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  • Open Access

    ARTICLE

    Locating Famous Tea’s Picking Point Based on Shi-Tomasi Algorithm

    Lei Zhang1,2, Lang Zou1,2, Chuanyu Wu1,2,*, Jianneng Chen1,2, Heping Chen3

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1109-1122, 2021, DOI:10.32604/cmc.2021.016495

    Abstract To address the difficulty of locating the picking point of a tea sprout during the intelligent automatic picking of famous tea, this study proposes a method to obtain information on the picking point on the basis of the Shi-Tomasi algorithm. This method can rapidly identify a tea sprout’s picking point and obtain its coordinates. Images of tea sprouts in a tea garden were collected, and the G-B component of tea sprouts was segmented using the Otsu algorithm. The region of interest was set with the lowest point of its contour as the center. The characteristics of tea buds and branches… More >

  • Open Access

    ARTICLE

    Robust Magnification Independent Colon Biopsy Grading System over Multiple Data Sources

    Tina Babu1, Deepa Gupta1, Tripty Singh1,*, Shahin Hameed2, Mohammed Zakariah3, Yousef Ajami Alotaibi4

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 99-128, 2021, DOI:10.32604/cmc.2021.016341

    Abstract Automated grading of colon biopsy images across all magnifications is challenging because of tailored segmentation and dependent features on each magnification. This work presents a novel approach of robust magnification-independent colon cancer grading framework to distinguish colon biopsy images into four classes: normal, well, moderate, and poor. The contribution of this research is to develop a magnification invariant hybrid feature set comprising cartoon feature, Gabor wavelet, wavelet moments, HSV histogram, color auto-correlogram, color moments, and morphological features that can be used to characterize different grades. Besides, the classifier is modeled as a multiclass structure with six binary class Bayesian optimized… More >

  • Open Access

    ARTICLE

    An Identity-Based Secure and Optimal Authentication Scheme for the Cloud Computing Environment

    K. Raju*, M. Chinnadurai

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1057-1072, 2021, DOI:10.32604/cmc.2021.016068

    Abstract Security is a critical issue in cloud computing (CC) because attackers can fabricate data by creating, copying, or deleting data with no user authorization. Most of the existing techniques make use of password-based authentication for encrypting data. Password-based schemes suffer from several issues and can be easily compromised. This paper presents a new concept of hybrid metaheuristic optimization as an identity-based secure and optimal authentication (HMO-ISOA) scheme for CC environments. The HMO-ISOA technique makes use of iris and fingerprint biometrics. Initially, the HMO-ISOA technique involves a directional local ternary quantized extrema pattern–based feature extraction process to extract features from the… More >

  • Open Access

    ARTICLE

    Scattered Data Interpolation Using Cubic Trigonometric Bézier Triangular Patch

    Ishak Hashim1, Nur Nabilah Che Draman2, Samsul Ariffin Abdul Karim3,*, Wee Ping Yeo4, Dumitru Baleanu5,6,7

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 221-236, 2021, DOI:10.32604/cmc.2021.016006

    Abstract This paper discusses scattered data interpolation using cubic trigonometric Bézier triangular patches with continuity everywhere. We derive the condition on each adjacent triangle. On each triangular patch, we employ convex combination method between three local schemes. The final interpolant with the rational corrected scheme is suitable for regular and irregular scattered data sets. We tested the proposed scheme with 36,65, and 100 data points for some well-known test functions. The scheme is also applied to interpolate the data for the electric potential. We compared the performance between our proposed method and existing scattered data interpolation schemes such as Powell–Sabin (PS)… More >

  • Open Access

    ARTICLE

    Classification and Categorization of COVID-19 Outbreak in Pakistan

    Amber Ayoub1, Kainaat Mahboob1, Abdul Rehman Javed2, Muhammad Rizwan1, Thippa Reddy Gadekallu2, Mustufa Haider Abidi3,*, Mohammed Alkahtani4,5

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1253-1269, 2021, DOI:10.32604/cmc.2021.015655

    Abstract Coronavirus is a potentially fatal disease that normally occurs in mammals and birds. Generally, in humans, the virus spreads through aerial droplets of any type of fluid secreted from the body of an infected person. Coronavirus is a family of viruses that is more lethal than other unpremeditated viruses. In December 2019, a new variant, i.e., a novel coronavirus (COVID-19) developed in Wuhan province, China. Since January 23, 2020, the number of infected individuals has increased rapidly, affecting the health and economies of many countries, including Pakistan. The objective of this research is to provide a system to classify and… More >

  • Open Access

    ARTICLE

    Rotational Effect on the Propagation of Waves in a Magneto-Micropolar Thermoelastic Medium

    A. M. Abd-Alla1,*, S. M. Abo-Dahab2, M. A. Abdelhafez1, A. M. Farhan3,4

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 205-220, 2021, DOI:10.32604/cmc.2021.015563

    Abstract The present paper aims to explore how the magnetic field, ramp parameter, and rotation affect a generalized micropolar thermoelastic medium that is standardized isotropic within the half-space. By employing normal mode analysis and Lame’s potential theory, the authors could express analytically the components of displacement, stress, couple stress, and temperature field in the physical domain. They calculated such manners of expression numerically and plotted the matching graphs to highlight and make comparisons with theoretical findings. The highlights of the paper cover the impacts of various parameters on the rotating micropolar thermoelastic half-space. Nevertheless, the non-dimensional temperature is not affected by… More >

  • Open Access

    ARTICLE

    Real-Time Multimodal Biometric Authentication of Human Using Face Feature Analysis

    Rohit Srivastava1, Ravi Tomar1, Ashutosh Sharma2, Gaurav Dhiman3, Naveen Chilamkurti4, Byung-Gyu Kim5,*

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1-19, 2021, DOI:10.32604/cmc.2021.015466

    Abstract As multimedia data sharing increases, data security in mobile devices and its mechanism can be seen as critical. Biometrics combines the physiological and behavioral qualities of an individual to validate their character in real-time. Humans incorporate physiological attributes like a fingerprint, face, iris, palm print, finger knuckle print, Deoxyribonucleic Acid (DNA), and behavioral qualities like walk, voice, mark, or keystroke. The main goal of this paper is to design a robust framework for automatic face recognition. Scale Invariant Feature Transform (SIFT) and Speeded-up Robust Features (SURF) are employed for face recognition. Also, we propose a modified Gabor Wavelet Transform for… More >

  • Open Access

    ARTICLE

    Hep-Pred: Hepatitis C Staging Prediction Using Fine Gaussian SVM

    Taher M. Ghazal1,2, Marrium Anam3, Mohammad Kamrul Hasan1, Muzammil Hussain4,*, Muhammad Sajid Farooq5, Hafiz Muhammad Ammar Ali4, Munir Ahmad6, Tariq Rahim Soomro7

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 191-203, 2021, DOI:10.32604/cmc.2021.015436

    Abstract Hepatitis C is a contagious blood-borne infection, and it is mostly asymptomatic during the initial stages. Therefore, it is difficult to diagnose and treat patients in the early stages of infection. The disease’s progression to its last stages makes diagnosis and treatment more difficult. In this study, an AI system based on machine learning algorithms is presented to help healthcare professionals with an early diagnosis of hepatitis C. The dataset used for our Hep-Pred model is based on a literature study, and includes the records of 1385 patients infected with the hepatitis C virus. Patients in this dataset received treatment… More >

  • Open Access

    ARTICLE

    A Highly Efficient Algorithm for Phased-Array mmWave Massive MIMO Beamforming

    Ayman Abdulhadi Althuwayb1, Fazirulhisyam Hashim2, Jiun Terng Liew2, Imran Khan3, Jeong Woo Lee4, Emmanuel Ampoma Affum5, Abdeldjalil Ouahabi6,7,*, Sébastien Jacques8

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 679-694, 2021, DOI:10.32604/cmc.2021.015421

    Abstract With the rapid development of the mobile internet and the internet of things (IoT), the fifth generation (5G) mobile communication system is seeing explosive growth in data traffic. In addition, low-frequency spectrum resources are becoming increasingly scarce and there is now an urgent need to switch to higher frequency bands. Millimeter wave (mmWave) technology has several outstanding features—it is one of the most well-known 5G technologies and has the capacity to fulfil many of the requirements of future wireless networks. Importantly, it has an abundant resource spectrum, which can significantly increase the communication rate of a mobile communication system. As… More >

  • Open Access

    ARTICLE

    3D Semantic Deep Learning Networks for Leukemia Detection

    Javaria Amin1, Muhammad Sharif2, Muhammad Almas Anjum3, Ayesha Siddiqa1, Seifedine Kadry4, Yunyoung Nam5,*, Mudassar Raza2

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 785-799, 2021, DOI:10.32604/cmc.2021.015249

    Abstract White blood cells (WBCs) are a vital part of the immune system that protect the body from different types of bacteria and viruses. Abnormal cell growth destroys the body’s immune system, and computerized methods play a vital role in detecting abnormalities at the initial stage. In this research, a deep learning technique is proposed for the detection of leukemia. The proposed methodology consists of three phases. Phase I uses an open neural network exchange (ONNX) and YOLOv2 to localize WBCs. The localized images are passed to Phase II, in which 3D-segmentation is performed using deeplabv3 as a base network of… More >

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