Machine learning
Researchers from the City College of New York have proposed an innovative framework for enhancing the accuracy and resilience of vehicle classification systems using LiDAR sensors. The framework integrates inductive loop sensors and LiDAR technology to address the limitations of legacy signature-based models, which may become obsolete with the introduction
Machine learning
Research from Melbourne, Australia, explores the use of the AI language model, ChatGPT, in providing parenting guidance for managing attention-deficit hyperactivity disorder (ADHD) in children. The study, published in the Child and Adolescent Mental Health journal, assessed the model's ability to provide actionable behavioral strategies and clinical relevance
Machine learning
Researchers from the Birla Institute of Technology and Science in Hyderabad, India, have employed machine learning techniques to predict power loss in vanadium redox flow batteries (VRFBs). This breakthrough could greatly enhance the efficiency and scalability of VRFBs, a crucial technology for the transition to renewable energy. The study demonstrates
Machine learning
Researchers from Sandip University have developed a new control framework that utilizes machine learning predictions and automata-based decision rules to enhance the reliability and efficiency of space-based solar power (SBSP) systems. The SBSP system collects solar energy on orbiting platforms and transmits it to Earth, but it faces challenges such
Machine learning
The AI in aviation market is expected to reach USD 4.86bn by 2030, growing at a compound annual growth rate (CAGR) of 22.6% from USD 1.75bn in 2025. This rapid growth is driven by advancements in machine learning, computer vision, sensor fusion, and natural language processing technologies.
Machine learning
The AI in aviation market is rapidly growing, driven by advancements in machine learning, computer vision, sensor fusion, and natural language processing technologies. The market is expected to reach $4.86 billion by 2030, from $1.75 billion in 2025, with a compound annual growth rate (CAGR) of 22.6%
Machine learning
Research conducted by University Paris-Dauphine has explored the application of physics-informed graph neural networks (PIGNN) in predicting attack paths within complex infrastructure systems. The study aimed to address the limitations of existing methods, such as machine learning (ML), which struggle to predict full attack paths due to inadequate datasets and
Machine learning
Professor Tamas Kiss, a renowned expert in distributed computing, recently attended the European Security Research Event in Warsaw, Poland, to present his project, Harpocrates, to Commissioner Magnus Brunner of the European Union's Internal Affairs and Migration. The Harpocrates project, funded by the European Commission and UK Research and
Machine learning
Researchers at Tashkent State University of Economics have investigated the potential of Julian Jaynes' bicameral mind theory in enhancing reinforcement learning (RL) algorithms and large language models (LLMs) for artificial intelligence (AI) systems. According to a study published in the journal Computers, the researchers drew parallels between the dual-process
Machine learning
A recent study published in JAMA Network Open demonstrates the superior reproducibility and prognostic associations of an artificial intelligence (AI) algorithm in quantifying tumor-infiltrating lymphocytes (TIL) in melanoma patients compared to traditional pathologist-read methods. The study, led by Thazin N. Aung, Ph.D., from Yale University School of Medicine, analyzed
Machine learning
Research has shown that both biotic and abiotic stresses pose significant threats to crop plant growth and productivity, including maize worldwide. Identifying genes and associated networks underlying stress resistance responses in maize is crucial for developing stress-resistant varieties. A recent study from Louisiana State University employed a meta-transcriptome approach to
Machine learning
Scientists at the National Research Council Italy (CNR) have made a groundbreaking discovery in the field of artificial intelligence. By developing a machine learning-based algorithm called CIAO, they have significantly improved the accuracy of satellite-derived Chlorophyll-a estimates in the Arctic Ocean. The research, published in the journal Science of Remote
