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  • Open Access

    ARTICLE

    Human Gait Recognition Using Deep Learning and Improved Ant Colony Optimization

    Awais Khan1, Muhammad Attique Khan1, Muhammad Younus Javed1, Majed Alhaisoni2, Usman Tariq3, Seifedine Kadry4, Jung-In Choi5, Yunyoung Nam6,*

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2113-2130, 2022, DOI:10.32604/cmc.2022.018270

    Abstract Human gait recognition (HGR) has received a lot of attention in the last decade as an alternative biometric technique. The main challenges in gait recognition are the change in in-person view angle and covariant factors. The major covariant factors are walking while carrying a bag and walking while wearing a coat. Deep learning is a new machine learning technique that is gaining popularity. Many techniques for HGR based on deep learning are presented in the literature. The requirement of an efficient framework is always required for correct and quick gait recognition. We proposed a fully automated deep learning and improved… More >

  • Open Access

    ARTICLE

    Fuzzy Based Ant Colony Optimization Scheduling in Cloud Computing

    K. Rajakumari1,*, M.Vinoth Kumar2, Garima Verma3, S. Balu4, Dilip Kumar Sharma5, Sudhakar Sengan6

    Computer Systems Science and Engineering, Vol.40, No.2, pp. 581-592, 2022, DOI:10.32604/csse.2022.019175

    Abstract Cloud computing is an Information Technology deployment model established on virtualization. Task scheduling states the set of rules for task allocations to an exact virtual machine in the cloud computing environment. However, task scheduling challenges such as optimal task scheduling performance solutions, are addressed in cloud computing. First, the cloud computing performance due to task scheduling is improved by proposing a Dynamic Weighted Round-Robin algorithm. This recommended DWRR algorithm improves the task scheduling performance by considering resource competencies, task priorities, and length. Second, a heuristic algorithm called Hybrid Particle Swarm Parallel Ant Colony Optimization is proposed to solve the task… More >

  • Open Access

    ARTICLE

    Artificial Intelligence Based Reliable Load Balancing Framework in Software-Defined Networks

    Mohammad Riyaz Belgaum1, Fuead Ali1, Zainab Alansari2, Shahrulniza Musa1,*, Muhammad Mansoor Alam1,3, M. S. Mazliham4

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 251-266, 2022, DOI:10.32604/cmc.2022.018211

    Abstract Software-defined networking (SDN) plays a critical role in transforming networking from traditional to intelligent networking. The increasing demand for services from cloud users has increased the load on the network. An efficient system must handle various loads and increasing needs representing the relationships and dependence of businesses on automated measurement systems and guarantee the quality of service (QoS). The multiple paths from source to destination give a scope to select an optimal path by maintaining an equilibrium of load using some best algorithms. Moreover, the requests need to be transferred to reliable network elements. To address SDN’s current and future… More >

  • Open Access

    ARTICLE

    Remote Health Monitoring Using IoT-Based Smart Wireless Body Area Network

    Farhan Aadil1, Bilal Mehmood1, Najam Ul Hasan2, Sangsoon Lim3,*, Sadia Ejaz1, Noor Zaman4

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2499-2513, 2021, DOI:10.32604/cmc.2021.014647

    Abstract A wireless body area network (WBAN) consists of tiny health-monitoring sensors implanted in or placed on the human body. These sensors are used to collect and communicate human medical and physiological data and represent a subset of the Internet of Things (IoT) systems. WBANs are connected to medical servers that monitor patients’ health. This type of network can protect critical patients’ lives due to the ability to monitor patients’ health continuously and remotely. The inter-WBAN communication provides a dynamic environment for patients allowing them to move freely. However, during patient movement, the WBAN patient nodes may become out of range… More >

  • Open Access

    ARTICLE

    Reconstruction and Optimization of Complex Network Community Structure under Deep Learning and Quantum Ant Colony Optimization Algorithm

    Peng Mei1, Gangyi Ding1, Qiankun Jin1, Fuquan Zhang2,*, Yeh-Cheng Chen3

    Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 159-171, 2021, DOI:10.32604/iasc.2021.012813

    Abstract Community structure is a key component in complex network systems. This paper aims to improve the effectiveness of community detection and community discovery in complex network systems by providing directions for the reconstruction and optimization of community structures to expand the application of intelligent optimization algorithms in community structures. First, deep learning algorithms and ant colony algorithms are used to elaborate the community detection and community discovery in complex networks. Next, we introduce the technology of transfer learning and propose an algorithm of deep self-encoder modeling based on transfer learning (DSEM-TL). The DSEM-TL algorithm’s indicators include normalized mutual information and… More >

  • Open Access

    ARTICLE

    IWD-Miner: A Novel Metaheuristic Algorithm for Medical Data Classification

    Sarab AlMuhaideb*, Reem BinGhannam, Nourah Alhelal, Shatha Alduheshi, Fatimah Alkhamees, Raghad Alsuhaibani

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1329-1346, 2021, DOI:10.32604/cmc.2020.013576

    Abstract Medical data classification (MDC) refers to the application of classification methods on medical datasets. This work focuses on applying a classification task to medical datasets related to specific diseases in order to predict the associated diagnosis or prognosis. To gain experts’ trust, the prediction and the reasoning behind it are equally important. Accordingly, we confine our research to learn rule-based models because they are transparent and comprehensible. One approach to MDC involves the use of metaheuristic (MH) algorithms. Here we report on the development and testing of a novel MH algorithm: IWD-Miner. This algorithm can be viewed as a fusion… More >

  • Open Access

    ARTICLE

    Personalized Nutrition Recommendation for Diabetic Patients Using Optimization Techniques

    Bhavithra Janakiraman1,*, Saradha Arumugam2

    Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 269-280, 2020, DOI:10.31209/2019.100000150

    Abstract Personalization in recommendation system has been emerging as the most predominant area in service computing. Collaborative filtering and content based approaches are two major techniques applied for recommendation. However, to improve the accuracy and enhance user satisfaction, optimization techniques such as Ant Colony and Particle Swarm Optimization were analyzed in this paper. For theoretical analysis, this paper investigates web page recommender system. For experimentation, Diabetic patient’s health records were investigated and recommendation algorithms are applied to suggest appropriate nutrition for improving their health. Experiment result shows that Particle Swarm Optimization outperforms other traditional methods with improved performance and accuracy. More >

  • Open Access

    ARTICLE

    Hybrid Soft Computing Technique Based Trust Evaluation Protocol for Wireless Sensor Networks

    Supreet Kaur*, Vijay Kumar Joshi

    Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 217-226, 2020, DOI:10.31209/2018.100000064

    Abstract Wireless sensor networks (WSNs) are susceptible to safety threats due to cumulative dependence upon transmission, computing, and control mechanisms. Therefore, securing the end-to-end communication becomes a major area of research in WSNs. A majority of existing protocols are based upon signature and recommended-based trust evaluation techniques only. However, these techniques are vulnerable to wormhole attacks that happen due to lesser synchronization between the sensor nodes. Therefore, to handle this problem, a novel hybrid crossover-based ant colony optimization-based routing protocol is proposed. An integrated modified signature and recommendationbased trust evaluation protocol for WSNs is presented. Extensive experiments reveal that the proposed… More >

  • Open Access

    ARTICLE

    Discrete Wavelet Transmission and Modified PSO with ACO Based Feed Forward Neural Network Model for Brain Tumour Detection

    Machiraju Jayalakshmi1, *, S. Nagaraja Rao2

    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1081-1096, 2020, DOI:10.32604/cmc.2020.011710

    Abstract In recent years, the development in the field of computer-aided diagnosis (CAD) has increased rapidly. Many traditional machine learning algorithms have been proposed for identifying the pathological brain using magnetic resonance images. The existing algorithms have drawbacks with respect to their accuracy, efficiency, and limited learning processes. To address these issues, we propose a pathological brain tumour detection method that utilizes the Weiner filter to improve the image contrast, 2D- discrete wavelet transformation (2D-DWT) to extract the features, probabilistic principal component analysis (PPCA) and linear discriminant analysis (LDA) to normalize and reduce the features, and a feed-forward neural network (FNN)… More >

  • Open Access

    ARTICLE

    Feature Selection and Representation of Evolutionary Algorithm on Keystroke Dynamics

    Purvashi Baynath, Sunjiv Soyjaudah, Maleika Heenaye-Mamode Khan

    Intelligent Automation & Soft Computing, Vol.25, No.4, pp. 651-661, 2019, DOI:10.31209/2018.100000060

    Abstract The goal of this paper is (i) adopt fusion of features (ii) determine the best method of feature selection technique among ant Colony optimisation, artificial bee colony optimisation and genetic algorithm. The experimental results reported that ant colony Optimisation is a promising techniques as feature selection on Keystroke Dynamics as it outperforms in terms of recognition rate for our inbuilt database where the distance between the keys has been considered for the password derivation with recognition rate 97.85%. Finally the results have shown that a small improvement is obtained by fused features, which suggest that an effective fusion is necessary. More >

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