Academic Articles & Research Papers

AI-Based Environmental Color System in Achieving Sustainable Urban Development

Confronting the age of artificial intelligence, exploring art through technology has become one of the directions of interdisciplinary development. Not only does artificial intelligence technology explore sustainability on a technical level...

Colonoscopy Quality and Strategies for Improvement

Colonoscopy plays a pivotal role in colorectal cancer (CRC) screening and reduces CRC incidence and mortality. Its effectiveness depends on colonoscopist performance, which can vary. Missed lesions during colonoscopy can lead to post-colono...

On the practical aspects of machine learning based active power loss forecasting in transmission networks

Abstract The cost for covering active power losses makes a significant item in transmission system operators (TSO) annual budgets, and still it received limited attention in the existing literature. The focus of accurate power loss forecast...

Biomaterial Engineering for Spatiotemporal Regulation of Exosome Functions: From Design Principles to Key Applications in Regenerative Medicine

As natural nanoscale intercellular messengers, exosomes exhibit considerable potential in modulating inflammation, angiogenesis, immunoregulation, and tissue remodeling, making them attractive candidates for regenerative medicine. However, ...

MCoGCN-motif high-order feature-guided embedding learning framework for social link prediction

Abstract Traditional social link prediction models primarily concentrate on the adjacency features of the network, overlooking the rich high-order structural information within. Therefore, the study of effective extraction and encoding of t...

Patient information needs for transparent and trustworthy cardiovascular artificial intelligence: A qualitative study.

As health systems incorporate artificial intelligence (AI) into various aspects of patient care, there is growing interest in understanding how to ensure transparent and trustworthy implementation. However, little attention has been given t...

Evolving artificial intelligence

The majority of research in artificial intelligence has been devoted to modeling the symptoms of intelligent behavior as we observe them in ourselves. Investigation into the causative factors of intelligence have been passed over in order t...

The Promise of Artificial Intelligence

An argument that—despite dramatic advances in the field—artificial intelligence is nowhere near developing systems that are genuinely intelligent. In this provocative book, Brian Cantwell Smith argues that artificial intelligence is nowhere...

Energy expenditure during treadmill walking with a commercial plantar-vibration shoe and internal-focus attentional instructions in healthy young women: an exploratory randomized crossover study.

From Promise to Peril: generative artificial intelligence's potential to deepen educational inequalities in geographically diverse contexts

PurposeThis study critically examines how van Dijk's Digital Divide Theory applies to generative artificial intelligence (GenAI) access in regional, remote and rural (RRR) educational contexts. It interrogates whether a framework designed f...

A multi-branch network for cooperative spectrum sensing via attention-based and CNN feature fusion

Abstract In cognitive radio (CR) systems, the accurate detection of spectrum holes is a cornerstone for efficient spectrum utilization. However, the increasing complexity of CR environments, particularly those with multiple primary users (P...

REVIEW OF THEORETICAL APPROACHES TO USING OF ARTIFICIAL INTELLIGENCE FOR PLANNING PROBLEMS IN ECONOMICS

Artificial intelligence methods and technologies are increasingly included in human's everyday life. Managing actors in the context of their activities, from the planning stage to the decision-making stage, are faced with the need to operat...

Demand response potential evaluation based on feature fusion with expert knowledge and multi‐image

Abstract Potential evaluation to assist demand response decisions has garnered significant attention with the development of new power systems. However, existing data‐driven methods are challenging to properly exploit multivariate features ...

Static voltage stability margin prediction considering new energy uncertainty based on graph attention networks and long short‐term memory networks

Abstract The existing static voltage stability margin evaluation methods cannot meet the actual demand of current power grid well in terms of calculation speed and accuracy. Thus, this paper proposes a static voltage stability margin predic...

Is Math Anxiety Always Bad for Math Learning? The Role of Math Motivation

The linear relations between math anxiety and math cognition have been frequently studied. However, the relations between anxiety and performance on complex cognitive tasks have been repeatedly demonstrated to follow a curvilinear fashion. ...