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  • Open Access

    ARTICLE

    PSO-DBNet for Peak-to-Average Power Ratio Reduction Using Deep Belief Network

    A. Jameer Basha1,*, M. Ramya Devi2, S. Lokesh1, P. Sivaranjani3, D. Mansoor Hussain4, Venkat Padhy5

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1483-1493, 2023, DOI:10.32604/csse.2023.021540

    Abstract Data transmission through a wireless network has faced various signal problems in the past decades. The orthogonal frequency division multiplexing (OFDM) technique is widely accepted in multiple data transfer patterns at various frequency bands. A recent wireless communication network uses OFDM in long-term evolution (LTE) and 5G, among others. The main problem faced by 5G wireless OFDM is distortion of transmission signals in the network. This transmission loss is called peak-to-average power ratio (PAPR). This wireless signal distortion can be reduced using various techniques. This study uses machine learning-based algorithm to solve the problem of PAPR in 5G wireless communication.… More >

  • Open Access

    ARTICLE

    Double Update Intelligent Strategy for Permanent Magnet Synchronous Motor Parameter Identification

    Shuai Zhou1, Dazhi Wang1,*, Mingtian Du2, Ye Li1, Shuo Cao3

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3391-3404, 2023, DOI:10.32604/cmc.2023.033397

    Abstract The parameters of permanent magnet synchronous motor (PMSM) affect the performance of vector control servo system. Because of the complexity of nonlinear model of PMSM, it is very difficult to identify the parameters of PMSM. Aiming at the problems of large amount of data calculation, low identification accuracy and poor robustness in the process of multi parameter identification of permanent magnet synchronous motor, this paper proposes a weighted differential evolutionary particle swarm optimization algorithm based on double update strategy. By introducing adaptive judgment factor to control the proportion of weighted difference evolution (WDE) algorithm and particle swarm optimization (PSO) algorithm… More >

  • Open Access

    ARTICLE

    Fusion Strategy for Improving Medical Image Segmentation

    Fahad Alraddady1, E. A. Zanaty2, Aida H. Abu bakr3, Walaa M. Abd-Elhafiez4,5,*

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3627-3646, 2023, DOI:10.32604/cmc.2023.027606

    Abstract In this paper, we combine decision fusion methods with four meta-heuristic algorithms (Particle Swarm Optimization (PSO) algorithm, Cuckoo search algorithm, modification of Cuckoo Search (CS McCulloch) algorithm and Genetic algorithm) in order to improve the image segmentation. The proposed technique based on fusing the data from Particle Swarm Optimization (PSO), Cuckoo search, modification of Cuckoo Search (CS McCulloch) and Genetic algorithms are obtained for improving magnetic resonance images (MRIs) segmentation. Four algorithms are used to compute the accuracy of each method while the outputs are passed to fusion methods. In order to obtain parts of the points that determine similar… More >

  • Open Access

    ARTICLE

    Dark-Forest: Analysis on the Behavior of Dark Web Traffic via DeepForest and PSO Algorithm

    Xin Tong1, Changlin Zhang2,*, Jingya Wang1, Zhiyan Zhao1, Zhuoxian Liu1

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 561-581, 2023, DOI:10.32604/cmes.2022.022495

    Abstract The dark web is a shadow area hidden in the depths of the Internet, which is difficult to access through common search engines. Because of its anonymity, the dark web has gradually become a hotbed for a variety of cyber-crimes. Although some research based on machine learning or deep learning has been shown to be effective in the task of analyzing dark web traffic in recent years, there are still pain points such as low accuracy, insufficient real-time performance, and limited application scenarios. Aiming at the difficulties faced by the existing automated dark web traffic analysis methods, a novel method… More >

  • Open Access

    ARTICLE

    An Optimal DPM Based Energy-Aware Task Scheduling for Performance Enhancement in Embedded MPSoC

    Hamayun Khan1,*, Irfan Ud Din2, Arshad Ali3, Mohammad Husain3

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 2097-2113, 2023, DOI:10.32604/cmc.2023.032999

    Abstract Minimizing the energy consumption to increase the life span and performance of multiprocessor system on chip (MPSoC) has become an integral chip design issue for multiprocessor systems. The performance measurement of computational systems is changing with the advancement in technology. Due to shrinking and smaller chip size power densities on-chip are increasing rapidly that increasing chip temperature in multi-core embedded technologies. The operating speed of the device decreases when power consumption reaches a threshold that causes a delay in complementary metal oxide semiconductor (CMOS) circuits because high on-chip temperature adversely affects the life span of the chip. In this paper… More >

  • Open Access

    ARTICLE

    A New Framework for Employing Responsive End-Users Using FAHP and PSO Algorithm

    Reza Etemad1, Mohammad Sadegh Ghazizadeh1, Mehrdad Ahmadi Kamarposhti2,*, Ilhami Colak3, Kei Eguchi4

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 951-964, 2023, DOI:10.32604/cmc.2023.032631

    Abstract The capacitor bank and synchronous condenser have been the only available sources of reactive power. Nowadays, most of the appliances use a power electronic interface for their connection. Applying a power electronic interface adds many features to these appliances. One of the promising features is their capability to interact with Volt-VAR programs. In this paper was investigated the reactive power interaction of the end-user appliances. For this purpose, the distribution network buses are ranked based on their effectiveness, followed by studying their interaction in the Volt-VAR program. To be able to consider the uncertainties, Probability Density Function (PDF) curve was… More >

  • Open Access

    ARTICLE

    Hybrid Global Optimization Algorithm for Feature Selection

    Ahmad Taher Azar1,2,*, Zafar Iqbal Khan2, Syed Umar Amin2, Khaled M. Fouad1,3

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 2021-2037, 2023, DOI:10.32604/cmc.2023.032183

    Abstract This paper proposes Parallelized Linear Time-Variant Acceleration Coefficients and Inertial Weight of Particle Swarm Optimization algorithm (PLTVACIW-PSO). Its designed has introduced the benefits of Parallel computing into the combined power of TVAC (Time-Variant Acceleration Coefficients) and IW (Inertial Weight). Proposed algorithm has been tested against linear, non-linear, traditional, and multiswarm based optimization algorithms. An experimental study is performed in two stages to assess the proposed PLTVACIW-PSO. Phase I uses 12 recognized Standard Benchmarks methods to evaluate the comparative performance of the proposed PLTVACIW-PSO vs. IW based Particle Swarm Optimization (PSO) algorithms, TVAC based PSO algorithms, traditional PSO, Genetic algorithms (GA),… More >

  • Open Access

    ARTICLE

    Energy-Efficient Scheduling Based on Task Migration Policy Using DPM for Homogeneous MPSoCs

    Hamayun Khan1,*, Irfan Ud din2, Arshad Ali3, Sami Alshmrany3

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 965-981, 2023, DOI:10.32604/cmc.2023.031223

    Abstract Increasing the life span and efficiency of Multiprocessor System on Chip (MPSoC) by reducing power and energy utilization has become a critical chip design challenge for multiprocessor systems. With the advancement of technology, the performance management of central processing unit (CPU) is changing. Power densities and thermal effects are quickly increasing in multi-core embedded technologies due to shrinking of chip size. When energy consumption reaches a threshold that creates a delay in complementary metal oxide semiconductor (CMOS) circuits and reduces the speed by 10%–15% because excessive on-chip temperature shortens the chip’s life cycle. In this paper, we address the scheduling… More >

  • Open Access

    ARTICLE

    An Improved Hybrid Indoor Positioning Algorithm via QPSO and MLP Signal Weighting

    Edgar Scavino1,*, Mohd Amiruddin Abd Rahman1, Zahid Farid2

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 379-397, 2023, DOI:10.32604/cmc.2023.023824

    Abstract Accurate location or positioning of people and self-driven devices in large indoor environments has become an important necessity The application of increasingly automated self-operating moving transportation units, in large indoor spaces demands a precise knowledge of their positions. Technologies like WiFi and Bluetooth, despite their low-cost and availability, are sensitive to signal noise and fading effects. For these reasons, a hybrid approach, which uses two different signal sources, has proven to be more resilient and accurate for the positioning determination in indoor environments. Hence, this paper proposes an improved hybrid technique to implement a fingerprinting based indoor positioning, using Received… More >

  • Open Access

    ARTICLE

    Tasks Scheduling in Cloud Environment Using PSO-BATS with MLRHE

    Anwar R Shaheen*, Sundar Santhosh Kumar

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2963-2978, 2023, DOI:10.32604/iasc.2023.025780

    Abstract Cloud computing plays a significant role in Information Technology (IT) industry to deliver scalable resources as a service. One of the most important factor to increase the performance of the cloud server is maximizing the resource utilization in task scheduling. The main advantage of this scheduling is to maximize the performance and minimize the time loss. Various researchers examined numerous scheduling methods to achieve Quality of Service (QoS) and to reduce execution time. However, it had disadvantages in terms of low throughput and high response time. Hence, this study aimed to schedule the task efficiently and to eliminate the faults… More >

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