Technical institutes
Research from Dalian Polytechnic University has harnessed the power of chaos theory to enhance video transmission and storage security. This groundbreaking study, published in the journal Computer Science Review, has shed light on the potential of chaotic systems in encryption design, paving the way for more secure video communication. Key
Eindhoven University of Technology
Researchers at the Eindhoven University of Technology have found that cognitive assessment games may pose challenges for individuals who rarely play video games. The study, conducted with the support of the Netherlands Organization for Scientific Research (NWO), aimed to understand whether and how these games under-serve infrequent video game players.
Technical institutes
Research conducted by investigators at Sethu Institute of Technology in Tamil Nadu, India, has led to the development of a novel optical fiber with a hollow core and metamaterial cladding formed with a chalcogenide material (Sb2Te3). This innovative design allows for the manipulation of electromagnetic responses, paving the way for
Machine learning
A recent study from the New Jersey Institute of Technology has developed a competitive bidding framework to help contractors prepare for bundled contracts in transportation infrastructure. The framework involves machine-learning models that predict the level of competition on bundled contracts based on input variables such as contract characteristics. This research
Electric cars
Research has proposed an economic dispatch strategy to optimize the economy of distribution networks (DN) with a large number of electric vehicles (EVs) connected. The strategy incorporates a data-driven uncertainty set into a two-stage robust optimization (TSRO) model to minimize planning and operational costs. The model has been tested on
Technical institutes
Researchers at Zhejiang Science Technical University in Hangzhou, China, have developed a novel approach to enhance the accuracy and efficiency of adaptive ensemble surrogate models (AESMs). The study proposes an adaptive ensemble surrogate model based on fuzzy C-means (FCM-AESM) and a parallel adaptive infilling (PAI) strategy to optimize new samplings
Technical institutes
Researchers from Tianjin University of Technology have made a significant discovery in the field of neuromorphic computing, developing a low-power memristor that can be used for energy-efficient image information sensing, processing, and protection. The memristor, which is a type of device that can store and process information, is essential for
Eindhoven University of Technology
Researchers at the Eindhoven University of Technology have found that cognitive assessment games may pose challenges for individuals who rarely play video games. The study, conducted with the support of the Netherlands Organization for Scientific Research (NWO), aimed to understand whether and how these games under-serve infrequent video game players.
Technical institutes
Researchers at the South China University of Technology have conducted a study on the interaction between arc plasma and keyhole in deep-penetration K-TIG welding, focusing on the effects of metal vapour on arc plasma characteristics. The research, funded by the National Key Research & Development Program of China and the
Technical institutes
Researchers at Zhejiang Science Technical University in Hangzhou, China, have developed a novel approach to enhance the accuracy and efficiency of adaptive ensemble surrogate models (AESMs). The study proposes an adaptive ensemble surrogate model based on fuzzy C-means (FCM-AESM) and a parallel adaptive infilling (PAI) strategy to optimize new samplings
Data mining
Researchers at Isfahan University of Technology in Iran have conducted a comprehensive study on rule extraction methods in data mining, highlighting the importance of these methods in various domains such as expert systems, decision support, and automated control. The team analyzed 19 studies selected from 678 articles collected from reputable
Machine learning
A recent study from the New Jersey Institute of Technology has developed a competitive bidding framework to help contractors prepare for bundled contracts in transportation infrastructure. The framework involves machine-learning models that predict the level of competition on bundled contracts based on input variables such as contract characteristics. This research
