2025 August - 33 articles
Efficient spectrum utilization is critical for meeting the growing data demands of modern wireless communication networks. Automatic Modulation Classification (AMC) plays a key role in enhancing spectrum efficiency by accurately identifying modulatio...
Social media empowers freedom of expression but is often misused for abuse and hate. The detection of such content is crucial, especially in under-resourced languages like Urdu. To address this challenge, this paper designed a comprehensive multilabe...
As large language model (LLM) tutors evolve from scripted helpers into adaptive educational partners, their capacity for self-regulation, ethical decision-making, and internal monitoring will become increasingly critical. This paper introduces the Ne...
The uncertainty and confrontational nature of war itself pose significant challenges to the collection and storage of aerial battlefield temporal data. To address the issue of insufficient training of intelligent models caused by the scarcity of air...
Depression is a serious mental health disorder affecting cognition, emotions, and behavior. It impacts over 300 million people globally, with mental health care costs exceeding $1 trillion annually. Traditional diagnostic methods are often expensive,...
In recent years, artificial intelligence (AI) has emerged as a transformative force across various sectors of modern society, reshaping economic landscapes, social interactions, and ethical considerations. This paper explores the multifaceted impact...
Sign language recognition (SLR) plays a crucial role in bridging the communication gap between deaf individuals and the hearing population. However, achieving subject-independent SLR remains a significant challenge due to variations in signing styles...
Retrieval-Augmented Generation (RAG) combined with Large Language Models (LLMs) introduces a new paradigm for clinical-trial data analysis that is both real-time and knowledge-traceable. This study targets a multi-site, real-world data environment. I...
The protective role of progesterone against estradiol-driven proliferation is essential for preserving endometrial homeostasis. However, the factors that influence the progesterone–estradiol (P4:E2) ratio remain poorly characterized. This study...
We present Liquid Adaptive AI as a theoretical framework and mathematical basis for artificial intelligence systems capable of continuous structural adaptation and autonomous capability development. This work explores the conceptual boundaries of ada...
This study investigates global innovation trends in machine learning (ML) and deep learning (DL) technologies within the automotive sector through a patent analysis of 5314 applications filed between 2005 and 2022 across the five major patent offices...
Human personality (HP) is seen as an individual’s consistent patterns of feeling, thinking, and behaving by today’s psychological studies, in which HPs are characterized in terms of traits—in particular, as relatively enduring chara...
This paper presents a comprehensive deep reinforcement learning (DRL) framework for developing strategic trading models tailored to the Indian NIFTY 50 index, leveraging the temporal and nonlinear nature of financial markets. Three advanced DRL archi...
Large language models (LLMs) generally perform well in common tasks, yet are often susceptible to errors in sophisticated natural language processing (NLP) on classification applications. Prompt engineering has emerged as a strategy to enhance their...
Image dehazing is an effective approach for enhancing the quality of images captured under foggy or hazy conditions. Although existing methods have achieved certain success in dehazing performance, many rely on deep network architectures, leading to...
Accurate full-body motion reconstruction from sparse sensors is crucial for VR/AR applications but remains challenging due to the under-constrained nature of limited observations and the computational constraints of mobile platforms. This paper prese...
Condition monitoring and fault detection in wind turbines are essential for reducing repair and maintenance costs. Early detection of faults enables timely interventions before the damage worsens. However, existing methods often rely on costly schedu...
As large language models (LLMs) gain traction among researchers and practitioners, particularly in digital marketing for tasks such as customer feedback analysis and automated communication, concerns remain about the reliability and consistency of th...
Efficient and accurate panel assignment is critical in expert and peer review processes. Traditional methods—based on manual preferences or Heuristic rules—often introduce bias, inconsistency, and scalability challenges. We present an aut...
Artificial intelligence has taken a seat at the executive table and is threatening the fact that human beings are the only ones who should be in a position of power. This article gives conjectures on the future of leadership in which managers will co...
In the twenty-first century, humanity is compelled to face global challenges. Such challenges involve complex systems. However, science has some cognitive and predictive limits in dealing with complex systems. Some of these limits are related to comp...
Background and Objective: Temperature management is key for reliable operation of permanent magnet synchronous motors (PMSMs). The lumped-parameter thermal network (LPTN) is fast and interpretable but struggles with nonlinear behavior under high powe...
Despite the focus on improving cybersecurity awareness, the number of cyberattacks has increased significantly, leading to huge financial losses, with their risks spreading throughout the world. This is due to the techniques deployed in cyberattacks...
Objectives: This study introduces an automated classification system for noisy kidney ultrasound images using an ensemble of deep neural networks (DNNs) with transfer learning. Methods: The method was tested using a dataset with two categories: norma...
Forming interdisciplinary research teams is challenging, especially when the pool of candidates is large and/or the addressed research projects require multi-disciplinary expertise. Based on their previous research outputs, like published work, a dat...
Trust in Traditional Thai Medicine (TTM) among Thai people has been reduced due to a lack of objective standards and the susceptibility of the general population to false information. The emergence of generative artificial intelligence (Gen AI) has s...
Artificial Intelligence (AI) and Generative AI are transformative yet double-edged technologies with evolving risks. While research emphasises trustworthy, fair, and responsible AI by focusing on its “what” and “why,” it overl...
With the growing number and diversity of network attacks, traditional security measures such as firewalls and data encryption are no longer sufficient to ensure robust network protection. As a result, intrusion detection systems (IDSs) have become a...
Breast cancer (BRCA) remains a significant cause of mortality among women, particularly in developing and underdeveloped regions, where early detection is crucial for effective treatment. This research introduces an innovative hybrid model that combi...
Dense video captioning involves identifying, localizing, and describing multiple events within a video. Capturing temporal and contextual dependencies between events is essential for generating coherent and accurate captions. To effectively capture t...
Background: As intelligent systems increasingly operate in high-risk environments, understanding how they perceive and respond to hazards is critical for ensuring safety. Methods: In this study, we conduct a comparative analysis of 60 real-world acci...
The escalating sophistication of cyber threats underscores the critical need for intelligent and adaptive intrusion detection systems (IDSs) to identify known and novel attack vectors in real time. Feature selection is a key enabler of performance in...
Large language models (LLMs) are increasingly being applied to clinical tasks, but it remains unclear whether medical-specific models consistently outperform smaller, generalpurpose ones. This study investigates that assumption in the context of card...
