Luda Chen¹, Kuangzhu Bao², Ying Chen², Jingang Hao^2,*, Jianfeng He^1,3,*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 409-427, 2024, DOI:10.32604/cmc.2024.048507

Abstract Pancreatic diseases, including mass-forming chronic pancreatitis (MFCP) and pancreatic ductal adenocarcinoma (PDAC), present with similar imaging features, leading to diagnostic complexities. Deep Learning (DL) methods have been shown to perform well on diagnostic tasks. Existing DL pancreatic lesion diagnosis studies based on Magnetic Resonance Imaging (MRI) utilize the prior information to guide models to focus on the lesion region. However, over-reliance on prior information may ignore the background information that is helpful for diagnosis. This study verifies the diagnostic significance of the background information using a clinical dataset. Consequently, the Prior Difference Guidance Network (PDGNet) is proposed, merging decoupled lesion… More >

Haoran Huang, Weiting Chen^*, Zheming Fan

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3665-3681, 2024, DOI:10.32604/cmc.2024.048008

Abstract Time series forecasting plays an important role in various fields, such as energy, finance, transport, and weather. Temporal convolutional networks (TCNs) based on dilated causal convolution have been widely used in time series forecasting. However, two problems weaken the performance of TCNs. One is that in dilated casual convolution, causal convolution leads to the receptive fields of outputs being concentrated in the earlier part of the input sequence, whereas the recent input information will be severely lost. The other is that the distribution shift problem in time series has not been adequately solved. To address the first problem, we propose… More >

Dewi Puspitasari¹, Diah Kusuma Pratiwi¹, Pramadhony Amran², Kaprawi Sahim^1,*

Frontiers in Heat and Mass Transfer, Vol.22, No.1, pp. 305-315, 2024, DOI:10.32604/fhmt.2023.041882

Abstract The natural convection from a vertical hot plate with radiation and constant flux is studied numerically to know the velocity and temperature distribution characteristics over a vertical hot plate. The governing equations of the natural convection in two-dimension are solved with the implicit finite difference method, whereas the discretized equations are solved with the iterative relaxation method. The results show that the velocity and the temperature increase along the vertical wall. The influence of the radiation parameter in the boundary layer is significant in increasing the velocity and temperature profiles. The velocity profiles increase with the increase of the radiation… More >

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 >

Jiajie He^1,2, Fuzheng Liu³, Xiangyi Geng³, Xifeng Liang¹, Faye Zhang^3,*, Mingshun Jiang³

Structural Durability & Health Monitoring, Vol.18, No.1, pp. 37-54, 2024, DOI:10.32604/sdhm.2023.029428

Abstract Incomplete fault signal characteristics and ease of noise contamination are issues with the current rolling bearing early fault diagnostic methods, making it challenging to ensure the fault diagnosis accuracy and reliability. A novel approach integrating enhanced Symplectic geometry mode decomposition with cosine difference limitation and calculus operator (ESGMD-CC) and artificial fish swarm algorithm (AFSA) optimized extreme learning machine (ELM) is proposed in this paper to enhance the extraction capability of fault features and thus improve the accuracy of fault diagnosis. Firstly, SGMD decomposes the raw vibration signal into multiple Symplectic geometry components (SGCs). Secondly, the iterations are reset by the… More >

Yi Shi, Fangfang Shangguan^*, Jing Xiao^*

International Journal of Mental Health Promotion, Vol.25, No.12, pp. 1257-1263, 2023, DOI:10.32604/ijmhp.2023.030516

Abstract Background: Social support is related to depression, but the gender differences and related factors that contribute to low social support among adolescents with subthreshold depression remain to be elucidated. This study explores the relationship between social support and depression, in addition to the gender difference in the incidence of low social support among adolescents with subthreshold depression and its related factors. Methods: A total of 371 Chinese adolescents with subthreshold depression were recruited. All subjects were rated on the Social Support Scale for Adolescents, the Response Style Scale, the Self-Perception Profile for Children, the Individualism-collectivism scale. Results: Binary logistic regression… More >

D. Dorathy Prema Kavitha¹, L. Francis Raj¹, Sandeep Kautish^2,#, Abdulaziz S. Almazyad³, Karam M. Sallam⁴, Ali Wagdy Mohamed^5,6,*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 801-816, 2024, DOI:10.32604/cmes.2023.030902

Abstract The intuitive fuzzy set has found important application in decision-making and machine learning. To enrich and utilize the intuitive fuzzy set, this study designed and developed a deep neural network-based glaucoma eye detection using fuzzy difference equations in the domain where the retinal images converge. Retinal image detections are categorized as normal eye recognition, suspected glaucomatous eye recognition, and glaucomatous eye recognition. Fuzzy degrees associated with weighted values are calculated to determine the level of concentration between the fuzzy partition and the retinal images. The proposed model was used to diagnose glaucoma using retinal images and involved utilizing the Convolutional… More >

Hua Leng¹, Silin He², Jian Qiu³, Feng Liu^4,*, Xinfei Huang⁴, Jiran Zhu²

Energy Engineering, Vol.121, No.1, pp. 77-94, 2024, DOI:10.32604/ee.2023.028340

Abstract The distribution network exhibits complex structural characteristics, which makes fault localization a challenging task. Especially when a branch of the multi-branch distribution network fails, the traditional multi-branch fault location algorithm makes it difficult to meet the demands of high-precision fault localization in the multi-branch distribution network system. In this paper, the multi-branch mainline is decomposed into single branch lines, transforming the complex multi-branch fault location problem into a double-ended fault location problem. Based on the different transmission characteristics of the fault-traveling wave in fault lines and non-fault lines, the endpoint reference time difference matrix S and the fault time difference… More >

Ziqiang Bai¹, Wenzhen Qu^2,*, Guanghua Wu^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2955-2972, 2024, DOI:10.32604/cmes.2023.031474

Abstract In the past decade, notable progress has been achieved in the development of the generalized finite difference method (GFDM). The underlying principle of GFDM involves dividing the domain into multiple sub-domains. Within each sub-domain, explicit formulas for the necessary partial derivatives of the partial differential equations (PDEs) can be obtained through the application of Taylor series expansion and moving-least square approximation methods. Consequently, the method generates a sparse coefficient matrix, exhibiting a banded structure, making it highly advantageous for large-scale engineering computations. In this study, we present the application of the GFDM to numerically solve inverse Cauchy problems in two-… More >

Suripeddi Srinivas^a , Akshay Gupta^b,*, Ashish Kumar Kandoi^b

Frontiers in Heat and Mass Transfer, Vol.5, pp. 1-12, 2014, DOI:10.5098/hmt.5.21

Abstract The present work deals with the flow and thermal analysis of nanofluid in the wavy channels. The governing flow equations are solved numerically using CFD package assuming single phase approach. To study the effect of the concentration and size variation of the nanoparticle, the concentration and size are varied from 0% - 5% and 25 nm - 100 nm respectively over the Reynolds number range of 250-1500 for Au-water nanofluid. The effect on heat transfer enhancement because of corrugation of wavy channel is analyzed on four different shapes (sinusoidal, triangular, trapezoidal and square) channels. The effect of amplitude of the… More >