Chen Chen, Kai Qiao, Jie Yang, Jian Chen, Bin Yan^*

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2629-2642, 2024, DOI:10.32604/cmc.2024.056038 - 18 November 2024

Abstract Computed Tomography (CT) is a commonly used technology in Printed Circuit Boards (PCB) non-destructive testing, and element segmentation of CT images is a key subsequent step. With the development of deep learning, researchers began to exploit the “pre-training and fine-tuning” training process for multi-element segmentation, reducing the time spent on manual annotation. However, the existing element segmentation model only focuses on the overall accuracy at the pixel level, ignoring whether the element connectivity relationship can be correctly identified. To this end, this paper proposes a PCB CT image element segmentation model optimizing the semantic perception… More >

Kaixin Xia¹, Yu Gong^2,*, Xinxin Qi^3,4, Libin Zhao^3,4,*, Linjuan Wang¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.1, pp. 1-1, 2024, DOI:10.32604/icces.2024.011650

Abstract The crack tip of the asymmetric four-point bend end-notched flexure (4AENF) delamination testing under shear loading often exhibits a proportion of mode I component, making it a typical mixed-mode I/II problem. Characterizing the total fracture toughness in 4AENF laminates is crucial for understanding the delamination phenomenon in composites. In this study, 4AENF tests were conducted on carbon fiber-reinforced epoxy asymmetric laminates to evaluate the total interlaminar fracture toughness under shear loading conditions. Additionally, the variation of interlaminar fracture toughness in asymmetric laminates with different fiber orientation angles was considered. Theoretical modelling was performed using an More >

Xingbin Zhao¹, Neng Yang², Hao Liang³, Mingqiang Wei^2,*, Benteng Ma², Dongling Qiu²

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.11, pp. 2523-2540, 2024, DOI:10.32604/fdmp.2024.052766 - 28 October 2024

Abstract The transient flow testing of ultra-deepwater gas wells is greatly impacted by the low temperatures of seawater encountered over extended distances. This leads to a redistribution of temperature within the wellbore, which in turn influences the flow behavior. To accurately predict such a temperature distribution, in this study a comprehensive model of the flowing temperature and pressure fields is developed. This model is based on principles of fluid mechanics, heat transfer, mass conservation, and energy conservation and relies on the Runge-Kutta method for accurate integration in time of the resulting equations. The analysis includes the… More >

Deqing Han, Yong Zeng^*, Jintong Gu, Bin Yan

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.10, pp. 2393-2415, 2024, DOI:10.32604/fdmp.2024.053114 - 23 September 2024

Abstract To accurately predict the film thickness distribution during dynamic spraying performed with air guns and support accordingly the development of intelligent spray painting, the spray problem was analyzed numerically. In particular, the Eulerian-Eulerian approach was employed to calculate the paint atomization and film deposition process. Different spray heights, spray angles, spray gun movement speeds, spray trajectory curvature radii, and air pressure values were considered. Numerical simulation results indicate that the angle of spray painting significantly affects the velocity of droplets near the spray surface. With an increase in the spraying angle, spraying height and spray… More >

Irum Ilays¹, Yaser Hafeez^1,*, Nabil Almashfi², Sadia Ali¹, Mamoona Humayun^3,*, Muhammad Aqib¹, Ghadah Alwakid⁴

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 3761-3784, 2024, DOI:10.32604/cmc.2024.053830 - 12 September 2024

Abstract Software testing is a critical phase due to misconceptions about ambiguities in the requirements during specification, which affect the testing process. Therefore, it is difficult to identify all faults in software. As requirement changes continuously, it increases the irrelevancy and redundancy during testing. Due to these challenges; fault detection capability decreases and there arises a need to improve the testing process, which is based on changes in requirements specification. In this research, we have developed a model to resolve testing challenges through requirement prioritization and prediction in an agile-based environment. The research objective is to… More >

Ana Elena de Villalobos^1,2,*, María Andrea Long^1,2

Phyton-International Journal of Experimental Botany, Vol.93, No.8, pp. 2037-2050, 2024, DOI:10.32604/phyton.2024.053928 - 30 August 2024

Abstract Livestock grazing has a significant impact on natural grasslands, with approximately one-third of the world’s land area dedicated to this industry. Around 20% of global grasslands are highly degraded due to overgrazing, affecting their productivity and conservation capacity. Best practices are required to ensure sustainable livestock production that supports biodiversity. The Intermediate Disturbance Hypothesis (IDH) suggests that environments with moderate levels of disturbance exhibit a higher species diversity. Moderate grazing can reduce the dominance of certain species, thereby enhancing plant diversity. However, concerns arise regarding the increase of exotic and unpalatable species under moderate grazing… More >

Liqiong Chen¹, Kai Zhang^1,*, Song Yang¹, Duo Xu¹, Weihe Huang¹, Hongxuan Hu², Haonan Liu²

Structural Durability & Health Monitoring, Vol.18, No.5, pp. 683-706, 2024, DOI:10.32604/sdhm.2024.049536 - 19 July 2024

Abstract The North China Plain and the agricultural region are crossed by the Shanxi-Beijing natural gas pipeline. Residents in the area use rototillers for planting and harvesting; however, the depth of the rototillers into the ground is greater than the depth of the pipeline, posing a significant threat to the safe operation of the pipeline. Therefore, it is of great significance to study the dynamic response of rotary tillers impacting pipelines to ensure the safe operation of pipelines. This article focuses on the Shanxi-Beijing natural gas pipeline, utilizing finite element simulation software to establish a finite More >

Jiawei Qin^1,2, Hua Zhang^1,*, Hanbing Yan², Tian Zhu², Song Hu¹, Dingyu Yan²

Intelligent Automation & Soft Computing, Vol.39, No.3, pp. 527-544, 2024, DOI:10.32604/iasc.2024.047509 - 11 July 2024

Abstract By the analysis of vulnerabilities of Android native system services, we find that some vulnerabilities are caused by inconsistent data transmission and inconsistent data processing logic between client and server. The existing research cannot find the above two types of vulnerabilities and the test cases of them face the problem of low coverage. In this paper, we propose an extraction method of test cases based on the native system services of the client and design a case construction method that supports multi-parameter mutation based on genetic algorithm and priority strategy. Based on the above method, More >

Ziqiao Zhou¹, Tianyang Zhou^1,*, Jinghao Xu², Junhu Zhu¹

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2613-2634, 2024, DOI:10.32604/cmes.2023.028553 - 08 July 2024

Abstract Intelligent penetration testing is of great significance for the improvement of the security of information systems, and the critical issue is the planning of penetration test paths. In view of the difficulty for attackers to obtain complete network information in realistic network scenarios, Reinforcement Learning (RL) is a promising solution to discover the optimal penetration path under incomplete information about the target network. Existing RL-based methods are challenged by the sizeable discrete action space, which leads to difficulties in the convergence. Moreover, most methods still rely on experts’ knowledge. To address these issues, this paper… More >

Yanmei Shi¹, Wei Yu^2,*, Yanxia Zhao^3,*, Yungang Jia⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 887-906, 2024, DOI:10.32604/cmes.2024.046140 - 16 April 2024

Abstract Web application fingerprint recognition is an effective security technology designed to identify and classify web applications, thereby enhancing the detection of potential threats and attacks. Traditional fingerprint recognition methods, which rely on preannotated feature matching, face inherent limitations due to the ever-evolving nature and diverse landscape of web applications. In response to these challenges, this work proposes an innovative web application fingerprint recognition method founded on clustering techniques. The method involves extensive data collection from the Tranco List, employing adjusted feature selection built upon Wappalyzer and noise reduction through truncated SVD dimensionality reduction. The core… More >