Rakesh Kumar^1,*, Ajay Singh², Ahmed Subahi Ahmed Kassar³, Mohammed Ismail Humaida³, Sudhanshu Joshi⁴, Manu Sharma⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 1289-1349, 2025, DOI:10.32604/cmes.2025.059152 - 27 January 2025

Abstract This review aims to analyze the development and impact of Artificial Intelligence (AI) in the context of Saudi Arabia’s public healthcare system to fulfill Vision 2030 objectives. It is extensively devoted to AI technology deployment relevant to disease management, healthcare delivery, epidemiology, and policy-making. However, its AI is culturally sensitive and ethically grounded in Islam. Based on the PRISMA framework, an SLR evaluated primary academic literature, cases, and practices of Saudi Arabia’s AI implementation in the public healthcare sector. Instead, it categorizes prior research based on how AI can work, the issues it poses, and… More >

Syed Ijaz Ur Rahman¹, Naveed Abbas¹, Sikandar Ali², Muhammad Salman¹, Ahmed Alkhayat³, Jawad Khan^4,*, Dildar Hussain⁵, Yeong Hyeon Gu^5,*

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 1199-1231, 2025, DOI:10.32604/cmes.2025.057462 - 27 January 2025

Abstract Automatic detection of Leukemia or blood cancer is one of the most challenging tasks that need to be addressed in the healthcare system. Analysis of white blood cells (WBCs) in the blood or bone marrow microscopic slide images play a crucial part in early identification to facilitate medical experts. For Acute Lymphocytic Leukemia (ALL), the most preferred part of the blood or marrow is to be analyzed by the experts before it spreads in the whole body and the condition becomes worse. The researchers have done a lot of work in this field, to demonstrate… More >

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 - 10 January 2025

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 >

Nazreen Banu A^*, S.K.B. Sangeetha

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 579-607, 2025, DOI:10.32604/cmc.2024.059805 - 03 January 2025

Abstract The increasing use of cloud-based devices has reached the critical point of cybersecurity and unwanted network traffic. Cloud environments pose significant challenges in maintaining privacy and security. Global approaches, such as IDS, have been developed to tackle these issues. However, most conventional Intrusion Detection System (IDS) models struggle with unseen cyberattacks and complex high-dimensional data. In fact, this paper introduces the idea of a novel distributed explainable and heterogeneous transformer-based intrusion detection system, named INTRUMER, which offers balanced accuracy, reliability, and security in cloud settings by multiple modules working together within it. The traffic captured… More >

Min-kyeong Kim¹, Yeong Geol Lee², Won-Hee Park^2,*, Su-hwan Yun², Tae-Soon Kwon², Duckhee Lee²

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 1277-1293, 2025, DOI:10.32604/cmc.2024.058386 - 03 January 2025

Abstract Urban railways are vital means of public transportation in Korea. More than 30% of metropolitan residents use the railways, and this proportion is expected to increase. To enhance safety, the government has mandated the installation of closed-circuit televisions in all carriages by 2024. However, cameras still monitored humans. To address this limitation, we developed a dataset of risk factors and a smart detection system that enables an immediate response to any abnormal behavior and intensive monitoring thereof. We created an innovative learning dataset that takes into account seven unique risk factors specific to Korean railway More >

Congcong Wang¹, Chen Wang^2,3,*, Wenying Zheng^4,*, Wei Gu⁵

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 799-816, 2025, DOI:10.32604/cmc.2024.057975 - 03 January 2025

Abstract As smart grid technology rapidly advances, the vast amount of user data collected by smart meter presents significant challenges in data security and privacy protection. Current research emphasizes data security and user privacy concerns within smart grids. However, existing methods struggle with efficiency and security when processing large-scale data. Balancing efficient data processing with stringent privacy protection during data aggregation in smart grids remains an urgent challenge. This paper proposes an AI-based multi-type data aggregation method designed to enhance aggregation efficiency and security by standardizing and normalizing various data modalities. The approach optimizes data preprocessing, More >

Khalil Ullah^1,*, Song Jian¹, Muhammad Naeem Ul Hassan¹, Suliman Khan², Mohammad Babar^3,*, Arshad Ahmad⁴, Shafiq Ahmad⁵

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 1151-1169, 2025, DOI:10.32604/cmc.2024.057328 - 03 January 2025

Abstract The emergence of next generation networks (NextG), including 5G and beyond, is reshaping the technological landscape of cellular and mobile networks. These networks are sufficiently scaled to interconnect billions of users and devices. Researchers in academia and industry are focusing on technological advancements to achieve high-speed transmission, cell planning, and latency reduction to facilitate emerging applications such as virtual reality, the metaverse, smart cities, smart health, and autonomous vehicles. NextG continuously improves its network functionality to support these applications. Multiple input multiple output (MIMO) technology offers spectral efficiency, dependability, and overall performance in conjunction with More >

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 - 03 January 2025

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 >

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 - 03 January 2025

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 >

XIANG LI^1,#, WENKE JIN^2,#, LIFENG WU², HUAN WANG¹, XIN XIE¹, WEI HUANG^1,*, BO LIU^2,*

Oncology Research, Vol.33, No.1, pp. 67-81, 2025, DOI:10.32604/or.2024.055921 - 20 December 2024

Abstract Background: Triple-negative breast cancer (TNBC), characterized by its lack of traditional hormone receptors and HER2, presents a significant challenge in oncology due to its poor response to conventional therapies. Autophagy is an important process for maintaining cellular homeostasis, and there are currently autophagy biomarkers that play an effective role in the clinical treatment of tumors. In contrast to targeting protein activity, intervention with protein-protein interaction (PPI) can avoid unrelated crosstalk and regulate the autophagy process with minimal interference pathways. Methods: Here, we employed Naive Bayes, Decision Tree, and k-Nearest Neighbors to elucidate the complex PPI… More >