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  • Open Access

    ARTICLE

    Heterophilic Graph Neural Network Based on Spatial and Frequency Domain Adaptive Embedding Mechanism

    Lanze Zhang, Yijun Gu*, Jingjie Peng

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1701-1731, 2024, DOI:10.32604/cmes.2023.045129 - 29 January 2024

    Abstract Graph Neural Networks (GNNs) play a significant role in tasks related to homophilic graphs. Traditional GNNs, based on the assumption of homophily, employ low-pass filters for neighboring nodes to achieve information aggregation and embedding. However, in heterophilic graphs, nodes from different categories often establish connections, while nodes of the same category are located further apart in the graph topology. This characteristic poses challenges to traditional GNNs, leading to issues of “distant node modeling deficiency” and “failure of the homophily assumption”. In response, this paper introduces the Spatial-Frequency domain Adaptive Heterophilic Graph Neural Networks (SFA-HGNN), which… More >

  • Open Access

    ARTICLE

    Reliability-Based Model for Incomplete Preventive Replacement Maintenance of Photovoltaic Power Systems

    Wei Chen, Ming Li*, Tingting Pei, Cunyu Sun, Huan Lei

    Energy Engineering, Vol.121, No.1, pp. 125-144, 2024, DOI:10.32604/ee.2023.042812 - 27 December 2023

    Abstract At present, the operation and maintenance of photovoltaic power generation systems mainly comprise regular maintenance, breakdown maintenance, and condition-based maintenance, which is very likely to lead to over- or under-repair of equipment. Therefore, a preventive maintenance and replacement strategy for PV power generation systems based on reliability as a constraint is proposed. First, a hybrid failure function with a decreasing service age factor and an increasing failure rate factor is introduced to describe the deterioration of PV power generation equipment, and the equipment is replaced when its reliability drops to the replacement threshold in the… More >

  • Open Access

    ARTICLE

    Finite Element Simulations on Failure Behaviors of Granular Materials with Microstructures Using a Micromechanics-Based Cosserat Elastoplastic Model

    Chenxi Xiu1,2,*, Xihua Chu2

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2305-2338, 2024, DOI:10.32604/cmes.2023.030194 - 15 December 2023

    Abstract This paper presents a micromechanics-based Cosserat continuum model for microstructured granular materials. By utilizing this model, the macroscopic constitutive parameters of granular materials with different microstructures are expressed as sums of microstructural information. The microstructures under consideration can be classified into three categories: a medium-dense microstructure, a dense microstructure consisting of one-sized particles, and a dense microstructure consisting of two-sized particles. Subsequently, the Cosserat elastoplastic model, along with its finite element formulation, is derived using the extended Drucker-Prager yield criteria. To investigate failure behaviors, numerical simulations of granular materials with different microstructures are conducted using… More >

  • Open Access

    ARTICLE

    Gradient Optimizer Algorithm with Hybrid Deep Learning Based Failure Detection and Classification in the Industrial Environment

    Mohamed Zarouan1, Ibrahim M. Mehedi1,2,*, Shaikh Abdul Latif3, Md. Masud Rana4

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1341-1364, 2024, DOI:10.32604/cmes.2023.030037 - 17 November 2023

    Abstract Failure detection is an essential task in industrial systems for preventing costly downtime and ensuring the seamless operation of the system. Current industrial processes are getting smarter with the emergence of Industry 4.0. Specifically, various modernized industrial processes have been equipped with quite a few sensors to collect process-based data to find faults arising or prevailing in processes along with monitoring the status of processes. Fault diagnosis of rotating machines serves a main role in the engineering field and industrial production. Due to the disadvantages of existing fault, diagnosis approaches, which greatly depend on professional… More >

  • Open Access

    ARTICLE

    Surgical treatment for BPH refractory to medication: robotic water jet ablation vs. TURP functional outcomes from two FDA clinical trials

    Alexis E. Te1, Christina Sze1, Steven A. Kaplan2, Bilal Chughtai1

    Canadian Journal of Urology, Vol.30, No.1, pp. 11408-11413, 2023

    Abstract Introduction: A common indication for benign prostate hyperplasia (BPH) therapies is failure to improve with medical therapy. However, pivotal Federal Drug Administration (FDA) registered randomized clinical trials (RCTs) for minimally invasive surgical therapies (MISTs) are designed to be compared to either sham or placebo while off medical therapy at baseline, and as an alternative to medical therapy. There are few if any RCTs reporting the MISTS efficacy in patients with true medical therapy failure. We report on the efficacy of robotic water jet ablation therapy (RWT) and TURP in patients who have failed to improve with… More >

  • Open Access

    ARTICLE

    Tensile Failure Characterization of Glass/Epoxy Composites using Acoustic Emission RMS Data

    K. KRISHNAMOORTHYa,*, N. PRABHUb

    Journal of Polymer Materials, Vol.40, No.3-4, pp. 215-226, 2023, DOI:10.32381/JPM.2023.40.3-4.7

    Abstract The acoustic emission monitoring with artificial neural networks predicts the ultimate strength of glass/epoxy composite laminates using Acoustic Emission Data. The ultimate loads of all the specimens were used to characterise the emission of hits during failure modes. The six layered glass fiber laminates were prepared (in woven mat form) with epoxy as the binding medium by hand lay-up technique. At room temperature, with a pressure of 30 kg/cm2, the laminates were cured. The laminates of standard dimensions as per ASTM D3039 for the tensile test were cut from the lamina. The Acoustic Emission (AE) test More >

  • Open Access

    ARTICLE

    Risk Factors for Abuse in Children with Congenital Heart Disease Presenting at a Pediatric Tertiary Care Hospital

    Kristi K. Westphaln1,2,*, Karen Kay Imagawa2,3, Lorena Espinosa Smith1,4, Julia Srivastava5, Nancy A. Pike1,5

    Congenital Heart Disease, Vol.18, No.6, pp. 657-670, 2023, DOI:10.32604/chd.2023.044179 - 19 January 2024

    Abstract Background: Congenital heart disease (CHD) is a chronic medical condition often diagnosed at birth and requires surgical intervention, multiple hospitalizations, and lifelong care. This can put significant stress on the family, leading to altered maternal mental health, bonding and attachment issues, and the potential for child abuse. The purpose of this study is to explore the characteristics of a sample of young children with CHD who experienced hospitalization with concurrent concern for child abuse in a free-standing pediatric tertiary care hospital. Methods: Electronic medical records were reviewed for children aged 0–5 years old who were… More >

  • Open Access

    PROCEEDINGS

    Fragile Points Method for Modeling Complex Structural Failure

    Mingjing Li1,*, Leiting Dong1, Satya N. Atluri2

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.4, pp. 1-2, 2023, DOI:10.32604/icces.2023.09689

    Abstract The Fragile Points Method (FPM) is a discontinuous meshless method based on the Galerkin weak form [1]. In the FPM, the problem domain is discretized by spatial points and subdomains, and the displacement trial function of each subdomain is derived based on the points within the support domain. For this reason, the FPM doesn’t suffer from the mesh distortion and is suitable to model complex structural deformations. Furthermore, similar to the discontinuous Galerkin finite element method, the displacement trial functions used in the FPM is piece-wise continuous, and the numerical flux is introduced across each… More >

  • Open Access

    PROCEEDINGS

    A Modified Rate-Dependent Peridynamic Model with Rotation Effect for Dynamic Mechanical Behavior of Ceramic Materials

    Yaxun Liu1,2, Lisheng Liu1,2,*, Hai Mei1,2, Qiwen Liu1,2, Xin Lai1,2

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.4, pp. 1-1, 2023, DOI:10.32604/icces.2023.09007

    Abstract As a mathematical expression of the dynamic mechanical behavior, the constitutive model plays an indispensable role in numerical simulations of ceramic materials. The current bond-based peridynamic constitutive models can accurately describe the dynamic mechanical behavior of partial ceramic materials under impact loading, however, the predicted value of the Poisson’s ratio is 0.25, which is not true for most of the known ceramic materials. Herein, based on the existing bond-based peridynamic constitutive model, the current study utilizes the description of tangential bond force and considers the influence of bond force on rotation to accurately predict the… More >

  • Open Access

    ARTICLE

    Identification of High-Risk Scenarios for Cascading Failures in New Energy Power Grids Based on Deep Embedding Clustering Algorithms

    Xueting Cheng1, Ziqi Zhang2,*, Yueshuang Bao1, Huiping Zheng1

    Energy Engineering, Vol.120, No.11, pp. 2517-2529, 2023, DOI:10.32604/ee.2023.042633 - 31 October 2023

    Abstract At present, the proportion of new energy in the power grid is increasing, and the random fluctuations in power output increase the risk of cascading failures in the power grid. In this paper, we propose a method for identifying high-risk scenarios of interlocking faults in new energy power grids based on a deep embedding clustering (DEC) algorithm and apply it in a risk assessment of cascading failures in different operating scenarios for new energy power grids. First, considering the real-time operation status and system structure of new energy power grids, the scenario cascading failure risk More >

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