Academic Articles & Research Papers

Prototype-oriented contrastive mean-teacher for unsupervised domain adaptive object detection

Abstract Unsupervised domain adaptive object detection (UDA-OD) aims to deploy a detector trained on source domain(s) to a new, unlabeled target domain. Carrying out mean-teacher self-training for UDA-OD poses a significant challenge, given...

AI-Driven Identification of Critical Dependencies in US-China Technology Supply Chains: Implications for Economic Security Policy

This research examines the critical dependencies within US-China technology supply chains through advanced artificial intelligence methodologies, addressing significant economic security implications in an era of strategic competition. The ...

Application Research of Microstructured Flexible Sensors in Rehabilitative Wearable Sensing

ABSTRACT Flexible sensors enable the continuous, real‐time monitoring of the physiological and movement signals of patients, providing data support for precise rehabilitation strategies and playing a crucial role in rehabilitation medicine....

Evaluating new technology for biodiversity monitoring: Are drone surveys biased?

Abstract Drones and machine learning‐based automated detection methods are being used by ecologists to conduct wildlife surveys with increasing frequency. When traditional survey methods have been evaluated, a range of factors have been fou...

A multi-organization epigenetic age prediction based on a channel attention perceptron networks

DNA methylation indicates the individual’s aging, so-called Epigenetic clocks, which will improve the research and diagnosis of aging diseases by investigating the correlation between methylation loci and human aging. Although this discover...

Precision Periodontics: Reimagining Periodontal Care through Precision Diagnostics and Targeted Therapies

Periodontitis is a chronic inflammatory disease that affects the tissues supporting teeth and represents a significant global health issue. Traditional diagnostic and treatment methods often use a broad approach and fall short due to the co...

Mapping artificial intelligence research in higher education toward sustainable development

Abstract The rapid development of Artificial Intelligence (AI) has had a profound impact on higher education (HE), fundamentally changing teaching, learning, research and academic management. Although there have been many studies on the app...

Innovation and Design in the Age of Artificial Intelligence

At the heart of any innovation process lies a fundamental practice: the way people create ideas and solve problems. This “decision making” side of innovation is what scholars and practitioners refer to as “design.” Decisions in innovation p...

Traditional Chinese Medicine Enhances Survival in Cancer Patients on Immunotherapy or Chemotherapy.

AI-driven data fusion modeling for enhanced prediction of mixed-mode I/III fracture toughness

This research evaluates the use of artificial intelligence to enhance the accuracy of predictions for mixed-mode I/III fracture toughness in polymethyl methacrylate . Traditionally, assessing fracture toughness relies heavily on destructive...

A physics-informed spatiotemporal graph neural network for photovoltaic power forecasting and micro-anomaly localization

Accurate power forecasting and precise fault diagnosis are critical for the reliable operation of large-scale photovoltaic systems. However, existing data-driven models often fail to capture complex spatiotemporal dependencies and lack phys...

Artificial intelligence and the future of global health

Concurrent advances in information technology infrastructure and mobile computing power in many low and middle-income countries (LMICs) have raised hopes that artificial intelligence (AI) might help to address challenges unique to the field...

Artificial Intelligence with Uncertainty

This book develops a framework that shows how uncertainty in Artificial Intelligence (AI) expands and generalizes traditional AI. It explores the uncertainties of knowledge and intelligence. The authors focus on the importance of natural la...

Leveraging the Potential of Novel Data in Power Line Communication of Electricity Grids

Electricity grids have become an essential part of daily life, even if they are often not noticed in everyday life. We usually only become particularly aware of this dependence by the time the electricity grid is no longer available. Howeve...

Developing Artificial Intelligence-Powered Monetary Policy Communication Indicators for Macroeconomic Inquiries in Ghana

Central bank communication is a valuable source of information designed to shape the expectations of economic agents within and outside an economy. In particular, the content of Monetary Policy Committees’ press releases and statements refl...

Meta-surface plasmon resonance microscopy for sensitive, high-throughput, and long-term label-free analysis of cell adhesion dynamics

Abstract Quantitative, label-free monitoring of dynamic cell adhesion remains challenging. Meta-Surface Plasmon Resonance Microscopy (Meta-SPRM) is a novel platform integrating bright-field microscopy with engineered Meta-SPR nanocup arrays...

Deep nested U-structure network with frequency attention for building semantic segmentation

Abstract The automated segmentation of buildings from remotely sensed imagery has undergone extensive research and application across various industrial domains. Despite this, several challenges persist, including incomplete internal extrac...

AI-Driven Integration of Deep Learning With Lung Imaging, Functional Analysis, and Blood Gas Metrics for Perioperative Hypoxemia Prediction

This viewpoint article explores the transformative role of artificial intelligence (AI) in predicting perioperative hypoxemia through the integration of deep learning with multimodal clinical data, including lung imaging, pulmonary function...

Artificial Intelligence and Surgical Decision-making

Importance: Surgeons make complex, high-stakes decisions under time constraints and uncertainty, with significant effect on patient outcomes. This review describes the weaknesses of traditional clinical decision-support systems and proposes...

Personalized ideological content recommendation via reinforcement learning as a digital therapeutic for anxiety reduction in youth

Abstract Adaptive digital therapies are needed with increasing rates of youth anxiety. However, existing systems lack personalization and dynamic learning. To solve this, the proposed research is to build a personalized ideological content ...