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People with disabilities mostly communicate using sign language, but the public still has little understanding of the Indonesian Sign Language System (ISLS). This causes obstacles in daily interactions. Advances in artif...

INTRODUCTION: Accurate power quality disturbances (PQDs) classification is critical for maintaining grid stability and reliability in modern power systems. However, existing deep learning methods predominantly rely on si...

Cities of the future will have to overcome congestion, air pollution and increasing infrastructure cost while moving more people and goods smoothly, efficiently and in an eco-friendly manner. Urban air mobility (UAM) is ...

In this research, we address a critical problem for strawberry growers in Lima: the management of phytosanitary diseases. Traditionally, these farmers relied on time-consuming, imprecise, and error-prone visual observati...

Abstract In response to the dual challenges of complex static obstacles and frequent dynamic disturbances in the construction site environment, this paper proposes a hybrid path planning strategy that integrates global s...

Immersive walkthroughs are increasingly used to document, interpret, and communicate heritage sites to remote audiences. This study presents a framework for designing and implementing a cross-platform WebVR walkthrough o...

Dear Readers,It gives me great pleasure to announce the fourth regular issue of 2026. In this issue, 6 papers by 25 authors from 6 countries - Colombia, Greece, Mexico, Republic of Serbia, South Africa, Türkiye ...

Monitoring chicken health is essential for maintaining the production efficiency of poultry farms and meeting the demand for poultry products. Previous studies have explored various methods, including utilizing sound, be...

With the increasing aging population, the health management of older people has become an increasingly important issue. The author aims to meet the health needs of older people by designing a wearable device and a vital ...

This paper explores the application of convolutional neural networks (CNNs) in predictive modelling for seismic events and flood risks, with a particular focus on forecasting extreme quantile events that exceed historica...

Abstract In the power operation scenarios, there are problems such as large differences in target scales, small targets susceptible to occlusion, and limited computational resources for edge devices. This leads to insuff...

ABSTRACT Adversarial jamming attacks have increased on communication systems, causing distortion and threatening transmissions. Typical attacks rely on traditional, well‐defined cryptographic protocols and frequency‐...

Abstract The Error Diffusion Learning Algorithm (EDLA) is a learning scheme that performs synaptically local weight updates driven by a single, globally defined error signal. Although originally proposed as an alternativ...

Accurate detection of pediatric fractures in radiographs remains challenging due to subtle visual cues and the high prevalence of false-positive detections produced by automated systems. To address this limitation, we pr...

Abstract Physical sciences are essential to the predictive modeling of complex environmental systems, particularly environmental monitoring and sustainability applications, as they provide the deterministic foundation re...

ABSTRACT Intelligent and adaptive defence systems that can quickly thwart changing cyberthreats are becoming more and more necessary in the dynamic and data‐intensive Internet of things (IoT) environment. Using the NSL...

Abstract The emergence of Internet-of-Things devices and expanding data processing demands have led to the popularization of edge computing. But energy efficiency challenges and security problems also remain difficult in...

IntroductionTo optimize radiotherapy treatment and minimize toxicities, effective segmentation of organs-at-risk (OARs) and clinical target volume (CTV) is essential. Deep learning (DL) models can achieve high segmentati...

Abstract Skin diseases affect a considerable part of the world population, but it is not easy to diagnose these diseases on time because of the limited availability of dermatologists and the similarity of lesions. This r...

The rapid proliferation of digital devices has generated vast amounts of data, presenting significant challenges in collection, processing, and analysis that traditional systems struggle to overcome. This study investiga...

This paper addresses the growing need for implementing intelligent Natural Language Processing (NLP) systems on low-power, memory-limited devices such as Raspberry Pi, mobile phones, and IoT edge hardware. As edge comput...

Abstract This research is concerned with the innovative use of AI in cross-cultural music learning, more particularly in the creation of a multimodal learning model that combines audio identification, image analysis, and...

Abstract Quantum networks (QNs) have been predominantly driven by discrete-variable (DV) architectures. Yet, optical platforms naturally generate Gaussian states—the common states of continuous-variable (CV) systems, m...

Background For those with hearing loss, sign language (SL) is an essential communication tool. The most common and basic type of SL is American SL (ASL). ASL plays a vital role in various communicative contexts, includin...