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  • Open Access

    ARTICLE

    STPEIC: A Swin Transformer-Based Framework for Interpretable Post-Earthquake Structural Classification

    Xinrui Ma, Shizhi Chen*

    Structural Durability & Health Monitoring, Vol.19, No.6, pp. 1745-1767, 2025, DOI:10.32604/sdhm.2025.071148 - 17 November 2025

    Abstract The rapid and accurate assessment of structural damage following an earthquake is crucial for effective emergency response and post-disaster recovery. Traditional manual inspection methods are often slow, labor-intensive, and prone to human error. To address these challenges, this study proposes STPEIC (Swin Transformer-based Framework for Interpretable Post-Earthquake Structural Classification), an automated deep learning framework designed for analyzing post-earthquake images. STPEIC performs two key tasks: structural components classification and damage level classification. By leveraging the hierarchical attention mechanisms of the Swin Transformer (Shifted Window Transformer), the model achieves 85.4% accuracy in structural component classification and 85.1% More >

  • Open Access

    ARTICLE

    Reducing UI Complexity Using Use Case Analysis in Adaptive Interfaces

    Qing-Xing Qu1,*, Le Zhang2,*, Fu Guo1, Vincent G. Duffy3

    CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 4607-4627, 2025, DOI:10.32604/cmc.2025.069245 - 23 October 2025

    Abstract This study aims to validate the Object-Oriented User Interface Customization (OOUIC) framework by employing Use Case Analysis (UCA) to facilitate the development of adaptive User Interfaces (UIs). The OOUIC framework advocates for User-Centered Design (UCD) methodologies, including UCA, to systematically identify intricate user requirements and construct adaptive UIs tailored to diverse user needs. To operationalize this approach, thirty users of Product Lifecycle Management (PLM) systems were interviewed across six distinct use cases. Interview transcripts were subjected to deductive content analysis to classify UI objects systematically. Subsequently, adaptive UIs were developed for each use case, and… More >

  • Open Access

    ARTICLE

    Optimization of Interactive Videos Empowered the Experience of Learning Management System

    Muhammad Akram1, Muhammad Waseem Iqbal2,*, M. Usman Ashraf3, Erssa Arif1, Khalid Alsubhi4, Hani Moaiteq Aljahdali5

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 1021-1038, 2023, DOI:10.32604/csse.2023.034085 - 20 January 2023

    Abstract The Learning management system (LMS) is now being used for uploading educational content in both distance and blended setups. LMS platform has two types of users: the educators who upload the content, and the students who have to access the content. The students, usually rely on text notes or books and video tutorials while their exams are conducted with formal methods. Formal assessments and examination criteria are ineffective with restricted learning space which makes the student tend only to read the educational contents and videos instead of interactive mode. The aim is to design an… More >

  • Open Access

    ARTICLE

    Usability-Driven Mobile Application Development

    Fadwa Yahya1,2,*, Lassaad Ben Ammar1,2, Gasmi Karim3

    Computer Systems Science and Engineering, Vol.45, No.3, pp. 3165-3180, 2023, DOI:10.32604/csse.2023.030358 - 21 December 2022

    Abstract Recently, a specific interest is being taken in the development of mobile application (app) via Model-Based User Interface Development (MBUID) approach. MBUID allows the generation of mobile apps in the target platform(s) from conceptual models. As such it simplified the development process of mobile app. However, the interest is only focused on the functional aspects of the mobile app while neglecting the non-functional aspects, such as usability. The latter is largely considered as the main factor leading to the success or failure of any software system. This paper aims at addressing non-functional aspects of mobile More >

  • Open Access

    ARTICLE

    User Interface-Based Repeated Sequence Detection Method for Authentication

    Shin Jin Kang1, Soo Kyun Kim2,*

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2573-2588, 2023, DOI:10.32604/iasc.2023.029893 - 17 August 2022

    Abstract In this paper, we propose an authentication method that use mouse and keystroke dynamics to enhance online privacy and security. The proposed method identifies personalized repeated user interface (UI) sequences by analyzing mouse and keyboard data. To this end, an Apriori algorithm based on the keystroke-level model (KLM) of the human–computer interface domain was used. The proposed system can detect repeated UI sequences based on KLM for authentication in the software. The effectiveness of the proposed method is verified through access testing using commercial applications that require intensive UI interactions. The results show using our More >

  • Open Access

    ARTICLE

    Bacterial Foraging Based Algorithm Front-end to Solve Global Optimization Problems

    Betania Hernández-Ocaña, Adrian García-López, José Hernández-Torruco, Oscar Chávez-Bosquez*

    Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1797-1813, 2022, DOI:10.32604/iasc.2022.023570 - 09 December 2021

    Abstract The Bacterial Foraging Algorithm (BFOA) is a well-known swarm collective intelligence algorithm used to solve a variety of constraint optimization problems with wide success. Despite its universality, implementing the BFOA may be complex due to the calibration of multiple parameters. Moreover, the Two-Swim Modified Bacterial Foraging Optimization Algorithm (TS-MBFOA) is a state-of-the-art modification of the BFOA which may lead to solutions close to the optimal but with more parameters than the original BFOA. That is why in this paper we present the design using the Unified Modeling Language (UML) and the implementation in the MATLAB… More >

  • Open Access

    ARTICLE

    Automated Identification Algorithm Using CNN for Computer Vision in Smart Refrigerators

    Pulkit Jain1, Paras Chawla1, Mehedi Masud2,*, Shubham Mahajan3, Amit Kant Pandit3

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3337-3353, 2022, DOI:10.32604/cmc.2022.023053 - 07 December 2021

    Abstract Machine Learning has evolved with a variety of algorithms to enable state-of-the-art computer vision applications. In particular the need for automating the process of real-time food item identification, there is a huge surge of research so as to make smarter refrigerators. According to a survey by the Food and Agriculture Organization of the United Nations (FAO), it has been found that 1.3 billion tons of food is wasted by consumers around the world due to either food spoilage or expiry and a large amount of food is wasted from homes and restaurants itself. Smart refrigerators… More >

  • Open Access

    ARTICLE

    Design Principles-Based Interactive Learning Tool for Solving Nonlinear Equations

    Ahad Alloqmani1, Omimah Alsaedi1, Nadia Bahatheg1, Reem Alnanih1,*, Lamiaa Elrefaei1,2

    Computer Systems Science and Engineering, Vol.40, No.3, pp. 1023-1042, 2022, DOI:10.32604/csse.2022.019704 - 24 September 2021

    Abstract Interactive learning tools can facilitate the learning process and increase student engagement, especially tools such as computer programs that are designed for human-computer interaction. Thus, this paper aims to help students learn five different methods for solving nonlinear equations using an interactive learning tool designed with common principles such as feedback, visibility, affordance, consistency, and constraints. It also compares these methods by the number of iterations and time required to display the result. This study helps students learn these methods using interactive learning tools instead of relying on traditional teaching methods. The tool is implemented More >

  • Open Access

    ARTICLE

    Unsupervised Semantic Segmentation Method of User Interface Component of Games

    Shinjin Kang1, Jongin Choi2,*

    Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 1089-1105, 2022, DOI:10.32604/iasc.2022.019979 - 22 September 2021

    Abstract The game user interface (UI) provides a large volume of information necessary to analyze the game screen. The availability of such information can be functional in vision-based machine learning algorithms. With this, there will be an enhancement in the application power of vision deep learning neural networks. Therefore, this paper proposes a game UI segmentation technique based on unsupervised learning. We developed synthetic labeling created on the game engine, image-to-image translation and segmented UI components in the game. The network learned in this manner can segment the target UI area in the target game regardless More >

  • Open Access

    ARTICLE

    Blind and Visually Impaired User Interface to Solve Accessibility Problems

    Azeem Shera1, Muhammad Waseem Iqbal2,*, Syed Khuram Shahzad3, Madeeha Gul1, Natash Ali Mian4, Muhammad Raza Naqvi5, Babar Ayub Khan1

    Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 285-301, 2021, DOI:10.32604/iasc.2021.018009 - 26 July 2021

    Abstract Blind and visually impaired (BVI) users often have interface accessibility problems while using mobile applications. This study was conducted to reduce the cognitive effort required for interface navigation by identifying the accessibility issues according to the user’s mental model. The study evaluated the accessibility of smartphone screens to solve organizational, presentation, and behavioral (OPB) problems of using mobile applications. Usability evaluation of an application was conducted and validated with a specific focus on BVI user experience. A total of 56 BVI participants were included in the evaluation. Overall, four tasks to assess organization, avoidance of… More >

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