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  • Open Access

    ARTICLE

    Hybrid Online Model for Predicting Diabetes Mellitus

    C. Mallika1,*, S. Selvamuthukumaran2

    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1873-1885, 2022, DOI:10.32604/iasc.2022.020543 - 09 October 2021

    Abstract Modern healthcare systems have become smart by synergizing the potentials of wireless sensors, the medical Internet of things, and big data science to provide better patient care while decreasing medical expenses. Large healthcare organizations generate and accumulate an incredible volume of data continuously. The already daunting volume of medical information has a massive amount of diagnostic features and logged details of patients for certain diseases such as diabetes. Diabetes mellitus has emerged as along-haul fatal disease across the globe and particularly in developing countries. Exact and early diagnosis of diabetes from big medical data is… More >

  • Open Access

    ARTICLE

    Hybrid Feature Extractions and CNN for Enhanced Periocular Identification During Covid-19

    Raniyah Wazirali1, Rami Ahmed2,*

    Computer Systems Science and Engineering, Vol.41, No.1, pp. 305-320, 2022, DOI:10.32604/csse.2022.020504 - 08 October 2021

    Abstract The global pandemic of novel coronavirus that started in 2019 has seriously affected daily lives and placed everyone in a panic condition. Widespread coronavirus led to the adoption of social distancing and people avoiding unnecessary physical contact with each other. The present situation advocates the requirement of a contactless biometric system that could be used in future authentication systems which makes fingerprint-based person identification ineffective. Periocular biometric is the solution because it does not require physical contact and is able to identify people wearing face masks. However, the periocular biometric region is a small area,… More >

  • Open Access

    REVIEW

    A Review of Recent Advances in Hybrid Natural Fiber Reinforced Polymer Composites

    Jorge Neto, Henrique Queiroz, Ricardo Aguiar, Rosemere Lima, Daniel Cavalcanti, Mariana Doina Banea*

    Journal of Renewable Materials, Vol.10, No.3, pp. 561-589, 2022, DOI:10.32604/jrm.2022.017434 - 28 September 2021

    Abstract Natural fiber reinforced polymer composites (NFRCs) have demonstrated great potential for many different applications in various industries due to their advantages compared to synthetic fiber-reinforced composites, such as low environmental impact and low cost. However, one of the drawbacks is that the NFRCs present relatively low mechanical properties and the absorption of humidity due to the hydrophilic characteristic of the natural fibre. One method to increase their performance is hybridization. Therefore, understanding the properties and potential of using multiple reinforcement’s materials to develop hybrid composites is of great interest. This paper provides an overview of… More > Graphic Abstract

    A Review of Recent Advances in Hybrid Natural Fiber Reinforced Polymer Composites

  • Open Access

    ARTICLE

    Training Multi-Layer Perceptron with Enhanced Brain Storm Optimization Metaheuristics

    Nebojsa Bacanin1, Khaled Alhazmi2,*, Miodrag Zivkovic1, K. Venkatachalam3, Timea Bezdan1, Jamel Nebhen4

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 4199-4215, 2022, DOI:10.32604/cmc.2022.020449 - 27 September 2021

    Abstract In the domain of artificial neural networks, the learning process represents one of the most challenging tasks. Since the classification accuracy highly depends on the weights and biases, it is crucial to find its optimal or suboptimal values for the problem at hand. However, to a very large search space, it is very difficult to find the proper values of connection weights and biases. Employing traditional optimization algorithms for this issue leads to slow convergence and it is prone to get stuck in the local optima. Most commonly, back-propagation is used for multi-layer-perceptron training and… More >

  • Open Access

    ARTICLE

    Identification of Composite-Metal Bolted Structures with Nonlinear Contact Effect

    Mohammad Ghalandari1, Ibrahim Mahariq2, Majid Pourghasem3, Hasan Mulki2, Fahd Jarad4,5,*

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3383-3397, 2022, DOI:10.32604/cmc.2022.020245 - 27 September 2021

    Abstract The middle layer model has been used in recent years to better describe the connection behavior in composite structures. The influencing parameters including low pre-screw and high preload have the main effects on nonlinear behavior of the connection as well as the amplitude of the excitation force applied to the structure. Therefore, in this study, the effects of connection behavior on the general structure in two sections of increasing damping and reducing the stiffness of the structures that lead to non-linear phenomena have been investigated. Due to the fact that in composite structure we are… More >

  • Open Access

    ARTICLE

    Neural Network and Fuzzy Control Based 11-Level Cascaded Inverter Operation

    Buddhadeva Sahoo1,*, Sangram Keshari Routray2, Pravat Kumar Rout2, Mohammed M. Alhaider3

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2319-2346, 2022, DOI:10.32604/cmc.2022.019559 - 27 September 2021

    Abstract This paper presents a combined control and modulation technique to enhance the power quality (PQ) and power reliability (PR) of a hybrid energy system (HES) through a single-phase 11-level cascaded H-bridge inverter (11-CHBI). The controller and inverter specifically regulate the HES and meet the load demand. To track optimum power, a Modified Perturb and Observe (MP&O) technique is used for HES. Ultra-capacitor (UCAP) based energy storage device and a novel current control strategy are proposed to provide additional active power support during both voltage sag and swell conditions. For an improved PQ and PR, a… More >

  • Open Access

    ARTICLE

    A Hybrid Approach for COVID-19 Detection Using Biogeography-Based Optimization and Deep Learning

    K. Venkatachalam1, Siuly Siuly2, M. Vinoth Kumar3, Praveen Lalwani1, Manas Kumar Mishra1, Enamul Kabir4,*

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3717-3732, 2022, DOI:10.32604/cmc.2022.018487 - 27 September 2021

    Abstract The COVID-19 pandemic has created a major challenge for countries all over the world and has placed tremendous pressure on their public health care services. An early diagnosis of COVID-19 may reduce the impact of the coronavirus. To achieve this objective, modern computation methods, such as deep learning, may be applied. In this study, a computational model involving deep learning and biogeography-based optimization (BBO) for early detection and management of COVID-19 is introduced. Specifically, BBO is used for the layer selection process in the proposed convolutional neural network (CNN). The computational model accepts images, such More >

  • Open Access

    ARTICLE

    Image Segmentation Based on Block Level and Hybrid Directional Local Extrema

    Ghanshyam Raghuwanshi1, Yogesh Gupta2, Deepak Sinwar1, Dilbag Singh3, Usman Tariq4, Muhammad Attique5, Kuntha Pin6, Yunyoung Nam7,*

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3939-3954, 2022, DOI:10.32604/cmc.2022.018423 - 27 September 2021

    Abstract In the recent decade, the digitalization of various tasks has added great flexibility to human lifestyle and has changed daily routine activities of communities. Image segmentation is a key step in digitalization. Segmentation plays a key role in almost all areas of image processing, and various approaches have been proposed for image segmentation. In this paper, a novel approach is proposed for image segmentation using a nonuniform adaptive strategy. Region-based image segmentation along with a directional binary pattern generated a better segmented image. An adaptive mask of 8 × 8 was circulated over the pixels whose bit… More >

  • Open Access

    ARTICLE

    Contrasting Characteristics of Lodging Resistance in Two Super-Rice Hybrids Differing in Harvest Index

    Zui Tao1, Tao Lei1, Fangbo Cao1, Jiana Chen1, Xiaohong Yin1,2, Tianfeng Liang2,*, Min Huang1,*

    Phyton-International Journal of Experimental Botany, Vol.91, No.2, pp. 429-437, 2022, DOI:10.32604/phyton.2022.016955 - 26 September 2021

    Abstract The “super rice” breeding program in China has been successful in developing high-yielding hybrids, including few with high harvest index values. However, there is limited information on the relationship between lodging resistance and harvest index, and the mechanisms underlying the relationship in super-rice hybrids. In this study, a two-year field experiment was conducted to compare lodging resistance and its related traits between two super-rice hybrids differing in harvest index, i.e., Guiliangyou 2 (G2) with a high harvest index and Y-liangyou 1 (Y1) with a typical harvest index of modern high-yielding rice varieties. Results showed that More >

  • Open Access

    ARTICLE

    Hybrid Active Contour Mammographic Mass Segmentation and Classification

    K. Yuvaraj*, U. S. Ragupathy

    Computer Systems Science and Engineering, Vol.40, No.3, pp. 823-834, 2022, DOI:10.32604/csse.2022.018837 - 24 September 2021

    Abstract This research implements a novel segmentation of mammographic mass. Three methods are proposed, namely, segmentation of mass based on iterative active contour, automatic region growing, and fully automatic mask selection-based active contour techniques. In the first method, iterative threshold is performed for manual cropped preprocessed image, and active contour is applied thereafter. To overcome manual cropping in the second method, an automatic seed selection followed by region growing is performed. Given that the result is only a few images owing to over segmentation, the third method uses a fully automatic active contour. Results of the… More >

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