Nobuhito Nagasato¹, Zhengyuan Pei¹, Yasushi Koito^2,*

Frontiers in Heat and Mass Transfer, Vol.22, No.1, pp. 49-63, 2024, DOI:10.32604/fhmt.2024.047502

Abstract Visualization experiments were conducted to clarify the operational characteristics of a polymer pulsating heat pipe (PHP). Hydrofluoroether (HFE)-7100 was used as a working fluid, and its filling ratio was 50% of the entire PHP channel. A semi-transparent PHP was fabricated using a transparent polycarbonate sheet and a plastic 3D printer, and the movements of liquid slugs and vapor plugs of the working fluid were captured with a high-speed camera. The video images were then analyzed to obtain the flow patterns in the PHP. The heat transfer characteristics of the PHP were discussed based on the flow patterns and temperature distributions… More >

Xin Fan^1,2,3, Jingen Mao^2,3,*, Liangjue Lian^2,3, Li Yu¹, Wei Zheng^2,3, Yun Ge^2,3

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 65-84, 2024, DOI:10.32604/cmc.2023.045522

Abstract The purpose of software defect prediction is to identify defect-prone code modules to assist software quality assurance teams with the appropriate allocation of resources and labor. In previous software defect prediction studies, transfer learning was effective in solving the problem of inconsistent project data distribution. However, target projects often lack sufficient data, which affects the performance of the transfer learning model. In addition, the presence of uncorrelated features between projects can decrease the prediction accuracy of the transfer learning model. To address these problems, this article propose a software defect prediction method based on stable learning (SDP-SL) that combines code… More >

Ziguang Song^1,2, Jiangbo Yu¹, Mengmeng Wang³, Weitao Shen⁴, Chengcheng Wang¹, Tianyi Lu¹, Gaojun Shan¹, Guo Dong¹, Yiru Wang¹, Jiyi Zhao^1,*

Congenital Heart Disease, Vol.18, No.6, pp. 693-701, 2023, DOI:10.32604/chd.2024.048081

Abstract CHDTEPDB (URL: ) is a manually integrated database for congenital heart disease (CHD) that stores the expression profiling data of CHD derived from published papers, aiming to provide rich resources for investigating a deeper correlation between human CHD and aberrant transcriptome expression. The development of human diseases involves important regulatory roles of RNAs, and expression profiling data can reflect the underlying etiology of inherited diseases. Hence, collecting and compiling expression profiling data is of critical significance for a comprehensive understanding of the mechanisms and functions that underpin genetic diseases. CHDTEPDB stores the expression profiles of over 200 sets of 7… More >

Youming Guo, Qinmu Wu^*

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1489-1514, 2023, DOI:10.32604/cmc.2023.042313

Abstract Permanent magnet synchronous motor (PMSM) is widely used in various production processes because of its high efficiency, fast reaction time, and high power density. With the continuous promotion of new energy vehicles, timely detection of PMSM faults can significantly reduce the accident rate of new energy vehicles, further enhance consumers’ trust in their safety, and thus promote their popularity. Existing fault diagnosis methods based on deep learning can only distinguish different PMSM faults and cannot interpret and analyze them. Convolutional neural networks (CNN) show remarkable accuracy in image data analysis. However, due to the “black box” problem in deep learning… More >

Yongning Yuan¹, Dong Zhang², Usama Sayed³, Hao Zhu¹, Jun Wang⁴, Xiaojun Yang², Zheng Wang^2,*

Journal of Renewable Materials, Vol.11, No.11, pp. 3917-3932, 2023, DOI:10.32604/jrm.2023.028764

Abstract In order to optimize the wood internal quality detection and evaluation system and improve the comprehensive utilization rate of wood, this paper invented a set of log internal defect detection and visualization system by using the ultrasonic dry coupling agent method. The detection and visualization analysis of internal log defects were realized through log specimen test. The main conclusions show that the accuracy, reliability and practicability of the system for detecting the internal defects of log specimens have been effectively verified. The system can make the edge of the detected image smooth by interpolation algorithm, and the edge detection algorithm… More >

Jingyao Liu^1,2, Qinghe Feng⁴, Jiashi Zhao^2,3, Yu Miao^2,3, Wei He², Weili Shi^2,3, Zhengang Jiang^2,3,*

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 2649-2665, 2023, DOI:10.32604/cmc.2023.038891

Abstract The coronavirus disease 2019 (COVID-19) has severely disrupted both human life and the health care system. Timely diagnosis and treatment have become increasingly important; however, the distribution and size of lesions vary widely among individuals, making it challenging to accurately diagnose the disease. This study proposed a deep-learning disease diagnosis model based on weakly supervised learning and clustering visualization (W_CVNet) that fused classification with segmentation. First, the data were preprocessed. An optimizable weakly supervised segmentation preprocessing method (O-WSSPM) was used to remove redundant data and solve the category imbalance problem. Second, a deep-learning fusion method was used for feature extraction… More >

Patrick C. Doherty, Heather E. Dillon^† , Justin Roberts

Frontiers in Heat and Mass Transfer, Vol.9, pp. 1-6, 2017, DOI:10.5098/hmt.9.1

Abstract The onset of turbulence in natural convection systems is difficult to predict using traditional computational techniques. The flow patterns that occur before and after the onset of turbulence may be better understood with the help of visual techniques like Schlieren imaging. Schlieren imaging allows visualization of the density gradients of a fluid using collimated light and refractive properties. In this experiment, a device was designed to test the behavior of airflow with non-isothermal boundary conditions within a rectangular cavity. Previous computational fluid modeling suggested a period doubling route to chaos in a cavity with a high aspect ratio and free… More >

Amnart Boonloi^a, Withada Jedsadaratanachai^b,*

Frontiers in Heat and Mass Transfer, Vol.10, pp. 1-19, 2018, DOI:10.5098/hmt.10.6

Abstract Convective heat transfer, pressure loss and thermal performance in a heat exchanger tube inserted with the modified V-shaped baffle are investigated numerically. The influences of the flow attack angle (α = 20o , 30o and 45o ), baffle height in term of blockage ratio (b/D = BR = 0.05, 0.10, 0.15, 0.20 and 0.25) and arrangement (The V-tip pointing downstream is called “V-Downstream”, while the V-tip pointing upstream is named “V-Upstream”.) on heat transfer and friction loss are presented for the Reynolds number in range 100 – 1200 (laminar region). The numerical study (finite volume method) is selected to solve… More >

Wenlei Lian, Zijian Sun, Taoyi Han, Yimin Xuan^*

Frontiers in Heat and Mass Transfer, Vol.14, pp. 1-6, 2020, DOI:10.5098/hmt.14.10

Abstract An experimental facility is developed to investigate the characteristics of the nucleate boiling heat transfer in a rotating water film. The High speed photography technique is used to visualize the flow field of the rotating water film. Along with the bubble photographs, the centrifugal acceleration, heat flux into the film, and the heat transfer coefficient are calculated to learn the heat transfer characteristics of the water film. It is found that the boiling heat transfer coefficient decreases with the increment of heat flux. The heat transfer coefficient increases with acceleration increasing from 20g to 60g, but show no obvious increase… More >

Hyunkyu Shin¹, Yonghan Ahn², Mihwa Song³, Heungbae Gil³, Jungsik Choi^4,*, Sanghyo Lee^5,*

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 4753-4766, 2023, DOI:10.32604/cmc.2023.038362

Abstract Recently, convolutional neural network (CNN)-based visual inspection has been developed to detect defects on building surfaces automatically. The CNN model demonstrates remarkable accuracy in image data analysis; however, the predicted results have uncertainty in providing accurate information to users because of the “black box” problem in the deep learning model. Therefore, this study proposes a visual explanation method to overcome the uncertainty limitation of CNN-based defect identification. The visual representative gradient-weights class activation mapping (Grad-CAM) method is adopted to provide visually explainable information. A visualizing evaluation index is proposed to quantitatively analyze visual representations; this index reflects a rough estimate… More >