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 Artif. Intell. Syst.)

    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

    The journal provides a platform for the integration of digital tools, simulation, and real-time monitoring within the fields of welding and additive manufacturing. We prioritize research that enhances the precision, predictability, and scalability of fabrication processes through digital innovation.

    Core research areas include:

    • Digital Twins & Simulation: Virtual modeling of weld pools, thermal stresses, and microstructural evolution during additive processes.

    • Process Monitoring & Control: High-speed sensing, computer vision for defect detection, and closed-loop control systems.

    • Data-Driven Fabrication: The use of big data and machine learning to optimize parameters for metal 3D printing and robotic welding.

    • Hybrid Manufacturing: Integration of subtractive and additive digital workflows into a single automated system.

    • Cyber-Physical Systems: Secure, networked manufacturing environments and the implementation of "Industry 4.0" in the workshop.