly defined to include technologies pertinent to information, telecommunications, the Internet, transportation, energy storage and transmission, and water resources. The journal publishes a full spectrum of high quality work in networks and spatial economics including theoretical studies, case studies and algorithmic investigations, as well as manuscripts that combine these aspects. Although not devoted exclusively to theoretical studies, the journal is 'theory-friendly'.Officially cited as: Netw Spat Econ

Neural Computation disseminates important, multidisciplinary research in a field that attracts psychologists, physicists, computer scientists, neuroscientists, and artificial intelligenceinvestigators, among others. For researchers looking at the scientific and engineering challenges of understanding the brain and building computers, Neural Computation highlights common problems and techniques in modeling the brain, and in the design and construction of neurally-inspired information processing systems.

Neural Computing & Applications is an international journal which publishes original research and other information in the field of practical applications of neural computing and related techniques such as genetic algorithms, fuzzy logic and neuro-fuzzy systems.All items relevant to building practical systems are within its scope, including contributions in the area of applicable neural networks theory, supervised and unsupervised learning methods, algorithms, architectures, performance measures, applied statistics, software simulations, hardware implementations, benchmarks, system engineering and integration and case histories of innovative applications.Featured contributions fall into several categories: Original Articles, Review Articles, Forum Presentations, Book Reviews, Announcements and NCAF News.The Original Articles will be high-quality contributions, representing new and significant research, developments or applications of practical use and value. They will be reviewed by at least two referees. T

Neural Networks is the archival journal of the world's three oldest neural modeling societies: the International Neural Network Society (INNS), the European Neural Network Society (ENNS), and the Japanese Neural Network Society (JNNS). A subscription to the journal is included with membership in each of these societies.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 and related approaches to computational intelligence. Neural Networks welcomes high quality submissions that contribute to the full range of neural networks research, from behavioral and brain modeling, learning algorithms, through mathematical and computational analyses, to engineering and technological applications of systems that significantly use neural network concepts and 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-inspired computational intelligence. Accordingly, Neural Networkseditorial board represents experts in fields including psychology, neurobiology, computer science, engineering, mathematics, and physics. The journal publishes articles, letters and reviews, as well as letters to the editor, editorials, current events, software surveys, and patent information. Articles are published in one of five sections: Cognitive Science, Neuroscience, Learning Systems, Mathematical and Computational Analysis, Engineering and Applications.The journal is published twelve times a year. Neural Networks can be accessed electronically via Science Direct (http://www.sciencedirect.com/science/journal/08936080), which is used by over eight million individuals world-wide.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

Neural Processing Letters is an international journal publishing research results and innovative ideas on all aspects of artificial neural networks. Coverage includes theoretical developments, biological models, new formal modes, learning, applications, software and hardware developments, and prospective researches.The journal promotes fast exchange of information in the community of neural network researchers and users. The resurgence of interest in the field of artificial neural networks since the beginning of the 1980s is coupled to tremendous research activity in specialized or multidisciplinary groups. Research, however, is not possible without good communication between people and the exchange of information, especially in a field covering such different areas; fast communication is also a key aspect, and this is the reason for Neural Processing Letters.

Neurocomputing publishes articles describing recent fundamental contributions in the field of neurocomputing. Neurocomputing theory, practice and applications are the essential topics being covered.Neurocomputing welcomes theoretical contributions aimed at winning further understanding of neural networks and learning systems, including, but not restricted to, architectures, learning methods, analysis of network dynamics, theories of learning, self-organization, biological neural network modelling, sensorimotor transformations and interdisciplinary topics with artificial intelligence, artificial life, cognitive science, computational learning theory, fuzzy logic, genetic algorithms, information theory, machine learning, neurobiology and pattern recognition.Neurocomputing covers practical aspects with contributions on advances in hardware and software development environments for neurocomputing, including, but not restricted to, simulation software environments, emulation hardware architectures, models of concurrent computation, neurocomputers, and neurochips (digital, analog, optical, and biodevices).Neurocomputing reports on applications in different fields, including, but not restricted to, signal processing, speech processing, image processing, computer vision, control, robotics, optimization, scheduling, resource allocation and financial forecasting.Neurocomputing publishes reviews of literature about neurocomputing and affine fields.Neurocomputing reports on meetings, including, but not restricted to, conferences, workshops and seminars.Neurocomputing reports on functionality/availability of software, on comparative assessments, and on discussions of neurocomputing software issues.Now also including: Neurocomputing Letters - for the rapid publication of special short communications.

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

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.