Machine learning
Researchers at Wenzhou Medical University, in collaboration with several institutions, have published a new study on personalized medicine, focusing on immunogenic cell death (ICD) and its impact on bladder cancer prognosis and treatment. The study, published in ACS Omega, identified 32 key ICD-risk genes (IRGs) and constructed an ICD-based prognostic
Machine learning
A new research paper has presented a novel method that integrates the Harris Hawks Optimizer (HHO) with reinforcement learning to improve the efficiency of cloud data centers. The proposed method outperforms traditional techniques in virtual machine placement by achieving up to 25% better energy efficiency, reducing resource waste by 27%
Machine learning
Researchers at the Universidad de Caldas have published a study on the use of machine learning algorithms to differentiate between cross-linked and non-cross-linked gelatin samples using Fourier transform infrared spectroscopy (FTIR). The study found that machine learning classification models developed in the Python language were effective in distinguishing between cross-linked
Machine learning
Researchers at the South China University of Technology have proposed a novel genetic algorithm, GA-ComFit, to solve the multimodal opinion maximization (mOM) problem. This problem aims to identify multiple heterogeneous well-performed seed sets for the primal OM problem, which is crucial in social network analysis. The proposed algorithm uses a
Machine learning
A new study from North Carolina State University has demonstrated the efficacy of federated learning for human factors research, providing a promising alternative to traditional centralized machine learning methods that often encounter critical data privacy issues. The research aimed to develop a privacy-preserving federated learning framework for two specific human
Machine learning
A new patent application by inventor Sato, Shogo, proposes a technology to enhance image processing using machine learning models by adapting to differences in image capturing conditions. The proposed system includes a first image acquisition unit, a second image acquisition unit, an image conversion unit, an extraction unit, and a
Machine learning
Research published by New York University (NYU) has made significant progress in the field of robotics by developing a new method for generating training data for contact-rich manipulation tasks. The study, conducted by a team of researchers, focuses on leveraging model-based planning and optimization to create demonstrations for complex tasks
Machine learning
A team of researchers at Sun Yat-sen University in Shenzhen, People's Republic of China, has developed a groundbreaking quadrotor aerial docking system that utilizes both vision and magnetic field guidance to achieve high-precision docking. The innovative system, which has been peer-reviewed and published in the IEEE Robotics and
Machine learning
Recent advances in MRI reconstruction have demonstrated remarkable success through deep learning-based models, according to research from Boston University. The study introduced Regularization by Neural Style Transfer (RNST), a novel framework that integrates a neural style transfer engine with a denoiser to enable magnetic field-transfer reconstruction. RNST generates high-field-quality images
Machine learning
Researchers from Tianjin University have designed a portable semi-active upper-limb exoskeleton to address the challenges of long-term working in fixed postures. The exoskeleton is equipped with three pneumatic-driven variable-stiffness units, including a bending actuator, a tensile actuator, and a teeth-engagement clutch. This innovative design aims to reduce muscle fatigue and
Machine learning
Climate change poses significant global challenges, requiring precise assessment and prediction to formulate effective mitigation strategies. Researchers at Rajasthan Technical University have leveraged machine learning techniques to evaluate and forecast the climatic variable rainfall in the Thar Desert, located in western Rajasthan, India. The study employed conventional Seasonal AutoRegressive Integrated
Machine learning
Researchers at Sidi Mohamed Ben Abdellah University have conducted a comprehensive study on the use of artificial intelligence in predicting depression among individuals with diabetes. According to the study, diabetes represents a significant challenge that increases the susceptibility of individuals to develop depression, emphasizing the need for effective management of
