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 >

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 - 29 April 2023

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… More >

Zhiguo Chen^1,2,*, Jiabing Cao^1,2

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4445-4465, 2023, DOI:10.32604/cmc.2023.038639 - 31 March 2023

Abstract The Corona Virus Disease 2019 (COVID-19) effect has made telecommuting and remote learning the norm. The growing number of Internet-connected devices provides cyber attackers with more attack vectors. The development of malware by criminals also incorporates a number of sophisticated obfuscation techniques, making it difficult to classify and detect malware using conventional approaches. Therefore, this paper proposes a novel visualization-based malware classification system using transfer and ensemble learning (VMCTE). VMCTE has a strong anti-interference ability. Even if malware uses obfuscation, fuzzing, encryption, and other techniques to evade detection, it can be accurately classified into its… More >

Ming Li¹, Kuntharrgyal Khysru², Haiqiang Shi^2,*, Qiang Fang^3,*, Jinrong Hu⁴, Yun Chen⁵

Computer Systems Science and Engineering, Vol.46, No.1, pp. 783-798, 2023, DOI:10.32604/csse.2023.034687 - 20 January 2023

Abstract The Internet of Things (IoT) plays an essential role in the current and future generations of information, network, and communication development and applications. This research focuses on vocal tract visualization and modeling, which are critical issues in realizing inner vocal tract animation. That is applied in many fields, such as speech training, speech therapy, speech analysis and other speech production-related applications. This work constructed a geometric model by observation of Magnetic Resonance Imaging data, providing a new method to annotate and construct 3D vocal tract organs. The proposed method has two advantages compared with previous… More >

Yu Su^1,2,3, Lingjuan Hou^2,3,*, Sinan Li¹, Zhaochang Jiang¹, Haoran Peng⁴

Computer Systems Science and Engineering, Vol.46, No.1, pp. 521-536, 2023, DOI:10.32604/csse.2022.028606 - 20 January 2023

Abstract Mobile location-based services (MLBS) refer to services around geographic location data. Mobile terminals use wireless communication networks (or satellite positioning systems) to obtain users’ geographic location coordinate information based on spatial databases and integrate with other information to provide users with required location-related services. The development of systems based on MLBS has significance and practical value. In this paper a visualization management information system for personnel in major events based on microservices, namely MEPMIS, is designed and implemented by using MLBS. The system consists of a server and a client app, and it has some… More >

Jingwei Hao^*, Senlin Luo, Limin Pan

Computer Systems Science and Engineering, Vol.46, No.1, pp. 719-734, 2023, DOI:10.32604/csse.2023.033923 - 20 January 2023

Abstract The byte stream is widely used in malware detection due to its independence of reverse engineering. However, existing methods based on the byte stream implement an indiscriminate feature extraction strategy, which ignores the byte function difference in different segments and fails to achieve targeted feature extraction for various byte semantic representation modes, resulting in byte semantic confusion. To address this issue, an enhanced adversarial byte function associated method for malware backdoor attack is proposed in this paper by categorizing various function bytes into three functions involving structure, code, and data. The Minhash algorithm, grayscale mapping, More >

Umair Yousaf¹, Muhammad Asif¹, Shahbaz Ahmed¹, Noman Tahir¹, Azeem Irshad², Akber Abid Gardezi³, Muhammad Shafiq^4,*, Jin-Ghoo Choi⁴, Habib Hamam^5,6,7,8

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4165-4181, 2023, DOI:10.32604/cmc.2023.026607 - 31 October 2022

Abstract The research volume increases at the study rate, causing massive text corpora. Due to these enormous text corpora, we are drowning in data and starving for information. Therefore, recent research employed different text mining approaches to extract information from this text corpus. These proposed approaches extract meaningful and precise phrases that effectively describe the text's information. These extracted phrases are commonly termed keyphrases. Further, these key phrases are employed to determine the different fields of study trends. Moreover, these key phrases can also be used to determine the spatiotemporal trends in the various research fields.… More >