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  • Open Access

    ARTICLE

    A potential impact of A Disintegrin and Metalloproteinase DomainLike Protein Decysin-1 (ADAMDEC1) on clear cell renal cell carcinoma propagation

    MAGDALENA RUDZIŃSKA-RADECKA*

    BIOCELL, Vol.46, No.8, pp. 1893-1901, 2022, DOI:10.32604/biocell.2022.019724

    Abstract Clear cell renal cell carcinoma (KIRC) is the most common and aggressive malignancy subtype of renal neoplasm that arises from proximal convoluted tubules. It is characterized by poor clinical outcomes and high mortality of patients due to the lack of specific biomarkers for varying stages of the disease and no effective treatment. Proteases are associated with the development of several malignant tumors in humans by their ability to degrade extracellular matrices, facilitating metastasis. Herein, differentially expressed genes in KIRC cases compared to healthy kidneys were screened out from the Gene Expression Profiling Interactive Analysis (GEPIA) database. This data was applied… More >

  • Open Access

    ARTICLE

    An Advanced Stochastic Numerical Approach for Host-Vector-Predator Nonlinear Model

    Prem Junswang1, Zulqurnain Sabir2, Muhammad Asif Zahoor Raja3, Soheil Salahshour4, Thongchai Botmart5,*, Wajaree Weera5

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5823-5843, 2022, DOI:10.32604/cmc.2022.027629

    Abstract A novel design of the computational intelligent framework is presented to solve a class of host-vector-predator nonlinear model governed with set of ordinary differential equations. The host-vector-predator nonlinear model depends upon five groups or classes, host plant susceptible and infected populations, vectors population of susceptible and infected individuals and the predator population. An unsupervised artificial neural network is designed using the computational framework of local and global search competencies of interior-point algorithm and genetic algorithms. For solving the host-vector-predator nonlinear model, a merit function is constructed using the differential model and its associated boundary conditions. The optimization of this merit… More >

  • Open Access

    ARTICLE

    Optimized Hybrid Block Adams Method for Solving First Order Ordinary Differential Equations

    Hira Soomro1,*, Nooraini Zainuddin1, Hanita Daud1, Joshua Sunday2

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2947-2961, 2022, DOI:10.32604/cmc.2022.025933

    Abstract Multistep integration methods are being extensively used in the simulations of high dimensional systems due to their lower computational cost. The block methods were developed with the intent of obtaining numerical results on numerous points at a time and improving computational efficiency. Hybrid block methods for instance are specifically used in numerical integration of initial value problems. In this paper, an optimized hybrid block Adams block method is designed for the solutions of linear and nonlinear first-order initial value problems in ordinary differential equations (ODEs). In deriving the method, the Lagrange interpolation polynomial was employed based on some data points… More >

  • Open Access

    ARTICLE

    Modelling an Efficient Clinical Decision Support System for Heart Disease Prediction Using Learning and Optimization Approaches

    Sridharan Kannan*

    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 677-694, 2022, DOI:10.32604/cmes.2022.018580

    Abstract With the worldwide analysis, heart disease is considered a significant threat and extensively increases the mortality rate. Thus, the investigators mitigate to predict the occurrence of heart disease in an earlier stage using the design of a better Clinical Decision Support System (CDSS). Generally, CDSS is used to predict the individuals’ heart disease and periodically update the condition of the patients. This research proposes a novel heart disease prediction system with CDSS composed of a clustering model for noise removal to predict and eliminate outliers. Here, the Synthetic Over-sampling prediction model is integrated with the cluster concept to balance the… More >

  • Open Access

    ARTICLE

    COVID-19 Detection via a 6-Layer Deep Convolutional Neural Network

    Shouming Hou, Ji Han*

    CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 855-869, 2022, DOI:10.32604/cmes.2022.016621

    Abstract Many people around the world have lost their lives due to COVID-19. The symptoms of most COVID-19 patients are fever, tiredness and dry cough, and the disease can easily spread to those around them. If the infected people can be detected early, this will help local authorities control the speed of the virus, and the infected can also be treated in time. We proposed a six-layer convolutional neural network combined with max pooling, batch normalization and Adam algorithm to improve the detection effect of COVID-19 patients. In the 10-fold cross-validation methods, our method is superior to several state-of-the-art methods. In… More >

  • Open Access

    ARTICLE

    Numerical Solutions of a Novel Designed Prevention Class in the HIV Nonlinear Model

    Zulqurnain Sabir1, Muhammad Umar1, Muhammad Asif Zahoor Raja2,*, Dumitru Baleanu3,4

    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 227-251, 2021, DOI:10.32604/cmes.2021.016611

    Abstract The presented research aims to design a new prevention class (P) in the HIV nonlinear system, i.e., the HIPV model. Then numerical treatment of the newly formulated HIPV model is portrayed handled by using the strength of stochastic procedure based numerical computing schemes exploiting the artificial neural networks (ANNs) modeling legacy together with the optimization competence of the hybrid of global and local search schemes via genetic algorithms (GAs) and active-set approach (ASA), i.e., GA-ASA. The optimization performances through GA-ASA are accessed by presenting an error-based fitness function designed for all the classes of the HIPV model and its corresponding… More >

  • Open Access

    ARTICLE

    UFC-Net with Fully-Connected Layers and Hadamard Identity Skip Connection for Image Inpainting

    Chung-Il Kim1, Jehyeok Rew2, Yongjang Cho2, Eenjun Hwang2,*

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3447-3463, 2021, DOI:10.32604/cmc.2021.017633

    Abstract Image inpainting is an interesting technique in computer vision and artificial intelligence for plausibly filling in blank areas of an image by referring to their surrounding areas. Although its performance has been improved significantly using diverse convolutional neural network (CNN)-based models, these models have difficulty filling in some erased areas due to the kernel size of the CNN. If the kernel size is too narrow for the blank area, the models cannot consider the entire surrounding area, only partial areas or none at all. This issue leads to typical problems of inpainting, such as pixel reconstruction failure and unintended filling.… More >

  • Open Access

    ARTICLE

    NURBS Modeling and Curve Interpolation Optimization of 3D Graphics

    Hao Zhu1,*, Mulan Wang2, Kun Liu2, Weiye Xu3

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1799-1811, 2021, DOI:10.32604/cmc.2020.012706

    Abstract In order to solve the problem of complicated Non-Uniform Rational B-Splines (NURBS) modeling and improve the real-time performance of the high-order derivative of the curve interpolation process, the method of NURBS modeling based on the slicing and layering of triangular mesh is introduced. The research and design of NURBS curve interpolation are carried out from the two aspects of software algorithm and hardware structure. Based on the analysis of the characteristics of traditional computing methods with Taylor series expansion, the Adams formula and the Runge-Kutta formula are used in the NURBS curve interpolation process, and the process is then optimized… More >

  • Open Access

    ARTICLE

    Dynamic Simulation Analysis of the Working Device of a ZL50 Loader

    Guiju Zhang1,2, Caiyuan Xiao1,2,*

    FDMP-Fluid Dynamics & Materials Processing, Vol.16, No.4, pp. 699-707, 2020, DOI:10.32604/fdmp.2020.09481

    Abstract In this study, assuming a certain type of wheel loader as the main objective of the research, the performances of the working device of the loader are investigated on the basis of an in-house code. After creating a three-dimensional model of the working device using Solidworks, this model has been imported into the dynamic simulation software ADAMS, and the simulation problem has been completed by adding the relevant constraints and loadings. The load stress curve relating to the main connecting point of the working device has been obtained in the frame work of this approach and it has been shown… More >

  • Open Access

    ARTICLE

    Development of Biocomposites of MCC Extracted From Non-Wood Sources

    T. Dipin1, T. V. Jinitha1, E. Purushothaman1,*

    Journal of Renewable Materials, Vol.7, No.11, pp. 1109-1119, 2019, DOI:10.32604/jrm.2019.07636

    Abstract The present work mainly focuses on the estimation of various components and the extraction of microcrystalline cellulose (MCC) from non- wood sources like Country Almond/Badam shell through acid hydrolysis. This hydrolyzed MCC was successfully used as reinforcement for development of biocomposites. Country Almond/Badam trees are found all over Kerala, India and they give nuts once in a year. Usually the nut shells are discarded and are becoming one of the sources of agricultural waste. During this investigation various components were isolated from the Country Almond shells and they were characterised using different spectral and analytical techniques thereby the composition of… More >

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