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Abstract With the increasingly widespread application scenarios of the Internet of Things, the demand for lightweight ciphers continues to grow. For some lightweight ciphers whose only nonlinear component is the AND gate...

Abstract Spatiotemporal analysis of professional sports like American football is a research area that has grown in recent years with the emergence of reliable tracking technologies for both players as well as the ball. ...

Abstract Learning to program is not just about writing code. It is a complex process involving trial and error, hesitation, corrections, and sometimes silence. And each student experiences it in their own way. Understand...

Dynamic gesture recognition is a core technology for human–computer interaction, yet existing methods face prominent limitations in hand spatial topology modeling, long–short-term temporal feature fusion, and general...

Abstract Long-range dependency processing is the core challenge of sequence modeling, and traditional sequence modeling algorithms suffer from information decay and low parallel computing efficiency in ultra long sequenc...

Background Female Technology (FemTech) apps are increasingly used worldwide, but perspectives from Arabic-speaking users remain underreported. Understanding user priorities in this context is critical for culturally rele...

Abstract High-electron-mobility transistors (HEMTs) based on wide bandgap (WBG) materials like gallium nitride (GaN) are vital for next-generation power electronics and high-frequency applications, offering high breakdow...

Mathematics and computer science play a pivotal role in modern biology. Dynamical models based on differential equations are particularly adapted to describe dynamic behaviors of many biological processes. However, tradi...

Abstract Purpose To design a coach-interpretable movement quality score for badminton footwork training using an adaptive neuro-fuzzy inference system. Methodology We derived compact biomechanical descriptors of timing, ...

Abstract River water quality forecasting on directed river networks requires jointly modeling temporal dynamics and directional spatial dependencies among monitoring sites. Existing spatio-temporal models often emphasize...

Abstract Occupational Health and Safety (OHS), which holds substantial importance due to its profound human implications and far-reaching economic consequences, requires effective management to minimize workplace acciden...

Abstract Traffic flow prediction is a fundamental building block for Intelligent Transportation Systems (ITS), enabling proactive congestion mitigation, adaptive traffic signal control, and reliable route guidance. Howev...

Abstract Accurate differentiation of pulmonary emphysema from chest X-rays remains challenging due to imbalanced data, image noise, and the limitations of traditional deep networks in managing diagnostic uncertainty. In ...

The functioning of an industria l enterprise of discrete production is considered as a set of interconnected production аnd design processes and managing them. Computer modeling of processes is used to review options fo...

The analysis and modeling of educational data are of great significance to the evaluation of teaching quality and personalized learning guidance. However, the acquisition of academic data is often limited by the costs of...

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 Traditional bridge structural condition assessments struggle to integrate the physical topological information of BIM models with the spatiotemporal evolution of long-term monitoring data, resulting in low asses...

Abstract Wearable sensor–based human activity recognition (HAR) is central to smart sport and health-monitoring applications, yet existing deep learning models often rely on ad hoc multimodal fusion and offer limited i...

Abstract Unmanned Aerial Vehicles (UAVs) are pivotal in tasks such as traffic monitoring and rescue operations, yet detecting small objects in UAV images remains challenging due to their diminutive size, low resolution, ...

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...

Federated learning (FL) is a pivotal paradigm for financial institutions to collaboratively train models while preserving data privacy, yet standard frameworks are hampered by a triad of challenges: vulnerability to pois...

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...

IntroductionThis study examines the impact of Customer Big Data Analytics (CBDA) on customer satisfaction and firm performance in business-to-business (B2B) firms operating in emerging markets, specifically Pakistan. Des...

Abstract This paper seeks to investigate the use of Natural Language Processing techniques in analyzing the Bhagavad Gita, a fundamental text in Hindu philosophy that has stood the test of time and centuries of interpret...