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  • Open Access

    ARTICLE

    Examining the Use of Scott’s Formula and Link Expiration Time Metric for Vehicular Clustering

    Fady Samann1,2,*, Shavan Askar3

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2421-2444, 2024, DOI:10.32604/cmes.2023.031265

    Abstract Implementing machine learning algorithms in the non-conducive environment of the vehicular network requires some adaptations due to the high computational complexity of these algorithms. K-clustering algorithms are simplistic, with fast performance and relative accuracy. However, their implementation depends on the initial selection of clusters number (K), the initial clusters’ centers, and the clustering metric. This paper investigated using Scott’s histogram formula to estimate the K number and the Link Expiration Time (LET) as a clustering metric. Realistic traffic flows were considered for three maps, namely Highway, Traffic Light junction, and Roundabout junction, to study the effect of road layout on… More >

  • Open Access

    ARTICLE

    Modeling Geometrically Nonlinear FG Plates: A Fast and Accurate Alternative to IGA Method Based on Deep Learning

    Se Li1, Tiantang Yu1,*, Tinh Quoc Bui2

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2793-2808, 2024, DOI:10.32604/cmes.2023.030278

    Abstract Isogeometric analysis (IGA) is known to show advanced features compared to traditional finite element approaches. Using IGA one may accurately obtain the geometrically nonlinear bending behavior of plates with functional grading (FG). However, the procedure is usually complex and often is time-consuming. We thus put forward a deep learning method to model the geometrically nonlinear bending behavior of FG plates, bypassing the complex IGA simulation process. A long bidirectional short-term memory (BLSTM) recurrent neural network is trained using the load and gradient index as inputs and the displacement responses as outputs. The nonlinear relationship between the outputs and the inputs… More >

  • Open Access

    ARTICLE

    A DRYING AND THERMOELASTIC MODEL FOR FAST MICROWAVE HEATING OF CONCRETE

    Benjamin Lepersa,*, Aditya Putrantob,c, Martin Ummingerd, Guido Linka, John Jelonneka

    Frontiers in Heat and Mass Transfer, Vol.5, pp. 1-11, 2014, DOI:10.5098/hmt.5.13

    Abstract The use of high power microwaves to perform explosive spalling of surface concrete is a promising technique with applications in the area of concrete facilities decommissioning. The mechanism that creates explosive spalling is an interactive process of the thermal stress from high temperature gradients and the pore pressure generated from the water vaporization. In order to better predict the total stress distribution, the temperature has to be calculated by including the effect of water vaporization and water transport through a porous medium. In this paper, a one dimensional model solving the heat and diffusion equation for liquid and vapor phase… More >

  • Open Access

    ARTICLE

    Visualization for Explanation of Deep Learning-Based Fault Diagnosis Model Using Class Activation Map

    Youming Guo, Qinmu Wu*

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1489-1514, 2023, DOI:10.32604/cmc.2023.042313

    Abstract Permanent magnet synchronous motor (PMSM) is widely used in various production processes because of its high efficiency, fast reaction time, and high power density. With the continuous promotion of new energy vehicles, timely detection of PMSM faults can significantly reduce the accident rate of new energy vehicles, further enhance consumers’ trust in their safety, and thus promote their popularity. Existing fault diagnosis methods based on deep learning can only distinguish different PMSM faults and cannot interpret and analyze them. Convolutional neural networks (CNN) show remarkable accuracy in image data analysis. However, due to the “black box” problem in deep learning… More >

  • Open Access

    ARTICLE

    Knowledge-Based Efficient N-1 Analysis Calculation Method for Urban Distribution Networks with CIM File Data

    Lingyu Liang1, Xiangyu Zhao1,*, Wenqi Huang1, Liming Sun2,3, Ziyao Wang3, Yaosen Zhan2

    Energy Engineering, Vol.120, No.12, pp. 2839-2856, 2023, DOI:10.32604/ee.2023.042042

    Abstract The N-1 criterion is a critical factor for ensuring the reliable and resilient operation of electric power distribution networks. However, the increasing complexity of distribution networks and the associated growth in data size have created a significant challenge for distribution network planners. To address this issue, we propose a fast N-1 verification procedure for urban distribution networks that combines CIM file data analysis with MILP-based mathematical modeling. Our proposed method leverages the principles of CIM file analysis for distribution network N-1 analysis. We develop a mathematical model of distribution networks based on CIM data and transfer it into MILP. We… More >

  • Open Access

    ARTICLE

    A NEURAL NETWORK BASED METHOD FOR ESTIMATION OF HEAT GENERATION FROM A TEFLON CYLINDER

    Sharath Kumar, Harsha Kumar, N. Gnanasekaran*

    Frontiers in Heat and Mass Transfer, Vol.7, pp. 1-7, 2016, DOI:10.5098/hmt.7.15

    Abstract The paper reports the estimation of volumetric heat generation (qv) from a Teflon cylinder. An aluminum heater, which acts as a heat source, is placed at the center of the Teflon cylinder. The problem under consideration is modeled as a three dimensional steady state conjugate heat transfer from the Teflon cylinder. The model is created and simulations are performed using ANSYS FLUENT to obtain temperature data for the known heat generation qv. The numerical model developed using ANSYS acts as a forward model. The inverse model used in this work is Artificial Neural Network (ANN). Estimation of heat generation is… More >

  • Open Access

    ARTICLE

    Fast and Accurate Detection of Masked Faces Using CNNs and LBPs

    Sarah M. Alhammad1, Doaa Sami Khafaga1,*, Aya Y. Hamed2, Osama El-Koumy3, Ehab R. Mohamed3, Khalid M. Hosny3

    Computer Systems Science and Engineering, Vol.47, No.3, pp. 2939-2952, 2023, DOI:10.32604/csse.2023.041011

    Abstract Face mask detection has several applications, including real-time surveillance, biometrics, etc. Identifying face masks is also helpful for crowd control and ensuring people wear them publicly. With monitoring personnel, it is impossible to ensure that people wear face masks; automated systems are a much superior option for face mask detection and monitoring. This paper introduces a simple and efficient approach for masked face detection. The architecture of the proposed approach is very straightforward; it combines deep learning and local binary patterns to extract features and classify them as masked or unmasked. The proposed system requires hardware with minimal power consumption… More >

  • Open Access

    ARTICLE

    Experimental Investigation on the Strength and Ductility Performance of SteelTimber-Steel Joints with Screw and Steel-Tube Fasteners

    Huifeng Yang, Mingwang Wu, Rixin Gu, Hang Cao, Kai Xiao, Benkai Shi*

    Journal of Renewable Materials, Vol.11, No.12, pp. 4175-4195, 2023, DOI:10.32604/jrm.2023.028507

    Abstract This article presents experimental results of steel-timber-steel (STS) joints loaded parallel to grain. Eight groups of specimens were designed, and tensile tests were performed. The fastener types and fastener numbers were considered to evaluate the tensile strengths and ductility performances of the STS joints. The screws with 6 mm diameter and the innovative steel-tubes with 18 mm diameter were adopted as connecting fasteners. The experimental results were discussed in terms of yielding and ultimate strengths, slip stiffness, and ductility factors. The ductility classification and failure mechanisms of each group of specimens were analyzed. It was demonstrated that the STS joint… More >

  • Open Access

    ARTICLE

    Deep Learning-Based Model for Detection of Brinjal Weed in the Era of Precision Agriculture

    Jigna Patel1, Anand Ruparelia1, Sudeep Tanwar1,*, Fayez Alqahtani2, Amr Tolba3, Ravi Sharma4, Maria Simona Raboaca5,6,*, Bogdan Constantin Neagu7

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 1281-1301, 2023, DOI:10.32604/cmc.2023.038796

    Abstract The overgrowth of weeds growing along with the primary crop in the fields reduces crop production. Conventional solutions like hand weeding are labor-intensive, costly, and time-consuming; farmers have used herbicides. The application of herbicide is effective but causes environmental and health concerns. Hence, Precision Agriculture (PA) suggests the variable spraying of herbicides so that herbicide chemicals do not affect the primary plants. Motivated by the gap above, we proposed a Deep Learning (DL) based model for detecting Eggplant (Brinjal) weed in this paper. The key objective of this study is to detect plant and non-plant (weed) parts from crop images.… More >

  • Open Access

    PROCEEDINGS

    Design Sensitivity Analysis of Thin-Body Acoustic Problems Above an Infinite Impedance Plane by Using a Fast Multipole Indirect BEM

    Menghui Liang1, Changjun Zheng1,*, Yongbin Zhang1, Chuanxing Bi1

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.1, pp. 1-1, 2023, DOI:10.32604/icces.2023.09605

    Abstract This paper presents an accurate and efficient indirect boundary element method (IBEM) accelerated by the fast multipole algorithm (FMA)for the design sensitivity analysis of large-scale thin-body acoustic problems above an infinite impedance plane. The non-uniqueness issue of the IBEM in solving exterior acoustic problems is avoided by applying a hybrid combination of single- and double-layer potentials. The half-space impedance Green’s function which involves an image complex line source and is valid for both mass-like and spring-like impedance plane is employed to involve the sound-absorbing effect of the ground surface. Explicit evaluation formulations of the singular boundary integrals are derived and… More >

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