Machine learning
Researchers at Arni University have made a significant contribution to the field of artificial intelligence by developing a novel approach to network intrusion detection using machine learning and meta-modeling. The study, published in the Journal of Mechanics of Continua and Mathematical Sciences, aims to enhance the accuracy and reliability of
Machine learning
Research at Universitas Bina Darma in Indonesia aims to develop a translation machine for the Besemah language, which is spoken by a tribe in South Sumatra Province. The study utilizes machine learning and neural networks to create a model that can translate the Besemah language into Indonesian and vice versa.
Machine learning
Researchers at the Karlsruhe Institute of Technology (KIT) have developed neural network models that can predict the biological activity of complex molecules using molecular dynamics data. According to the study, these models can accurately predict the cytotoxic activity of similar peptide analogs and reliably distinguish between the photoisomers of the
Machine learning
Scientists at Konya Technical University in Konya, Turkey have made a breakthrough in using artificial neural networks to optimize adsorption processes for wastewater treatment. The research, which focused on activated olive stone (AOS) as an eco-friendly adsorbent, demonstrated a 93% removal efficiency of Methylene Blue (MB) dye from aqueous solutions.
Artificial intelligence
A new research report from Stockholm, Sweden, by KTH Royal Institute of Technology, has made significant advancements in sensor research, specifically focusing on protecting neural networks from soft errors. The study, funded by Kth Royal Institute of Technology with The Industrial Research Project Adinsos, employed a Reinforcement-Learning-based approach to address
Artificial intelligence
Researchers at the University of Wisconsin have made significant strides in understanding the interactions between neurochemicals and neuroreceptors, which could lead to the development of more targeted and effective antidepressants. By utilizing a graph convolutional neural network fingerprint-enabled artificial neural network (GCN-ANN), the study has provided physical insights into the
Artificial intelligence
Researchers from the Beijing University of Technology have made a breakthrough in addressing the challenge of supporting efficient deep neural network (DNN) inference on mobile devices. With the rapid advancement of artificial intelligence applications, DNNs are increasingly being deployed on mobile devices, which have limited computational capabilities and small battery
Artificial intelligence
Researchers from the Research Institute for Development have made a groundbreaking discovery in the field of morphotectonics, harnessing the power of deep learning to automatically characterize fault markers. By utilizing a Bayesian supervised machine learning method and one-dimensional convolutional neural networks (CNN), the team developed a proof-of-concept study, dubbed ScarpLearn,
Machine learning
Researchers at Tsinghua University have developed advanced models to predict steady-state trough concentrations in pediatric patients with epilepsy, providing improved dosing recommendations for valproic acid therapy. This study, published in the European Journal of Clinical Pharmacology, employed population pharmacokinetics, maximum a posteriori Bayesian, and machine learning methods, including neural networks,
Machine learning
Researchers from Universidad Industrial de Santander in Colombia have developed a robust machine learning model based on artificial neural networks to classify six flow patterns in oil-water two-phase flow within horizontal pipelines. This innovation provides significant value for improving pipeline design, optimizing flow assurance strategies, enhancing corrosion control, and supporting
Machine learning
The global Tensor Processing Unit (TPU) Market is experiencing substantial growth, driven by the increasing demands of artificial intelligence (AI) and machine learning (ML) workloads. TPUs are specialized application-specific integrated circuits (ASICs) engineered to accelerate tensor operations, making them ideal for deep learning across industries such as healthcare, finance, automotive,
Machine learning
Research by King Abdullah University of Science and Technology has revealed that Deep Neural Networks (DNNs) exhibit superior performance in solving complex problems such as computer vision and natural language processing compared to classic machine learning techniques. The study, which focuses on Convolutional Neural Networks (CNNs) as an example of
