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  • 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 >

  • Open Access

    ARTICLE

    Power Scheduling with Max User Comfort in Smart Home: Performance Analysis and Tradeoffs

    Muhammad Irfan1, Ch. Anwar Ul Hassan2, Faisal Althobiani3, Nasir Ayub4,*, Raja Jalees Ul Hussen Khan5, Emad Ismat Ghandourah6, Majid A. Almas7, Saleh Mohammed Ghonaim3, V. R. Shamji3, Saifur Rahman1

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 1723-1740, 2023, DOI:10.32604/csse.2023.035141 - 09 February 2023

    Abstract The smart grid has enabled users to control their home energy more effectively and efficiently. A home energy management system (HEM) is a challenging task because this requires the most effective scheduling of intelligent home appliances to save energy. Here, we presented a meta-heuristic-based HEM system that integrates the Greywolf Algorithm (GWA) and Harmony Search Algorithms (HSA). Moreover, a fusion initiated on HSA and GWA operators is used to optimize energy intake. Furthermore, many knapsacks are being utilized to ensure that peak-hour load usage for electricity customers does not surpass a certain edge. Hybridization has… More >

  • Open Access

    ARTICLE

    A New Hybrid Approach Using GWO and MFO Algorithms to Detect Network Attack

    Hasan Dalmaz*, Erdal Erdal, Halil Murat Ünver

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1277-1314, 2023, DOI:10.32604/cmes.2023.025212 - 06 February 2023

    Abstract This paper addresses the urgent need to detect network security attacks, which have increased significantly in recent years, with high accuracy and avoid the adverse effects of these attacks. The intrusion detection system should respond seamlessly to attack patterns and approaches. The use of metaheuristic algorithms in attack detection can produce near-optimal solutions with low computational costs. To achieve better performance of these algorithms and further improve the results, hybridization of algorithms can be used, which leads to more successful results. Nowadays, many studies are conducted on this topic. In this study, a new hybrid… More >

  • Open Access

    ARTICLE

    CFD Analysis of Spiral Flow Fields in Proton Exchange Membrane Fuel Cells

    Jian Yao, Fayi Yan*, Xuejian Pei

    FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.6, pp. 1425-1445, 2023, DOI:10.32604/fdmp.2023.025282 - 30 January 2023

    Abstract Proton exchange membrane fuel cells (PEMFCs) are largely used in various applications because of their pollution-free products and high energy conversion efficiency. In order to improve the related design, in the present work a new spiral flow field with a bypass is proposed. The reaction gas enters the flow field in the central path and diffuses in two directions through the flow channel and the bypass. The bypasses are arranged incrementally. The number of bypasses and the cross-section size of the bypasses are varied parametrically while a single-cell model of the PEMFC is used. The More > Graphic Abstract

    CFD Analysis of Spiral Flow Fields in Proton Exchange Membrane Fuel Cells

  • Open Access

    ARTICLE

    Moth Flame Optimization Based FCNN for Prediction of Bugs in Software

    C. Anjali*, Julia Punitha Malar Dhas, J. Amar Pratap Singh

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1241-1256, 2023, DOI:10.32604/iasc.2023.029678 - 05 January 2023

    Abstract The software engineering technique makes it possible to create high-quality software. One of the most significant qualities of good software is that it is devoid of bugs. One of the most time-consuming and costly software procedures is finding and fixing bugs. Although it is impossible to eradicate all bugs, it is feasible to reduce the number of bugs and their negative effects. To broaden the scope of bug prediction techniques and increase software quality, numerous causes of software problems must be identified, and successful bug prediction models must be implemented. This study employs a hybrid… More >

  • Open Access

    ARTICLE

    Multi-label Emotion Classification of COVID–19 Tweets with Deep Learning and Topic Modelling

    K. Anuratha1,*, M. Parvathy2

    Computer Systems Science and Engineering, Vol.45, No.3, pp. 3005-3021, 2023, DOI:10.32604/csse.2023.031553 - 21 December 2022

    Abstract The COVID-19 pandemic has become one of the severe diseases in recent years. As it majorly affects the common livelihood of people across the universe, it is essential for administrators and healthcare professionals to be aware of the views of the community so as to monitor the severity of the spread of the outbreak. The public opinions are been shared enormously in microblogging media like twitter and is considered as one of the popular sources to collect public opinions in any topic like politics, sports, entertainment etc., This work presents a combination of Intensity Based… More >

  • Open Access

    ARTICLE

    Comparative Study of Two Materials Combining a Standard Building Material with a PCM

    Marwa El Yassi1,2,*, Ikram El Abbassi1,2, Alexandre Pierre2, Yannick Melinge3

    FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.5, pp. 1283-1290, 2023, DOI:10.32604/fdmp.2022.023183 - 30 November 2022

    Abstract Phase change materials (PCMs) have the ability to store thermal energy and make it available at a later stage to keep indoor temperature within a specific range and achieve better thermal comfort in buildings. This study focuses on the performances of materials obtained by combining a standard building material with a PCM. In particular, two different materials mixed with the same PCM are considered under the same climatic conditions. The related thermal behavior is assessed in the framework of numerical simulations conducted with ANSYS Fluent assuming parameters representative of a city located in Europe. The More >

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