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  • Open Access


    An Opposition-Based Learning-Based Search Mechanism for Flying Foxes Optimization Algorithm

    Chen Zhang1, Liming Liu1, Yufei Yang1, Yu Sun1, Jiaxu Ning2, Yu Zhang3, Changsheng Zhang1,4,*, Ying Guo4

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 5201-5223, 2024, DOI:10.32604/cmc.2024.050863

    Abstract The flying foxes optimization (FFO) algorithm, as a newly introduced metaheuristic algorithm, is inspired by the survival tactics of flying foxes in heat wave environments. FFO preferentially selects the best-performing individuals. This tendency will cause the newly generated solution to remain closely tied to the candidate optimal in the search area. To address this issue, the paper introduces an opposition-based learning-based search mechanism for FFO algorithm (IFFO). Firstly, this paper introduces niching techniques to improve the survival list method, which not only focuses on the adaptability of individuals but also considers the population’s crowding degree More >

  • Open Access


    Bearing Fault Diagnosis Based on Optimized Feature Mode Decomposition and Improved Deep Belief Network

    Guangfei Jia*, Yanchao Meng, Zhiying Qin

    Structural Durability & Health Monitoring, Vol.18, No.4, pp. 445-463, 2024, DOI:10.32604/sdhm.2024.049298

    Abstract The vibration signals of rolling bearings exhibit nonlinear and non-stationary characteristics under the influence of noise. In intelligent fault diagnosis, unprocessed signals will lead to weak fault characteristics and low diagnostic accuracy. To solve the above problem, a fault diagnosis method based on parameter optimization feature mode decomposition and improved deep belief networks is proposed. The feature mode decomposition is used to decompose the vibration signals. The parameter adaptation of feature mode decomposition is implemented by improved whale optimization algorithm including Levy flight strategy and adaptive weight. The selection of activation function and parameters is More > Graphic Abstract

    Bearing Fault Diagnosis Based on Optimized Feature Mode Decomposition and Improved Deep Belief Network

  • Open Access


    A Numerical Study on the Effect of the Backflow Hole Position on the Performances of a Self-Priming Pump

    Dongwei Wang1,*, Lijian Cao1, Weidong Wang2, Jiajun Hu1

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.5, pp. 1103-1122, 2024, DOI:10.32604/fdmp.2023.042654

    Abstract A self-priming pump is a centrifugal pump that has the ability to prime itself. Typically, its performance depends on the configuration of its reflux hole. In this study, the ANSYS FLUENT software is used to investigate the effects of three different radial positions of the reflux hole on gas-liquid two-phase distribution, pressure pulsation, and imp during self-priming. The research results indicate that: (1) The effective channel size for the reflux liquid to enter the volute varies depending on the location of the reflux hole. The effect of the impeller rotation on the reflux liquid becomes… More >

  • Open Access


    Improved Unit Commitment with Accurate Dynamic Scenarios Clustering Based on Multi-Parametric Programming and Benders Decomposition

    Zhang Zhi1, Haiyu Huang2, Wei Xiong2, Yijia Zhou3, Mingyu Yan3,*, Shaolian Xia2, Baofeng Jiang2, Renbin Su2, Xichen Tian4

    Energy Engineering, Vol.121, No.6, pp. 1557-1576, 2024, DOI:10.32604/ee.2024.047401

    Abstract Stochastic unit commitment is one of the most powerful methods to address uncertainty. However, the existing scenario clustering technique for stochastic unit commitment cannot accurately select representative scenarios, which threatens the robustness of stochastic unit commitment and hinders its application. This paper provides a stochastic unit commitment with dynamic scenario clustering based on multi-parametric programming and Benders decomposition. The stochastic unit commitment is solved via the Benders decomposition, which decouples the primal problem into the master problem and two types of subproblems. In the master problem, the committed generator is determined, while the feasibility and… More >

  • Open Access


    Stubborn Hypoxia in Neonates with D-Transposition of the Great Arteries after Arterial Switch Operation: Central Sleep Apnea as the Cause and Potential Indicator of Brain Immaturity

    Camden L. Hebson1,*, Kyle Bliton2, Amr Y. Hammouda1, Kaitlyn Barr3, W. Hampton Gray4, Mohini Gunnett2, Waldemar F. Carlo1

    Congenital Heart Disease, Vol.19, No.2, pp. 185-195, 2024, DOI:10.32604/chd.2024.048871

    Abstract D-transposition of the great arteries (d-TGA) is surgically repaired with the arterial switch operation (ASO) with excellent results, however short and long-term morbidities still develop including neurocognitive delay. Clinically significant central sleep apnea is uncommon in non-premature infants, but when present indicates immature autonomic control of respiration likely due to a neurologic disorder. We report the unanticipated finding of central sleep apnea in four-term neonates with d-TGA after uncomplicated ASO, with the short-term complication of delayed hospital discharge and long-term concerns regarding this early marker of brain immaturity and its hindrance to normal development. Within More >

  • Open Access


    Positron Emission Tomography Lung Image Respiratory Motion Correcting with Equivariant Transformer

    Jianfeng He1,2, Haowei Ye1, Jie Ning1, Hui Zhou1,2,*, Bo She3,*

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 3355-3372, 2024, DOI:10.32604/cmc.2024.048706

    Abstract In addressing the challenge of motion artifacts in Positron Emission Tomography (PET) lung scans, our study introduces the Triple Equivariant Motion Transformer (TEMT), an innovative, unsupervised, deep-learning-based framework for efficient respiratory motion correction in PET imaging. Unlike traditional techniques, which segment PET data into bins throughout a respiratory cycle and often face issues such as inefficiency and overemphasis on certain artifacts, TEMT employs Convolutional Neural Networks (CNNs) for effective feature extraction and motion decomposition.TEMT’s unique approach involves transforming motion sequences into Lie group domains to highlight fundamental motion patterns, coupled with employing competitive weighting for More >

  • Open Access


    A Wind Power Prediction Framework for Distributed Power Grids

    Bin Chen1, Ziyang Li1, Shipeng Li1, Qingzhou Zhao1, Xingdou Liu2,*

    Energy Engineering, Vol.121, No.5, pp. 1291-1307, 2024, DOI:10.32604/ee.2024.046374

    Abstract To reduce carbon emissions, clean energy is being integrated into the power system. Wind power is connected to the grid in a distributed form, but its high variability poses a challenge to grid stability. This article combines wind turbine monitoring data with numerical weather prediction (NWP) data to create a suitable wind power prediction framework for distributed grids. First, high-precision NWP of the turbine range is achieved using weather research and forecasting models (WRF), and Kriging interpolation locates predicted meteorological data at the turbine site. Then, a preliminary predicted power series is obtained based on More >

  • Open Access


    The Effects of the Geometry of a Current Collector with an Equal Open Ratio on Output Power of a Direct Methanol Fuel Cell

    Yingli Zhu1,*, Jiachi Xie1, Mingwei Zhu1, Jun Zhang2, Miaomiao Li3

    Energy Engineering, Vol.121, No.5, pp. 1161-1172, 2024, DOI:10.32604/ee.2024.041205

    Abstract The open ratio of a current collector has a great impact on direct methanol fuel cell (DMFC) performance. Although a number of studies have investigated the influence of the open ratio of DMFC current collectors, far too little attention has been given to how geometry (including the shape and feature size of the flow field) affects a current collector with an equal open ratio. In this paper, perforated and parallel current collectors with an equal open ratio of 50% and different feature sizes are designed, and the corresponding experimental results are shown to explain the… More >

  • Open Access


    Correlation Composition Awareness Model with Pair Collaborative Localization for IoT Authentication and Localization

    Kranthi Alluri, S. Gopikrishnan*

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 943-961, 2024, DOI:10.32604/cmc.2024.048621

    Abstract Secure authentication and accurate localization among Internet of Things (IoT) sensors are pivotal for the functionality and integrity of IoT networks. IoT authentication and localization are intricate and symbiotic, impacting both the security and operational functionality of IoT systems. Hence, accurate localization and lightweight authentication on resource-constrained IoT devices pose several challenges. To overcome these challenges, recent approaches have used encryption techniques with well-known key infrastructures. However, these methods are inefficient due to the increasing number of data breaches in their localization approaches. This proposed research efficiently integrates authentication and localization processes in such a… More >

  • Open Access


    Effect of Feed Composition in Gas-phase Polymerization on Structure and Properties of In Situ Impact Polypropylene Copolymer


    Journal of Polymer Materials, Vol.36, No.2, pp. 121-132, 2019, DOI:10.32381/JPM.2019.36.02.2

    Abstract In this work, three in situ impact polypropylene copolymer(IPC) samples were prepared through Ziegler-Natta catalyst only changing the feed composition (ethylene to ethylene and propylene molar ratio, C2/C2+C3) in gas-phase polymerization reactor. Polymer (IPC) were characterical by solvent classification, gel permeation chromatography (GPC), differential scanning calorimetry (DSC), successive self-nucleation and annealing (SSA), nuclear magnetic resonance(13C-NMR) and scanning electron microscopy(SEM). The mechanical properties of IPC samples were tested.The results indicate that with similar ethylene content, the feed composition which determines the content and structure of EPR and EbP component in IPC, further impacts the rubber phase More >

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