Hao Bai¹, Beiyuan Liu^2,*, Hongwen Liu³, Jupeng Zeng², Jian Ouyang⁴, Yipeng Liu¹

Energy Engineering, Vol.121, No.8, pp. 2191-2211, 2024, DOI:10.32604/ee.2024.049848

Abstract Most ground faults in distribution network are caused by insulation deterioration of power equipment. It is difficult to find the insulation deterioration of the distribution network in time, and the development trend of the initial insulation fault is unknown, which brings difficulties to the distribution inspection. In order to solve the above problems, a situational awareness method of the initial insulation fault of the distribution network based on a multi-feature index comprehensive evaluation is proposed. Firstly, the insulation situation evaluation index is selected by analyzing the insulation fault mechanism of the distribution network, and the… More >

Mingguan Zhao^1,4, Lida Liao^2,*, Penglong Liang¹, Meng Li¹, Xinsheng Dong¹, Yang Yang¹, Hongxia Wang¹, Zhenhao Zhang³

Energy Engineering, Vol.121, No.8, pp. 2313-2330, 2024, DOI:10.32604/ee.2024.048261

Abstract The rapid growth of distributed renewable energy penetration is promoting the evolution of the energy system toward decentralization and decentralized and digitized smart grids. This study was based on energy blockchain, and developed a dual-biding mechanism based on the real-time energy surplus and demand in the local smart grid, which is expected to enable reliable, affordable, and clean energy supply in smart communities. In the proposed system, economic benefits could be achieved by replacing fossil-fuel-based electricity with the high penetration of affordable solar PV electricity. The reduction of energy surplus realized by distributed energy production More >

Xingxing Zhang¹, Liang Liu^1,*, Yu Fan¹, Qian Zhou²

Computer Systems Science and Engineering, Vol.48, No.4, pp. 969-987, 2024, DOI:10.32604/csse.2024.046615

Abstract System calls are essential interfaces that enable applications to access and utilize the operating system’s services and resources. Attackers frequently exploit application’s vulnerabilities and misuse system calls to execute malicious code, aiming to elevate privileges and so on. Consequently, restricting the misuse of system calls becomes a crucial measure in ensuring system security. It is an effective method known as reducing the attack surface. Existing attack surface reduction techniques construct a global whitelist of system calls for the entire lifetime of the application, which is coarse-grained. In this paper, we propose a Fine-grained Function-level framework… More >

Punam Gulande^*, R. N. Awale

Computer Systems Science and Engineering, Vol.48, No.4, pp. 937-952, 2024, DOI:10.32604/csse.2024.046123

Abstract The study of gene expression has emerged as a vital tool for cancer diagnosis and prognosis, particularly with the advent of microarray technology that enables the measurement of thousands of genes in a single sample. While this wealth of data offers invaluable insights for disease management, the high dimensionality poses a challenge for multiclass classification. In this context, selecting relevant features becomes essential to enhance classification model performance. Swarm Intelligence algorithms have proven effective in addressing this challenge, owing to their ability to navigate intricate, non-linear feature-class relationships. This paper introduces a novel hybrid swarm More >

Meignanamoorthi Dhandapani^*, V. Vetriselvi, R. Aishwarya

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2449-2486, 2024, DOI:10.32604/cmes.2024.050986

Abstract The emergence of beyond 5G networks has the potential for seamless and intelligent connectivity on a global scale. Network slicing is crucial in delivering services for different, demanding vertical applications in this context. Next-generation applications have time-sensitive requirements and depend on the most efficient routing path to ensure packets reach their intended destinations. However, the existing IP (Internet Protocol) over a multi-domain network faces challenges in enforcing network slicing due to minimal collaboration and information sharing among network operators. Conventional inter-domain routing methods, like Border Gateway Protocol (BGP), cannot make routing decisions based on performance,… More >

Marya Iqbal¹, Yaser Hafeez¹, Nabil Almashfi², Amjad Alsirhani³, Faeiz Alserhani⁴, Sadia Ali¹, Mamoona Humayun^5,*, Muhammad Jamal⁶

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 5031-5049, 2024, DOI:10.32604/cmc.2024.051371

Abstract Embracing software product lines (SPLs) is pivotal in the dynamic landscape of contemporary software development. However, the flexibility and global distribution inherent in modern systems pose significant challenges to managing SPL variability, underscoring the critical importance of robust cybersecurity measures. This paper advocates for leveraging machine learning (ML) to address variability management issues and fortify the security of SPL. In the context of the broader special issue theme on innovative cybersecurity approaches, our proposed ML-based framework offers an interdisciplinary perspective, blending insights from computing, social sciences, and business. Specifically, it employs ML for demand analysis, More >

Chen Zhang¹, Liming Liu¹, Yufei Yang¹, Yu Sun¹, Jiaxu Ning², Yu Zhang³, Changsheng Zhang^1,4,*, Ying Guo⁴

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 5201-5223, 2024, DOI:10.32604/cmc.2024.050863

Abstract The flying foxes optimization (FFO) algorithm, as a newly introduced metaheuristic algorithm, is inspired by the survival tactics of flying foxes in heat wave environments. FFO preferentially selects the best-performing individuals. This tendency will cause the newly generated solution to remain closely tied to the candidate optimal in the search area. To address this issue, the paper introduces an opposition-based learning-based search mechanism for FFO algorithm (IFFO). Firstly, this paper introduces niching techniques to improve the survival list method, which not only focuses on the adaptability of individuals but also considers the population’s crowding degree More >

Imtiaz Ahmad¹, Tariq Hussain², Babar Shah³, Altaf Hussain⁴, Iqtidar Ali¹, Farman Ali^5,*

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3585-3629, 2024, DOI:10.32604/cmc.2024.050596

Abstract Numerous wireless networks have emerged that can be used for short communication ranges where the infrastructure-based networks may fail because of their installation and cost. One of them is a sensor network with embedded sensors working as the primary nodes, termed Wireless Sensor Networks (WSNs), in which numerous sensors are connected to at least one Base Station (BS). These sensors gather information from the environment and transmit it to a BS or gathering location. WSNs have several challenges, including throughput, energy usage, and network lifetime concerns. Different strategies have been applied to get over these… More >

Bui Van Cong¹, Cho Do Xuan^2,*

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3699-3723, 2024, DOI:10.32604/cmc.2024.050019

Abstract The detection of software vulnerabilities written in C and C++ languages takes a lot of attention and interest today. This paper proposes a new framework called DrCSE to improve software vulnerability detection. It uses an intelligent computation technique based on the combination of two methods: Rebalancing data and representation learning to analyze and evaluate the code property graph (CPG) of the source code for detecting abnormal behavior of software vulnerabilities. To do that, DrCSE performs a combination of 3 main processing techniques: (i) building the source code feature profiles, (ii) rebalancing data, and (iii) contrastive… More >

Yasser Hachaichi¹, Ayman E. Khedr¹, Amira M. Idrees^2,*

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4081-4105, 2024, DOI:10.32604/cmc.2024.048929

Abstract The diversity of data sources resulted in seeking effective manipulation and dissemination. The challenge that arises from the increasing dimensionality has a negative effect on the computation performance, efficiency, and stability of computing. One of the most successful optimization algorithms is Particle Swarm Optimization (PSO) which has proved its effectiveness in exploring the highest influencing features in the search space based on its fast convergence and the ability to utilize a small set of parameters in the search task. This research proposes an effective enhancement of PSO that tackles the challenge of randomness search which… More >