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  • Open Access

    ARTICLE

    Film Flow of Nano-Micropolar Fluid with Dissipation Effect

    Abuzar Abid Siddiqui1, Mustafa Turkyilmazoglu2,3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2487-2512, 2024, DOI:10.32604/cmes.2024.050525

    Abstract The physical problem of the thin film flow of a micropolar fluid over a dynamic and inclined substrate under the influence of gravitational and thermal forces in the presence of nanoparticles is formulated. Five different types of nanoparticle samples are accounted for in this current study, namely gold Au, silver Ag, molybdenum disulfide MoS2, aluminum oxide Al2O3, and silicon dioxide SiO2. Blood, a micropolar fluid, serves as the common base fluid. An exact closed-form solution for this problem is derived for the first time in the literature. The results are particularly validated against those for the Newtonian fluid… More >

  • Open Access

    ARTICLE

    Integrating Neighborhood Geographic Distribution and Social Structure Influence for Social Media User Geolocation

    Meng Zhang1,2, Xiangyang Luo1,2,*, Ningbo Huang2

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2513-2532, 2024, DOI:10.32604/cmes.2024.050517

    Abstract Geolocating social media users aims to discover the real geographical locations of users from their publicly available data, which can support online location-based applications such as disaster alerts and local content recommendations. Social relationship-based methods represent a classical approach for geolocating social media. However, geographically proximate relationships are sparse and challenging to discern within social networks, thereby affecting the accuracy of user geolocation. To address this challenge, we propose user geolocation methods that integrate neighborhood geographical distribution and social structure influence (NGSI) to improve geolocation accuracy. Firstly, we propose a method for evaluating the homophily… More >

  • Open Access

    ARTICLE

    An Elastoplastic Fracture Model Based on Bond-Based Peridynamics

    Liping Zu1, Yaxun Liu1, Haoran Zhang1, Lisheng Liu2,*, Xin Lai2,*, Hai Mei2

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2349-2371, 2024, DOI:10.32604/cmes.2024.050488

    Abstract Fracture in ductile materials often occurs in conjunction with plastic deformation. However, in the bond-based peridynamic (BB-PD) theory, the classic mechanical stress is not defined inherently. This makes it difficult to describe plasticity directly using the classical plastic theory. To address the above issue, a unified bond-based peridynamics model was proposed as an effective tool to solve elastoplastic fracture problems. Compared to the existing models, the proposed model directly describes the elastoplastic theory at the bond level without the need for additional calculation means. The results obtained in the context of this model are shown More >

  • Open Access

    REVIEW

    A Comprehensive Systematic Review: Advancements in Skin Cancer Classification and Segmentation Using the ISIC Dataset

    Madiha Hameed1,3, Aneela Zameer1,*, Muhammad Asif Zahoor Raja2

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2131-2164, 2024, DOI:10.32604/cmes.2024.050124

    Abstract The International Skin Imaging Collaboration (ISIC) datasets are pivotal resources for researchers in machine learning for medical image analysis, especially in skin cancer detection. These datasets contain tens of thousands of dermoscopic photographs, each accompanied by gold-standard lesion diagnosis metadata. Annual challenges associated with ISIC datasets have spurred significant advancements, with research papers reporting metrics surpassing those of human experts. Skin cancers are categorized into melanoma and non-melanoma types, with melanoma posing a greater threat due to its rapid potential for metastasis if left untreated. This paper aims to address challenges in skin cancer detection… More >

  • Open Access

    ARTICLE

    Finite Difference-Peridynamic Differential Operator for Solving Transient Heat Conduction Problems

    Chunlei Ruan1,2,*, Cengceng Dong1, Zeyue Zhang1, Boyu Chen1, Zhijun Liu1

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2707-2728, 2024, DOI:10.32604/cmes.2024.050003

    Abstract Transient heat conduction problems widely exist in engineering. In previous work on the peridynamic differential operator (PDDO) method for solving such problems, both time and spatial derivatives were discretized using the PDDO method, resulting in increased complexity and programming difficulty. In this work, the forward difference formula, the backward difference formula, and the centered difference formula are used to discretize the time derivative, while the PDDO method is used to discretize the spatial derivative. Three new schemes for solving transient heat conduction equations have been developed, namely, the forward-in-time and PDDO in space (FT-PDDO) scheme,… More >

  • Open Access

    ARTICLE

    A Framework Based on the DAO and NFT in Blockchain for Electronic Document Sharing

    Lin Chen1, Jiaming Zhu1, Yuting Xu1, Huanqin Zheng1, Shen Su1,2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2373-2395, 2024, DOI:10.32604/cmes.2024.049996

    Abstract In the information age, electronic documents (e-documents) have become a popular alternative to paper documents due to their lower costs, higher dissemination rates, and ease of knowledge sharing. However, digital copyright infringements occur frequently due to the ease of copying, which not only infringes on the rights of creators but also weakens their creative enthusiasm. Therefore, it is crucial to establish an e-document sharing system that enforces copyright protection. However, the existing centralized system has outstanding vulnerabilities, and the plagiarism detection algorithm used cannot fully detect the context, semantics, style, and other factors of the… More >

  • Open Access

    ARTICLE

    Blockchain-Assisted Unsupervised Learning Method for Crowdsourcing Reputation Management

    Tianyu Wang1,2, Kongyang Chen2,3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2297-2314, 2024, DOI:10.32604/cmes.2024.049964

    Abstract Crowdsourcing holds broad applications in information acquisition and dissemination, yet encounters challenges pertaining to data quality assessment and user reputation management. Reputation mechanisms stand as crucial solutions for appraising and updating participant reputation scores, thereby elevating the quality and dependability of crowdsourced data. However, these mechanisms face several challenges in traditional crowdsourcing systems: 1) platform security lacks robust guarantees and may be susceptible to attacks; 2) there exists a potential for large-scale privacy breaches; and 3) incentive mechanisms relying on reputation scores may encounter issues as reputation updates hinge on task demander evaluations, occasionally lacking… More >

  • Open Access

    ARTICLE

    Advancements in Remote Sensing Image Dehazing: Introducing URA-Net with Multi-Scale Dense Feature Fusion Clusters and Gated Jump Connection

    Hongchi Liu1, Xing Deng1,*, Haijian Shao1,2

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2397-2424, 2024, DOI:10.32604/cmes.2024.049737

    Abstract The degradation of optical remote sensing images due to atmospheric haze poses a significant obstacle, profoundly impeding their effective utilization across various domains. Dehazing methodologies have emerged as pivotal components of image preprocessing, fostering an improvement in the quality of remote sensing imagery. This enhancement renders remote sensing data more indispensable, thereby enhancing the accuracy of target identification. Conventional defogging techniques based on simplistic atmospheric degradation models have proven inadequate for mitigating non-uniform haze within remotely sensed images. In response to this challenge, a novel UNet Residual Attention Network (URA-Net) is proposed. This paradigmatic approach… More > Graphic Abstract

    Advancements in Remote Sensing Image Dehazing: Introducing URA-Net with Multi-Scale Dense Feature Fusion Clusters and Gated Jump Connection

  • Open Access

    ARTICLE

    Comparing Fine-Tuning, Zero and Few-Shot Strategies with Large Language Models in Hate Speech Detection in English

    Ronghao Pan, José Antonio García-Díaz*, Rafael Valencia-García

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2849-2868, 2024, DOI:10.32604/cmes.2024.049631

    Abstract Large Language Models (LLMs) are increasingly demonstrating their ability to understand natural language and solve complex tasks, especially through text generation. One of the relevant capabilities is contextual learning, which involves the ability to receive instructions in natural language or task demonstrations to generate expected outputs for test instances without the need for additional training or gradient updates. In recent years, the popularity of social networking has provided a medium through which some users can engage in offensive and harmful online behavior. In this study, we investigate the ability of different LLMs, ranging from zero-shot… More >

  • Open Access

    ARTICLE

    A Novel ISSA–DELM Model for Predicting Rock Mass Permeability

    Chen Xing1, Leihua Yao1,*, Yingdong Wang2

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2825-2848, 2024, DOI:10.32604/cmes.2024.049330

    Abstract In pumped storage projects, the permeability of rock masses is a crucial parameter in engineering design and construction. The rock mass permeability coefficient (K) is influenced by various geological parameters, and previous studies aimed to establish an accurate relationship between K and geological parameters. This study uses the improved sparrow search algorithm (ISSA) to optimize the parameter settings of the deep extreme learning machine (DELM), constructing a prediction model with flexible parameter selection and high accuracy. First, the Spearman method is applied to analyze the correlation between geological parameters. A sample database is built by comprehensively… More >

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