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  • Open Access

    PROCEEDINGS

    Topological Design of Negative Poisson’s Ratio Material Microstructure Under Large Deformation with a Gradient-Free Method

    Pai Liu1,*, Weida Wu1, Yangjun Luo1, Yifan Zhang1

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.2, pp. 1-1, 2023, DOI:10.32604/icces.2023.09893

    Abstract Lightweight metamaterials with negative Poisson’s ratios (NPRs) have great potential for controlling deformation, absorbing energy, etc. The topology optimization [1] technique is an effective way to design metamaterials. However, as studied in [2], the NPR metamaterial configuration obtained under small deformation assumption may not maintain the desired Poisson’s ratio under relatively large deformation conditions. This paper focuses on the large-deformation NPR metamaterial design based on a gradient-free topology optimization method, i.e. the material-field series expansion (MFSE) method [3]. The metamaterial’s performance is evaluated using the finite element method, taking into account the geometry nonlinearity. By… More >

  • Open Access

    ARTICLE

    Speed Measurement Feasibility by Eddy Current Effect in the High-Speed MFL Testing

    Zhaoting Liu1, Jianbo Wu1,*, Sha He2, Xin Rao3, Shiqiang Wang2, Shen Wang1, Wei Wei4

    Structural Durability & Health Monitoring, Vol.17, No.4, pp. 299-314, 2023, DOI:10.32604/sdhm.2023.022554 - 02 August 2023

    Abstract It is known that eddy current effect has a great influence on magnetic flux leakage testing (MFL). Usually, contact-type encoder wheels are used to measure MFL testing speed to evaluate the effect and further compensate testing signals. This speed measurement method is complicated, and inevitable abrasion and occasional slippage will reduce the measurement accuracy. In order to solve this problem, based on eddy current effect due to the relative movement, a speed measurement method is proposed, which is contactless and simple. In the high-speed MFL testing, eddy current induced in the specimen will cause an More > Graphic Abstract

    Speed Measurement Feasibility by Eddy Current Effect in the High-Speed MFL Testing

  • Open Access

    ARTICLE

    Fractional Processing Based Adaptive Beamforming Algorithm

    Syed Asghar Ali Shah1, Tariqullah Jan1, Syed Muslim Shah2, Ruhul Amin Khalil1,*, Ahmad Sawalmeh3, Muhammad Anan4

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 1065-1084, 2023, DOI:10.32604/cmc.2023.039826 - 08 June 2023

    Abstract Fractional order algorithms have shown promising results in various signal processing applications due to their ability to improve performance without significantly increasing complexity. The goal of this work is to investigate the use of fractional order algorithm in the field of adaptive beamforming, with a focus on improving performance while keeping complexity lower. The effectiveness of the algorithm will be studied and evaluated in this context. In this paper, a fractional order least mean square (FLMS) algorithm is proposed for adaptive beamforming in wireless applications for effective utilization of resources. This algorithm aims to improve… More >

  • Open Access

    ARTICLE

    MFF-Net: Multimodal Feature Fusion Network for 3D Object Detection

    Peicheng Shi1,*, Zhiqiang Liu1, Heng Qi1, Aixi Yang2

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5615-5637, 2023, DOI:10.32604/cmc.2023.037794 - 29 April 2023

    Abstract In complex traffic environment scenarios, it is very important for autonomous vehicles to accurately perceive the dynamic information of other vehicles around the vehicle in advance. The accuracy of 3D object detection will be affected by problems such as illumination changes, object occlusion, and object detection distance. To this purpose, we face these challenges by proposing a multimodal feature fusion network for 3D object detection (MFF-Net). In this research, this paper first uses the spatial transformation projection algorithm to map the image features into the feature space, so that the image features are in the… More >

  • Open Access

    ARTICLE

    Peer Pressure and Harmful Use of Alcohol in Thailand: A Spatial Autoregressive Model Application

    Ravikan Nonkhuntod, Suchuan Yu*

    International Journal of Mental Health Promotion, Vol.25, No.5, pp. 613-626, 2023, DOI:10.32604/ijmhp.2023.025648 - 28 April 2023

    Abstract Due to peer pressure playing a crucial role in the decision to drink, people who have a more fragile temperament might be expected to be at higher risk. Moreover, many studies have investigated the influence of peer pressure on alcohol consumption, but few have examined the relationship between heavy drinking and peer pressure via a spatial autoregressive model (SAR) in low/middle-income countries, such as Thailand. This paper investigated the connection between heavy drinkers over the age of 15 years who drink more than or equal to 60 grams of unmixed alcohol at least once per… More >

  • Open Access

    ARTICLE

    Performance Analysis of Three Spectrum Sensing Detection Techniques with Ambient Backscatter Communication in Cognitive Radio Networks

    Shayla Islam1, Anil Kumar Budati1,*, Mohammad Kamrul Hasan2, Saoucene Mahfoudh3, Syed Bilal Hussian Shah3

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 813-825, 2023, DOI:10.32604/cmes.2023.027595 - 23 April 2023

    Abstract In wireless communications, the Ambient Backscatter Communication (AmBC) technique is a promising approach, detecting user presence accurately at low power levels. At low power or a low Signal-to-Noise Ratio (SNR), there is no dedicated power for the users. Instead, they can transmit information by reflecting the ambient Radio Frequency (RF) signals in the spectrum. Therefore, it is essential to detect user presence in the spectrum for the transmission of data without loss or without collision at a specific time. In this paper, the authors proposed a novel Spectrum Sensing (SS) detection technique in the Cognitive… More >

  • Open Access

    ARTICLE

    Experimental Mode and Vibration Comfort Analysis of High-Rise Glulam Building Floor Structure

    Yuhang He, Rongzhuo Zhang, Yifan Zhang, Zheng Wang*

    Journal of Renewable Materials, Vol.11, No.6, pp. 2729-2743, 2023, DOI:10.32604/jrm.2023.025867 - 27 April 2023

    Abstract In order to better meet the objective requirements of the use safety of the high-rise glulam building floor structure and the living comfort of the residents, the transient excitation, environmental excitation and frequency spectrum identification methods were used to carry out experimental modal test in-site on the three rooms numbered A, B and C of the same glulam structural building. The three rooms have different functions, different floor sizes and different floor supporting structures. The research results have shown that the first-order bending frequency of the floor structure of Room A is 27.50 Hz, the… More > Graphic Abstract

    Experimental Mode and Vibration Comfort Analysis of High-Rise Glulam Building Floor Structure

  • Open Access

    ARTICLE

    Real-Time Multi-Feature Approximation Model-Based Efficient Brain Tumor Classification Using Deep Learning Convolution Neural Network Model

    Amarendra Reddy Panyala1,2, M. Baskar3,*

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3883-3899, 2023, DOI:10.32604/csse.2023.037050 - 03 April 2023

    Abstract The deep learning models are identified as having a significant impact on various problems. The same can be adapted to the problem of brain tumor classification. However, several deep learning models are presented earlier, but they need better classification accuracy. An efficient Multi-Feature Approximation Based Convolution Neural Network (CNN) model (MFA-CNN) is proposed to handle this issue. The method reads the input 3D Magnetic Resonance Imaging (MRI) images and applies Gabor filters at multiple levels. The noise-removed image has been equalized for its quality by using histogram equalization. Further, the features like white mass, grey… More >

  • Open Access

    ARTICLE

    SMOGN, MFO, and XGBoost Based Excitation Current Prediction Model for Synchronous Machine

    Ping-Huan Kuo1,2, Yu-Tsun Chen1, Her-Terng Yau1,2,*

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 2687-2709, 2023, DOI:10.32604/csse.2023.036293 - 03 April 2023

    Abstract The power factor is the ratio between the active and apparent power, and it is available to determine the operational capability of the intended circuit or the parts. The excitation current of the synchronous motor is an essential parameter required for adjusting the power factor because it determines whether the motor is under the optimal operating status. Although the excitation current should predict with the experimental devices, such a method is unsuitable for online real-time prediction. The artificial intelligence algorithm can compensate for the defect of conventional measurement methods requiring the measuring devices and the… More >

  • Open Access

    ARTICLE

    MAQMC: Multi-Agent Deep Q-Network for Multi-Zone Residential HVAC Control

    Zhengkai Ding1,2, Qiming Fu1,2,*, Jianping Chen2,3,4,*, You Lu1,2, Hongjie Wu1, Nengwei Fang4, Bin Xing4

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2759-2785, 2023, DOI:10.32604/cmes.2023.026091 - 09 March 2023

    Abstract The optimization of multi-zone residential heating, ventilation, and air conditioning (HVAC) control is not an easy task due to its complex dynamic thermal model and the uncertainty of occupant-driven cooling loads. Deep reinforcement learning (DRL) methods have recently been proposed to address the HVAC control problem. However, the application of single-agent DRL for multi-zone residential HVAC control may lead to non-convergence or slow convergence. In this paper, we propose MAQMC (Multi-Agent deep Q-network for multi-zone residential HVAC Control) to address this challenge with the goal of minimizing energy consumption while maintaining occupants’ thermal comfort. MAQMC… More >

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