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This study aims to critically evaluate the class stratification strategy in enhancing Qira’ah (Arabic reading) proficiency at Ma’had Al-Jami’ah IAIN Kerinci. Using a qualitative approach, the study explores the ped...

Abstract This paper proposes a novel hybrid ensemble machine learning framework integrated with Explainable AI (XAI) to overcome the fundamental trade-off between non-detection zones (NDZ) and false positives in conventi...

The Global Flood Awareness System (GloFAS) is a promising flood-modelling tool available for most river basins worldwide. However, it contains inherent biases, notably linked to its spatial resolution. This study propose...

Abstract DriveEmo-FL presents a privacy-preserving, radar-based emotion-recognition framework tailored for autonomous-vehicle (AV) cabins. Leveraging a compact embedded mmWave radar, the system captures upper-body emotio...

Abstract Emotion recognition is fundamental to building socially intelligent robotic systems capable of effective and adaptive Human-Robot Interaction (HRI) and Collaboration (HRC). This literature review synthesizes rec...

IntroductionReliable classification of lung nodules from computed tomography (CT) images remains a challenging problem due to variations in image intensity, noise, and unstable feature representations during deep network...

Human–wildlife relations in alpine ecosystems reflect the combined effects of climate change, land-use transitions, and governance capacity. Rather than focusing solely on local conflict dynamics, this study investigat...

The article analyzes the theoretical foundations and practical aspects of implementing artificial intelligence (AI) technologies in educational and scientific space. Based on a systematic analysis of international resear...

The digital transformation of higher education has redefined pedagogical paradigms, particularly in postgraduate science programs, where disciplinary content demands adaptive, technology-enriched instructional frameworks...

Intelligent mining area detection is fundamental for ecological monitoring and sustainable development of mining areas. However, current remote sensing detection lacks high-quality multimineral rotated object detection d...

Purpose –This study aims to explore how teachers' professional competencies are implemented and sustained in island territories, with a particular focus on professional development practices, reflective processes, and ...

Convolutional neural networks (CNNs) and visual Transformers have become the dominant approaches for hyperspectral image (HSI) classification due to their powerful feature representation capabilities. However, CNNs are l...

Background: Climate change and increasing water scarcity pose significant challenges to sustainable water, sanitation and hygiene (WASH) service delivery in rural Africa. In Ethiopia, poor maintenance of rural water sch...

Abstract Training deep learning models requires substantial financial and human resources, so once deployed in untrusted environments, these models immediately attract the attention of attackers who seek to steal and mis...

Grounded in the need to modernize science education and promote learner-centred approaches, this study examined the effectiveness of integrating context-based 7E instructional strategies, rooted in constructivist learnin...

This study examines the role of artificial intelligence in improving the efficiency of photovoltaic (PV) systems through maximum power point tracking (MPPT) under dynamic operating conditions. A simulation-based model wa...

During their studies, musicians transition to work-readiness, develop a professional persona and graduate from skills acquisition in a traditional master-mentor relationship towards heterarchical collaboration in ensembl...

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 Modern broadband access networks increasingly carry heterogeneous, delay-sensitive traffic generated by cloud-assisted applications, real-time communication services, and short-form multimedia exchanges. These w...

Unsupervised anomaly detection identifying both structural and logical anomalies is essential for modern industrial manufacturing. Although multi-score frameworks have been proposed, existing methods tend to reuse identi...

This study investigates how the green economy agenda is operationalised through eco-edu tourism along the Ciliwung River in Kelurahan Cikoko, South Jakarta. Drawing on qualitative case-study evidence, the research docume...

Autonomous underwater vehicles (AUVs) operating in harsh, communication-limited underwater environments require robust fault diagnosis systems to ensure mission success and safety. Existing model-based approaches suffer ...

Trong bối cảnh toàn cầu, chuyển đổi số đang trở thành động lực quan trọng định hình lại hệ thống giáo dục đại học. Tuy nhiên, nhiều nghiên cứu và chính sách hiện nay ...

Abstract Large-scale mining equipment operates under extreme conditions, making accurate fault prediction and remaining useful life (RUL) estimation essential for predictive maintenance strategies. This paper proposes a ...