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This study examines the relationship between preschool children’s emotional expression and colour use in digital drawings produced during an authentic classroom activity. A total of 216 children created drawings a...

Ising machines, including quantum annealing machines, are promising next-generation computers for combinatorial optimization problems. However, due to hardware limitations, most Ising-type hardware can only solve objecti...

Arc fault, especially series arc fault, has been the primary cause of electrical fire, which is intermittent, hidden, random and uncertain, difficult to detect, and serious harm. The characteristics of arc fault are firs...

Options trading is a type of financial trading that can offer significant profit opportunities depending on market conditions, but its profit and loss structure is complex. Traditional trading decisions are often made ba...

This paper introduces CONV_GBERT, a hybrid deep learning framework for robust sentiment classification. The model integrates the bidirectional contextual understanding of BERT, the generative capabilities of GPT, and the...

In this work, a structured hierarchy of hyperdatasets for Monkeypox image classification is presented, aiming to evaluate the robustness and generalization ability of deep classification models for Mpox detection. A syst...

The low visual contrast between dermatological lesions and normal skin, coupled with the masking effect of surface artefacts, presents two major obstacles to precise automated skin lesion segmentation. In order to addres...

The remarkable success of large language models (LLMs) in code generation has transformed software development, with systems like Codex, CodeGen, and StarCoder demonstrating strong capabilities in synthesizing functional...

This review provides a comprehensive introduction to the current state of optimization through quantum computing, as well as its main methods and highlights. It begins with an overview of the history and principles of qu...

Reservoirs are critical infrastructure for global water, food, and energy security, yet their storage dynamics remain poorly characterized across most of the world. Accurate and timely knowledge of reservoir storage is e...

High-quality, openly accessible clinical datasets remain a significant bottleneck in advancing both research and clinical applications within medical artificial intelligence. Case reports, often rich in multimodal clinic...

Forecasting vaccine demand and determining inventory policies are critical challenges in healthcare supply chains, where uncertainty poses significant operational risks. This study proposes a two-step data-driven framewo...

Introduction. Stator flow-oriented control is currently the most widely used system in industry or in previous research for improving the quality of mechanical power generated by permanent magnet synchronous motors (PMSM...

ARM-based systems are widely deployed in edge and IoT settings, where penetration-testing tools must operate under strict memory, power, and thermal constraints, yet prior work offers limited deployment-oriented guidance...

Abstract This research proposes an innovative Arabic financial forecasting model that integrates linguistic relation extraction with advanced deep learning and machine learning techniques. The framework combines Arabic O...

Abstract In an elastic network paradigm, where the transceiver is able to control several characteristics of the transmitted signal according to the optical link quality and capacity demand, receivers able to automatical...

Machine learning has evolved into a potent tool for analysing patterns and making predictions from complex data. In this machine learning era, we employed neural network techniques to estimate the parameters of statistic...

Heart disease is rapidly increasing. For early and accurate prediction, advanced machine learning (ML) models are needed. However, the sensitive nature of clinical data, along with strict regulatory constraints, creates ...

Dual-drive feed systems are widely adopted in high-end CNC machines because of their high precision, rigidity, and operational stability. Vibration suppression during machining is critical to maintaining feed accuracy an...

Introduction. Nowadays, the most widely used wind energy conversion system in wind farms is based on a doubly fed induction generator (DFIG); it has a large speed range and can function in multiple modes. Problem. Harmon...

Botnet communications often rely on Domain Generation Algorithms (DGAs) to establish channels among attack orchestrators and compromised hosts (bots). Our approach leverages on Artificial Intelligence (AI) to differentia...

The growing demand for intensive artificial intelligence applications, such as deep neural networks and Large Language Models (LLMs), has driven the creation of architecture extensions and accelerators for matrix multipl...

Metamaterial based approaches have emerged as promising solutions for mitigating mutual coupling in compact multiple input multiple output antenna systems operating at fifth generation sub-6 GHz frequencies for smartphon...

Currently, numerous vocational colleges have incorporated practical training courses focused on automated production lines. However, due to spatial constraints and insufficient availability of physical equipment, the imp...