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Search Results (18)
  • Open Access

    ARTICLE

    Hybrid Task Scheduling Algorithm for Makespan Optimisation in Cloud Computing: A Performance Evaluation

    Abdulrahman M. Abdulghani*

    Journal on Artificial Intelligence, Vol.6, pp. 241-259, 2024, DOI:10.32604/jai.2024.056259 - 16 October 2024

    Abstract Cloud computing has rapidly evolved into a critical technology, seamlessly integrating into various aspects of daily life. As user demand for cloud services continues to surge, the need for efficient virtualization and resource management becomes paramount. At the core of this efficiency lies task scheduling, a complex process that determines how tasks are allocated and executed across cloud resources. While extensive research has been conducted in the area of task scheduling, optimizing multiple objectives simultaneously remains a significant challenge due to the NP (Non-deterministic Polynomial) Complete nature of the problem. This study aims to address… More >

  • Open Access

    ARTICLE

    Contact Stress Reliability Analysis Model for Cylindrical Gear with Circular Arc Tooth Trace Based on an Improved Metamodel

    Qi Zhang1,2,4,5, Zhixin Chen3, Yang Wu4,*, Guoqi Xiang2, Guang Wen1, Xuegang Zhang2, Yongchun Xie2, Guangchun Yang2

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 593-619, 2024, DOI:10.32604/cmes.2023.046319 - 16 April 2024

    Abstract Although there is currently no unified standard theoretical formula for calculating the contact stress of cylindrical gears with a circular arc tooth trace (referred to as CATT gear), a mathematical model for determining the contact stress of CATT gear is essential for studying how parameters affect its contact stress and building the contact stress limit state equation for contact stress reliability analysis. In this study, a mathematical relationship between design parameters and contact stress is formulated using the Kriging Metamodel. To enhance the model’s accuracy, we propose a new hybrid algorithm that merges the genetic… More >

  • Open Access

    ARTICLE

    Hybrid Optimization Algorithm for Handwritten Document Enhancement

    Shu-Chuan Chu1, Xiaomeng Yang1, Li Zhang2, Václav Snášel3, Jeng-Shyang Pan1,4,*

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3763-3786, 2024, DOI:10.32604/cmc.2024.048594 - 26 March 2024

    Abstract The Gannet Optimization Algorithm (GOA) and the Whale Optimization Algorithm (WOA) demonstrate strong performance; however, there remains room for improvement in convergence and practical applications. This study introduces a hybrid optimization algorithm, named the adaptive inertia weight whale optimization algorithm and gannet optimization algorithm (AIWGOA), which addresses challenges in enhancing handwritten documents. The hybrid strategy integrates the strengths of both algorithms, significantly enhancing their capabilities, whereas the adaptive parameter strategy mitigates the need for manual parameter setting. By amalgamating the hybrid strategy and parameter-adaptive approach, the Gannet Optimization Algorithm was refined to yield the AIWGOA. More >

  • Open Access

    ARTICLE

    Hybrid Algorithm-Driven Smart Logistics Optimization in IoT-Based Cyber-Physical Systems

    Abdulwahab Ali Almazroi1,*, Nasir Ayub2

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3921-3942, 2023, DOI:10.32604/cmc.2023.046602 - 26 December 2023

    Abstract Effectively managing complex logistics data is essential for development sustainability and growth, especially in optimizing distribution routes. This article addresses the limitations of current logistics path optimization methods, such as inefficiencies and high operational costs. To overcome these drawbacks, we introduce the Hybrid Firefly-Spotted Hyena Optimization (HFSHO) algorithm, a novel approach that combines the rapid exploration and global search abilities of the Firefly Algorithm (FO) with the localized search and region-exploitation skills of the Spotted Hyena Optimization Algorithm (SHO). HFSHO aims to improve logistics path optimization and reduce operational costs. The algorithm’s effectiveness is systematically… More >

  • Open Access

    ARTICLE

    Automated X-ray Defect Inspection on Occluded BGA Balls Using Hybrid Algorithm

    Ki-Yeol Eom1, Byungseok Min2,*

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 6337-6350, 2023, DOI:10.32604/cmc.2023.035336 - 29 April 2023

    Abstract Automated X-ray defect inspection of occluded objects has been an essential topic in semiconductors, autonomous vehicles, and artificial intelligence devices. However, there are few solutions to segment occluded objects in the X-ray inspection efficiently. In particular, in the Ball Grid Array inspection of X-ray images, it is difficult to accurately segment the regions of occluded solder balls and detect defects inside solder balls. In this paper, we present a novel automatic inspection algorithm that segments solder balls, and detects defects fast and efficiently when solder balls are occluded. The proposed algorithm consists of two stages.… More >

  • Open Access

    ARTICLE

    Enhanced Detection of Cerebral Atherosclerosis Using Hybrid Algorithm of Image Segmentation

    Shakunthala Masi*, Helenprabha Kuttiappan

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 733-744, 2023, DOI:10.32604/iasc.2023.025919 - 29 September 2022

    Abstract In medical science for envisaging human body’s phenomenal structure a major part has been driven by image processing techniques. Major objective of this work is to detect of cerebral atherosclerosis for image segmentation application. Detection of some abnormal structures in human body has become a difficult task to complete with some simple images. For expounding and distinguishing neural architecture of human brain in an effective manner, MRI (Magnetic Resonance Imaging) is one of the most suitable and significant technique. Here we work on detection of Cerebral Atherosclerosis from MRI images of patients. Cerebral Atherosclerosis is… More >

  • Open Access

    ARTICLE

    Detecting and Preventing of Attacks in Cloud Computing Using Hybrid Algorithm

    R. S. Aashmi1, T. Jaya2,*

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 79-95, 2023, DOI:10.32604/iasc.2023.024291 - 06 June 2022

    Abstract

    Cloud computing is the technology that is currently used to provide users with infrastructure, platform, and software services effectively. Under this system, Platform as a Service (PaaS) offers a medium headed for a web development platform that uniformly distributes the requests and resources. Hackers using Denial of service (DoS) and Distributed Denial of Service (DDoS) attacks abruptly interrupt these requests. Even though several existing methods like signature-based, statistical anomaly-based, and stateful protocol analysis are available, they are not sufficient enough to get rid of Denial of service (DoS) and Distributed Denial of Service (DDoS) attacks

    More >

  • Open Access

    ARTICLE

    Near Term Hybrid Quantum Computing Solution to the Matrix Riccati Equations

    Augusto González Bonorino1,*, Malick Ndiaye2, Casimer DeCusatis2

    Journal of Quantum Computing, Vol.4, No.3, pp. 135-146, 2022, DOI:10.32604/jqc.2022.036706 - 03 July 2023

    Abstract The well-known Riccati differential equations play a key role in many fields, including problems in protein folding, control and stabilization, stochastic control, and cybersecurity (risk analysis and malware propagation). Quantum computer algorithms have the potential to implement faster approximate solutions to the Riccati equations compared with strictly classical algorithms. While systems with many qubits are still under development, there is significant interest in developing algorithms for near-term quantum computers to determine their accuracy and limitations. In this paper, we propose a hybrid quantum-classical algorithm, the Matrix Riccati Solver (MRS). This approach uses a transformation of More >

  • Open Access

    ARTICLE

    A Hybrid Neural Network-based Approach for Forecasting Water Demand

    Al-Batool Al-Ghamdi1,*, Souad Kamel2, Mashael Khayyat3

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1365-1383, 2022, DOI:10.32604/cmc.2022.026246 - 18 May 2022

    Abstract Water is a vital resource. It supports a multitude of industries, civilizations, and agriculture. However, climatic conditions impact water availability, particularly in desert areas where the temperature is high, and rain is scarce. Therefore, it is crucial to forecast water demand to provide it to sectors either on regular or emergency days. The study aims to develop an accurate model to forecast daily water demand under the impact of climatic conditions. This forecasting is known as a multivariate time series because it uses both the historical data of water demand and climatic conditions to forecast… More >

  • Open Access

    ARTICLE

    A Novel Approach Based on Hybrid Algorithm for Energy Efficient Cluster Head Identification in Wireless Sensor Networks

    C. Ram Kumar1,*, K. Murali Krishna2, Mohammad Shabbir Alam3, K. Vigneshwaran4, Sridharan Kannan5, C. Bharatiraja6

    Computer Systems Science and Engineering, Vol.43, No.1, pp. 259-273, 2022, DOI:10.32604/csse.2022.023477 - 23 March 2022

    Abstract The Wireless Sensor Networks (WSN) is a self-organizing network with random deployment of wireless nodes that connects each other for effective monitoring and data transmission. The clustering technique employed to group the collection of nodes for data transmission and each node is assigned with a cluster head. The major concern with the identification of the cluster head is the consideration of energy consumption and hence this paper proposes an hybrid model which forms an energy efficient cluster head in the Wireless Sensor Network. The proposed model is a hybridization of Glowworm Swarm Optimization (GSO) and More >

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