This research was based on teaching experience as an architecture lecturer who taught a lighting course for undergraduate students in the Department of Architecture. Simulation software is often used to teach lighting to learners. However, in practic...
In the original publication [...]
Neonatal cerebral atrophy is a serious form of structural brain anomaly observed in up to 15% of newborns admitted to neonatal intensive care units (NICUs). Early and accurate assessment is clinically important because it can inform prognosis, guide...
Commercial cloud-controlled service robots are increasingly deployed in shared public facilities, yet many remain task-centric delivery platforms that cannot be easily extended with surrounding-people recognition, situated communication policy, or co...
Accurately identifying whether a vehicle is controlled by a human driver or by an autonomous policy is critical in future mixed-traffic environments for safety monitoring and liability attribution. To achieve accurate classification or identification...
Early-warning systems aim to identify students at risk of failing or withdrawing in time to act. On two modules of the Open University Learning Analytics Dataset, we evaluated a hybrid model in which a Transformer encoder summarises ten weeks of virt...
Learned resource allocators for sixth-generation edge networks usually treat operational limits as penalties and may return infeasible decisions. This paper studies energy minimization in multi-cell uplink non-orthogonal multiple access mobile edge c...
In digital decision-support environments, users continuously generate analytical experiences, annotations, and metadata while interacting with data warehouse systems. Reusing these experiences can improve decision-making, reduce redundant analytical...
When an operator’s instruction conflicts with a codified safety rule, an assistant should recognize the conflict and defer to the rule. This is a pragmatic problem with an objective answer: the correct action follows from a published regulation...
Context: The increasing adoption of Internet of Things (IoT) technologies has transformed digital marketing into a software-intensive, data-driven ecosystem requiring continuous optimization under uncertainty. Existing decision-support approaches pri...
The long-term reliability of selective laser melting (SLM) equipment is constrained by the latent degradation and coupled faults of multiple underlying hardware systems under continuous high-load operations. Transitioning from passive defect detectio...
Facility-layout decisions in small manufacturing firms are often evaluated with heterogeneous indicators, which complicates comparison and reproducibility. This study develops a traceable decision-support workflow and applies it to two manufacturing...
Data are becoming increasingly crucial to business and social digitalization, as such data have become a strategic asset that accelerates economic competitiveness and digitalization of society. In a societal context, it is important to maintain compl...
Digital transformation can improve supply chain sensing, but recovery depends on whether reliable information is converted into coordinated operational action. This study develops a simulation-based case study that integrates data-quality-adjusted in...
Human Digital Twins (HDTs) extend traditional Digital Twin (DT) concepts by modeling both humans and hospital processes to support smarter and more human-centered healthcare. By integrating Industry 4.0 (I4.0) technologies with the human-centric prin...
Automated bridge surface defect detection is essential for improving the efficiency and objectivity of infrastructure inspection under complex field imaging conditions. This study proposes a Multi-Scale Detection Transformer (MS-DETR), an RT-DETR-bas...
The increasing integration of Artificial Intelligence (AI) into classroom practice has created the need for valid instruments to assess teachers’ readiness for AI integration. The present study developed and psychometrically validated the Teach...
STEAM approaches create new opportunities for students to develop thinking skills connected to technical and scientific education. By combining different areas of knowledge, STEAM encourages students to explore ideas from multiple perspectives and fi...
This exploratory mixed-methods study examines how an edge artificial intelligence (edge AI) gas-sensing project is associated with vocational upper-secondary students’ self-reported problem-solving attitudes in an authentic classroom setting. T...
Wireless Sensor Networks (WSNs) are fundamental to the expansion of the Internet of Things (IoT), yet severe node energy constraints remain the primary bottleneck for remote environmental monitoring where power infrastructure is unavailable. Because...
Manufacturing sectors and ecosystems can improve their innovation performance through digital platforms, connected intelligence, and organisational settings that enable collaboration among experts and ecosystem members. The convergence of skills and...
Transitioning cultivated land from a narrowly defined production resource into a coordinated multifunctional asset is a cornerstone of agricultural modernization. Despite this imperative, current land utilization in China remains largely constrained...
Crime offense descriptions are often recorded as unstructured text, making large-scale analysis and categorization difficult. This study proposes a semantic clustering framework for Thai crime offense descriptions using sentence embeddings, dimension...
Today, data are no longer confined to numerical values arranged in row-by-column matrices or stored neatly within relational databases. One of the defining characteristics of big data is its high variety, encompassing unstructured and multimodal form...
In the original publication [...]
Recent lunar missions have generated a growing demand for automated and reliable processing of lunar regolith images. However, imaging degradations, limited annotations, and the lack of paired clean–degraded reference data still hinder the robu...
Potato quality is determined by multiple physicochemical indicators, including dry matter content (DC), starch content (SC), and color parameters (lightness L*, redness a*, yellowness b*, and browning index (BI)). Conventional spectrometers are costl...
Image interpolation plays an important role in many computer vision and image processing tasks, such as image resizing, denoising, and restoration. Most traditional interpolation algorithms work on the time domain and deal with all image regions in a...
This paper provides a comprehensive and systematic review of artificial intelligence (AI) integration in smart logistics management, evaluating seven core technology clusters: machine learning (ML), deep learning (DL), natural language processing (NL...
(1) Background: Hypertension is a prevalent chronic condition requiring sustained self-management to prevent complications; however, long-term adherence to monitoring, medication, and lifestyle modification remains suboptimal. Mobile health (mHealth)...
Hyperspectral imaging is a well-established remote sensing technique for material detection and classification, relying on hundreds of reflectance bands to exploit the spectral signatures of surface materials. Although hyperspectral imagery has demon...
In the original publication [...]
In the original publication [...]
In the original publication [...]
Customer prioritization in e-commerce remains dominated by value-based logics that allocate retention effort to the most profitable customers, even though risk-based targeting can be ineffective when intervention responsiveness is ignored. This study...
This study describes the second iteration of VLEPIC, a gamified and personalised virtual learning environment (VLE) for secondary English students in Ecuador. Adopting a design-based research approach, it focuses on student interaction and system imp...
Ecuador’s agricultural sector plays a strategic role in the national economy; however, agricultural data remains fragmented across heterogeneous and isolated sources, limiting integrated analysis and evidence-based decision-making. This study p...
Deep Neural Networks (DNNs) are increasingly being used in the design of industrial safety-critical autonomous applications such as autonomous vehicles, industrial robotics, and medical instrumentation and control systems. Ensuring reliable and robus...
Digital twin (DT) technology has expanded far beyond its industrial origins, increasingly finding application across environmental and territorial domains. This review provides a structured mapping of DT deployments at environmental and territorial s...
Traditional dementia care training often falls short in equipping staff with the knowledge and skills needed to improve quality of life for people with dementia. Virtual Reality (VR)-based experiential learning has emerged as a promising approach, en...
In today’s manufacturing industry, work-related musculoskeletal disorders (WMSDs) remain among the most prevalent occupational health issues. Collaborative robots (cobots) represent a promising technology to address this challenge. Consequently...
In today’s educational context, Game-Based Learning (GBL) has emerged as a promising methodology for promoting active learning in an engaging and motivating way. This study aims to analyze the impact of a video game-based intervention on the de...
Reliable delineation of brain tumor boundaries in multimodal magnetic resonance imaging (MRI) remains challenging despite substantial advances in deep learning–based segmentation. Although modern encoder–decoder architectures achieve stro...
This study aims to investigate the integration of generative artificial intelligence (GAI) and advanced large language models (LLMs) in financial sentiment research, focusing on improving the accuracy and robustness of financial sentiment classificat...
The rapid advancement of information technology and multimedia applications has led to an increasing demand for video data processing. In particular, video fusion technology in multi-camera environments, which integrates and optimizes video data from...
Digital resilience has become an increasingly important concept in information systems research due to growing dependence on digital infrastructures, escalating cyber threats, and the emergence of regulatory frameworks that formalize resilience oblig...
Pipelines remain the primary mode of oil and gas transportation but are vulnerable to leaks that pose environmental and safety risks, particularly in two-phase flow systems. Conventional detection methods often struggle under transient multiphase con...
With the rapid growth of edge computing applications, optimizing both edge server placement and task offloading decisions is critical for minimizing system latency in edge–cloud environments. However, these two problems are tightly coupled and...
Digital Product Passports (DPPs) are being introduced in the European Union to support circular economy strategies, improve product transparency, and enable lifecycle-based compliance and decision-making. Despite growing interest, research on DPPs re...
Employee attrition presents a significant threat to organizational continuity, as frequent turnover depletes valuable intellectual capital and incurs heavy recruitment costs. Although ensemble machine learning models often achieve high accuracy in pr...
