Journals

  • EUSIVOR Advanced Engineering

    EUSIVOR Advanced Engineering is a premier, peer-reviewed international journal dedicated to the rapid dissemination of high-impact research across the vast landscape of modern engineering. As the flagship multidisciplinary publication of the EUSIVOR portfolio, the journal serves as a vital bridge between traditional engineering disciplines and the emerging frontiers of technological innovation.

    Aims and Scope

    The journal provides an elite platform for scientists, researchers, and professional engineers to share breakthroughs that address complex, real-world challenges. We prioritize "Advanced" engineering—research that integrates multiple fields to create smarter, more efficient, and sustainable solutions.

    Key areas of focus include, but are not limited to:

    • Integrated Systems: Mechatronics, robotics, and automated control systems.

    • Infrastructure & Sustainability: Smart cities, civil engineering innovations, and renewable energy systems.

    • Materials & Mechanics: Advanced structural materials, biomechanics, and computational fluid dynamics.

    • Cross-Disciplinary Innovation: Bio-medical engineering, nanotechnology, and the intersection of data science with physical engineering.

  • EUSIVOR Artificial Intelligence Systems

    EUSIVOR Artificial Intelligence Systems 

    EUSIVOR Artificial Intelligence Systems is a high-impact, peer-reviewed journal focused on the intersection of computational intelligence and physical implementation. While many journals focus solely on abstract algorithms, EAIS is dedicated to the systems—the architectural, industrial, and practical frameworks that allow AI to function in the real world.

    Aims and Scope

    The journal provides a premier platform for researchers and practitioners to explore the full lifecycle of intelligent systems. We emphasize the transition of AI from "code" to "complex system," focusing on reliability, scalability, and hardware integration.

    Core research areas include:

    • Industrial AI & Automation: Deep learning and neural networks applied to manufacturing, predictive maintenance, and supply chain optimization.

    • Autonomous & Embedded Systems: Edge computing, robotics, and the integration of AI into physical hardware and sensor networks.

    • Intelligent Logic & Decision Frameworks: Advances in SWOT analysis automation, marketing mix optimization, and strategic business intelligence.

    • Data Systems & Analytics: Systematic analysis of industrial data, sector distributions, and unit price growth trends using machine learning.

    • Human-AI Interaction: The ethics, safety, and interface design of systems that collaborate with human operators.

  • EUSIVOR Digital Welding and Additive Manufacturing

    Aims and Scope

    EUSIVOR Digital Welding and Additive Manufacturing

    Aim
    EUSIVOR Digital Welding and Additive Manufacturing is an international peer-reviewed journal dedicated to advancing innovative research, emerging technologies, and industrial applications in the fields of welding science, digital manufacturing, additive manufacturing, and intelligent production systems. The journal aims to provide a global platform for researchers, engineers, academicians, and industry professionals to publish high-quality original research, reviews, technical communications, and case studies that contribute to the development of next-generation manufacturing technologies.

    The journal promotes interdisciplinary research integrating advanced welding processes, automation, artificial intelligence, robotics, data-driven manufacturing, materials engineering, and smart production technologies for sustainable and high-performance manufacturing industries.

    Scope

    The journal welcomes theoretical, experimental, computational, and industrial studies in, but not limited to, the following areas:

    Digital Welding Technologies

    Additive Manufacturing

    Materials and Metallurgy

    Artificial Intelligence and Data Analytics

    Manufacturing and Industrial Applications

    Computational and Numerical Methods

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  • Eusivor Semiconductor Frontiers

    Eusivor Semiconductor Frontiers (ESF) is an international peer-reviewed journal dedicated to publishing cutting-edge research and technological advancements in semiconductor science, engineering, manufacturing, and emerging electronic systems. The journal serves as a global platform for researchers, industry experts, and technology innovators working on next-generation semiconductor materials, devices, fabrication processes, intelligent manufacturing, and advanced electronic applications.

    ESF focuses on both fundamental and applied research covering semiconductor materials, nanoelectronics, integrated circuits, power electronics, photonics, semiconductor packaging, reliability engineering, and smart manufacturing technologies. The journal particularly encourages interdisciplinary studies integrating artificial intelligence, machine learning, automation, robotics, digital manufacturing, and data-driven process optimization within semiconductor industries.

    The journal welcomes contributions related to advanced semiconductor technologies for applications in artificial intelligence hardware, electric vehicles, renewable energy systems, communication technologies, aerospace, biomedical electronics, quantum computing, and sustainable manufacturing.

    By bridging academia and industry, ESF aims to accelerate innovation, support industrial transformation, and promote high-impact research that shapes the future of semiconductor and intelligent electronic technologies worldwide.

    Topics Covered Include

    • Semiconductor materials and devices
    • Nanoelectronics and microelectronics
    • Semiconductor manufacturing and processing
    • AI-driven semiconductor technologies
    • Advanced packaging and chiplet integration
    • Semiconductor reliability and failure analysis
    • Power electronics and energy semiconductors
    • Photonics and optoelectronics
    • Flexible and wearable electronics
    • Quantum semiconductor technologies
    • Smart factories and Industry 4.0
    • Semiconductor automation and robotics
    • Semiconductor applications in EVs and renewable energy
    • Sustainable semiconductor manufacturing
    • Machine learning and data analytics in semiconductor industries