Information systems journals | Elsevier

Autonomous Transportation Research

ISSN: 3050-8622

Chip

ISSN: 2709-4723

An official journal of Shanghai Jiao Tong University.Chip is an international journal that publishes innovative research in the emerging field of integrated chips that feature revolutionary information technology.Chip will bridge the boundaries between theory and technology and form the aggregation effect of chip research. It aims to become a competitive top journal with strong international recognition and will serve as a platform for graduate students, professionals, and the engineering industry to jointly boost the cutting-edge information sciences and technologies.The journal focuses on the rapid development and potential application of new-generation information technologies. These include but are not limited to the following fields:•Quantum information: quantum algorithm, quantum machine learning, analog quantum computing, quantum circuits, quantum annealing•New types of Non-von Neumann computing and post-Moore devices: photonic computing, neuromorphic computing, other promising classical (not quantum) computing technologies•Internet of things and edge computing: advanced sensors, wireless signal transmission, low-power computing, energy harvesting, biomedical systems•Big Data and artificial intelligence: innovative hardware and architecture for data mining, information retrieval, machine learning, natural language processing, computer vision, robotics•Interdisciplinary area related to chip issues: new chip materials, new device manufacturing techniques, algorithm and architecture of chips.The Print ISSN of the journal is 2709-4723.

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Cognitive Robotics

ISSN: 2667-2413

Cognitive Robotics merges two research fields, physical systems and control architectures. The physical systems are designed to adapt to dynamic environments while the control architectures explicitly take into account the need to acquire and exploit past experiences. It paves the way for machines to have reasoning abilities which is analogous to human. The research field of cognitive robotics is interdisciplinary, and uses knowledge and methods from many areas such as psychology, biology, signal processing, physics, information theory, mathematics, and statistics. The development of cognitive robotics will keep cross-fertilizing these research areas.This journal aim to collect the state-of-the-art contributions on the Computational Neuroscience, Computational Cognition and Perception, Computer Vision, Natural Language Processing, Human Action Analysis, and related applications in robotics.Editorial Board

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Computers & Mathematics with Applications

ISSN: 0898-1221
5 Year impact factor: 2.6
Impact factor: 2.9

Computers & Mathematics with Applications provides a medium of exchange for those engaged in fields contributing to building successful simulations for science and engineering using Partial Differential Equations (PDEs).The following are the principal areas of interest of the journal: Modeling using PDEs.Analysis of mathematical models, formulated in terms of PDEs.Discretization Methods and Numerical Analysis for PDEs.Numerical linear and nonlinear algebra. Fast numerical algorithms.Algorithms and Data Structures. Adaptivity. Computational Geometry.Software Design, Code verification and Quality Assurance (QA).Verification and Validation.This journal has an Open Archive. All published items, including research articles, have unrestricted access and will remain permanently free to read and download 48 months after publication. All papers in the Archive are subject to Elsevier's user license.If you have questions about submissions, scope, or content, please contact our Support Center

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Computers in Industry

ISSN: 0166-3615
5 Year impact factor: 9.3
Impact factor: 8.2

An International, Application Oriented Research JournalThe aim of Computers in Industry is to publish original, high-quality, application-oriented research papers that:• Show new trends in and options for the use of Information and Communication Technology in industry; • Link or integrate different technology fields in the broad area of computer applications for industry; • Link or integrate different application areas of ICT in industry.General topics covered include the following areas:• The unique application of ICT in business processes such as design, engineering, manufacturing, purchasing, physical distribution, production management and supply chain management. This is the main thrust of the journal. It includes research in integration of business process support, such as in enterprise modelling, ERP, EDM. • The industrial use of ICT in knowledge intensive fields such as quality control, logistics, engineering data management, and product documentation will certainly be considered. • Demonstration of enabling capabilities of new or existing technologies such as hard real time systems, knowledge engineering, applied fuzzy logic, collaborative work systems, and intelligence agents are also welcomed. • Papers solely focusing on ICT or manufacturing processes may be considered out of scope.A continuous quality policy, based on strict peer reviewing shall ensure that published articles are:- Technologically outstanding and front-end - Application-oriented with a generalised message - Representative for research at an international levelBenefits 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

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Cyber-Physical Energy Systems

ISSN: 3050-7448

Cyber-Physical Energy Systems(CPES) is an interdisciplinary journal aimed at integrating energy systems with advanced sensing, communication, computation, control and decision technologies. Cyber-Physical Energy System in a broader sense provides a desirable infrastructure for efficient energy production and consumption with resilience to high uncertainties. The journal pays specific attentions to the innovative ideas and insights both on cyber and physical spaces to address the theoretical and practical challenges on green energy systems, and publishes original research on theories and applications in but not limited to integrated energy systems and information networks, zero-carbon energy systems, smart building energy systems, microgrids, renewable energy power systems, advanced methods of sensing, communication, computation, control and decision for energy systems, and so on. The Topics within the journal scope include, but are not limited to, the following:structure and design of CPESmodeling and simulation of CPESsensing, computation and communication for CPEScontrol theory and technology for CPESoptimization theory and technology for CPEScyber-physical securityreliability and resilience of CPESenergy market and economics with CPES AI for CPESdevices and equipment in CPESCPES in infrastructure

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Data & Knowledge Engineering

ISSN: 0169-023X
5 Year impact factor: 2.2
Impact factor: 2.7

Database Systems and Knowledgebase Systems share many common principles. Data & Knowledge Engineering (DKE) stimulates the exchange of ideas and interaction between these two related fields of interest. DKE reaches a world-wide audience of researchers, designers, managers and users. The major aim of the journal is to identify, investigate and analyze the underlying principles in the design and effective use of these systems. DKE achieves this aim by publishing original research results, technical advances and news items concerning data engineering, knowledge engineering, and the interface of these two fields.DKE covers the following topics:1. Representation and Manipulation of Data & Knowledge: Conceptual data models. Knowledge representation techniques. Data/knowledge manipulation languages and techniques.2. Architectures of database, expert, or knowledge-based systems: New architectures for database / knowledge base / expert systems, design and implementation techniques, languages and user interfaces, distributed architectures.3. Construction of data/knowledge bases: Data / knowledge base design methodologies and tools, data/knowledge acquisition methods, integrity/security/maintenance issues.4. Applications, case studies, and management issues: Data administration issues, knowledge engineering practice, office and engineering applications.5. Tools for specifying and developing Data and Knowledge Bases using tools based on Linguistics or Human Machine Interface principles.6. Communication aspects involved in implementing, designing and using KBSs in Cyberspace.Plus... conference reports, calendar of events, book reviews etc.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

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Data Science and Management

ISSN: 2096-739X

Data Science and Management (DSM) is a peer-reviewed open access journal for original research articles, review articles and technical reports related to all aspects of data science and its application in the field of business, economics, finance, operations, engineering, healthcare, transportation, agriculture, energy, environment, sports, and social management. DSM was launched in 2021, and published quarterly by Xi'an Jiaotong University.Current areas of interest include, but are not limited to:Machine learning and intelligent managementData mining and business analyticsData statistics and decision makingIntelligent computing and algorithmsData-driven management decisionsData-based policy evaluationBusiness intelligenceBusiness data scienceDigital economyData quality and data privacyData and knowledge managementEnterprise digital managementCyberspace managementData security managementSmart city managementSmart society managementDigital engineering managementData visualizationData-driven intelligent system managementData science applicationsAbout the Journal: The journal has a distinguished editorial board with extensive academic qualifications, ensuring that the journal maintains high scientific standards and has a broad coverage. DSM seeks to publish original, high quality, peer-reviewed papers including original research articles and reviews as well as technical reports. Submission would be encouraged on all aspects of data science and its application in the field of business, economics, finance, operations, engineering, healthcare, transportation, agriculture, energy, environment, sports, and social management. The aim of this journal is to become a highly respected and trusted resource of leading knowledge in this field and to promote worldwide academic exchange. DSM is going to be an interdisciplinary forum opened to all professionals in the world.Editorial Board

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Data Science and Management

ISSN: 2666-7649

Data Science and Management (DSM) is a peer-reviewed open access journal for original research articles, review articles and technical reports related to all aspects of data science and its application in the field of business, economics, finance, operations, engineering, healthcare, transportation, agriculture, energy, environment, sports, and social management. DSM was launched in 2021, and published quarterly by Xi'an Jiaotong University.Current areas of interest include, but are not limited to:Machine learning and intelligent managementData mining and business analyticsData statistics and decision makingIntelligent computing and algorithmsData-driven management decisionsData-based policy evaluationBusiness intelligenceBusiness data scienceDigital economyData quality and data privacyData and knowledge managementEnterprise digital managementCyberspace managementData security managementSmart city managementSmart society managementDigital engineering managementData visualizationData-driven intelligent system managementData science applicationsAbout the Journal: The journal has a distinguished editorial board with extensive academic qualifications, ensuring that the journal maintains high scientific standards and has a broad coverage. DSM seeks to publish original, high quality, peer-reviewed papers including original research articles and reviews as well as technical reports. Submission would be encouraged on all aspects of data science and its application in the field of business, economics, finance, operations, engineering, healthcare, transportation, agriculture, energy, environment, sports, and social management. The aim of this journal is to become a highly respected and trusted resource of leading knowledge in this field and to promote worldwide academic exchange. DSM is going to be an interdisciplinary forum opened to all professionals in the world.Editorial Board

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Decision Support Systems

ISSN: 0167-9236
5 Year impact factor: 7.5
Impact factor: 6.7

and Electronic CommerceThe common thread of articles published in Decision Support Systems is their relevance to theoretical and technical issues in the support of enhanced decision making. The areas addressed may include foundations, functionality, interfaces, implementation, impacts, and evaluation of decision support systems (DSSs). Manuscripts may draw from diverse methods and methodologies, including those from decision theory, economics, econometrics, statistics, computer supported cooperative work, data base management, linguistics, management science, mathematical modeling, operations management, cognitive science, psychology, user interface management, and others. However, a manuscript focused on direct contributions to any of these related areas should be submitted to an outlet appropriate to the specific area.Examples of research topics that would be appropriate for Decision Support Systems include the following:1. DSS Foundations e.g. principles, concepts, and theories of enhanced decision making; formal languages and research methods enabling improvements in decision making. It is important that theory validation be carefully addressed.2. DSS Functionality e.g. methods, tools, and techniques for developing thefunctional aspects of enhanced decision making; solver, model, and/or data management in DSSs; rule formulation and management in DSSs; DSS development and use in computer supported cooperative work, negotiation, research and product.3. DSS Interfaces e.g. methods, tools, and techniques for designing and developing DSS interfaces; development, management, and presentation of knowledge in a DSS; coordination of a DSS's interface with its functionality.4. DSS Implementation - experiences in DSS development and utilization; DSS management and updating; DSS instruction/training. A critical consideration must be how specific experiences provide more general implications.5. DSS Evaluation and Impact e.g. evaluation metrics and processes; DSS impact on decision makers, organizational processes and performance.

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Journals in Information systems

Autonomous Transportation Research

Chip

Cognitive Robotics

Computers & Mathematics with Applications

Computers in Industry

Cyber-Physical Energy Systems

Data & Knowledge Engineering

Data Science and Management

Data Science and Management

Decision Support Systems

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