Machine learning
A recent study from Shandong University has introduced a novel hybrid decision-making model that incorporates the weighted aggregated sum product assessment (WASPAS) technique into the q-rung linear Diophantine fuzzy set (q-RLDFS) framework to select the most suitable artificial intelligence (AI) algorithms in uncertain and vague environments. The primary objective is
Machine learning
Researchers at Abdullah Gul University have made significant progress in using artificial intelligence and machine learning to predict fracture toughness in human bones. The study used Raman spectroscopy and machine learning algorithms to analyze ex vivo human femoral cortical bone specimens, providing a new approach to bone research. The findings
Artificial intelligence
A team of researchers from Ohio State University has published a study on the external validation of a winning artificial intelligence (AI) algorithm from the RSNA 2022 Cervical Spine Fracture Detection Challenge. The study, published in the American Journal of Neuroradiology, aimed to assess the feasibility of using AI algorithms
Artificial intelligence
Synthetic data generation is a rapidly evolving field, with the potential to significantly improve data privacy. However, evaluating the performance of synthetic data generation methods, particularly the trade-off between fairness and utility of the generated data, remains a challenge. Researchers at the German Research Center for Artificial Intelligence (DFKI) have
Machine learning
Researchers at Imam Mohammad Ibn Saud Islamic University have successfully employed machine learning algorithms to develop advanced predictive frameworks for predicting hydrogen solubility in aqueous environments. According to the study, the sophisticated modeling required to decipher complex parameter interactions identified key factors influencing hydrogen solubility dynamics, including temperature, pressure, and
Machine learning
Researchers at Tongji University have developed a high-precision robotic arm motion control algorithm, which has potential applications in pyrotechnic grain assembly and engineering. The algorithm, known as the multi-strategy enhanced secretary bird optimization algorithm (ISBOA), reformulates the inverse kinematics problem as a constrained optimization problem and employs a multi-strategy improved
Artificial intelligence
Researchers from the University of Padova have made significant progress in developing an artificial intelligence (AI)-based algorithm for predicting cardio-cerebrovascular complications in patients with type 2 diabetes mellitus (T2D). The study analyzed medical records of 532 T2D patients from the Diabetology Unit in Padova, Italy, using the Metaclinic AI
Machine learning
A significant threat to the stability of IoT-enabled infrastructures is emerging due to the rapid expansion of IoT ecosystems, particularly in energy hub (EH) networks. Researchers at the Faculty of Engineering Technology have developed a new AI-powered DDoS detection system, using machine learning models and hybrid ensemble techniques tailored for
Genetic research
Researchers at Szechenyi Istvan University in Gyor, Hungary, have made a groundbreaking discovery in artificial intelligence, presenting a novel approach to sign language recognition that overcomes significant challenges in recognizing diverse signing patterns, hand shapes, and movement patterns among users. The study proposes an adaptive SLR framework that integrates Markov
Machine learning
Researchers from the Korea Institute of Materials Science have proposed a novel approach to design biodegradable Mg-Zn-Mn-Sr-Ca (ZMJX) alloys for load-bearing orthopedic implants. By utilizing interpretable machine learning and a multi-objective genetic algorithm, the team aimed to optimize the composition of the alloys to achieve both mechanical strength and biologically
Genetic research
Researchers from the University of Science and Technology of China have developed a genetic algorithm-based energy management strategy for fuel cell hybrid electric vehicles. This strategy, designed to minimize the overall operating cost of the system, involves establishing dynamic and static models of the hydrogen-electric hybrid vehicle, as well as
Machine learning
Researchers at the University of Petra have developed a novel optimization framework called Quantum Epigenetic Algorithm (QEA), which combines quantum-inspired probabilistic representation with biologically motivated epigenetic gene regulation to perform efficient and adaptive feature selection. The QEA was evaluated across four benchmark datasets and consistently outperformed baseline methods, achieving the
