Jianhua Liu^*, Jincheng Wei, Rongxin Luo, Guilin Yuan, Jiajia Liu, Xiaoguang Tu

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1337-1361, 2024, DOI:10.32604/cmc.2024.056286 - 15 October 2024

Abstract With the rapid advancement of Internet of Vehicles (IoV) technology, the demands for real-time navigation, advanced driver-assistance systems (ADAS), vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications, and multimedia entertainment systems have made in-vehicle applications increasingly computing-intensive and delay-sensitive. These applications require significant computing resources, which can overwhelm the limited computing capabilities of vehicle terminals despite advancements in computing hardware due to the complexity of tasks, energy consumption, and cost constraints. To address this issue in IoV-based edge computing, particularly in scenarios where available computing resources in vehicles are scarce, a multi-master and multi-slave double-layer game model More >

Yizhuo Zhu¹, Shaosi He², Deming Lei^2,*

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 843-866, 2024, DOI:10.32604/cmc.2024.054473 - 15 October 2024

Abstract Unrelated parallel machine scheduling problem (UPMSP) is a typical scheduling one and UPMSP with various real-life constraints such as additional resources has been widely studied; however, UPMSP with additional resources, maintenance, and energy-related objectives is seldom investigated. The Artificial Bee Colony (ABC) algorithm has been successfully applied to various production scheduling problems and demonstrates potential search advantages in solving UPMSP with additional resources, among other factors. In this study, an energy-efficient UPMSP with additional resources and maintenance is considered. A dynamical artificial bee colony (DABC) algorithm is presented to minimize makespan and total energy consumption… 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 - 17 July 2024

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 >

Shasha Zhao^1,2,3,*, Huanwen Yan^1,2, Qifeng Lin^1,2, Xiangnan Feng^1,2, He Chen^1,2, Dengyin Zhang^1,2

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1135-1156, 2024, DOI:10.32604/cmc.2024.045660 - 30 January 2024

Abstract Task scheduling plays a key role in effectively managing and allocating computing resources to meet various computing tasks in a cloud computing environment. Short execution time and low load imbalance may be the challenges for some algorithms in resource scheduling scenarios. In this work, the Hierarchical Particle Swarm Optimization-Evolutionary Artificial Bee Colony Algorithm (HPSO-EABC) has been proposed, which hybrids our presented Evolutionary Artificial Bee Colony (EABC), and Hierarchical Particle Swarm Optimization (HPSO) algorithm. The HPSO-EABC algorithm incorporates both the advantages of the HPSO and the EABC algorithm. Comprehensive testing including evaluations of algorithm convergence speed,… More >

Qiangfei Cao¹, Huilai Wang², Zijia Hui¹, Lingyun Chen^2,*

Energy Engineering, Vol.121, No.2, pp. 499-521, 2024, DOI:10.32604/ee.2023.042702 - 25 January 2024

Abstract Distribution generation (DG) technology based on a variety of renewable energy technologies has developed rapidly. A large number of multi-type DG are connected to the distribution network (DN), resulting in a decline in the stability of DN operation. It is urgent to find a method that can effectively connect multi-energy DG to DN. photovoltaic (PV), wind power generation (WPG), fuel cell (FC), and micro gas turbine (MGT) are considered in this paper. A multi-objective optimization model was established based on the life cycle cost (LCC) of DG, voltage quality, voltage fluctuation, system network loss, power… More >

Shazia Shamas¹, Surya Narayan Panda^1,*, Ishu Sharma^1,*, Kalpna Guleria¹, Aman Singh^2,3,4, Ahmad Ali AlZubi⁵, Mallak Ahmad AlZubi⁶

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1051-1075, 2024, DOI:10.32604/cmes.2023.030712 - 17 November 2023

Abstract The distinction and precise identification of tumor nodules are crucial for timely lung cancer diagnosis and planning intervention. This research work addresses the major issues pertaining to the field of medical image processing while focusing on lung cancer Computed Tomography (CT) images. In this context, the paper proposes an improved lung cancer segmentation technique based on the strengths of nature-inspired approaches. The better resolution of CT is exploited to distinguish healthy subjects from those who have lung cancer. In this process, the visual challenges of the K-means are addressed with the integration of four nature-inspired… More >

Yazeed Yasin Ghadi¹, Mohammed S. Alshehri², Sultan Almakdi², Oumaima Saidani^3,*, Nazik Alturki³, Fawad Masood⁴, Muhammad Shahbaz Khan⁵

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 781-797, 2023, DOI:10.32604/cmc.2023.042777 - 31 October 2023

Abstract Securing digital image data is a key concern in today’s information-driven society. Effective encryption techniques are required to protect sensitive image data, with the Substitution-box (S-box) often playing a pivotal role in many symmetric encryption systems. This study introduces an innovative approach to creating S-boxes for encryption algorithms. The proposed S-boxes are tested for validity and non-linearity by incorporating them into an image encryption scheme. The nonlinearity measure of the proposed S-boxes is 112. These qualities significantly enhance its resistance to common cryptographic attacks, ensuring high image data security. Furthermore, to assess the robustness of… More >

Muhammad Naeem Akbar^1,*, Seemab Khan², Muhammad Umar Farooq¹, Majed Alhaisoni³, Usman Tariq⁴, Muhammad Usman Akram¹

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3275-3295, 2023, DOI:10.32604/cmc.2023.039289 - 08 October 2023

Abstract The combination of spatiotemporal videos and essential features can improve the performance of human action recognition (HAR); however, the individual type of features usually degrades the performance due to similar actions and complex backgrounds. The deep convolutional neural network has improved performance in recent years for several computer vision applications due to its spatial information. This article proposes a new framework called for video surveillance human action recognition dubbed HybridHR-Net. On a few selected datasets, deep transfer learning is used to pre-trained the EfficientNet-b0 deep learning model. Bayesian optimization is employed for the tuning of… More >

Huaixi Xing^*, Qinghua Xing

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 2685-2705, 2023, DOI:10.32604/cmc.2023.036223 - 08 October 2023

Abstract With the advancement of combat equipment technology and combat concepts, new requirements have been put forward for air defense operations during a group target attack. To achieve high-efficiency and low-loss defensive operations, a reasonable air defense weapon assignment strategy is a key step. In this paper, a multi-objective and multi-constraints weapon target assignment (WTA) model is established that aims to minimize the defensive resource loss, minimize total weapon consumption, and minimize the target residual effectiveness. An optimization framework of air defense weapon mission scheduling based on the multi-objective artificial bee colony (MOABC) algorithm is proposed.… More >

Hang Yang^1,2,*, Xunbo Li¹, Witold Pedrycz²

Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1531-1551, 2023, DOI:10.32604/iasc.2023.039256 - 21 June 2023

Abstract Energy supply is one of the most critical challenges of wireless sensor networks (WSNs) and industrial wireless sensor networks (IWSNs). While research on coverage optimization problem (COP) centers on the network’s monitoring coverage, this research focuses on the power banks’ energy supply coverage. The study of 2-D and 3-D spaces is typical in IWSN, with the realistic environment being more complex with obstacles (i.e., machines). A 3-D surface is the field of interest (FOI) in this work with the established hybrid power bank deployment model for the energy supply COP optimization of IWSN. The hybrid… More >