Machine learning
A team of researchers from Tecnologico Nacional de Mexico has made a significant discovery in the field of artificial neural networks. Their study, published in the journal Nova Scientia, found that a Multi-Layer Perceptron (MLP) outperformed traditional regression models in predicting dissolved oxygen levels in water. The researchers utilized data
Machine learning
Current research in machine learning has led to the development of effective ecological security patterns in regional ecosystems. A study published in the Journal of Cleaner Production utilized machine learning algorithms, circuit theory, and the ecological protection red line method to construct an ecological security pattern in Kunming City, China.
Machine learning
Researchers from Chengdu Sport University in China have developed an SVM-based action recognition model that utilizes skeletal key point analysis with posture sensors to provide accurate sports training analysis tools. The study, published in Bmc Sports Science Medicine and Rehabilitation, employed the quaternion method to model human skeleton features, acquired
Machine learning
Researchers from Superior University in Pakistan have made significant contributions to the field of Robotics and Machine Learning by developing a new method for detecting tampered images. This technique, which utilizes edge-weighted local texture features, has achieved an accuracy of up to 98.49% on the CASIA v1.0 dataset,
Machine learning
Researchers at the Department of Electrical and Communication Engineering have developed a novel image denoising model, combining Improved Convolutional Neural Network (ICNN) with the Self-Improved Orca Predation Algorithm (SI-OPA), to overcome noise distortions in medical images. The proposed model demonstrates superior noise suppression, achieving 94% accuracy, 0.91 Structural Similarity
Machine learning
Research in China has made significant advancements in crop breeding with the introduction of the Breeding 5.0 framework, leveraging artificial intelligence (AI) and robotics to improve crop yields and resilience to environmental challenges. Investigators have developed a new system that decodes the architecture and interactions of germplasm, enabling predictive
Machine learning
A team of researchers at the University of Padua has proposed a novel approach to estimate human pose in real-time, even in the presence of occlusions, which is crucial for facilitating advanced Human-Robot Collaboration (HRC) applications. The approach combines information from RGB-D cameras and inertial measurement units, leveraging a multimodal
Machine learning
A recent study published in Frontiers in Pharmacology has found that Quinoline Yellow, a synthetic dye commonly used as an additive in food products, poses significant health risks to humans. Researchers from the Medical University of Warsaw used a combination of computational and in vivo models to investigate the toxic
Machine learning
Artificial neural networks have emerged as a promising solution for predicting midterm electrical load demands. According to a recent study from Sulaimani Polytechnic University, researchers utilized a medium-term load forecasting model based on artificial neural networks (ANNs) to predict the electrical demand for Duhok city up to the year 2025.
Machine learning
Researchers have made significant strides in underwater autonomous capture operations, presenting a comprehensive solution for cross-domain object detection and autonomous capture. This innovation offers substantial potential for reducing labor and health risks in sea organism industries. Funded by the National Natural Science Foundation of China and the National Key Research
Machine learning
A breakthrough device for positioning and holding optical elements has been patented by Carl Zeiss SMT GmbH, a leading technology company. The innovative device, designed for use in semiconductor lithography and measurement, aims to improve the positioning and alignment of optical elements while minimizing wear and contamination. The patent, filed
Machine learning
A recent study proposes a new method for predicting sentence severity in traffic accident cases using large language models (LLMs) in the Korean legal system. The researchers from Soonchunhyang University have developed a traffic accident criminal sentencing prediction method based on LLMs, called TRACS-LLM, which analyzes legal texts related to
