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  • Open Access

    ARTICLE

    Analysis of Color Landscape Characteristics in “Beautiful Village” of China Based on 3D Real Scene Models

    Yiyi Cen1,3, Wenzheng Jia2, Wen Dai3,*, Chun Wang4, He Wu1

    Revue Internationale de Géomatique, Vol.33, pp. 93-109, 2024, DOI:10.32604/rig.2024.050273

    Abstract Color, as a significant element of village landscapes, serves various functions such as enhancing aesthetic appeal and attractiveness, conveying emotions and cultural values. To explore the three-dimensional spatial characteristics of color landscapes in beautiful villages, this study conducted a comparative experiment involving eight provincial-level beautiful villages and eight ordinary villages in Jinzhai County. Landscape pattern indices were used to analyze the color landscape patterns on the facades of these villages, complemented by a quantitative analysis of color attributes using the Munsell color system. The results indicate that (1) Natural landscape colors in beautiful villages are primarily concentrated in the yellow-red… More >

  • Open Access

    ARTICLE

    A Deep Learning Model for Insurance Claims Predictions

    Umar Isa Abdulkadir*, Anil Fernando*

    Journal on Artificial Intelligence, Vol.6, pp. 71-83, 2024, DOI:10.32604/jai.2024.045332

    Abstract One of the significant issues the insurance industry faces is its ability to predict future claims related to individual policyholders. As risk varies from one policyholder to another, the industry has faced the challenge of using various risk factors to accurately predict the likelihood of claims by policyholders using historical data. Traditional machine-learning models that use neural networks are recognized as exceptional algorithms with predictive capabilities. This study aims to develop a deep learning model using sequential deep regression techniques for insurance claim prediction using historical data obtained from Kaggle with 1339 cases and eight variables. This study adopted a… More >

  • Open Access

    ARTICLE

    A Hand Features Based Fusion Recognition Network with Enhancing Multi-Modal Correlation

    Wei Wu*, Yuan Zhang, Yunpeng Li, Chuanyang Li, Yan Hao

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 537-555, 2024, DOI:10.32604/cmes.2024.049174

    Abstract Fusing hand-based features in multi-modal biometric recognition enhances anti-spoofing capabilities. Additionally, it leverages inter-modal correlation to enhance recognition performance. Concurrently, the robustness and recognition performance of the system can be enhanced through judiciously leveraging the correlation among multimodal features. Nevertheless, two issues persist in multi-modal feature fusion recognition: Firstly, the enhancement of recognition performance in fusion recognition has not comprehensively considered the inter-modality correlations among distinct modalities. Secondly, during modal fusion, improper weight selection diminishes the salience of crucial modal features, thereby diminishing the overall recognition performance. To address these two issues, we introduce an enhanced DenseNet multimodal recognition network… More > Graphic Abstract

    A Hand Features Based Fusion Recognition Network with Enhancing Multi-Modal Correlation

  • Open Access

    ARTICLE

    Large-Scale Multi-Objective Optimization Algorithm Based on Weighted Overlapping Grouping of Decision Variables

    Liang Chen1, Jingbo Zhang1, Linjie Wu1, Xingjuan Cai1,2,*, Yubin Xu1

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 363-383, 2024, DOI:10.32604/cmes.2024.049044

    Abstract The large-scale multi-objective optimization algorithm (LSMOA), based on the grouping of decision variables, is an advanced method for handling high-dimensional decision variables. However, in practical problems, the interaction among decision variables is intricate, leading to large group sizes and suboptimal optimization effects; hence a large-scale multi-objective optimization algorithm based on weighted overlapping grouping of decision variables (MOEAWOD) is proposed in this paper. Initially, the decision variables are perturbed and categorized into convergence and diversity variables; subsequently, the convergence variables are subdivided into groups based on the interactions among different decision variables. If the size of a group surpasses the set… More >

  • Open Access

    ARTICLE

    Decoupling Algorithms for the Gravitational Wave Spacecraft

    Xue Wang1,2, Weizhou Zhu1,2, Zhao Cui2,3, Xingguang Qian2,3, Jinke Yang1,2, Jianjun Jia1,2,*, Yikun Wang2,3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 325-337, 2024, DOI:10.32604/cmes.2024.048804

    Abstract The gravitational wave spacecraft is a complex multi-input multi-output dynamic system. The gravitational wave detection mission requires the spacecraft to achieve single spacecraft with two laser links and high-precision control. Establishing one spacecraft with two laser links, compared to one spacecraft with a single laser link, requires an upgraded decoupling algorithm for the link establishment. The decoupling algorithm we designed reassigns the degrees of freedom and forces in the control loop to ensure sufficient degrees of freedom for optical axis control. In addressing the distinct dynamic characteristics of different degrees of freedom, a transfer function compensation method is used in… More >

  • Open Access

    ARTICLE

    Effect of Modulus Heterogeneity on the Equilibrium Shape and Stress Field of α Precipitate in Ti-6Al-4V

    Di Qiu1,3,4, Rongpei Shi2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 1017-1028, 2024, DOI:10.32604/cmes.2024.048797

    Abstract For media with inclusions (e.g., precipitates, voids, reinforcements, and others), the difference in lattice parameter and the elastic modulus between the matrix and inclusions cause stress concentration at the interfaces. These stress fields depend on the inclusions’ size, shape, and distribution and will respond instantly to the evolving microstructure. This study develops a phase-field model concerning modulus heterogeneity. The effect of modulus heterogeneity on the growth process and equilibrium state of the α plate in Ti-6Al-4V during precipitation is evaluated. The α precipitate exhibits strong anisotropy in shape upon cooling due to the interplay of the elastic strain and interfacial… More >

  • Open Access

    ARTICLE

    NFHP-RN: A Method of Few-Shot Network Attack Detection Based on the Network Flow Holographic Picture-ResNet

    Tao Yi1,3, Xingshu Chen1,2,*, Mingdong Yang3, Qindong Li1, Yi Zhu1

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 929-955, 2024, DOI:10.32604/cmes.2024.048793

    Abstract Due to the rapid evolution of Advanced Persistent Threats (APTs) attacks, the emergence of new and rare attack samples, and even those never seen before, make it challenging for traditional rule-based detection methods to extract universal rules for effective detection. With the progress in techniques such as transfer learning and meta-learning, few-shot network attack detection has progressed. However, challenges in few-shot network attack detection arise from the inability of time sequence flow features to adapt to the fixed length input requirement of deep learning, difficulties in capturing rich information from original flow in the case of insufficient samples, and the… More >

  • Open Access

    ARTICLE

    Application of the CatBoost Model for Stirred Reactor State Monitoring Based on Vibration Signals

    Xukai Ren1,2,*, Huanwei Yu2, Xianfeng Chen2, Yantong Tang2, Guobiao Wang1,*, Xiyong Du2

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 647-663, 2024, DOI:10.32604/cmes.2024.048782

    Abstract Stirred reactors are key equipment in production, and unpredictable failures will result in significant economic losses and safety issues. Therefore, it is necessary to monitor its health state. To achieve this goal, in this study, five states of the stirred reactor were firstly preset: normal, shaft bending, blade eccentricity, bearing wear, and bolt looseness. Vibration signals along x, y and z axes were collected and analyzed in both the time domain and frequency domain. Secondly, 93 statistical features were extracted and evaluated by ReliefF, Maximal Information Coefficient (MIC) and XGBoost. The above evaluation results were then fused by D-S evidence… More >

  • Open Access

    ARTICLE

    A Fault-Tolerant Mobility-Aware Caching Method in Edge Computing

    Yong Ma1, Han Zhao2, Kunyin Guo3,*, Yunni Xia3,*, Xu Wang4, Xianhua Niu5, Dongge Zhu6, Yumin Dong7

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 907-927, 2024, DOI:10.32604/cmes.2024.048759

    Abstract Mobile Edge Computing (MEC) is a technology designed for the on-demand provisioning of computing and storage services, strategically positioned close to users. In the MEC environment, frequently accessed content can be deployed and cached on edge servers to optimize the efficiency of content delivery, ultimately enhancing the quality of the user experience. However, due to the typical placement of edge devices and nodes at the network’s periphery, these components may face various potential fault tolerance challenges, including network instability, device failures, and resource constraints. Considering the dynamic nature of MEC, making high-quality content caching decisions for real-time mobile applications, especially… More >

  • Open Access

    ARTICLE

    A Privacy Preservation Method for Attributed Social Network Based on Negative Representation of Information

    Hao Jiang1, Yuerong Liao1, Dongdong Zhao2, Wenjian Luo3, Xingyi Zhang1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 1045-1075, 2024, DOI:10.32604/cmes.2024.048653

    Abstract Due to the presence of a large amount of personal sensitive information in social networks, privacy preservation issues in social networks have attracted the attention of many scholars. Inspired by the self-nonself discrimination paradigm in the biological immune system, the negative representation of information indicates features such as simplicity and efficiency, which is very suitable for preserving social network privacy. Therefore, we suggest a method to preserve the topology privacy and node attribute privacy of attribute social networks, called AttNetNRI. Specifically, a negative survey-based method is developed to disturb the relationship between nodes in the social network so that the… More >

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