Machine learning
Research conducted by the Huazhong University of Science and Technology has led to the development of a new method for addressing the issue of LiDAR scan distortions caused by high-speed ground robots moving on unstructured terrains. The study, published in IEEE Robotics and Automation Letters, introduces post-undistortion uncertainty to improve
Machine learning
Researchers at Hengshui University have made significant findings in the field of artificial intelligence, proposing a deep learning-based algorithm to improve creative efficiency and precision in image processing for visual communication design. The algorithm, designed to optimize image processing workflows, has demonstrated excellent scalability, robust support for personalized design, and
Machine learning
Researchers from Nanjing University in China have developed an artificial intelligence (AI) model that can diagnose acute coronary syndrome (ACS) and predict future risk within defined timeframes. The study, published in eClinicalMedicine, used a multicentre cohort study in China between January 2012 and December 2021 to develop and validate the
Machine learning
Researchers at Zhengzhou University of Light Industry in China have developed a new algorithm that improves the efficiency and quality of video streaming. Driven by the growth of digital video traffic, users demand high-quality video experiences, which necessitates the optimization of video transmission performance. The new algorithm, called PLL-ABR, utilizes
Machine learning
Researchers from Central University of Jammu have developed a novel hybrid ensemble framework that leverages particle swarm optimization (PSO) to enhance intrusion detection capabilities. The framework, designed to tackle the increasing complexity of cyber threats, combines machine learning models, including Decision Trees, Artificial Neural Networks, and Random Forests, to achieve
Machine learning
Researchers at Taiyuan University of Technology have developed a fusion model that combines mechanism-based and machine learning methods to predict NOx emission concentration in CFB units with high accuracy. The model uses a one-dimensional semi-empirical model to simulate hydrodynamics, combustion, and NOx generation in the furnace, and a gated recurrent
Machine learning
A recent study published in the journal Discover Artificial Intelligence has presented a novel approach to improving the comfort and wearability of clothing through the use of fuzzy logic-based optimization. Researchers from the Jingzhou Institute of Technology have developed a smart clothing comfort evaluation and adjustment system that can dynamically
Machine learning
Accurate duration estimation is crucial for construction projects to maintain efficiency and quality control during early phases. However, traditional methodologies suffer due to limited data available in initial project planning stages. Researchers at the University of Jordan have proposed an innovative approach using artificial neural networks (ANNs) to address these
Machine learning
A new study from Tehran, Iran, has unveiled a significant breakthrough in predicting COVID-19 severity in pediatric patients. The research, conducted by a team from the Tehran University of Medical Sciences, employed machine learning algorithms to analyze the clinical characteristics of 588 pediatric patients with confirmed COVID-19. The findings suggest
Machine learning
Researchers in Algeria have made significant strides in using machine learning and deep learning algorithms to improve the diagnosis and prognosis of glioblastoma, a highly malignant primary brain cancer. Traditional diagnosis and prognosis are often subjective and time-consuming, whereas advances in machine learning and deep learning have accelerated research by
Machine learning
Researchers from the University of Basilicata have made a groundbreaking discovery in understanding the relationship between environmental factors and cardiorespiratory diseases. By applying machine learning techniques to a dataset of environmental and health data from 2013 to 2023, the team was able to identify specific environmental variables that contribute to
Machine learning
Researchers at the University of Information Technology and Communications have made significant breakthroughs in developing machine learning models for real-time robotic hand control systems based on motor imagery brain signals. According to a recent study published in Computers in Biology and Medicine, the team developed and tested a set of
