AI Open is a freely accessible platform to share actionable knowledge and forward-thinking perspectives on the theory of artificial intelligence and its applications. The journal welcomes research articles, review papers, perspectives, short communications and technical notes on all aspects of artificial intelligence and its applications.Topics covered include, but are not limited to:Deep learning and representation learningGraph theory and graph miningConstraints, satisfiability, and searchKnowledge representation, reasoning, and logicMachine learning and data miningKnowledge graph and applicationsAgent-based and multi-agent systemsWeb and knowledge-based information systemsNatural language processingImage processing and analysisUncertaintyBrain-based LearningImplicit Cognition and LearningEditorial Board
AI-Thermal/Fluids (AITF) is dedicated to exploratory research and advancements at the intersection of artificial intelligence (AI) and thermal-fluid science and engineering. The journal publishes full length Research Articles, Rapid Communications, Reviews, Letters to the Editor, and Vision Articles. It also publishes Original Software articles that describe and provide access to open-source software and Data Articles that describe and provide access to research data.AITF welcomes research that leverages AI techniques, such as machine learning, neural networks and data analytics, to promote fundamental understanding, improve prediction capabilities, solve problems and design or optimize thermal-fluid systems, with a view to stimulating innovation across a broad range of science and engineering applications. Contributions may include AI-driven modelling, simulation, data enhancement, AI-assisted experimentation, and control methodologies, among others.The list of focus areas includes (but is not limited to):Experimental Methodologies and Measurement Techniques: AITF showcases efforts to develop AI-based experimental methodologies, measurement techniques, and instrumentation for characterizing the thermal, mass transfer, reaction and/or fluid-flow dynamics aspects of a wide range of transport phenomena and processes.
Modelling and Simulation: AITF publishes studies on the development of AI-based methodologies to design, model or predict material properties, transport phenomena and processes, enhance the capabilities of physics-based modelling and simulation tools, and analyse the data they generate, either in support of or independently from experimental measurements.
Fluid Dynamics and Thermal Transport Phenomena: AITF seeks contributions aiming to elucidate transport phenomena. Examples are fluid flow behaviour, including turbulence, and transport processes within diverse flows, including single phase and multiphase flows, both isothermal and diabatic, as well as flows in the presence of phase change and reactive flows. AI-based approaches to process and analyse high throughput data, characterize flow dynamics, phase distribution, heat and mass transfer, reactions, and fluid-solid interactions are encouraged.
Process Enhancement: AITF encourages the submission of articles focusing on innovative approaches to enhance heat and mass transfer or chemical processes in a wide range of devices, systems and applications. This encompasses design and operational optimization of heat exchangers, absorbers, separators, or reactors, the development of novel management approaches, surface modification techniques, and other passive and active enhancement strategies.
Materials Properties: AITF welcomes research focused on the evaluation of thermophysical, thermochemical or thermodynamic materials properties relevant to the phenomena, problems, and applications of interest to the journal. This includes AI-based methods for predicting properties such as thermal conductivity, viscosity, density, phase behaviour, and other crucial attributes for accurate modelling, simulation, and optimization.
Energy Exchange and Conversion: AITF features research addressing energy exchange and transformation mechanisms and their implications in engineering applications. This includes AI-driven optimization of energy harvesting techniques, energy conversion processes, energy storage, and sustainable energy technologies.Environmental and Sustainable Applications: AITF promotes efforts to address the economic and environmental implications of relevant processes, including renewable energy technologies, energy recover and management and energy efficiency in industry, buildings and the built environment, pollution mitigation, carbon capture and storage, and a wide range of other sustainable energy production, storage, or utilization technologies.
An International Journal on Multi-Sensor, Multi-Source Information FusionThe journal is intended to present within a single forum all of the developments in the field of multi-sensor, multi-source, multi-process information fusion and thereby promote the synergism among the many disciplines that are contributing to its growth. The journal is the premier vehicle for disseminating information on all aspects of research and development in the field of information fusion. Articles are expected to emphasize one or more of the three facets: architectures, algorithms, and applications. Papers dealing with fundamental theoretical analyses as well as those demonstrating their application to real-world problems will be welcome. The journal publishes original papers, letters to the Editors and from time to time invited review articles, in all areas related to the information fusion arena including, but not limited to, the following suggested topics:• Data/Image, Feature, Decision, and Multilevel Fusion • Multi-classifier/Decision Systems • Multi-Look Temporal Fusion • Multi-Sensor, Multi-Source Fusion System Architectures • Distributed and Wireless Sensor Networks • Higher Level Fusion Topics Including Situation Awareness And Management • Multi-Sensor Management and Real-Time Applications • Adaptive And Self-Improving Fusion System Architectures • Active, Passive, And Mixed Sensor Suites • Multi-Sensor And Distributed Sensor System Design • Fusion Learning In Imperfect, Imprecise And Incomplete Environments • Intelligent Techniques For Fusion Processing • Fusion System Design And Algorithmic Issues • Fusion System Computational Resources and Demands Optimization • Special Purpose Hardware Dedicated To Fusion Applications • Mining Remotely Sensed Multi-Spectral/Hyper-Spectral Image Data Bases • Information Fusion Applications in Intrusion Detection, Network Security, Information Security and Assurance arena • Applications such as Robotics, Space, Bio-medical, Transportation, Economics, and Financial Information Systems • Real-World Issues such as Computational Demands, Real-Time Constraints in the context of Fusion systems.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
Cognitive computing is the creation of self-learning systems that use data mining, pattern recognition and natural language processing (NLP) to solve complicated problems without constant human oversight. It is a field that is highly transdisciplinary in nature, combining ideas, principles and methods of psychology, computer and internet technologies, linguistics, philosophy, neuroscience, etc.The goal of the International Journal of Cognitive Computing in Engineering is to explore how these data science technologies and new cognitive methods can be integrated to address real world engineering problems and challenges. For example, the journal welcomes submissions that look at the opportunities offered by combining existing data technologies with the knowledge of experts in the field and artificial intelligence. One of the benefits of cognitive computing is that it offers new analytics opportunities: the journal also welcomes designs for cognitive embedded data technologies that can process and analyse the large amount of data generated and aid decision-making.Submissions on a variety of cognitive computing-related topics will be considered.Editorial Board
International Journal of Intelligent Networks (IJIN) presents the most recent challenges and developments in computer networks with the objective of promoting awareness and best practices for the real-world problems. It aims to present new directions for further research and technology improvements in this important area.International Journal of Intelligent Networks (IJIN) presents research findings related to intelligent network of computing resources. It therefore invites original and timely research articles in the field of intelligent communication, technology, sustainability and social communication related research areas of current importance. IJIN will publish original papers, review papers, technical reports, case studies and book reviews.Topics of interest to the journal include, but are not limited to:Signal processing architectures, algorithms and applicationsImage computing and data science technologySmart sensor and agent networksGreen technologies in information, computing and communication systemsIntelligent computing for sustainable energyCommunication network architectures and securityBioinformatics and network computationWireless communication and network protocolsNetwork operation and managementIntelligent and information systemsNetwork coding theory and algorithmsSmart vehicular communication and technologyFuture AdvancementsEditorial Board
As of 2006, no longer published by ElsevierAuthors: Please note that Real-Time Imaging is no longer accepting new submissions, as the journal will be closed at the end of 2005. Authors are encouraged to submit their paper to http://www.elsevier.com/locate/jvci the Journal of Visual Communication and Image Representation.Real-time imaging is concerned with various imaging techniques, technologies and systems where timing constraints are as critical as being logically correct. Real-Time Imaging (RTI) is a peer-reviewed technical journal that serves as a convergence point for scientists and researchers working in real-time imaging and its application areas. It is intended to be a forum where new fundamental and practical advances in real-time imaging are unveiled.Papers include but are not limited to the following areas: • real-time image/video communication and compression • real-time machine vision and inspection • real-time imaging in multimedia and visualization • real-time target acquisition and tracking • real-time image/video processing and analysis • real-time imaging computer architectures • real-time document processing • real-time imaging industrial, medical, transport applications • real-time pattern recognition and classification systems • real-time imaging simulation systems 15/9
Affiliated with the Intelligent Autonomous Systems (IAS) SocietyRobotics and Autonomous Systems will carry articles describing fundamental developments in the field of robotics, with special emphasis on autonomous systems. An important goal of this journal is to extend the state of the art in both symbolic and sensory based robot control and learning in the context of autonomous systems.Robotics and Autonomous Systems will carry articles on the theoretical, computational and experimental aspects of autonomous systems, or modules of such systems.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