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  • Open Access

    ARTICLE

    Combined CNN-LSTM Deep Learning Algorithms for Recognizing Human Physical Activities in Large and Distributed Manners: A Recommendation System

    Ameni Ellouze1, Nesrine Kadri2, Alaa Alaerjan3,*, Mohamed Ksantini1

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 351-372, 2024, DOI:10.32604/cmc.2024.048061

    Abstract Recognizing human activity (HAR) from data in a smartphone sensor plays an important role in the field of health to prevent chronic diseases. Daily and weekly physical activities are recorded on the smartphone and tell the user whether he is moving well or not. Typically, smartphones and their associated sensing devices operate in distributed and unstable environments. Therefore, collecting their data and extracting useful information is a significant challenge. In this context, the aim of this paper is twofold: The first is to analyze human behavior based on the recognition of physical activities. Using the results of physical activity detection… More >

  • Open Access

    ARTICLE

    Uncertainty-Aware Physical Simulation of Neural Radiance Fields for Fluids

    Haojie Lian1, Jiaqi Wang1, Leilei Chen2,*, Shengze Li3, Ruochen Cao4, Qingyuan Hu5, Peiyun Zhao1

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 1143-1163, 2024, DOI:10.32604/cmes.2024.048549

    Abstract This paper presents a novel framework aimed at quantifying uncertainties associated with the 3D reconstruction of smoke from 2D images. This approach reconstructs color and density fields from 2D images using Neural Radiance Field (NeRF) and improves image quality using frequency regularization. The NeRF model is obtained via joint training of multiple artificial neural networks, whereby the expectation and standard deviation of density fields and RGB values can be evaluated for each pixel. In addition, customized physics-informed neural network (PINN) with residual blocks and two-layer activation functions are utilized to input the density fields of the NeRF into Navier-Stokes equations… More >

  • Open Access

    ARTICLE

    Optimal Bidding Strategies of Microgrid with Demand Side Management for Economic Emission Dispatch Incorporating Uncertainty and Outage of Renewable Energy Sources

    Mousumi Basu1, Chitralekha Jena2, Baseem Khan3,4,*, Ahmed Ali4

    Energy Engineering, Vol.121, No.4, pp. 849-867, 2024, DOI:10.32604/ee.2024.043294

    Abstract In the restructured electricity market, microgrid (MG), with the incorporation of smart grid technologies, distributed energy resources (DERs), a pumped-storage-hydraulic (PSH) unit, and a demand response program (DRP), is a smarter and more reliable electricity provider. DER consists of gas turbines and renewable energy sources such as photovoltaic systems and wind turbines. Better bidding strategies, prepared by MG operators, decrease the electricity cost and emissions from upstream grid and conventional and renewable energy sources (RES). But it is inefficient due to the very high sporadic characteristics of RES and the very high outage rate. To solve these issues, this study… More >

  • Open Access

    ARTICLE

    SYSTEMATIC STRATEGY FOR MODELING AND OPTIMIZATION OF THERMAL SYSTEMS WITH DESIGN UNCERTAINTIES

    Po Ting Lin, Hae Chang Gea, Yogesh Jaluria*

    Frontiers in Heat and Mass Transfer, Vol.1, No.1, pp. 1-20, 2010, DOI:10.5098/hmt.v1.1.3003

    Abstract Thermal systems play significant roles in the engineering practice and our lives. To improve those thermal systems, it is necessary to model and optimize the design and the operating conditions. More importantly, the design uncertainties should be considered because the failures of the thermal systems may be very dangerous and produce large loss. This review paper focuses on a systematic strategy of modeling and optimizing of the thermal systems with the considerations of the design uncertainties. To demonstrate the proposed strategy, one of the complicated thermal systems, Chemical Vapor Deposition (CVD), is simulated, parametrically modeled, and optimized. The operating conditions,… More >

  • Open Access

    ARTICLE

    ON UNCERTAINTY AND LOCAL SENSITIVITY ANALYSIS FOR STEADY-STATE CONJUGATE HEAT TRANSFER PROBLEMS PART 1: EMISSIVITY, FLUID TEMPERATURE, AND CONDUCTANCE

    Christian Rauch*

    Frontiers in Heat and Mass Transfer, Vol.2, No.3, pp. 1-8, 2011, DOI:10.5098/hmt.v2.3.3006

    Abstract In recent years, significant effort has been placed into developing automated multi-physics simulation. The exchange of boundary conditions has lead to more realistic as well as more complex simulations with usually slower convergence rate when the coupling is being performed between two different codes. In this paper the equations of local sensitivities for element centered steady-state combined convection, conduction, and thermal radiation problems are being derived. A numerical analysis on the stability of the solution matrix is being conducted. Partial uncertainties and the relative importance of the heat transfer modes are investigated by their uncertainty factors and conclusions are being… More >

  • Open Access

    ARTICLE

    Research on Regulation Method of Energy Storage System Based on Multi-Stage Robust Optimization

    Zaihe Yang1,*, Shuling Wang1, Runhang Zhu1, Jiao Cui2, Ji Su2, Liling Chen3

    Energy Engineering, Vol.121, No.3, pp. 807-820, 2024, DOI:10.32604/ee.2023.028167

    Abstract To address the scheduling problem involving energy storage systems and uncertain energy, we propose a method based on multi-stage robust optimization. This approach aims to regulate the energy storage system by using a multi-stage robust optimal control method, which helps overcome the limitations of traditional methods in terms of time scale. The goal is to effectively utilize the energy storage power station system to address issues caused by unpredictable variations in environmental energy and fluctuating load throughout the day. To achieve this, a mathematical model is constructed to represent uncertain energy sources such as photovoltaic and wind power. The generalized… More >

  • Open Access

    ARTICLE

    An Effective Hybrid Model of ELM and Enhanced GWO for Estimating Compressive Strength of Metakaolin-Contained Cemented Materials

    Abidhan Bardhan1,*, Raushan Kumar Singh2, Mohammed Alatiyyah3, Sulaiman Abdullah Alateyah4,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1521-1555, 2024, DOI:10.32604/cmes.2023.044467

    Abstract This research proposes a highly effective soft computing paradigm for estimating the compressive strength (CS) of metakaolin-contained cemented materials. The proposed approach is a combination of an enhanced grey wolf optimizer (EGWO) and an extreme learning machine (ELM). EGWO is an augmented form of the classic grey wolf optimizer (GWO). Compared to standard GWO, EGWO has a better hunting mechanism and produces an optimal performance. The EGWO was used to optimize the ELM structure and a hybrid model, ELM-EGWO, was built. To train and validate the proposed ELM-EGWO model, a sum of 361 experimental results featuring five influencing factors was… More >

  • Open Access

    ARTICLE

    On the Application of Mixed Models of Probability and Convex Set for Time-Variant Reliability Analysis

    Fangyi Li*, Dachang Zhu*, Huimin Shi

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1981-1999, 2024, DOI:10.32604/cmes.2023.031332

    Abstract In time-variant reliability problems, there are a lot of uncertain variables from different sources. Therefore, it is important to consider these uncertainties in engineering. In addition, time-variant reliability problems typically involve a complex multilevel nested optimization problem, which can result in an enormous amount of computation. To this end, this paper studies the time-variant reliability evaluation of structures with stochastic and bounded uncertainties using a mixed probability and convex set model. In this method, the stochastic process of a limit-state function with mixed uncertain parameters is first discretized and then converted into a time-independent reliability problem. Further, to solve the… More >

  • Open Access

    ARTICLE

    An Improved CREAM Model Based on DS Evidence Theory and DEMATEL

    Zhihui Xu1, Shuwen Shang2, Yuntong Pu3, Xiaoyan Su2,*, Hong Qian2, Xiaolei Pan2

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2597-2617, 2024, DOI:10.32604/cmes.2023.031247

    Abstract Cognitive Reliability and Error Analysis Method (CREAM) is widely used in human reliability analysis (HRA). It defines nine common performance conditions (CPCs), which represent the factors that may affect human reliability and are used to modify the cognitive failure probability (CFP). However, the levels of CPCs are usually determined by domain experts, which may be subjective and uncertain. What’s more, the classic CREAM assumes that the CPCs are independent, which is unrealistic. Ignoring the dependence among CPCs will result in repeated calculations of the influence of the CPCs on CFP and lead to unreasonable reliability evaluation. To address the issue… More > Graphic Abstract

    An Improved CREAM Model Based on DS Evidence Theory and DEMATEL

  • Open Access

    ARTICLE

    Modified Black Widow Optimization-Based Enhanced Threshold Energy Detection Technique for Spectrum Sensing in Cognitive Radio Networks

    R. Saravanan1,*, R. Muthaiah1, A. Rajesh2

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2339-2356, 2024, DOI:10.32604/cmes.2023.030898

    Abstract This study develops an Enhanced Threshold Based Energy Detection approach (ETBED) for spectrum sensing in a cognitive radio network. The threshold identification method is implemented in the received signal at the secondary user based on the square law. The proposed method is implemented with the signal transmission of multiple outputs-orthogonal frequency division multiplexing. Additionally, the proposed method is considered the dynamic detection threshold adjustments and energy identification spectrum sensing technique in cognitive radio systems. In the dynamic threshold, the signal ratio-based threshold is fixed. The threshold is computed by considering the Modified Black Widow Optimization Algorithm (MBWO). So, the proposed… More > Graphic Abstract

    Modified Black Widow Optimization-Based Enhanced Threshold Energy Detection Technique for Spectrum Sensing in Cognitive Radio Networks

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