Machine learning
Research investigators have made a significant advancement in the field of machine learning by developing a fractal Langmuir adsorption model that accurately characterizes CH4 and CO2 adsorption in real shale. This breakthrough has far-reaching implications for CH4 enhanced recovery and CO2 geological sequestration. The study's findings were published
Machine learning
Researchers at the University of Notre Dame have made a groundbreaking discovery in the field of materials research, using machine learning to accelerate the discovery of new materials. The study, published in Communications Materials, highlights the importance of selecting the most informative training data from large databases, a challenge that
Artificial intelligence
A comprehensive study by the Premiere Research Institute has critically assessed existing theories, conceptual models, and frameworks to explain the acceptance and resistance of artificial intelligence (AI) among medical doctors. The research, backed by the National Science And Technology Council, aimed to evaluate the capacity of various paradigms to explain
Artificial intelligence
A comprehensive study by the Premiere Research Institute has critically assessed existing theories, conceptual models, and frameworks to explain the acceptance and resistance of artificial intelligence (AI) among medical doctors. The research, backed by the National Science And Technology Council, aimed to evaluate the capacity of various paradigms to explain
Artificial intelligence
Medical school admissions committees rely on personal statements to evaluate applicants' values, motivations, and experiences. However, with the rise of artificial intelligence (AI), a new study suggests that AI-generated personal statements may become a concern for maintaining credibility in medical school admissions. Researchers from Nemours Children's Hospital
Artificial intelligence
Research conducted by Amrita Vishwa Vidyapeetham has led to the development of a new hybrid generative adversarial network called ProWGAN, which simplifies image production for video games, virtual reality, and motion pictures. This model combines ProGAN and WGAN approaches to automate landscape synthesis, reducing manual work, lowering production time, and
Cable News Network
Researchers at the University of Tabriz have made a significant breakthrough in the field of artificial intelligence, developing a new approach for automatic text summarization. The team, led by Mohammad Reza Feizi Derakhshi, has been working on a method that can effectively extract key points from large volumes of text
Algorithms
A new machine learning algorithm has been developed to tackle the critical step of feature selection in high-dimensional data sets. According to research from Yarmouk University, the Binary Improved Artificial Rabbit Optimization (BIARO) algorithm offers a novel approach to solving the feature selection problem in a reasonable time. BIARO improves
Inventory control
Researchers at Wuhan University of Technology have developed a novel approach to optimize inventory replenishment and routing problems in Vendor Managed Inventory (VMI) mode. The study, published in the Management System Engineering journal, proposes an enhanced Multi-Task Proximal Policy Optimization (MTPPO) with deep reinforcement learning to refine inventory replenishment strategies
Karlstad University
Researchers at Karlstad University have published a new study on machine learning, proposing a framework that enables efficient energy use in Narrowband Internet of Things (NB-IoT) devices. The deployment of Cellular Internet of Things (CIoT) is expected to reach over six billion devices by 2030, with many located in remote
Machine learning
Researchers at the University of Houston have published a groundbreaking study on the use of machine learning to accelerate the discovery of near-infrared (NIR) phosphors. The study, published in the journal Chemistry of Materials, demonstrates a machine-learned regression model that can predict the Dq/B ratio of Cr3+-based NIR
Disinformation
Researchers from Yeungnam University have made significant strides in identifying and mitigating the spread of disinformation, a phenomenon that distorts public perception and influences sociopolitical events. The study introduces a multi-view learning framework that achieves high precision by integrating diverse feature perspectives, including TF-IDF, word pairs, and readability scores. The
