Welcome to the Journal of Artificial Intelligence and Robotics, a pioneering platform at the intersection of cutting-edge research, innovation, and technological advancements in the fields of artificial intelligence (AI) and robotics.
Mission Statement: At the core of our mission is the advancement of knowledge and understanding in AI and robotics. We strive to be a leading catalyst for the exchange of ideas, insights, and breakthroughs, fostering a global community of researchers, scholars, and practitioners dedicated to pushing the boundaries of intelligent systems and robotic technologies.
Our Commitment: We are committed to promoting excellence in research and scholarly contributions. The Journal of Artificial Intelligence and Robotics serves as a reputable and peer-reviewed outlet for original research articles, reviews, and discussions that shape the landscape of AI and robotics. Our commitment extends to providing a platform for diverse perspectives and methodologies, ensuring a comprehensive and inclusive dialogue in these rapidly evolving fields.
The peer-review process for the Journal of Artificial Intelligence and Robotics (JOAIR) is designed ...
Open access (OA) encompasses a set of principles and diverse practices that facilitate the ...
The Journal of Artificial Intelligence and Robotics (JOAIR) maintains a strict policy against plagiarism.
The Journal of Artificial Intelligence and Robotics (JOAIR) is a peer-reviewed scholarly publication ...
As cities continue to grow and populations surge, ensuring easy access to essential services, including healthcare facilities, has become increasingly difficult. One of the major contributors to patient fatalities is the lack of timely access to medical care, which can severely compromise the effectiveness of treatment.
This article provides a comprehensive review of the application of Artificial Intelligence (AI) in the design and optimization of microsystem integrated circuits, particularly for robotic systems. The study covers AI-based methods for both single-field and multi-field designs.
Artificial Intelligence (AI) has become a transformative tool in medicine, improving disease prediction, its management and patient healthcare. This study employs a data driven approach to analyze the usage of AI techniques and Machine Learning (ML) models.
The indicated thermal efficiency is a core parameter that significantly affects the calculation accuracy of the fuel consumption rate in the diesel Mean Value Engine Model (MVEM). In order to improve the accuracy of the mean value engine model
This study presents a novel approach to electronically steering X-rays using Janus spheres arranged in multiple layers, each reflecting at an example 4o Bragg angle. Utilizing 11 layers of these dual-material spheres, our method aims to achieve rapid x-ray steering, significantly reducing radiation dose, particularly in early breast cancer detection, via new CTR algorithms.
University of Crete, Medical School, Andrea Kalokerinou 13, Heraklion, Crete 715 00, Greece.
Research Scientist Intelligent Fusion Technology, Inc. Germantown, MD 20874, USA.
Architecture and Engineering College, Sichuan Institute of Industrial Technology, Deyang 618500, China.
Bioresource Technology Division, School of Industrial Technology, Universiti Sains Malaysia, Penang, Malaysia.
Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy.
Department of Control Engineering, Northeastern University, Shenyang, China.
Stroke Monitoring and Diagnostic Division, AtheroPoin, Roseville, California, USA.
Department of Electrical and Systems Engineering, Washington University, USA.
