Research shows that compliance-focused safety training alone rarely delivers lasting risk reduction, prompting calls for ...

Professionals worldwide gain standardized recognition for web development skills through assessment-based certification ...

Nam, D.T. (2026) Research on the Selection of Master’s Thesis Topics for Vietnamese Chinese Language Majors—A Case Study of Vietnam National University, Hanoi . Open Access Library Journal, 13, 1-9.

Abstract: Large pre-trained models (LPMs) provide essential technical support for downstream Artificial Intelligence (AI) tasks spawning under the intelligent evolution of wireless networks. Using ...

Abstract: To address the problem of data sparsity in recommendation systems, various studies have used knowledge graphs as auxiliary information. These studies have employed multitask learning (MTL) ...

A second major Texas university system is restricting how faculty teach — and students learn — about race and gender in campus lecture halls. The Texas Tech University System banned courses that ...

The objectives of the eventare to provide basic awareness of information and computer security for nuclearsecurity professionals, as well as basic concepts of computer securityincluding threats, risk ...

Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. In today’s column, I address how you can discover hidden best ...

Political Director and Executive Director of Politics and White House, CBS News Fin Daniel Gómez is CBS News' political director and executive director, Politics and White House. In this role, Gómez ...

As conservative Texas politicians identify and target faculty who teach about gender identity, officials at six Texas public university systems have ordered reviews of curriculum, syllabi and course ...

The inherent noisy and sparse characteristics of radar data pose challenges in finding effective representations for 3D object detection. In this paper, we propose RadarDistill, a novel knowledge ...