Umer Sadiq Khan^1,2,*, Zhen Liu^1,2,*, Fang Xu^1,2, Muhib Ullah Khan^3,4, Lerui Chen⁵, Touseef Ahmed Khan^4,6, Muhammad Kashif Khattak⁷, Yuquan Zhang⁸

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3323-3348, 2024, DOI:10.32604/cmc.2024.046094

Abstract Image classification and unsupervised image segmentation can be achieved using the Gaussian mixture model. Although the Gaussian mixture model enhances the flexibility of image segmentation, it does not reflect spatial information and is sensitive to the segmentation parameter. In this study, we first present an efficient algorithm that incorporates spatial information into the Gaussian mixture model (GMM) without parameter estimation. The proposed model highlights the residual region with considerable information and constructs color saliency. Second, we incorporate the content-based color saliency as spatial information in the Gaussian mixture model. The segmentation is performed by clustering each pixel into an appropriate… More >

Qianqian Shao¹, Min Wang^2,*, Nuo Xu¹

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1337-1356, 2024, DOI:10.32604/cmes.2023.044313

Abstract To investigate the influences of co-flow and counter-flow modes of reactant flow arrangement on a proton exchange membrane fuel cell (PEMFC) during start-up, unsteady physical and mathematical models fully coupling the flow, heat, and electrochemical reactions in a PEMFC are established. The continuity equation and momentum equation are solved by handling pressure-velocity coupling using the SIMPLE algorithm. The electrochemical reaction rates in the catalyst layers (CLs) of the cathode and anode are calculated using the Butler-Volmer equation. The multiphase mixture model describes the multiphase transport process of gas mixtures and liquid water in the fuel cell. After validation, the influences… More >

Abdelwahed Berguiga^1,2,*, Ahlem Harchay^1,2, Ayman Massaoudi^1,2, Mossaad Ben Ayed³, Hafedh Belmabrouk⁴

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 379-402, 2023, DOI:10.32604/cmc.2023.041667

Abstract Smart Agriculture, also known as Agricultural 5.0, is expected to be an integral part of our human lives to reduce the cost of agricultural inputs, increasing productivity and improving the quality of the final product. Indeed, the safety and ongoing maintenance of Smart Agriculture from cyber-attacks are vitally important. To provide more comprehensive protection against potential cyber-attacks, this paper proposes a new deep learning-based intrusion detection system for securing Smart Agriculture. The proposed Intrusion Detection System IDS, namely GMLP-IDS, combines the feedforward neural network Multilayer Perceptron (MLP) and the Gaussian Mixture Model (GMM) that can better protect the Smart Agriculture… More >

Yu Chen^a , Shen Du^a, Dong Li^a, Yang Gao^b, Ya-Ling He^a,*

Frontiers in Heat and Mass Transfer, Vol.15, pp. 1-13, 2020, DOI:10.5098/hmt.15.19

Abstract Non-uniform heating and vapor blockage deteriorate the effectiveness of transpiration cooling, and an optimization method by using porous media with a gradually-changed structure is proposed. The numerical tool based on a two-phase mixture model and local thermal non-equilibrium assumption considering variable properties of coolant is applied. Porous media with linearly-changed porosity or particle diameter is analyzed. The transient results presented that the structure of gradually-changed porosity (or particle diameter) with appropriate parameters can delay the heat transfer deterioration. And it is confirmed that the present theoretical model is an effective tool for optimization design of transpiration cooling system. More >

Yue Yuan^1,*, Aibao Zhou^1,*, Tinghao Tang¹, Manying Kang², Haiyan Zhao¹, Zhi Wang³

International Journal of Mental Health Promotion, Vol.25, No.4, pp. 563-577, 2023, DOI:10.32604/ijmhp.2023.022161

Abstract Objective: In this research, we tried to explore how short-term mindfulness (STM) intervention affects adolescents’ anxiety, depression, and negative and positive emotion during the COVID-19 pandemic. Design: 10 classes were divided into experiment groups (5 classes; n = 238) and control (5 classes; n = 244) randomly. Hospital Anxiety and Depression Scale (HADS) and Positive and Negative Affect Schedule (PANAS) were used to measure participants’ dependent variables. In the experiment group, we conducted STM practice interventions every morning in their first class from March to November 2020. No interventions were conducted in the control group. Methods: Paired-sample t-tests were used to identify if a… More >

Debiao Meng^1,2,3, Shiyuan Yang¹, Tao Lin^4,5,*, Jiapeng Wang¹, Hengfei Yang¹, Zhiyuan Lv¹

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 553-568, 2022, DOI:10.32604/cmes.2022.020756

Abstract Actual engineering systems will be inevitably affected by uncertain factors. Thus, the Reliability-Based Multidisciplinary Design Optimization (RBMDO) has become a hotspot for recent research and application in complex engineering system design. The Second-Order/First-Order Mean-Value Saddlepoint Approximate (SOMVSA/FOMVSA) are two popular reliability analysis strategies that are widely used in RBMDO. However, the SOMVSA method can only be used efficiently when the distribution of input variables is Gaussian distribution, which significantly limits its application. In this study, the Gaussian Mixture Model-based Second-Order Mean-Value Saddlepoint Approximation (GMM-SOMVSA) is introduced to tackle above problem. It is integrated with the Collaborative Optimization (CO) method to… More >

T. Shanmuigapriya^1,*, S. Swamynathan², Thiruvaazhi Uloli³

Computer Systems Science and Engineering, Vol.43, No.3, pp. 1327-1339, 2022, DOI:10.32604/csse.2022.024440

Abstract Preserving privacy of the user is a very critical requirement to be met with all the international laws like GDPR, California privacy protection act and many other bills in place. On the other hand, Online Social Networks (OSN) has a wide spread recognition among the users, as a means of virtual communication. OSN may also acts as an identity provider for both internal and external applications. While it provides a simplified identification and authentication function to users across multiple applications, it also opens the users to a new spectrum of privacy threats. The privacy breaches costs to the users as… More >

Norah Saleh Alghamdi¹, Sami Bourouis^2,*, Nizar Bouguila³

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1139-1156, 2022, DOI:10.32604/cmc.2022.022959

Abstract Interest in automated data classification and identification systems has increased over the past years in conjunction with the high demand for artificial intelligence and security applications. In particular, recognizing human activities with accurate results have become a topic of high interest. Although the current tools have reached remarkable successes, it is still a challenging problem due to various uncontrolled environments and conditions. In this paper two statistical frameworks based on nonparametric hierarchical Bayesian models and Gamma distribution are proposed to solve some real-world applications. In particular, two nonparametric hierarchical Bayesian models based on Dirichlet process and Pitman-Yor process are developed.… More >

Hilly Gohain Baruah^*, Vijay Kumar Nath, Deepika Hazarika

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 137-164, 2022, DOI:10.32604/cmes.2022.018339

Abstract With the increasing popularity of high-resolution remote sensing images, the remote sensing image retrieval (RSIR) has always been a topic of major issue. A combined, global non-subsampled shearlet transform (NSST)-domain statistical features (NSSTds) and local three dimensional local ternary pattern (3D-LTP) features, is proposed for high-resolution remote sensing images. We model the NSST image coefficients of detail subbands using 2-state laplacian mixture (LM) distribution and its three parameters are estimated using Expectation-Maximization (EM) algorithm. We also calculate the statistical parameters such as subband kurtosis and skewness from detail subbands along with mean and standard deviation calculated from approximation subband, and… More >

S. Markkandan^1,*, S. Sivasubramanian², Jaison Mulerikkal³, Nazeer Shaik⁴, Beulah Jackson⁵, Lakshmi Naryanan⁶

Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 361-375, 2022, DOI:10.32604/iasc.2022.021779

Abstract The codebook design is the most essential core technique in constrained feedback massive multi-input multi-output (MIMO) system communications. MIMO vectors have been generally isotropic or evenly distributed in traditional codebook designs. In this paper, Gaussian mixture model (GMM) based clustering codebook design is proposed, which is inspired by the strong classification and analytical abilities of clustering techniques. Huge quantities of channel state information (CSI) are initially saved as entry data of the clustering process. Further, split into N number of clusters based on the shortest distance. The centroids part of clustering has been utilized for constructing a codebook with statistic… More >