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  • Open Access

    ARTICLE

    Bearing Fault Diagnosis Based on the Markov Transition Field and SE-IShufflenetV2 Model

    Chaozhi Cai*, Tiexin Xu, Jianhua Ren, Yingfang Xue

    Structural Durability & Health Monitoring, Vol.19, No.1, pp. 125-144, 2025, DOI:10.32604/sdhm.2024.052813 - 15 November 2024

    Abstract A bearing fault diagnosis method based on the Markov transition field (MTF) and SEnet (SE)-IShufflenetV2 model is proposed in this paper due to the problems of complex working conditions, low fault diagnosis accuracy, and poor generalization of rolling bearing. Firstly, MTF is used to encode one-dimensional time series vibration signals and convert them into time-dependent and unique two-dimensional feature images. Then, the generated two-dimensional dataset is fed into the SE-IShufflenetV2 model for training to achieve fault feature extraction and classification. This paper selects the bearing fault datasets from Case Western Reserve University and Paderborn University… More >

  • Open Access

    ARTICLE

    Impact of Different Rooftop Coverings on Photovoltaic Panel Temperature

    Aws Al-Akam1,*, Ahmed A. Abduljabbar2, Ali Jaber Abdulhamed1

    Energy Engineering, Vol.121, No.12, pp. 3761-3777, 2024, DOI:10.32604/ee.2024.055198 - 22 November 2024

    Abstract Photovoltaic (PV) panels are essential to the global transition towards sustainable energy, offering a clean, renewable source that reduces reliance on fossil fuels and mitigates climate change. High temperatures can significantly affect the performance of photovoltaic (PV) panels by reducing their efficiency and power output. This paper explores the consequential effect of various rooftop coverings on the thermal performance of photovoltaic (PV) panels. It investigates the relationship between the type of rooftop covering materials and the efficiency of PV panels, considering the thermal performance and its implications for enhancing their overall performance and sustainability. The… More >

  • Open Access

    ARTICLE

    Reinforcement Learning Model for Energy System Management to Ensure Energy Efficiency and Comfort in Buildings

    Inna Bilous1, Dmytro Biriukov1, Dmytro Karpenko2, Tatiana Eutukhova2, Oleksandr Novoseltsev2,*, Volodymyr Voloshchuk1

    Energy Engineering, Vol.121, No.12, pp. 3617-3634, 2024, DOI:10.32604/ee.2024.051684 - 22 November 2024

    Abstract This article focuses on the challenges of modeling energy supply systems for buildings, encompassing both methods and tools for simulating thermal regimes and engineering systems within buildings. Enhancing the comfort of living or working in buildings often necessitates increased consumption of energy and material, such as for thermal upgrades, which consequently incurs additional economic costs. It is crucial to acknowledge that such improvements do not always lead to a decrease in total pollutant emissions, considering emissions across all stages of production and usage of energy and materials aimed at boosting energy efficiency and comfort in… More > Graphic Abstract

    Reinforcement Learning Model for Energy System Management to Ensure Energy Efficiency and Comfort in Buildings

  • Open Access

    PROCEEDINGS

    Integrated Multiscale Unified Phase-Field Modellings (UPFM)

    Yuhong Zhao1,2,3,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.4, pp. 1-1, 2024, DOI:10.32604/icces.2024.012951

    Abstract For a long time, the phase-field method has been considered as a mesoscale phenomenological method lacking physical accuracy and unable to be associated with the mechanical/functional properties of materials, etc. Some misunderstandings existing in these viewpoints need to be clarified. Therefore, it is necessary to propose or adopt the perspective of “unified or unifying phase-field modeling (UPFM)” to address these issues, which means that phase-field modeling has multiple unifications. Specifically, the phase-field method is the perfect unity of thermodynamics and kinetics, the unity of multi-scale models from micro- to meso- and then to macroscopic scale, More >

  • Open Access

    PROCEEDINGS

    Analysis of Thermomechanical Delamination Mechanisms in Segmented High-Temperature Protective Coatings and Design Maps for the Durable Coatings

    Biao Li1,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.1, pp. 1-1, 2024, DOI:10.32604/icces.2024.012788

    Abstract Protective coatings play a crucial role in preserving high-temperature engineering components from environmental degradation [1-3]. The durability of these coatings is crucial for maintaining the structural integrity of the components. Introducing a segmented microstructure was recognized as an effective strategy for enhancing the strain tolerance of coatings by mitigating the in-plane stiffness of the coatings, thereby alleviating interface stresses and delamination driving forces. While previous studies on delamination mechanisms in high-temperature protective coatings have predominantly focused on either pure mechanical loading or pure thermal loading conditions (i.e., residual stress) due to their ease of implementation,… More >

  • Open Access

    ARTICLE

    Augmenting Internet of Medical Things Security: Deep Ensemble Integration and Methodological Fusion

    Hamad Naeem1, Amjad Alsirhani2,*, Faeiz M. Alserhani3, Farhan Ullah4, Ondrej Krejcar1

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 2185-2223, 2024, DOI:10.32604/cmes.2024.056308 - 31 October 2024

    Abstract When it comes to smart healthcare business systems, network-based intrusion detection systems are crucial for protecting the system and its networks from malicious network assaults. To protect IoMT devices and networks in healthcare and medical settings, our proposed model serves as a powerful tool for monitoring IoMT networks. This study presents a robust methodology for intrusion detection in Internet of Medical Things (IoMT) environments, integrating data augmentation, feature selection, and ensemble learning to effectively handle IoMT data complexity. Following rigorous preprocessing, including feature extraction, correlation removal, and Recursive Feature Elimination (RFE), selected features are standardized… More >

  • Open Access

    ARTICLE

    Reliability Prediction of Wrought Carbon Steel Castings under Fatigue Loading Using Coupled Mold Optimization and Finite Element Simulation

    Muhammad Azhar Ali Khan1, Syed Sohail Akhtar2,3,*, Abba A. Abubakar2,4, Muhammad Asad1, Khaled S. Al-Athel2,5

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 2325-2350, 2024, DOI:10.32604/cmes.2024.054741 - 31 October 2024

    Abstract The fatigue life and reliability of wrought carbon steel castings produced with an optimized mold design are predicted using a finite element method integrated with reliability calculations. The optimization of the mold is carried out using MAGMASoft mainly based on porosity reduction as a response. After validating the initial mold design with experimental data, a spring flap, a common component of an automotive suspension system is designed and optimized followed by fatigue life prediction based on simulation using Fe-safe. By taking into consideration the variation in both stress and strength, the stress-strength model is used… More >

  • Open Access

    ARTICLE

    Deep Learning-Driven Anomaly Detection for IoMT-Based Smart Healthcare Systems

    Attiya Khan1, Muhammad Rizwan2, Ovidiu Bagdasar2,3, Abdulatif Alabdulatif4,*, Sulaiman Alamro4, Abdullah Alnajim5

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 2121-2141, 2024, DOI:10.32604/cmes.2024.054380 - 31 October 2024

    Abstract The Internet of Medical Things (IoMT) is an emerging technology that combines the Internet of Things (IoT) into the healthcare sector, which brings remarkable benefits to facilitate remote patient monitoring and reduce treatment costs. As IoMT devices become more scalable, Smart Healthcare Systems (SHS) have become increasingly vulnerable to cyberattacks. Intrusion Detection Systems (IDS) play a crucial role in maintaining network security. An IDS monitors systems or networks for suspicious activities or potential threats, safeguarding internal networks. This paper presents the development of an IDS based on deep learning techniques utilizing benchmark datasets. We propose More >

  • Open Access

    ARTICLE

    Association between Job Satisfaction and Stress or Depressive Symptom of Employed Persons with Disabilities: Findings from the Panel Survey of Employment for the Disabled 2016–2023

    Jeong Min Yang1, Ji Sung Hong1, Jae Hyun Kim2,*

    International Journal of Mental Health Promotion, Vol.26, No.10, pp. 791-803, 2024, DOI:10.32604/ijmhp.2024.056433 - 31 October 2024

    Abstract Background: This study conducted a longitudinal analysis of the association between job satisfaction and stress or depressive symptoms of employed persons with disabilities (PWDs) based on the data from the 1st to 8th Pannel Survey of Employment for the Disabled (PSED). Methods: After excluding missing values, data on 1614 participants at baseline (1st wave) were analyzed using the chi-square test and generalized estimating equation (GEE) model for data from 1st to 8thPSED. Results: It was found that for each one-unit increase in the job satisfaction score, the stress scale decreased by 0.004 (B: −0.004, 95% CI:… More >

  • Open Access

    ARTICLE

    Privacy-Preserving and Lightweight V2I and V2V Authentication Protocol Using Blockchain Technology

    Muhammad Imran Ghafoor1, Awad Bin Naeem2,*, Biswaranjan Senapati3, Md. Sakiul Islam Sudman4, Satyabrata Pradhan5, Debabrata Das6, Friban Almeida6, Hesham A. Sakr7

    Intelligent Automation & Soft Computing, Vol.39, No.5, pp. 783-803, 2024, DOI:10.32604/iasc.2024.050819 - 31 October 2024

    Abstract The confidentiality of pseudonymous authentication and secure data transmission is essential for the protection of information and mitigating risks posed by compromised vehicles. The Internet of Vehicles has meaningful applications, enabling connected and autonomous vehicles to interact with infrastructure, sensors, computing nodes, humans, and fellow vehicles. Vehicular hoc networks play an essential role in enhancing driving efficiency and safety by reducing traffic congestion while adhering to cryptographic security standards. This paper introduces a privacy-preserving Vehicle-to-Infrastructure authentication, utilizing encryption and the Moore curve. The proposed approach enables a vehicle to deduce the planned itinerary of Roadside More >

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