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  • Open Access

    ARTICLE

    Design Optimization of Permanent Magnet Eddy Current Coupler Based on an Intelligence Algorithm

    Dazhi Wang*, Pengyi Pan, Bowen Niu

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1535-1555, 2023, DOI:10.32604/cmc.2023.042286

    Abstract The permanent magnet eddy current coupler (PMEC) solves the problem of flexible connection and speed regulation between the motor and the load and is widely used in electrical transmission systems. It provides torque to the load and generates heat and losses, reducing its energy transfer efficiency. This issue has become an obstacle for PMEC to develop toward a higher power. This paper aims to improve the overall performance of PMEC through multi-objective optimization methods. Firstly, a PMEC modeling method based on the Levenberg-Marquardt back propagation (LMBP) neural network is proposed, aiming at the characteristics of the complex input-output relationship and… More >

  • Open Access

    ARTICLE

    Mechanism of Thermally Radiative Prandtl Nanofluids and Double-Diffusive Convection in Tapered Channel on Peristaltic Flow with Viscous Dissipation and Induced Magnetic Field

    Yasir Khan1, Safia Akram2,*, Maria Athar3, Khalid Saeed4, Alia Razia2, A. Alameer1

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1501-1520, 2024, DOI:10.32604/cmes.2023.029878

    Abstract The application of mathematical modeling to biological fluids is of utmost importance, as it has diverse applications in medicine. The peristaltic mechanism plays a crucial role in understanding numerous biological flows. In this paper, we present a theoretical investigation of the double diffusion convection in the peristaltic transport of a Prandtl nanofluid through an asymmetric tapered channel under the combined action of thermal radiation and an induced magnetic field. The equations for the current flow scenario are developed, incorporating relevant assumptions, and considering the effect of viscous dissipation. The impact of thermal radiation and double diffusion on public health is… More >

  • Open Access

    ARTICLE

    Experimental Study on Gas Flow Uniformity in a Diesel Particulate Filter Carrier

    Zhengyong Wang1, Jianhua Zhang2, Guoliang Su3, Peixing Yang4, Xiantao Fan4, Shuzhan Bai1, Ke Sun1,*, Guihua Wang1,*

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.1, pp. 193-204, 2024, DOI:10.32604/fdmp.2023.030561

    Abstract A Diesel Particulate Filter (DPF) is a critical device for diesel engine exhaust products treatment. When using active-regeneration purification methods, on the one hand, a spatially irregular gas flow can produce relatively high local temperatures, potentially resulting in damage to the carrier; On the other hand, the internal temperature field can also undergo significant changes contributing to increase this risk. This study explores the gas flow uniformity in a DPF carrier and the related temperature behavior under drop-to-idle (DTI) condition by means of bench tests. It is shown that the considered silicon carbide carrier exhibits good flow uniformity, with a… More >

  • Open Access

    ARTICLE

    DTHN: Dual-Transformer Head End-to-End Person Search Network

    Cheng Feng*, Dezhi Han, Chongqing Chen

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 245-261, 2023, DOI:10.32604/cmc.2023.042765

    Abstract Person search mainly consists of two submissions, namely Person Detection and Person Re-identification (re-ID). Existing approaches are primarily based on Faster R-CNN and Convolutional Neural Network (CNN) (e.g., ResNet). While these structures may detect high-quality bounding boxes, they seem to degrade the performance of re-ID. To address this issue, this paper proposes a Dual-Transformer Head Network (DTHN) for end-to-end person search, which contains two independent Transformer heads, a box head for detecting the bounding box and extracting efficient bounding box feature, and a re-ID head for capturing high-quality re-ID features for the re-ID task. Specifically, after the image goes through… More >

  • Open Access

    ARTICLE

    NPBMT: A Novel and Proficient Buffer Management Technique for Internet of Vehicle-Based DTNs

    Sikandar Khan1, Khalid Saeed1, Muhammad Faran Majeed2,*, Salman A. AlQahtani3, Khursheed Aurangzeb3, Muhammad Shahid Anwar4,*

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 1303-1323, 2023, DOI:10.32604/cmc.2023.039697

    Abstract Delay Tolerant Networks (DTNs) have the major problem of message delay in the network due to a lack of end-to-end connectivity between the nodes, especially when the nodes are mobile. The nodes in DTNs have limited buffer storage for storing delayed messages. This instantaneous sharing of data creates a low buffer/shortage problem. Consequently, buffer congestion would occur and there would be no more space available in the buffer for the upcoming messages. To address this problem a buffer management policy is proposed named “A Novel and Proficient Buffer Management Technique (NPBMT) for the Internet of Vehicle-Based DTNs”. NPBMT combines appropriate-size… More >

  • Open Access

    ARTICLE

    DT-Net: Joint Dual-Input Transformer and CNN for Retinal Vessel Segmentation

    Wenran Jia1, Simin Ma1, Peng Geng1, Yan Sun2,*

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3393-3411, 2023, DOI:10.32604/cmc.2023.040091

    Abstract Retinal vessel segmentation in fundus images plays an essential role in the screening, diagnosis, and treatment of many diseases. The acquired fundus images generally have the following problems: uneven illumination, high noise, and complex structure. It makes vessel segmentation very challenging. Previous methods of retinal vascular segmentation mainly use convolutional neural networks on U Network (U-Net) models, and they have many limitations and shortcomings, such as the loss of microvascular details at the end of the vessels. We address the limitations of convolution by introducing the transformer into retinal vessel segmentation. Therefore, we propose a hybrid method for retinal vessel… More >

  • Open Access

    ARTICLE

    FedTC: A Personalized Federated Learning Method with Two Classifiers

    Yang Liu1,3, Jiabo Wang1,2,*, Qinbo Liu1, Mehdi Gheisari1, Wanyin Xu1, Zoe L. Jiang1, Jiajia Zhang1,*

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3013-3027, 2023, DOI:10.32604/cmc.2023.039452

    Abstract Centralized training of deep learning models poses privacy risks that hinder their deployment. Federated learning (FL) has emerged as a solution to address these risks, allowing multiple clients to train deep learning models collaboratively without sharing raw data. However, FL is vulnerable to the impact of heterogeneous distributed data, which weakens convergence stability and suboptimal performance of the trained model on local data. This is due to the discarding of the old local model at each round of training, which results in the loss of personalized information in the model critical for maintaining model accuracy and ensuring robustness. In this… More >

  • Open Access

    ARTICLE

    State Accurate Representation and Performance Prediction Algorithm Optimization for Industrial Equipment Based on Digital Twin

    Ying Bai1,*, Xiaoti Ren2, Hong Li1

    Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2999-3018, 2023, DOI:10.32604/iasc.2023.040124

    Abstract The combination of the Industrial Internet of Things (IIoT) and digital twin (DT) technology makes it possible for the DT model to realize the dynamic perception of equipment status and performance. However, conventional digital modeling is weak in the fusion and adjustment ability between virtual and real information. The performance prediction based on experience greatly reduces the inclusiveness and accuracy of the model. In this paper, a DT-IIoT optimization model is proposed to improve the real-time representation and prediction ability of the key equipment state. Firstly, a global real-time feedback and the dynamic adjustment mechanism is established by combining DT-IIoT… More >

  • Open Access

    ARTICLE

    DOUBLE-DIFFUSIVE NATURAL CONVECTION OF LOW PRANDTL NUMBER LIQUIDS WITH SORET AND DUFOUR EFFECTS

    Gang Qiua , Mo Yanga,*, Jin Wangb , Yuwen Zhangc

    Frontiers in Heat and Mass Transfer, Vol.10, pp. 1-8, 2018, DOI:10.5098/hmt.10.24

    Abstract An unsteady numerical model for double-diffusive natural convection of low Prandtl number liquids with Soret and Dufour effects inside the horizontal cavity is developed. The thermosolutal model is solved numerically using the SIMPLE algorithm with QUICK scheme. The flow field, temperature and concentration distributions for different buoyancy ratios, Rayleigh numbers and aspect ratios under different Prandtl numbers are studied systematically. The results reveal that the flow structure develops from conduction-dominated to convection as buoyancy ratio increases under different Prandtl numbers. Heat transfer intensity keeps constant and mass transfer intensity grows slowly before a critical point as Rayleigh number increases for… More >

  • Open Access

    ARTICLE

    SORET AND RADIATION EFFECTS ON AN UNSTEADY FLOW OF A CASSON FLUID THROUGH POROUS VERTICAL CHANNEL WITH EXPANSION AND CONTRACTION

    N. Vijayaa,*, Y. Hari Krishnaa , K. Kalyanib, G.V.R. Reddya

    Frontiers in Heat and Mass Transfer, Vol.11, pp. 1-11, 2018, DOI:10.5098/hmt.11.19

    Abstract The present paper deals with the thermo physical properties of a Casson fluid through an oscillating vertical wall embedded through porous medium under the influence transverse magnetic field, radiation, constant heat source and first order chemical reaction. The radiative heat loss is modelled by using Rosseland approximation. Similarity variables were used to convert the partial differential equations into ordinary differential equation. The transformed ordinary differential equations are solved numerically using Runge - Kutta -Fehlberg method with shooting technique. In order to get perfect perception of the flow pattern we obtain the graphs of axial velocity, temperature and concentrations profiles for… More >

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