Zhengyuan Pei¹, Yasushi Koito^2,*

Frontiers in Heat and Mass Transfer, Vol.22, No.5, pp. 1381-1397, 2024, DOI:10.32604/fhmt.2024.056624 - 30 October 2024

Abstract Extended experiments were conducted on the oscillation characteristics of merged liquid slugs in a horizontally oriented polymer pulsating heat pipe (PHP). The PHP’s serpentine channel comprised 14 parallel channels with a width of 1.3 and a height of 1.1 . The evaporator and condenser sections were 25 and 50 long, respectively, and the adiabatic section in between was 75 mm long. Using a plastic 3D printer and semi-transparent filament made from acrylonitrile butadiene styrene, the serpentine channel was printed directly onto a thin polycarbonate sheet to form the PHP. The PHP was charged with hydrofluoroether-7100.… More >

Fahim Nasir¹, Abdulghani Ali Ahmed^1,*, Mehmet Sabir Kiraz¹, Iryna Yevseyeva¹, Mubarak Saif²

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1703-1728, 2024, DOI:10.32604/cmc.2024.055192 - 15 October 2024

Abstract Integrating machine learning and data mining is crucial for processing big data and extracting valuable insights to enhance decision-making. However, imbalanced target variables within big data present technical challenges that hinder the performance of supervised learning classifiers on key evaluation metrics, limiting their overall effectiveness. This study presents a comprehensive review of both common and recently developed Supervised Learning Classifiers (SLCs) and evaluates their performance in data-driven decision-making. The evaluation uses various metrics, with a particular focus on the Harmonic Mean Score (F-1 score) on an imbalanced real-world bank target marketing dataset. The findings indicate… More >

Li Li^*, Qing Zhang, Youran Kong

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 801-818, 2024, DOI:10.32604/cmc.2024.051916 - 18 July 2024

Abstract Due to the diversity and unpredictability of changes in malicious code, studying the traceability of variant families remains challenging. In this paper, we propose a GAN-EfficientNetV2-based method for tracing families of malicious code variants. This method leverages the similarity in layouts and textures between images of malicious code variants from the same source and their original family of malicious code images. The method includes a lightweight classifier and a simulator. The classifier utilizes the enhanced EfficientNetV2 to categorize malicious code images and can be easily deployed on mobile, embedded, and other devices. The simulator utilizes… More >

Nguyen Trong Vinh¹, Lam Thanh Hien¹, Ha Manh Toan², Ngo Duc Vinh³, Do Nang Toan^2,*

Intelligent Automation & Soft Computing, Vol.39, No.2, pp. 281-299, 2024, DOI:10.32604/iasc.2024.045297 - 21 May 2024

Abstract Tuberculosis is a dangerous disease to human life, and we need a lot of attempts to stop and reverse it. Significantly, in the COVID-19 pandemic, access to medical services for tuberculosis has become very difficult. The late detection of tuberculosis could lead to danger to patient health, even death. Vietnam is one of the countries heavily affected by the COVID-19 pandemic, and many residential areas as well as hospitals have to be isolated for a long time. Reality demands a fast and effective tuberculosis diagnosis solution to deal with the difficulty of accessing medical services,… More >

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 - 21 March 2024

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… 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 - 30 January 2024

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… 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 - 19 January 2024

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… More >

Youming Guo, Qinmu Wu^*

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1489-1514, 2023, DOI:10.32604/cmc.2023.042313 - 29 November 2023

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… 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 - 31 October 2023

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, 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 - 08 October 2023

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… More >