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  • Open Access

    ARTICLE

    Research on Facial Expression Capture Based on Two-Stage Neural Network

    Zhenzhou Wang1, Shao Cui1, Xiang Wang1,*, JiaFeng Tian2

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4709-4725, 2022, DOI:10.32604/cmc.2022.027767

    Abstract To generate realistic three-dimensional animation of virtual character, capturing real facial expression is the primary task. Due to diverse facial expressions and complex background, facial landmarks recognized by existing strategies have the problem of deviations and low accuracy. Therefore, a method for facial expression capture based on two-stage neural network is proposed in this paper which takes advantage of improved multi-task cascaded convolutional networks (MTCNN) and high-resolution network. Firstly, the convolution operation of traditional MTCNN is improved. The face information in the input image is quickly filtered by feature fusion in the first stage and Octave Convolution instead of the… More >

  • Open Access

    ARTICLE

    Efficient Routing Protection Algorithm Based on Optimized Network Topology

    Haijun Geng1,2, Zikun Jin1, Jiangyuan Yao3,*, Han Zhang4, Zhiguo Hu6, Bo Yang5, Yingije Guo7, Wei Wang1, Qidong Zhang1, Guoao Duan8

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4525-4540, 2022, DOI:10.32604/cmc.2022.027725

    Abstract Network failures are unavoidable and occur frequently. When the network fails, intra-domain routing protocols deploying on the Internet need to undergo a long convergence process. During this period, a large number of messages are discarded, which results in a decline in the user experience and severely affects the quality of service of Internet Service Providers (ISP). Therefore, improving the availability of intra-domain routing is a trending research question to be solved. Industry usually employs routing protection algorithms to improve intra-domain routing availability. However, existing routing protection schemes compute as many backup paths as possible to reduce message loss due to… More >

  • Open Access

    ARTICLE

    Optimal Deep Learning Enabled Statistical Analysis Model for Traffic Prediction

    Ashit Kumar Dutta1, S. Srinivasan2, S. N. Kumar3, T. S. Balaji4,5, Won Il Lee6, Gyanendra Prasad Joshi7, Sung Won Kim8,*

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5563-5576, 2022, DOI:10.32604/cmc.2022.027707

    Abstract Due to the advances of intelligent transportation system (ITSs), traffic forecasting has gained significant interest as robust traffic prediction acts as an important part in different ITSs namely traffic signal control, navigation, route mapping, etc. The traffic prediction model aims to predict the traffic conditions based on the past traffic data. For more accurate traffic prediction, this study proposes an optimal deep learning-enabled statistical analysis model. This study offers the design of optimal convolutional neural network with attention long short term memory (OCNN-ALSTM) model for traffic prediction. The proposed OCNN-ALSTM technique primarily pre-processes the traffic data by the use of… More >

  • Open Access

    ARTICLE

    Frequency Domain Adaptive Learning Algorithm for Thoracic Electrical Bioimpedance Enhancement

    Md Zia Ur Rahman1,*, S. Rooban1, P. Rohini2, M. V. S. Ramprasad3, Pradeep Vinaik Kodavanti3

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5713-5726, 2022, DOI:10.32604/cmc.2022.027672

    Abstract The Thoracic Electrical Bioimpedance (TEB) helps to determine the stroke volume during cardiac arrest. While measuring cardiac signal it is contaminated with artifacts. The commonly encountered artifacts are Baseline wander (BW) and Muscle artifact (MA), these are physiological and non-stationary. As the nature of these artifacts is random, adaptive filtering is needed than conventional fixed coefficient filtering techniques. To address this, a new block based adaptive learning scheme is proposed to remove artifacts from TEB signals in clinical scenario. The proposed block least mean square (BLMS) algorithm is mathematically normalized with reference to data and error. This normalization leads, block… More >

  • Open Access

    ARTICLE

    A Hybrid Grey DEMATEL and PLS-SEM Model to Investigate COVID-19 Vaccination Intention

    Phi-Hung Nguyen1,2,*

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5059-5078, 2022, DOI:10.32604/cmc.2022.027630

    Abstract The main objective of this study is to comprehensively investigate individuals’ vaccination intention against COVID-19 during the second wave of COVID-19 spread in Vietnam using a novel hybrid approach. First, the Decision-Making Trial and Evaluation Laboratory based on Grey Theory (DEMATEL-G) was employed to explore the critical factors of vaccination intention among individuals. Second, Partial Least Squares-Structural Equation Modeling (PLS-SEM) was applied to test the hypotheses of individual behavioral intention to get the vaccine to prevent the outbreak of COVID-19. A panel of 661 valid respondents was collected from June 2021 to July 2021, and confidentiality was maintained for all… More >

  • Open Access

    ARTICLE

    An Advanced Stochastic Numerical Approach for Host-Vector-Predator Nonlinear Model

    Prem Junswang1, Zulqurnain Sabir2, Muhammad Asif Zahoor Raja3, Soheil Salahshour4, Thongchai Botmart5,*, Wajaree Weera5

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5823-5843, 2022, DOI:10.32604/cmc.2022.027629

    Abstract A novel design of the computational intelligent framework is presented to solve a class of host-vector-predator nonlinear model governed with set of ordinary differential equations. The host-vector-predator nonlinear model depends upon five groups or classes, host plant susceptible and infected populations, vectors population of susceptible and infected individuals and the predator population. An unsupervised artificial neural network is designed using the computational framework of local and global search competencies of interior-point algorithm and genetic algorithms. For solving the host-vector-predator nonlinear model, a merit function is constructed using the differential model and its associated boundary conditions. The optimization of this merit… More >

  • Open Access

    ARTICLE

    Wheat Breeding Strategies under Climate Change based on CERES-Wheat Model

    Jintao Cui1,2,*, Jihui Ding3, Sheng Deng4, Guangcheng Shao3, Weiguang Wang1,2, Xiaojun Wang5, Yesilekin Nebi6

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 6107-6118, 2022, DOI:10.32604/cmc.2022.027611

    Abstract Climate change has inevitably had a negative impact on agricultural production and food security. Crop breeding improvement is an efficient option to adapt to future climate and increase grain production. To study the potential to provide valuable advice for breeding under climate change condition, the crop growth model was used as basis to investigate, the effects of the cultivar genotype parameters of the crop estimation through resource and environment synthesis-wheat (CERES-Wheat) model on yield under different climate scenarios. In this study, solar radiation had a positive effect on the yield of winter wheat, while the effects of daily temperature change… More >

  • Open Access

    ARTICLE

    Automatic Detection of Weapons in Surveillance Cameras Using Efficient-Net

    Erssa Arif1,*, Syed Khuram Shahzad2, Muhammad Waseem Iqbal3, Muhammad Arfan Jaffar4, Abdullah S. Alshahrani5, Ahmed Alghamdi6

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4615-4630, 2022, DOI:10.32604/cmc.2022.027571

    Abstract The conventional Close circuit television (CCTV) cameras-based surveillance and control systems require human resource supervision. Almost all the criminal activities take place using weapons mostly a handheld gun, revolver, pistol, swords etc. Therefore, automatic weapons detection is a vital requirement now a day. The current research is concerned about the real-time detection of weapons for the surveillance cameras with an implementation of weapon detection using Efficient–Net. Real time datasets, from local surveillance department's test sessions are used for model training and testing. Datasets consist of local environment images and videos from different type and resolution cameras that minimize the idealism.… More >

  • Open Access

    ARTICLE

    Power Allocation in NOMA-CR for 5G Enabled IoT Networks

    Mohammed Basheri1, Mohammad Haseeb Zafar1,2,3,*, Imran Khan3

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5515-5530, 2022, DOI:10.32604/cmc.2022.027532

    Abstract In the power domain, non-orthogonal multiple access (NOMA) supports multiple users on the same time-frequency resources, assigns different transmission powers to different users, and differentiates users by user channel gains. Multi-user signals are superimposed and transmitted in the power domain at the transmitting end by actively implementing controllable interference information, and multi-user detection algorithms, such as successive interference cancellation (SIC) is performed at the receiving end to demodulate the necessary user signals. In contrast to the orthogonal transmission method, the non-orthogonal method can achieve higher spectrum utilization. However, it will increase the receiver complexity. With the development of microelectronics technology,… More >

  • Open Access

    ARTICLE

    Intelligent Networks for Chaotic Fractional-Order Nonlinear Financial Model

    Prem Junswang1, Zulqurnain Sabir2, Muhammad Asif Zahoor Raja3, Waleed Adel4,5, Thongchai Botmart6,*, Wajaree Weera6

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5015-5030, 2022, DOI:10.32604/cmc.2022.027523

    Abstract The purpose of this paper is to present a numerical approach based on the artificial neural networks (ANNs) for solving a novel fractional chaotic financial model that represents the effect of memory and chaos in the presented system. The method is constructed with the combination of the ANNs along with the Levenberg-Marquardt backpropagation (LMB), named the ANNs-LMB. This technique is tested for solving the novel problem for three cases of the fractional-order values and the obtained results are compared with the reference solution. Fifteen numbers neurons have been used to solve the fractional-order chaotic financial model. The selection of the… More >

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