Abstract: This paper introduces the Mobile Client Interface (MCI), an Android application, that grants remote access and experimentation with the Networked Control System Laboratory (NCSLab) resources ...
Abstract: Current network analysis algorithms often rely on search methods or centrality measures but face challenges such as 1) The solution space is large, resulting in high computational complexity ...
Abstract: The recommendation algorithm based on KG can capture rich semantic and structural information and analyze user preferences more accurately, which is becoming the latest technology of ...
Abstract: This paper presents the design of an intelligent image recognition algorithm based on optical sensors and Generative Adversarial Networks (GAN). In today’s digital era, the growth of image ...
Abstract: The risk of pedestrian-involved traffic accidents represents a significant challenge to road safety and necessitates objective methods for analyzing the contributing factors. This study ...
AI is beginning to make inroads into designing and managing programmable logic, where it can be used to simplify and speed up ...
Abstract: In this paper, the problem of rapidly reconstructing the kill chain for tasks due to the frequent changes of battlefield situation in the current beyond-visual-range cooperative air combat ...
Abstract: With the increasing concerns about railway energy efficiency, researchers have developed various approaches to optimize train trajectories for energy savings. However, these methods often ...
Abstract: Urban areas serve as one of the most important scenarios in sixth generation (6G) wireless communications, necessitating comprehensive and in-depth wireless channel characteristics studies.
Inspired by the Japanese art of kirigami, an MIT team has designed a technique that could transform flat panels into medical ...
Abstract: The continuous development of artificial intelligence technology is driving the transformation of traditional cultural techniques, leading the cultural industry into the digital age.
Abstract: The latent factor analysis (LFA) model is an effective tool for extracting valuable information from high-dimensional and sparse (HiDS) matrices. However, traditional LFA usually suffers ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results