Machine learning
Researchers at Clemson University have conducted an in-depth review of benchmark and test functions used in global optimization algorithms and metaheuristics, highlighting the importance of selecting appropriate benchmarks for various algorithmic challenges. The study categorizes and analyzes 25 commonly used functions, proposes two new functions, and identifies gaps in current
Machine learning
AI has transformed the landscape of Non-Small Cell Lung Cancer (NSCLC) diagnosis, treatment, and management by providing more accurate diagnoses, predicting treatment responses, and guiding personalized therapeutic strategies. Recent studies showcase AI's potential in identifying genetic mutations, predicting clinical outcomes, and aiding surgical resection. AI-driven genetic profiling and
Machine learning
Researchers at the Nanjing Institute of Technology have successfully developed a hardness prediction model for high-entropy borides (HEBs) using the gradient boosting algorithm. This breakthrough has significant implications for fields such as aerospace and energy chemistry. The model achieved a high R2 of 0.876 on the test set, with
Machine learning
Researchers at [San Francisco, CA, US] have filed a patent application for a system and method for automatic data retrieval and synchronization, tackling the challenges of manually integrating numerous applications and services. The proposed solution aims to streamline data management by utilizing trained artificial intelligence (AI) models and semantic search
Machine learning
Researchers from Federal University Pernambuco have made significant advancements in predicting dilution in underground mining operations using artificial intelligence. The study highlights the importance of mitigating unplanned dilution caused by blasting inefficiencies or poor rock stability. The research team introduced a statistically rigorous methodology incorporating machine learning algorithms and genetic
Machine learning
Researchers have filed a patent application for a hybrid natural language processing system that utilizes both a large language model and a dynamic, machine learning response application to generate customized responses to natural language formatted queries. The invention aims to address the limitations of conventional large language models, which often
Machine learning
Researchers at Space Engineering University in Beijing, People's Republic of China, have developed a novel framework called Transfficformer to generate adversarial attack traffic that can evade modern Network Intrusion Detection Systems (NIDS) powered by machine learning (ML) and deep learning (DL). The framework combines a heuristic algorithm and
Machine learning
The digital transformation of manufacturing through the integration of Operational Technology (OT), Internet of Things (IoT), and Artificial Intelligence (AI) has created a complex networked sensor ecosystem, introducing critical cybersecurity vulnerabilities at IT-OT interfaces. A recent study from Feng Chia University addresses this concern by designing a machine learning-based intrusion
Machine learning
Research from Suez Canal University in Ismailia, Egypt, reveals that Artificial Intelligence (AI) is transforming healthcare by enhancing diagnostics, treatment personalization, and operational efficiency in aesthetic medicine. The study focuses on AI's role in facial analysis, robotic-assisted procedures, predictive patient outcome modeling, and personalized treatment planning. While AI
Machine learning
Researchers from Tufts University have made a significant breakthrough in robotics and automation by developing a novel method for training Neural Radiance Fields (NeRF) to produce novel LiDAR views of a scene. This innovation, which has been peer-reviewed, allows for the classification of multiple LiDAR returns, reducing the likelihood of
Machine learning
Researchers at Northwestern Polytechnic University have made significant progress in robotics and automation, developing Cluster-ALIV, a real-time dense reconstruction system for multiple Uncrewed Aerial Vehicles (UAVs). The system integrates LiDAR, Inertial Measurement Unit, and camera sensors to generate accurate and robust maps in large-scale scenarios, even with lost global positioning
Machine learning
Researchers at Lincoln, Chia-CHIA, and Xie, Qiani, have developed an innovative sensor technology for semiconductor manufacturing, aiming to improve precision and throughput in the industry. Their patent application, filed on December 1, 2023, and made available online on June 5, 2025, presents an apparatus comprising a substrate with sensors for
