Open Access

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Ravi Saharan, Akrisht Singh, Prakash Choudhary^*

Computer Systems Science and Engineering, Vol.50, pp. 1-20, 2026, DOI:10.32604/csse.2026.081278 - 21 September 2026
Abstract The task of monitoring crowds for safety is a critical challenge, yet traditional surveillance systems are often visual only, error-prone, and lack interpretability. This paper presents SAFE (Semantic Audio-Visual Fusion Engine), a real-time, multi-modal framework that delivers interpretable, operator-facing alerts by fusing complementary audio-visual cues. The visual pipeline couples SSD–ResNet face detection and Hungarian tracking with facial emotion recognition and DBSCAN-based clustering of negative affect to compute a semantic visual anomaly score that includes an explicit overcrowding signal. In parallel, the audio pipeline extracts MFCCs (Mel-Frequency Cepstral Coefficients) and employs a lightweight one-dimensional convolutional neural… More >

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Abdulrahman M. Abdulghani^1,*, Azizol Abdullah¹, A. R. Rahiman¹, Nor Asilah Wati Abdul Hamid^1,2, Bilal Omar Akram^3,4, Hafsa Raissouli¹

Computer Systems Science and Engineering, Vol.49, pp. 123-157, 2025, DOI:10.32604/csse.2024.058314
Abstract This review article provides a comprehensive analysis of the latest advancements and persistent challenges in Software-Defined Wide Area Networks (SD-WANs), with a particular emphasis on the multi-objective Controller Placement Problem (CPP). As SD-WAN technology continues to gain prominence for its capacity to offer flexible and efficient network management, the task of 36optimally placing controllers—responsible for orchestrating and managing network traffic—remains a critical yet complex challenge. This review delves into recent innovations in multi-objective controller placement strategies, including clustering techniques, heuristic-based approaches, and the integration of machine learning and deep learning models. Each methodology is critically More >

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3856

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Nurhadi, Rabiah Abdul Kadir^*, Ely Salwana Mat Surin, Mahidur R. Sarker^*

Computer Systems Science and Engineering, Vol.48, No.6, pp. 1405-1435, 2024, DOI:10.32604/csse.2024.051851
Abstract A data lake (DL), abbreviated as DL, denotes a vast reservoir or repository of data. It accumulates substantial volumes of data and employs advanced analytics to correlate data from diverse origins containing various forms of semi-structured, structured, and unstructured information. These systems use a flat architecture and run different types of data analytics. NoSQL databases are nontabular and store data in a different manner than the relational table. NoSQL databases come in various forms, including key-value pairs, documents, wide columns, and graphs, each based on its data model. They offer simpler scalability and generally outperform… More >

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1625

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ARTICLE

Tabassum Kanwal¹, Saif Ur Rehman^1,*, Azhar Imran², Haitham A. Mahmoud³

Computer Systems Science and Engineering, Vol.49, pp. 185-212, 2025, DOI:10.32604/csse.2024.056535
Abstract This study presents an energy-efficient Internet of Things (IoT)-based wireless sensor network (WSN) framework for autonomous data validation in remote environmental monitoring. We address two critical challenges in WSNs: ensuring data reliability and optimizing energy consumption. Our novel approach integrates an artificial neural network (ANN)-based multi-fault detection algorithm with an energy-efficient IoT-WSN architecture. The proposed ANN model is designed to simultaneously detect multiple fault types, including spike faults, stuck-at faults, outliers, and out-of-range faults. We collected sensor data at 5-minute intervals over three months, using temperature and humidity sensors. The ANN was trained on 70%… More >

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2613

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Md Monir Ahammod Bin Atique^1,#, Md Ilias Bappi^1,#, Kwanghoon Choi^1,*, Kyungbaek Kim^1,*, Md Abul Ala Walid², Pranta Kumar Sarkar³

Computer Systems Science and Engineering, Vol.49, pp. 455-479, 2025, DOI:10.32604/csse.2025.069213
Abstract Employee turnover presents considerable challenges for organizations, leading to increased recruitment costs and disruptions in ongoing operations. High voluntary attrition rates can result in substantial financial losses, making it essential for Human Resource (HR) departments to prioritize turnover reduction. In this context, Artificial Intelligence (AI) has emerged as a vital tool in strengthening business strategies and people management. This paper incorporates two new representative features, introducing three types of feature engineering to enhance the analysis of employee turnover in the IBM HR Analytics dataset. Key Machine Learning (ML) techniques were subsequently employed in this work,… More >

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3381

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ARTICLE

Ayman Noor^*

Computer Systems Science and Engineering, Vol.49, pp. 259-286, 2025, DOI:10.32604/csse.2025.060387
Abstract Precisely forecasting the performance of Deep Learning (DL) models, particularly in critical areas such as Uniform Resource Locator (URL)-based threat detection, aids in improving systems developed for difficult tasks. In cybersecurity, recognizing harmful URLs is vital to lowering risks associated with phishing, malware, and other online-based attacks. Since it directly affects the model’s capacity to differentiate between benign and harmful URLs, finding the optimum mix of hyperparameters in DL models is a significant difficulty. Two commonly used architectures for sequential and spatial data processing, Long Short-Term Memory (LSTM)/Gated Recurrent Unit (GRU) and Convolutional Neural Network… More >

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4231

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2599

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Zain Anwar Ali^1,2,*, Dingnan Deng¹, Muhammad Kashif Shaikh³, Raza Hasan⁴, Muhammad Aamir Khan²

Computer Systems Science and Engineering, Vol.48, No.1, pp. 1-34, 2024, DOI:10.32604/csse.2023.041866
Abstract Technological advances in unmanned aerial vehicles (UAVs) pursued by artificial intelligence (AI) are improving remote sensing applications in smart agriculture. These are valuable tools for monitoring and disease identification of plants as they can collect data with no damage and effects on plants. However, their limited carrying and battery capacities restrict their performance in larger areas. Therefore, using multiple UAVs, especially in the form of a swarm is more significant for monitoring larger areas such as crop fields and forests. The diversity of research studies necessitates a literature review for more progress and contribution in… More >

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1794

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ARTICLE

Khadija El Fellah^1,*, Ikram El Azami^2,*, Adil El Makrani², Habiba Bouijij³, Oussama El Azzouzy⁴

Computer Systems Science and Engineering, Vol.49, pp. 99-122, 2025, DOI:10.32604/csse.2024.057754
Abstract The rapid growth of the automotive industry has raised significant concerns about the security of connected vehicles and their integrated supply chains, which are increasingly vulnerable to advanced cyber threats. Traditional authentication methods have proven insufficient, exposing systems to risks such as Sybil, Denial of Service (DoS), and Eclipse attacks. This study critically examines the limitations of current security protocols, focusing on authentication and data exchange vulnerabilities, and explores blockchain technology as a potential solution. Blockchain’s decentralized and cryptographically secure framework can significantly enhance Vehicle-to-Vehicle (V2V) communication, ensure data integrity, and enable transparent, immutable transactions More >

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4202

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2699

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ARTICLE

Pakorn Santakij¹, Samai Srisuay^2,*, Pongporn Punpeng¹

Computer Systems Science and Engineering, Vol.48, No.3, pp. 665-689, 2024, DOI:10.32604/csse.2024.045066
Abstract Social media has revolutionized the dissemination of real-life information, serving as a robust platform for sharing life events. Twitter, characterized by its brevity and continuous flow of posts, has emerged as a crucial source for public health surveillance, offering valuable insights into public reactions during the COVID-19 pandemic. This study aims to leverage a range of machine learning techniques to extract pivotal themes and facilitate text classification on a dataset of COVID-19 outbreak-related tweets. Diverse topic modeling approaches have been employed to extract pertinent themes and subsequently form a dataset for training text classification models.… More >

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ARTICLE

Abdelrahman Maharek^1,2,*, Amr Abozeid^2,3, Rasha Orban¹, Kamal ElDahshan²

Computer Systems Science and Engineering, Vol.48, No.2, pp. 305-320, 2024, DOI:10.32604/csse.2024.039436
（This article belongs to the Special Issue: Explainable AI and Cybersecurity Techniques for IoT-Based Medical and Healthcare Applications)
Abstract What causes object detection in video to be less accurate than it is in still images? Because some video frames have degraded in appearance from fast movement, out-of-focus camera shots, and changes in posture. These reasons have made video object detection (VID) a growing area of research in recent years. Video object detection can be used for various healthcare applications, such as detecting and tracking tumors in medical imaging, monitoring the movement of patients in hospitals and long-term care facilities, and analyzing videos of surgeries to improve technique and training. Additionally, it can be used… More >

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1330

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Verónica C. Tapia^1,2,*, Carlos M. Gaona²

Computer Systems Science and Engineering, Vol.49, pp. 1-17, 2025, DOI:10.32604/csse.2024.056979
Abstract In recent years, automation has become a key focus in software development as organizations seek to improve efficiency and reduce time-to-market. The integration of artificial intelligence (AI) tools, particularly those using natural language processing (NLP) like ChatGPT, has opened new possibilities for automating various stages of the development lifecycle. The primary objective of this study is to evaluate the effectiveness of ChatGPT in automating various phases of software development. An artificial intelligence (AI) tool was developed using the OpenAI—Application Programming Interface (API), incorporating two key functionalities: 1) generating user stories based on case or process… More >

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2809