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IEEE Transactions on Human-machine Systems | 2024 Impact Factor:4.4 | Cite Score:8.9 | Q1

IEEE Transactions on Human-machine Systems Journal

Impact Factor and Journal Rank of IEEE Transactions on Human-machine Systems

  • About: IEEE Transactions on Human-Machine Systems is a peer-reviewed journal that focuses on the advancement of theory and practice in the areas of human-machine systems. The journal covers various aspects, including system modeling, interface design, human-computer interaction, cognitive engineering, and user-centered design.
  • Objective:
    The objective of IEEE Transactions on Human-Machine Systems is to foster the development and dissemination of knowledge in the interdisciplinary field of human-machine systems. By publishing high-quality research, the journal aims to enhance understanding and improve the interaction between humans and machines in various applications.
  • Focus Areas:
    The journal publishes articles on a wide range of topics related to human-machine systems, including but not limited to: system modeling and analysis, interface and interaction design, cognitive engineering, user experience and usability, adaptive and intelligent systems, and applications in automation, robotics, and control systems.
  • Peer Review Process:
    All submissions to IEEE Transactions on Human-Machine Systems undergo a rigorous peer-review process to ensure the publication of high-quality and impactful research. The journal editorial board consists of experts in various sub-disciplines of human-machine systems, ensuring comprehensive and fair reviews.
  • Innovation and Impact:
    IEEE Transactions on Human-Machine Systems highlights cutting-edge research that advances the field and has practical implications for the design and implementation of human-machine systems. By promoting interdisciplinary collaboration and innovative methodologies, the journal contributes to the improvement of human-machine interactions and system performance.
  • Global Reach and Accessibility:
    As a leading journal in the field, IEEE Transactions on Human-Machine Systems attracts contributions from researchers worldwide. Its commitment to high standards of publication and wide dissemination ensures that the latest developments and insights in human-machine systems reach a global audience of researchers, practitioners, and educators.

  • Editor-in-Chief:  Ljiljana Trajkovic

  • Scope: The journal seeks to advance the understanding of complex interactions between humans and machines, fostering the development of technologies that improve the efficiency, effectiveness, and safety of these systems. By providing a multidisciplinary forum, the journal bridges the gap between engineering, computer science, human factors, and related disciplines.
  • Human-Machine Interaction:
    Research on the design, analysis, and evaluation of interactive systems that facilitate effective and efficient human-machine collaboration.
  • Human-Centered Computing:
    Studies focused on user-centered design, usability, and the impact of technology on users, aiming to enhance the user experience and overall system performance.
  • Automation and Control:
    Innovative approaches in the automation and control of machines and systems, with an emphasis on how humans interact and collaborate with automated systems.
  • Cognitive Engineering and Decision Making:
    Exploration of cognitive processes involved in human-machine systems, including decision-making, problem-solving, and human cognitive capabilities.
  • Robotics and Intelligent Systems:
    Advances in robotics and intelligent systems that integrate human inputs and facilitate human-robot collaboration in various applications.
  • Human Factors and Ergonomics:
    Investigation into the ergonomic design of systems to improve human comfort, safety, and performance in interacting with machines.
  • Adaptive and Learning Systems:
    Development of adaptive and learning systems that can adjust to human behaviors and preferences to enhance interaction and performance.
  • Human-Machine System Modeling:
    Mathematical and computational modeling of human-machine systems to predict and optimize system behavior and performance.
  • Latest Research Topics for PhD in Machine Learning
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  • Latest Research Topics for PhD in Artificial Intelligence

  • Print ISSN:  2168-2291

    Electronic ISSN:  2168-2305

  • Abstracting and Indexing:  Science Citation Index Expanded, Scopus.

  • Imapct Factor 2024:  4.4

  • Subject Area and Category:  Computer Sciences, Health Sciences, Electronics and Telecommunications, Industrial Engineering, Mathematics

  • Publication Frequency:  Bimonthly

  • H Index:  143

  • Best Quartile:

    Q1:  Computer Networks and Communications

    Q2:  

    Q3:  

    Q4:  

  • Cite Score:  8.9

  • SNIP:  1.698

  • Journal Rank(SJR):  1.132