Machine learning
A team of researchers from Institut Teknologi Sepuluh Nopember in Surabaya, Indonesia, has made significant advancements in optimizing the performance of Franklin microstrip antennas using machine learning techniques. The study focused on enhancing the antenna's bandwidth and gain for 5G technology applications. By leveraging machine learning methods, including
Machine learning
Researchers from Peking University recently conducted a network meta-analysis to compare the performance of various machine learning algorithms in predicting surgical site infections (SSI). The study, published in the journal Computers in Biology and Medicine, aimed to identify the best-performing algorithm for building SSI predictive models. The researchers found that
Machine learning
A new study has successfully developed an interpretable machine-learning approach that accurately predicts lithium-ion battery discharge capacity under variable operating conditions using minimal input descriptors. Funded by the Interdisciplinary Research Center for Construction & Building Materials (IRC-CBM), King Fahd University of Petroleum & Minerals, the research used three nature-inspired hybrid
Machine learning
New research conducted by the Pohang University of Science and Technology (POSTECH) has led to the development of an innovative autonomous robot designed to enhance hospital disinfection through targeted wiping and ultraviolet-C (UV-C) irradiation methods. The urgency for such advancements has been underscored by the COVID-19 pandemic, which revealed challenges
Machine learning
Researchers from the National University of Singapore have developed a compliant body weight support system powered by a series elastic actuator, enabling accurate and robust unloading force rendering for gait training. This innovative system addresses the limitations of previous methods, including post-SEA disturbances and intrinsic oscillatory modes. The proposed control
Machine learning
Researchers at the University of Haifa have developed a new framework, MoRPINet, that uses a neural network to improve the navigation solution of mobile robots in real-world scenarios. The MoRPINet framework was evaluated using a dataset of 290 minutes of inertial recordings during field experiments and showed an improvement of
Machine learning
A team of researchers at the Harbin Institute of Technology has introduced a new algorithm, CBTMP, designed to enhance the operational efficiency of intelligent warehouses by solving cooperative multi-agent path finding in heterogeneous environments. Funded by the Shenzhen Fundamental Research Program and the National Natural Science Foundation of China (NSFC)
Machine learning
Researchers at Mzumbe University in Morogoro, Tanzania, have proposed a machine learning algorithm to quantify the magnitude of academic misconduct among undergraduate students. According to the study, over 80% of students engage in the practice of academic misconduct, posing a significant risk to the quality of graduates. The proposed algorithm,
Machine learning
Artificial intelligence and machine learning have the potential to revolutionize sustainable agriculture by enabling real-time evaluations of crop output and health. Researchers at King Faisal University in Al Ahsa, Saudi Arabia, have employed a transfer learning approach to estimate above-ground biomass (AGB) in pearl millet using pre-trained convolutional neural networks
Machine learning
Dyna.Ai, a leading player in AI-as-a-Service (AIaaS), officially launched its operations in Nigeria on May 15, 2025, with a exclusive event themed 'AI Unleashed: Revolutionising Nigeria's Financial Future.' The launch brought together key stakeholders from Nigeria's AI, financial, fintech, telecom, and other sectors,
Machine learning
Researchers from Anhui Polytechnic University have found that the integration of virtual reality (VR) technology with machine translation (MT) enhances English language teaching, achieving a translation accuracy of 98.5%, an F1 score of 93%, and a semantic information recall rate of 92%. This innovative approach provides a more immersive
Machine learning
Researchers at the Indian Institute of Technology Bombay have made a breakthrough in the development of low-valent transition metal catalysts for nitrogen reduction reactions, a key step in sustainable ammonia production. By integrating quantum chemistry, molecular dynamics, and machine learning, the team uncovered mechanistic features governing nitrogen reduction reaction activity
