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Intelligent Computing Techniques and Their Real Life Applications

Submission Deadline: 31 December 2023 (closed)

Guest Editors

Dr. Nitish Pathak, Guru Gobind Singh Indraprastha University (GGSIPU), India.
Dr. Shabana Urooj, Princess Nourah bint Abdulrahman University, Saudi Arabia.
Dr. Neelam Sharma, Guru Gobind Singh Indraprastha University (GGSIPU), India.

Summary

In the present era of research and technology, several emerging concepts like Fog, Edge, and Big Data Analytics can support for design and development of intelligent systems in diverse domains, e.g., Transportation, Education, Healthcare and Industry etc. Artificial Intelligence, Intelligent Computing Techniques, and Deep Learning are offering practical tools for many Sustainable healthcare applications and systems. Artificial Intelligence, Intelligent Computing Techniques and Deep Learning are offering practical tools for many engineering applications. Computer learning, artificial intelligence and its learning, adaptation paradigms are able to improve engineering applications. This decade is really about adding intelligence to different devices, services, etc. We have been confronted with a new IoT-The intelligence of things. It means that AI/IoT will in the near future logically and effortlessly interrelate with human experts and operators, providing them with articulate clarifications and answers, even at the edge of the network or in robotic devices and navigation. Moreover, we shall witness the exploration of IoT cooperation, navigation at highest form autonomous automation navigation, wireless sensor network and Cloud integration. In this thematic issue, we solicit the submission of high-quality original research and articles closely related to the following topics, particularly interdisciplinary submissions that bring together next generation Intelligence of Things, Artificial intelligence, Smart information processing, IoT security, AI techniques and optimization algorithms. 
• Intelligent Computing Systems and their Applications
• Intelligent Communication Systems
• Machine Learning for Data Science
• AIoT, IoT, AI Role, techniques, and optimization algorithms for healthcare industrial-level real life Applications 
• Soft Computing for Emerging Applications
• High performance Computing systems for applications in healthcare and recommendation
• AI-driven cloud/fog-assisted Big-data intelligent analytic frameworks for healthcare sector and healthcare information technology
• Machine learning algorithms for medical imaging and pattern recognition
• Intelligent wearable and assistive robotic devices for healthcare
• AI-based health recommender systems
• Intelligent decision making systems for computer-aided diagnostic systems
• Healthcare data analytics with predictive data analytics and risk measures
• Artificial Intelligence for Engineering Applications
• Optimization Algorithms


Keywords

• Intelligent Computing Systems and their Applications
• Intelligent Communication Systems
• Machine Learning for Data Science
• AIoT, IoT, AI Role, techniques, and optimization algorithms for healthcare industrial-level real life Applications 
• Soft Computing for Emerging Applications
• High performance Computing systems for applications in healthcare and recommendation
• AI-driven cloud/fog-assisted Big-data intelligent analytic frameworks for healthcare sector and healthcare information technology
• Machine learning algorithms for medical imaging and pattern recognition
• Intelligent wearable and assistive robotic devices for healthcare
• AI-based health recommender systems
• Intelligent decision making systems for computer-aided diagnostic systems
• Healthcare data analytics with predictive data analytics and risk measures
• Artificial Intelligence for Engineering Applications
• Optimization Algorithms

Published Papers


  • Open Access

    ARTICLE

    A Hybrid Machine Learning Approach for Improvised QoE in Video Services over 5G Wireless Networks

    K. B. Ajeyprasaath, P. Vetrivelan
    CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2023.046911
    (This article belongs to this Special Issue: Intelligent Computing Techniques and Their Real Life Applications)
    Abstract Video streaming applications have grown considerably in recent years. As a result, this becomes one of the most significant contributors to global internet traffic. According to recent studies, the telecommunications industry loses millions of dollars due to poor video Quality of Experience (QoE) for users. Among the standard proposals for standardizing the quality of video streaming over internet service providers (ISPs) is the Mean Opinion Score (MOS). However, the accurate finding of QoE by MOS is subjective and laborious, and it varies depending on the user. A fully automated data analytics framework is required to reduce the inter-operator variability characteristic… More >

  • Open Access

    ARTICLE

    Using Improved Particle Swarm Optimization Algorithm for Location Problem of Drone Logistics Hub

    Li Zheng, Gang Xu, Wenbin Chen
    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 935-957, 2024, DOI:10.32604/cmc.2023.046006
    (This article belongs to this Special Issue: Intelligent Computing Techniques and Their Real Life Applications)
    Abstract Drone logistics is a novel method of distribution that will become prevalent. The advantageous location of the logistics hub enables quicker customer deliveries and lower fuel consumption, resulting in cost savings for the company’s transportation operations. Logistics firms must discern the ideal location for establishing a logistics hub, which is challenging due to the simplicity of existing models and the intricate delivery factors. To simulate the drone logistics environment, this study presents a new mathematical model. The model not only retains the aspects of the current models, but also considers the degree of transportation difficulty from the logistics hub to… More >

  • Open Access

    ARTICLE

    A Strengthened Dominance Relation NSGA-III Algorithm Based on Differential Evolution to Solve Job Shop Scheduling Problem

    Liang Zeng, Junyang Shi, Yanyan Li, Shanshan Wang, Weigang Li
    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 375-392, 2024, DOI:10.32604/cmc.2023.045803
    (This article belongs to this Special Issue: Intelligent Computing Techniques and Their Real Life Applications)
    Abstract The job shop scheduling problem is a classical combinatorial optimization challenge frequently encountered in manufacturing systems. It involves determining the optimal execution sequences for a set of jobs on various machines to maximize production efficiency and meet multiple objectives. The Non-dominated Sorting Genetic Algorithm III (NSGA-III) is an effective approach for solving the multi-objective job shop scheduling problem. Nevertheless, it has some limitations in solving scheduling problems, including inadequate global search capability, susceptibility to premature convergence, and challenges in balancing convergence and diversity. To enhance its performance, this paper introduces a strengthened dominance relation NSGA-III algorithm based on differential evolution… More >

  • Open Access

    ARTICLE

    An Improved Whale Optimization Algorithm for Global Optimization and Realized Volatility Prediction

    Xiang Wang, Liangsa Wang, Han Li, Yibin Guo
    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 2935-2969, 2023, DOI:10.32604/cmc.2023.044948
    (This article belongs to this Special Issue: Intelligent Computing Techniques and Their Real Life Applications)
    Abstract The original whale optimization algorithm (WOA) has a low initial population quality and tends to converge to local optimal solutions. To address these challenges, this paper introduces an improved whale optimization algorithm called OLCHWOA, incorporating a chaos mechanism and an opposition-based learning strategy. This algorithm introduces chaotic initialization and opposition-based initialization operators during the population initialization phase, thereby enhancing the quality of the initial whale population. Additionally, including an elite opposition-based learning operator significantly improves the algorithm’s global search capabilities during iterations. The work and contributions of this paper are primarily reflected in two aspects. Firstly, an improved whale algorithm… More >

  • Open Access

    ARTICLE

    Design Optimization of Permanent Magnet Eddy Current Coupler Based on an Intelligence Algorithm

    Dazhi Wang, Pengyi Pan, Bowen Niu
    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1535-1555, 2023, DOI:10.32604/cmc.2023.042286
    (This article belongs to this Special Issue: Intelligent Computing Techniques and Their Real Life Applications)
    Abstract The permanent magnet eddy current coupler (PMEC) solves the problem of flexible connection and speed regulation between the motor and the load and is widely used in electrical transmission systems. It provides torque to the load and generates heat and losses, reducing its energy transfer efficiency. This issue has become an obstacle for PMEC to develop toward a higher power. This paper aims to improve the overall performance of PMEC through multi-objective optimization methods. Firstly, a PMEC modeling method based on the Levenberg-Marquardt back propagation (LMBP) neural network is proposed, aiming at the characteristics of the complex input-output relationship and… More >

  • Open Access

    ARTICLE

    A Novel Human Interaction Framework Using Quadratic Discriminant Analysis with HMM

    Tanvir Fatima Naik Bukht, Naif Al Mudawi, Saud S. Alotaibi, Abdulwahab Alazeb, Mohammed Alonazi, Aisha Ahmed AlArfaj, Ahmad Jalal, Jaekwang Kim
    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1557-1573, 2023, DOI:10.32604/cmc.2023.041335
    (This article belongs to this Special Issue: Intelligent Computing Techniques and Their Real Life Applications)
    Abstract Human-human interaction recognition is crucial in computer vision fields like surveillance, human-computer interaction, and social robotics. It enhances systems’ ability to interpret and respond to human behavior precisely. This research focuses on recognizing human interaction behaviors using a static image, which is challenging due to the complexity of diverse actions. The overall purpose of this study is to develop a robust and accurate system for human interaction recognition. This research presents a novel image-based human interaction recognition method using a Hidden Markov Model (HMM). The technique employs hue, saturation, and intensity (HSI) color transformation to enhance colors in video frames,… More >

  • Open Access

    ARTICLE

    Multi-Objective Image Optimization of Product Appearance Based on Improved NSGA-Ⅱ

    Yinxue Ao, Jian Lv, Qingsheng Xie, Zhengming Zhang
    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3049-3074, 2023, DOI:10.32604/cmc.2023.040088
    (This article belongs to this Special Issue: Intelligent Computing Techniques and Their Real Life Applications)
    Abstract A second-generation fast Non-dominated Sorting Genetic Algorithm product shape multi-objective imagery optimization model based on degradation (DNSGA-II) strategy is proposed to make the product appearance optimization scheme meet the complex emotional needs of users for the product. First, the semantic differential method and K-Means cluster analysis are applied to extract the multi-objective imagery of users; then, the product multidimensional scale analysis is applied to classify the research objects, and again the reference samples are screened by the semantic differential method, and the samples are parametrized in two dimensions by using elliptic Fourier analysis; finally, the fuzzy dynamic evaluation function is… More >

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