Computer Sciences & Mathematics Forum, Volume 10, 2025

The rapid expansion of IoT in smart cities has improved traffic management but increased security risks. Traditional IDS struggle with advanced threats, prompting adaptive solutions. This work proposes a framework combining machine learning (ML), Zer...

The separation of respiratory and cardiac sounds is a significant challenge in biomedical signal processing due to their overlapping frequency and time characteristics. Traditional methods struggle with accurate extraction in noisy or diverse clinica...

Numerous studies in the healthcare field conducted in recent years have highlighted the impact of stress on health and its role in the development of several critical illnesses. Stress monitoring using wearable technologies, such as smartwatches and...

The importance of real-time big data has become crucial in the digital revolution of modern society, in the context of increasing data flows from multiple sources, including social media, internet connected devices (IOT) and financial systems, real-t...

The rapid growth of information and communication technologies, in particular big data, artificial intelligence (AI), and the Internet of Things (IoT), has made it possible to make smart cities a tangible reality. In this context, real-time video sur...

The digital age has transformed education, making distance learning essential. With rapid knowledge evolution, flexible and personalized learning is crucial. This article examines how ontology and semantic web technologies enhance e-learning. Ontolog...

Machine learning is revolutionizing healthcare by enhancing diagnosis and treatment personalization. This study explores ML applications in medical imaging, analyzing data from X-rays, CT, MRI, and ultrasound for early disease detection. It reviews k...

The application of machine learning (ML) to medical datasets offers significant potential for improving disease prediction and patient outcomes. However, challenges such as feature redundancy, overfitting, and suboptimal model performance limit the p...

Large language models (LLMs) are developing at a rapid pace, which has made it necessary to better understand how they train, especially when faced with resource limitations. This paper examines in detail how various state-of-the-art LLMs train on a...

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Digitalization has shaped every part of our world, from education to healthcare, from finance to entertainment, and from manufacturing to social interactions. This digital transformation has put tremendous power in the hands of individuals and delive...

Rapid urbanization and the rising demand for sustainable living have encouraged the growth of smart cities, which incorporate innovative technologies to ameliorate environmental sustainability, optimize resource management, and improve living standar...

This manuscript investigates the feasibility of Four-In-Wheel Electronic Differential Systems (4 IW-EDSs) within contemporary electric vehicles (EVs), emphasizing their benefits for stability regulation predicated on steering angles. Through an exten...

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The performance degradation of photovoltaic (PV) systems, comprising solar panels and DC-DC converters, is often caused by various anomalies related to manufacturing defects, operational conditions, or environmental factors. These faults significantl...

In the era of digital transformation, the environmental impact of software development has become a pressing concern, necessitating the integration of sustainability into software development processes. This paper addresses how DevOps, traditionally...

This study investigates the energy consumption and carbon footprint of two prominent automatic speech recognition (ASR) systems: OpenAI’s Whisper and Google’s Speech-to-Text API. We evaluate both local and cloud-based speech recognition approaches us...

The accurate and early detection of respiratory diseases is vital for effective diagnosis and treatment. This study presents a new approach for classifying lung sounds using a double denoising method combined with a 1D Convolutional Neural Network (C...