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  • Open Access

    ARTICLE

    How Software Engineering Transforms Organizations: An Open and Qualitative Study on the Organizational Objectives and Motivations in Agile Transformations

    Alonso Alvarez, Borja Bordel Sánchez*

    CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2935-2966, 2024, DOI:10.32604/cmc.2024.056990 - 18 November 2024

    Abstract Agile Transformations are challenging processes for organizations that look to extend the benefits of Agile philosophy and methods beyond software engineering. Despite the impact of these transformations on organizations, they have not been extensively studied in academia. We conducted a study grounded in workshops and interviews with 99 participants from 30 organizations, including organizations undergoing transformations (“final organizations”) and companies supporting these processes (“consultants”). The study aims to understand the motivations, objectives, and factors driving and challenging these transformations. Over 700 responses were collected to the question and categorized into 32 objectives. The findings show More >

  • Open Access

    ARTICLE

    Automatic Fetal Segmentation Designed on Computer-Aided Detection with Ultrasound Images

    Mohana Priya Govindarajan*, Sangeetha Subramaniam Karuppaiya Bharathi

    CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2967-2986, 2024, DOI:10.32604/cmc.2024.055536 - 18 November 2024

    Abstract In the present research, we describe a computer-aided detection (CAD) method aimed at automatic fetal head circumference (HC) measurement in 2D ultrasonography pictures during all trimesters of pregnancy. The HC might be utilized toward determining gestational age and tracking fetal development. This automated approach is particularly valuable in low-resource settings where access to trained sonographers is limited. The CAD system is divided into two steps: to begin, Haar-like characteristics were extracted from ultrasound pictures in order to train a classifier using random forests to find the fetal skull. We identified the HC using dynamic programming,… More >

  • Open Access

    ARTICLE

    Multiscale Feature Fusion for Gesture Recognition Using Commodity Millimeter-Wave Radar

    Lingsheng Li1, Weiqing Bai2, Chong Han2,*

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1613-1640, 2024, DOI:10.32604/cmc.2024.056073 - 15 October 2024

    Abstract Gestures are one of the most natural and intuitive approach for human-computer interaction. Compared with traditional camera-based or wearable sensors-based solutions, gesture recognition using the millimeter wave radar has attracted growing attention for its characteristics of contact-free, privacy-preserving and less environment-dependence. Although there have been many recent studies on hand gesture recognition, the existing hand gesture recognition methods still have recognition accuracy and generalization ability shortcomings in short-range applications. In this paper, we present a hand gesture recognition method named multiscale feature fusion (MSFF) to accurately identify micro hand gestures. In MSFF, not only the More >

  • Open Access

    ARTICLE

    Automated Angle Detection for Industrial Production Lines Using Combined Image Processing Techniques

    Pawat Chunhachatrachai1,*, Chyi-Yeu Lin1,2

    Intelligent Automation & Soft Computing, Vol.39, No.4, pp. 599-618, 2024, DOI:10.32604/iasc.2024.055385 - 06 September 2024

    Abstract Angle detection is a crucial aspect of industrial automation, ensuring precise alignment and orientation of components in manufacturing processes. Despite the widespread application of computer vision in industrial settings, angle detection remains an underexplored domain, with limited integration into production lines. This paper addresses the need for automated angle detection in industrial environments by presenting a methodology that eliminates training time and higher computation cost on Graphics Processing Unit (GPU) from machine learning in computer vision (e.g., Convolutional Neural Networks (CNN)). Our approach leverages advanced image processing techniques and a strategic combination of algorithms, including More >

  • Open Access

    EDITORIAL

    Introduction to the Special Issue on Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures

    Debiao Meng1,*, Abílio Manuel Pinho de Jesus2, Zeng Meng3

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 1-5, 2024, DOI:10.32604/cmes.2024.056319 - 20 August 2024

    Abstract This article has no abstract. More >

  • Open Access

    ARTICLE

    A Novel Framework to Construct S-Box Quantum Circuits Using System Modeling: Application to 4-Bit S-Boxes

    Yongjin Jeon, Seungjun Baek#, Jongsung Kim*

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 545-561, 2024, DOI:10.32604/cmes.2024.052374 - 20 August 2024

    Abstract Quantum computers accelerate many algorithms based on the superposition principle of quantum mechanics. The Grover algorithm provides significant performance to malicious users attacking symmetric key systems. Since the performance of attacks using quantum computers depends on the efficiency of the quantum circuit of the encryption algorithms, research research on the implementation of quantum circuits is essential. This paper presents a new framework to construct quantum circuits of substitution boxes (S-boxes) using system modeling. We model the quantum circuits of S-boxes using two layers: Toffoli and linear layers. We generate vector spaces based on the values… More >

  • Open Access

    REVIEW

    A Systematic Review of Computer Vision Techniques for Quality Control in End-of-Line Visual Inspection of Antenna Parts

    Zia Ullah1,2,*, Lin Qi1, E. J. Solteiro Pires2, Arsénio Reis2, Ricardo Rodrigues Nunes2

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2387-2421, 2024, DOI:10.32604/cmc.2024.047572 - 15 August 2024

    Abstract The rapid evolution of wireless communication technologies has underscored the critical role of antennas in ensuring seamless connectivity. Antenna defects, ranging from manufacturing imperfections to environmental wear, pose significant challenges to the reliability and performance of communication systems. This review paper navigates the landscape of antenna defect detection, emphasizing the need for a nuanced understanding of various defect types and the associated challenges in visual detection. This review paper serves as a valuable resource for researchers, engineers, and practitioners engaged in the design and maintenance of communication systems. The insights presented here pave the way… More >

  • Open Access

    ARTICLE

    Surface Defect Detection and Evaluation Method of Large Wind Turbine Blades Based on an Improved Deeplabv3+ Deep Learning Model

    Wanrun Li1,2,3,*, Wenhai Zhao1, Tongtong Wang1, Yongfeng Du1,2,3

    Structural Durability & Health Monitoring, Vol.18, No.5, pp. 553-575, 2024, DOI:10.32604/sdhm.2024.050751 - 19 July 2024

    Abstract The accumulation of defects on wind turbine blade surfaces can lead to irreversible damage, impacting the aerodynamic performance of the blades. To address the challenge of detecting and quantifying surface defects on wind turbine blades, a blade surface defect detection and quantification method based on an improved Deeplabv3+ deep learning model is proposed. Firstly, an improved method for wind turbine blade surface defect detection, utilizing Mobilenetv2 as the backbone feature extraction network, is proposed based on an original Deeplabv3+ deep learning model to address the issue of limited robustness. Secondly, through integrating the concept of… More > Graphic Abstract

    Surface Defect Detection and Evaluation Method of Large Wind Turbine Blades Based on an Improved Deeplabv3+ Deep Learning Model

  • Open Access

    ARTICLE

    GAN-DIRNet: A Novel Deformable Image Registration Approach for Multimodal Histological Images

    Haiyue Li1, Jing Xie2, Jing Ke3, Ye Yuan1, Xiaoyong Pan1, Hongyi Xin4, Hongbin Shen1,*

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 487-506, 2024, DOI:10.32604/cmc.2024.049640 - 18 July 2024

    Abstract Multi-modal histological image registration tasks pose significant challenges due to tissue staining operations causing partial loss and folding of tissue. Convolutional neural network (CNN) and generative adversarial network (GAN) are pivotal in medical image registration. However, existing methods often struggle with severe interference and deformation, as seen in histological images of conditions like Cushing’s disease. We argue that the failure of current approaches lies in underutilizing the feature extraction capability of the discriminator in GAN. In this study, we propose a novel multi-modal registration approach GAN-DIRNet based on GAN for deformable histological image registration. To… More >

  • Open Access

    ARTICLE

    Computational Fluid Dynamics Approach for Predicting Pipeline Response to Various Blast Scenarios: A Numerical Modeling Study

    Farman Saifi1,*, Mohd Javaid1, Abid Haleem1, S. M. Anas2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2747-2777, 2024, DOI:10.32604/cmes.2024.051490 - 08 July 2024

    Abstract Recent industrial explosions globally have intensified the focus in mechanical engineering on designing infrastructure systems and networks capable of withstanding blast loading. Initially centered on high-profile facilities such as embassies and petrochemical plants, this concern now extends to a wider array of infrastructures and facilities. Engineers and scholars increasingly prioritize structural safety against explosions, particularly to prevent disproportionate collapse and damage to nearby structures. Urbanization has further amplified the reliance on oil and gas pipelines, making them vital for urban life and prime targets for terrorist activities. Consequently, there is a growing imperative for computational… More >

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