Genetic research
Researchers from the Department of Electrical Engineering have published a study on the optimal sizing of hybrid renewable energy systems for auxiliary services in substations. The study, titled "Optimal Sizing of a Hybrid Renewable Energy System for Auxiliary Services in Substations Through Genetic Algorithm and Variable Neighborhood Search,"
Genetic research
Research conducted by Zhengwei Long and colleagues at Tianjin University in China has led to a significant improvement in the uniformity of air supply in airliner cockpits. The research focused on optimizing the air supply system using a hybrid optimization strategy that combined the adjoint method and genetic algorithm. This
Genetic research
Investigators at Northeast Petroleum University in Daqing, People's Republic of China, have proposed a novel intelligent classification method to improve the accuracy of reservoir evaluations in tight sandstone reservoirs. This method, called GA-XGBoost, integrates genetic algorithm optimization with extreme gradient boosting to enhance classification accuracy in small-sample scenarios.
Machine learning
A recent study conducted at Jinzhou Medical University in Jinzhou, People's Republic of China, has developed a machine learning model to predict the occurrence of kinesiophobia in postoperative lung cancer patients. Researchers found that the incidence of kinesiophobia among postoperative lung cancer patients was 43.74%, with significant
Machine learning
Research conducted in Guangdong, People's Republic of China, has found that ultrasound imaging, particularly in the intratumoral and peritumoral 2 mm regions, has significant potential for diagnosing non-massive breast cancer. A team of researchers from the Department of Ultrasonography at the Tenth Affiliated Hospital of Southern Medical University
Genetic research
Researchers from Indira Gandhi Delhi Technical University for Women have discovered that surface texture can enhance the performance of sliding bearings, with optimized dimple textures leading to remarkable improvements in load-carrying capacity and coefficient of friction. The study, published in the Proceedings of the Institution of Mechanical Engineers, Part J:
Machine learning
A recent study published in the journal Sustainable Futures has shed light on the environmental consequences of economic growth using four key dimensions: carbon dioxide emissions, freshwater availability, forest area, and biodiversity. The research, conducted by the Indian Institute of Science Education and Research (IISER) Bhopal, employed advanced machine learning
Machine learning
Researchers from Inje University, in partnership with Princess Nourah Bint Abdulrahman University, have made significant advancements in artificial intelligence by employing machine learning approaches for nuclei segmentation in pathological images. This innovative work assesses the quality of nuclei image segmentation using various methods, including K-means clustering, Random Forest, Support Vector
Machine learning
Researchers at the Agricultural Research Organization in Rishon LeZion, Israel, have made a significant breakthrough in the field of artificial intelligence. The team, led by Roni Azriel, has developed an improved methodology for characterizing task-oriented optimal manipulator configurations, which has been tested on a case study of selective spraying in
Machine learning
Research from Kingston University in London, United Kingdom, has published a study on the integration of artificial intelligence (AI) in automating the prediction and optimization of energy performance in residential buildings. The study aims to explore the potential of AI in enhancing energy efficiency, a key concern in architectural design,
Machine learning
A new research study, supported by the State Key Laboratory of Subtropical Building Science at South China University of Technology, has successfully integrated machine learning algorithms with multi-objective genetic optimization to predict and optimize the performance of high-rise office buildings in China's Hot Summer and Warm Winter (HSWW)
Genetic research
Researchers from York University have introduced a novel method for detecting and profiling smart contract vulnerabilities, leveraging an enhanced genetic algorithm and a new benchmark dataset. This approach aims to improve the security of blockchain networks by providing a more accurate and effective solution for identifying vulnerabilities. The research was
