The widespread use of earbuds among young adults presents public health concerns, including noise-induced hearing loss (NIHL), tinnitus, ear infections, and accidents due to reduced environmental awareness. This study assessed the knowledge, perceptions, and risk behaviours related to earbud use among undergraduates at...
Habeeb Omoponle Adewuyi, Oluwafemi Isaac Dipeolu· Journal of Research Innovati...· 0 citations
Observation is a fundamental scientific practice in science learning, particularly for understanding gradual biological phenomena such as plant adaptation. Despite the increasing integration of artificial intelligence (AI) in education, limited research has examined how AI-supported tools influence students' observatio...
Widi Purwianingsih, Pipih Nurhayati, Ari Widodo et al.· Social Sciences & Humanities...· 0 citations
Abstract Background Atrial cardiomyopathy (AtCM) is increasingly recognised as an underlying atrial substrate contributing to atrial fibrillation (AF), heart failure (HF), and cardio-embolic stroke. However, diagnostic criteria, disease thresholds, and targeted treatment strategies remain poorly defined. Objective To d...
Nick L. van Vreeswijk, Zarina Habibi, Sander van Doorn et al.· Netherlands Heart Journal· 1 citation
Abstract Wearable sensing and artificial intelligence (AI) are increasingly being used to quantify athlete movement, physiological response, training load, and recovery in field and laboratory settings. However, the practical value of these systems depends not only on the predictive capability of an algorithm but also...
nbspDr. Vikas Kundu· 0 citations
Reach audiences
Advertise in front of researchers, engineers, and readers.
Learning ObjectivesAfter studying this chapter, readers will be able to: Understand the concept of Artificial Intelligence. Explain the importance of AI security. Identify security risks associated with AI systems. Describe the AI security lifecycle. Recognize common AI attacks with real-world examples. Overview...
Dr. Vimala Roselin J, Dr.D.Priyadharsini, R. Manikandan et al.· 0 citations
This paper investigates the connection between SME and contextual bandits by focusing on linear contextual bandits as a starting point, and proposes an SME-based OFU algorithm and establishes a sublinear regret bound under proper assumptions.
Boltzmann margin is applied to the analysis of kNN classifiers and establish the first near-exponential convergence rates for kNN classification, which is also the first near-exponential convergence rates for kNN classification.
Probabilistic forecasts provide a principled representation of forecast uncertainty through predictive distributions. Directly propagating predictive distributions with conventional physical models requires solving distributional evolution equations, a task well-known to be computationally prohibitive for high-dimensio...
Tianlin Yang, Hailiang Du, Louis Aslett· 0 citations
The distance from calibration, introduced by B{\l}asiok, Gopalan, Hu, and Nakkiran (STOC 2023), has recently emerged as a central measure of miscalibration for probabilistic predictors. We study the fundamental problems of computing and estimating this quantity, given either an exact description of the data distributio...
When solving PDEs, classical numerical solvers are often computationally expensive, while machine learning methods can suffer from spectral bias, failing to capture high-frequency components. Designing an optimal hybrid iterative solver--where, at each iteration, a solver is selected from an ensemble of solvers to leve...
Stochastic gradient descent (SGD), one of the most fundamental optimization algorithms in machine learning (ML), can be recast through a continuous-time approximation as a Fokker-Planck equation for Langevin dynamics, a viewpoint that has motivated many theoretical studies. Within this framework, we study the relations...
Causal identification asks whether a causal target can be recovered from the observational distribution in an idealized infinite-data setting. In practice, only finite samples are available, and identifiability alone does not determine how much data are needed for reliable estimation. We introduce Probably Approximatel...
Is your company’s AI sovereign? A practical guide for CIOs on AI vendor lock-in, EU Data Act switching, cloud sovereignty, and testing your exit plan before you need it. The post Sovereignty Is the Option to Leave appeared first on GPT-Lab.
