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  • Open Access

    ARTICLE

    Motion In-Betweening via Frequency-Domain Diffusion Model

    Qiang Zhang1, Shuo Feng1, Shanxiong Chen2, Teng Wan1, Ying Qi1,*

    CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-22, 2026, DOI:10.32604/cmc.2025.068247 - 10 November 2025

    Abstract Human motion modeling is a core technology in computer animation, game development, and human-computer interaction. In particular, generating natural and coherent in-between motion using only the initial and terminal frames remains a fundamental yet unresolved challenge. Existing methods typically rely on dense keyframe inputs or complex prior structures, making it difficult to balance motion quality and plausibility under conditions such as sparse constraints, long-term dependencies, and diverse motion styles. To address this, we propose a motion generation framework based on a frequency-domain diffusion model, which aims to better model complex motion distributions and enhance generation… More >

  • Open Access

    ARTICLE

    General Improvement of Image Interpolation-Based Data Hiding Methods Using Multiple-Based Number Conversion

    Da-Chun Wu*, Bing-Han Sie

    CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.1, pp. 535-580, 2025, DOI:10.32604/cmes.2025.067239 - 31 July 2025

    Abstract Data hiding methods involve embedding secret messages into cover objects to enable covert communication in a way that is difficult to detect. In data hiding methods based on image interpolation, the image size is reduced and then enlarged through interpolation, followed by the embedding of secret data into the newly generated pixels. A general improving approach for embedding secret messages is proposed. The approach may be regarded a general model for enhancing the data embedding capacity of various existing image interpolation-based data hiding methods. This enhancement is achieved by expanding the range of pixel values… More >

  • Open Access

    ARTICLE

    Statistical and Visual Evaluation of Artificial Neural Networks and Multiple Linear Regression Performances in Estimating Reference Crop Evapotranspiration for Mersin

    Fatma Bunyan Unel1,*, Lutfiye Kusak1, Murat Yakar1, Abdullah Sahin2, Hakan Dogan3, Fikret Demir4

    Revue Internationale de Géomatique, Vol.34, pp. 433-460, 2025, DOI:10.32604/rig.2025.065502 - 29 July 2025

    Abstract This study aimed to create a model for calculating the total reference crop evapotranspiration (ETo) in Mersin Province from May 2015 to 2020 and to generate maps using spatial analysis. Lemons from citrus play a significant role in Mersin’s agriculture, and because of lemons’ sensitivity to temperature, ETo is essential for them. It was observed that the ETo value () calculated using the Penman-Monteith (PM) method increased over the years. A model was developed using data from 36 Automated Weather Observing Systems (AWOS) in Mersin, Türkiye, which is located in a semi-arid climate zone. The… More >

  • Open Access

    ARTICLE

    Interpolation-Based Reversible Data Hiding in Encrypted Audio with Scalable Embedding Capacity

    Yuan-Yu Tsai1,*, Alfrindo Lin1, Wen-Ting Jao1, Yi-Hui Chen2,*

    CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 681-697, 2025, DOI:10.32604/cmc.2025.064370 - 09 June 2025

    Abstract With the rapid expansion of multimedia data, protecting digital information has become increasingly critical. Reversible data hiding offers an effective solution by allowing sensitive information to be embedded in multimedia files while enabling full recovery of the original data after extraction. Audio, as a vital medium in communication, entertainment, and information sharing, demands the same level of security as images. However, embedding data in encrypted audio poses unique challenges due to the trade-offs between security, data integrity, and embedding capacity. This paper presents a novel interpolation-based reversible data hiding algorithm for encrypted audio that achieves… More >

  • Open Access

    ARTICLE

    Occluded Gait Emotion Recognition Based on Multi-Scale Suppression Graph Convolutional Network

    Yuxiang Zou1, Ning He2,*, Jiwu Sun1, Xunrui Huang1, Wenhua Wang1

    CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 1255-1276, 2025, DOI:10.32604/cmc.2024.055732 - 03 January 2025

    Abstract In recent years, gait-based emotion recognition has been widely applied in the field of computer vision. However, existing gait emotion recognition methods typically rely on complete human skeleton data, and their accuracy significantly declines when the data is occluded. To enhance the accuracy of gait emotion recognition under occlusion, this paper proposes a Multi-scale Suppression Graph Convolutional Network (MS-GCN). The MS-GCN consists of three main components: Joint Interpolation Module (JI Moudle), Multi-scale Temporal Convolution Network (MS-TCN), and Suppression Graph Convolutional Network (SGCN). The JI Module completes the spatially occluded skeletal joints using the (K-Nearest Neighbors)… More >

  • Open Access

    ARTICLE

    An Enhanced Integrated Method for Healthcare Data Classification with Incompleteness

    Sonia Goel1,#, Meena Tushir1, Jyoti Arora2, Tripti Sharma2, Deepali Gupta3, Ali Nauman4,#, Ghulam Muhammad5,*

    CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 3125-3145, 2024, DOI:10.32604/cmc.2024.054476 - 18 November 2024

    Abstract In numerous real-world healthcare applications, handling incomplete medical data poses significant challenges for missing value imputation and subsequent clustering or classification tasks. Traditional approaches often rely on statistical methods for imputation, which may yield suboptimal results and be computationally intensive. This paper aims to integrate imputation and clustering techniques to enhance the classification of incomplete medical data with improved accuracy. Conventional classification methods are ill-suited for incomplete medical data. To enhance efficiency without compromising accuracy, this paper introduces a novel approach that combines imputation and clustering for the classification of incomplete data. Initially, the linear More >

  • Open Access

    ARTICLE

    A Hermitian C Differential Reproducing Kernel Interpolation Meshless Method for the 3D Microstructure-Dependent Static Flexural Analysis of Simply Supported and Functionally Graded Microplates

    Chih-Ping Wu*, Ruei-Syuan Chang

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 917-949, 2024, DOI:10.32604/cmes.2024.052307 - 20 August 2024

    Abstract This work develops a Hermitian C differential reproducing kernel interpolation meshless (DRKIM) method within the consistent couple stress theory (CCST) framework to study the three-dimensional (3D) microstructure-dependent static flexural behavior of a functionally graded (FG) microplate subjected to mechanical loads and placed under full simple supports. In the formulation, we select the transverse stress and displacement components and their first- and second-order derivatives as primary variables. Then, we set up the differential reproducing conditions (DRCs) to obtain the shape functions of the Hermitian C differential reproducing kernel (DRK) interpolant’s derivatives without using direct differentiation. The interpolant’s… More >

  • Open Access

    ARTICLE

    Research on Interpolation Method for Missing Electricity Consumption Data

    Junde Chen1, Jiajia Yuan2, Weirong Chen3, Adnan Zeb4, Md Suzauddola5, Yaser A. Nanehkaran2,*

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2575-2591, 2024, DOI:10.32604/cmc.2024.048522 - 27 February 2024

    Abstract Missing value is one of the main factors that cause dirty data. Without high-quality data, there will be no reliable analysis results and precise decision-making. Therefore, the data warehouse needs to integrate high-quality data consistently. In the power system, the electricity consumption data of some large users cannot be normally collected resulting in missing data, which affects the calculation of power supply and eventually leads to a large error in the daily power line loss rate. For the problem of missing electricity consumption data, this study proposes a group method of data handling (GMDH) based… More >

  • Open Access

    ARTICLE

    An Efficient Reliability-Based Optimization Method Utilizing High-Dimensional Model Representation and Weight-Point Estimation Method

    Xiaoyi Wang1, Xinyue Chang2, Wenxuan Wang1,*, Zijie Qiao3, Feng Zhang3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1775-1796, 2024, DOI:10.32604/cmes.2023.043913 - 29 January 2024

    Abstract The objective of reliability-based design optimization (RBDO) is to minimize the optimization objective while satisfying the corresponding reliability requirements. However, the nested loop characteristic reduces the efficiency of RBDO algorithm, which hinders their application to high-dimensional engineering problems. To address these issues, this paper proposes an efficient decoupled RBDO method combining high dimensional model representation (HDMR) and the weight-point estimation method (WPEM). First, we decouple the RBDO model using HDMR and WPEM. Second, Lagrange interpolation is used to approximate a univariate function. Finally, based on the results of the first two steps, the original nested More >

  • Open Access

    ARTICLE

    Wavelet Multi-Resolution Interpolation Galerkin Method for Linear Singularly Perturbed Boundary Value Problems

    Jiaqun Wang1,2, Guanxu Pan2, Youhe Zhou2, Xiaojing Liu2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 297-318, 2024, DOI:10.32604/cmes.2023.030622 - 30 December 2023

    Abstract In this study, a wavelet multi-resolution interpolation Galerkin method (WMIGM) is proposed to solve linear singularly perturbed boundary value problems. Unlike conventional wavelet schemes, the proposed algorithm can be readily extended to special node generation techniques, such as the Shishkin node. Such a wavelet method allows a high degree of local refinement of the nodal distribution to efficiently capture localized steep gradients. All the shape functions possess the Kronecker delta property, making the imposition of boundary conditions as easy as that in the finite element method. Four numerical examples are studied to demonstrate the validity More >

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