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  • Open Access


    An Improved Two-stream Inflated 3D ConvNet for Abnormal Behavior Detection

    Jiahui Pan1,2,*, Liangxin Liu1, Mianfen Lin1, Shengzhou Luo1, Chengju Zhou1, Huijian Liao3, Fei Wang1,2

    Intelligent Automation & Soft Computing, Vol.30, No.2, pp. 673-688, 2021, DOI:10.32604/iasc.2021.020240

    Abstract Abnormal behavior detection is an essential step in a wide range of application domains, such as smart video surveillance. In this study, we proposed an improved two-stream inflated 3D ConvNet network approach based on probability regression for abnormal behavior detection. The proposed approach consists of four parts: (1) preprocessing pretreatment for the input video; (2) dynamic feature extraction from video streams using a two-stream inflated 3D (I3D) ConvNet network; (3) visual feature transfer into a two-dimensional matrix; and (4) feature classification using a generalized regression neural network (GRNN), which ultimately achieves a probability regression. Compared… More >

  • Open Access


    Utilizing Blockchain Technology to Improve WSN Security for Sensor Data Transmission

    Sung-Jung Hsiao1, Wen-Tsai Sung2,*

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 1899-1918, 2021, DOI:10.32604/cmc.2021.015762

    Abstract This paper proposes a method for improving the data security of wireless sensor networks based on blockchain technology. Blockchain technology is applied to data transfer to build a highly secure wireless sensor network. In this network, the relay stations use microcontrollers and embedded devices, and the microcontrollers, such as Raspberry Pi and Arduino Yun, represents mobile databases. The proposed system uses microcontrollers to facilitate the connection of various sensor devices. By adopting blockchain encryption, the security of sensing data can be effectively improved. A blockchain is a concatenated transaction record that is protected by cryptography.… More >

  • Open Access


    Time Series Facebook Prophet Model and Python for COVID-19 Outbreak Prediction

    Mashael Khayyat1,*, Kaouther Laabidi2, Nada Almalki1, Maysoon Al-zahrani1

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3781-3793, 2021, DOI:10.32604/cmc.2021.014918

    Abstract COVID-19 comes from a large family of viruses identified in 1965; to date, seven groups have been recorded which have been found to affect humans. In the healthcare industry, there is much evidence that Al or machine learning algorithms can provide effective models that solve problems in order to predict confirmed cases, recovered cases, and deaths. Many researchers and scientists in the field of machine learning are also involved in solving this dilemma, seeking to understand the patterns and characteristics of virus attacks, so scientists may make the right decisions and take specific actions. Furthermore,… More >

  • Open Access


    A Novel Approach for the Numerical Simulation of Fluid-Structure Interaction Problems in the Presence of Debris

    Miaomiao Ren*, Xiaobin Shu

    FDMP-Fluid Dynamics & Materials Processing, Vol.16, No.5, pp. 979-991, 2020, DOI:10.32604/fdmp.2020.09563

    Abstract A novel algorithm is proposed for the simulation of fluid-structure interaction problems. In particular, much attention is paid to natural phenomena such as debris flow. The fluid part (debris flow fluid) is simulated in the framework of the smoothed particle hydrodynamics (SPH) approach, while the solid part (downstream obstacles) is treated using the finite element method (FEM). Fluid-structure coupling is implemented through dynamic boundary conditions. In particular, the software “TensorFlow” and an algorithm based on Python are combined to conduct the required calculations. The simulation results show that the dynamics of viscous and non-viscous debris More >

  • Open Access


    A Failure-Predicting Intelligent PYTHON (IP) Code for Monitoring A Crack of Irregular Shape in A Pipe#

    Jeffrey T. Fong1,*, Pedro V. Marcal2, Robert Rainsberger3, N. A. Heckert1, J. J. Filliben1

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.21, No.2, pp. 45-45, 2019, DOI:10.32604/icces.2019.05432

    Abstract When a small crack is detected in a pressure vessel or piping, we can estimate the fatigue life of the vessel or piping by applying the classical law of fracture mechanics for crack growth if we are certain that the crack growth exponent is correct and the crack geometry is a simple plane. Unfortunately, for an ageing vessel or piping, the degradation will change the crack growth exponent, and the crack will advance not in a simple planar fashion. To validate the crack growth exponent for an ageing vessel or piping with a crack of… More >

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