Academic Articles & Research Papers

Enhancing AI Explainability Through the EXACT Framework: A User-Centric Approach

The increasing adoption of Artificial Intelligence (AI) in several industries has created a demand for user-centered explanations that align with how users think and understand concepts. This paper presents EXACT (EXplainable AI with Cognit...

APRICOIN: An Adaptive Approach for Prioritizing High-Risk Containers Inspections

Risk evaluation of the containers remains a difficult task, often due to incomplete or ambiguous information on containers. In addition, the evaluation process needs to be adapted on an ongoing basis to cope with emerging risk factors. Furt...

DCN-Deeplabv3+: A Novel Road Segmentation Algorithm Based on Improved Deeplabv3+

Road segmentation is an important task in the field of semantic segmentation, and the Deeplabv3+ algorithm, which is commonly used for road segmentation, has shortcomings, such as numerous parameters and a tendency to lose detailed informat...

A Scalo Gram-Based CNN Ensemble Method With Density-Aware SMOTE Oversampling for Improving Bearing Fault Diagnosis

Machine learning (ML) based bearing fault detection is an emerging application of Artificial Intelligence (AI) that has proven its utility in effectively classifying various faults for timely measures. There are myriad studies dedicated to ...

Artificial Intelligence in Meta-optics

Recent years have witnessed promising artificial intelligence (AI) applications in many disciplines, including optics, engineering, medicine, economics, and education. In particular, the synergy of AI and meta-optics has greatly benefited b...

Radiomics and radiogenomics: extracting more information from medical images for the diagnosis and prognostic prediction of ovarian cancer

Abstract Ovarian cancer (OC) remains one of the most lethal gynecological malignancies globally. Despite the implementation of various medical imaging approaches for OC screening, achieving accurate differential diagnosis of ovarian tumors ...

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 in glaucoma

PURPOSE OF REVIEW: The use of computers has become increasingly relevant to medical decision-making, and artificial intelligence methods have recently demonstrated significant advances in medicine. We therefore provide an overview of curren...

An Instructional Optimization Method Based on Bidirectional Transformer and Reinforcement Learning

With the rapid development of information technology, personalized education has become a key direction for improving the quality of online learning and optimizing individualized learning paths. However, accurately recommending appropriate ...

Towards an AI-Based Tailored Training Planning for Road Cyclists: A Case Study

In a world where the data is a central piece, we provide a novel technique to design training plans for road cyclists. This study exposes an in-depth review of a virtual coach based on state-of-the-art artificial intelligence techniques to ...

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...

A is for Artificial Intelligence

We developed a novel early childhood artificial intelligence (AI) platform, PopBots, where preschool children train and interact with social robots to learn three AI concepts: knowledge-based systems, supervised machine learning, and genera...

Designing novel linagliptin analogs through combined generative artificial intelligence, molecular docking, molecular dynamics simulation, and binding energy estimation for targeting fibroblast activation protein

Fibroblast activation protein (FAP) is a highly specific biomarker overexpressed in cancer-associated fibroblasts, making it a promising diagnostic target. Developing novel high-affinity molecular probes for FAP-targeted diagnostics remains...

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...

Trustworthy artificial intelligence

Abstract Artificial intelligence (AI) brings forth many opportunities to contribute to the wellbeing of individuals and the advancement of economies and societies, but also a variety of novel ethical, legal, social, and technological challe...

Timor Leste in ASEAN: Implications for ASEAN-Led Economic Multilateralism in the Digital Field

The paper explores the main implications of East Timor’s accession to the Association of Southeast Asian Nations (ASEAN) in October 2025 for ASEAN-led economic projects and initiatives in the digital field. The research aims to identify the...

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...

Development of a novel RNA modification-based risk model to predict prognosis and immunotherapy response in melanoma using machine learning.

Evaluating Artificial Intelligence’s Role in Developing Research Questions in Head and Neck Reconstruction

Summary:. Generative artificial intelligence (AI) large language models are an emerging technology, with ChatGPT and Gemini being 2 well-known examples. The current literature discusses clinical applications and limitations of AI, but its r...

Design of High-Dimensional Maps with Sine Terms

The use of the advancements in memristor technology to construct chaotic maps has garnered significant research attention in recent years. The combination of memristors and nonlinear terms provides an effective approach to proposing novel m...