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  • Open Access


    Recognition and Classification of Pomegranate Leaves Diseases by Image Processing and Machine Learning Techniques

    Mangena Venu Madhavan1, Dang Ngoc Hoang Thanh2, Aditya Khamparia1,*, Sagar Pande1, Rahul Malik1, Deepak Gupta3

    CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2939-2955, 2021, DOI:10.32604/cmc.2021.012466

    Abstract Disease recognition in plants is one of the essential problems in agricultural image processing. This article focuses on designing a framework that can recognize and classify diseases on pomegranate plants exactly. The framework utilizes image processing techniques such as image acquisition, image resizing, image enhancement, image segmentation, ROI extraction (region of interest), and feature extraction. An image dataset related to pomegranate leaf disease is utilized to implement the framework, divided into a training set and a test set. In the implementation process, techniques such as image enhancement and image segmentation are primarily used for identifying More >

  • Open Access


    Natural Convection in an H-Shaped Porous Enclosure Filled with a Nanofluid

    Zehba A. S. Raizah1, Abdelraheem M. Aly1,2,*

    CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 3233-3251, 2021, DOI:10.32604/cmc.2021.012402

    Abstract This study simulates natural convection flow resulting from heat partitions in an H-shaped enclosure filled with a nanofluid using an incompressible smoothed particle hydrodynamics (ISPH) method. The right area of the H-shaped enclosure is saturated with non-Darcy porous media. The center variable partitions of the H-shaped enclosure walls are kept at a high-temperature Th. The left and right walls of the H-shaped enclosure are positioned at a low temperature Tc and the other walls are adiabatic. In ISPH method, the source term in pressure Poisson equation (PPE) is modified. The influences of the controlling parameters on… More >

  • Open Access


    An Optimal Deep Learning Based Computer-Aided Diagnosis System for Diabetic Retinopathy

    Phong Thanh Nguyen1, Vy Dang Bich Huynh2, Khoa Dang Vo1, Phuong Thanh Phan1, Eunmok Yang3,*, Gyanendra Prasad Joshi4

    CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2815-2830, 2021, DOI:10.32604/cmc.2021.012315

    Abstract Diabetic Retinopathy (DR) is a significant blinding disease that poses serious threat to human vision rapidly. Classification and severity grading of DR are difficult processes to accomplish. Traditionally, it depends on ophthalmoscopically-visible symptoms of growing severity, which is then ranked in a stepwise scale from no retinopathy to various levels of DR severity. This paper presents an ensemble of Orthogonal Learning Particle Swarm Optimization (OPSO) algorithm-based Convolutional Neural Network (CNN) Model EOPSO-CNN in order to perform DR detection and grading. The proposed EOPSO-CNN model involves three main processes such as preprocessing, feature extraction, and classification.… More >

  • Open Access


    Optimal Control Model for the Transmission of Novel COVID-19

    Isa Abdullahi Baba1,*, Bashir Ahmad Nasidi1, Dumitru Baleanu2,3,4

    CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 3089-3106, 2021, DOI:10.32604/cmc.2021.012301

    Abstract As the corona virus (COVID-19) pandemic ravages socio-economic activities in addition to devastating infectious and fatal consequences, optimal control strategy is an effective measure that neutralizes the scourge to its lowest ebb. In this paper, we present a mathematical model for the dynamics of COVID-19, and then we added an optimal control function to the model in order to effectively control the outbreak. We incorporate three main control efforts (isolation, quarantine and hospitalization) into the model aimed at controlling the spread of the pandemic. These efforts are further subdivided into five functions; u1(t) (isolation of the… More >

  • Open Access


    An Automated Penetration Semantic Knowledge Mining Algorithm Based on Bayesian Inference

    Yichao Zang1,*, Tairan Hu2, Tianyang Zhou2, Wanjiang Deng3

    CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2573-2585, 2021, DOI:10.32604/cmc.2021.012220

    Abstract Mining penetration testing semantic knowledge hidden in vast amounts of raw penetration testing data is of vital importance for automated penetration testing. Associative rule mining, a data mining technique, has been studied and explored for a long time. However, few studies have focused on knowledge discovery in the penetration testing area. The experimental result reveals that the long-tail distribution of penetration testing data nullifies the effectiveness of associative rule mining algorithms that are based on frequent pattern. To address this problem, a Bayesian inference based penetration semantic knowledge mining algorithm is proposed. First, a directed More >

  • Open Access


    A Novel Collective User Web Behavior Simulation Method

    Hongri Liu1,2,3, Xu Zhang1,3, Jingjing Li1,3, Bailing Wang1,3,*

    CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2539-2553, 2021, DOI:10.32604/cmc.2021.012213


    A collective user web behavior simulation is an import means for generating a large-scale user network behavior in a network testbed or cyber range. Existing studies almost focus on individual web behavior analysis and prediction, which cannot simulate human dynamics that widely exist in large-scale users’ behaviors. To address these issues, we propose a novel collective user web behavior simulation method, in which an algorithm for constructing a connected virtual social network is proposed, and then a collective user web behavior simulation algorithm is designed on the virtual social network. In the simulation method, a

    More >

  • Open Access


    Experimental Investigation on the Performance of Heat Pump Operating with Copper and Alumina Nanofluids

    Faizan Ahmed*, Waqar Ahmed Khan, Jamal Nayfeh

    CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2843-2856, 2021, DOI:10.32604/cmc.2021.012041

    Abstract In the present study, an attempt is made to enhance the performance of heat pump by utilizing two types of nanofluids namely, copper and alumina nanofluids. These nanofluids were employed around the evaporator coil of the heat pump. The nanofluids were used to enhance the heat input to the system by means of providing an external jacket around the evaporator coil. Both the nanofluids were prepared in three volume fractions 1%, 2% and 5%. Water was chosen as the base fluid. The performance of the heat pump was assessed by calculating the coefficient of performance… More >

  • Open Access


    Long-Term Preservation of Electronic Record Based on Digital Continuity in Smart Cities

    Yongjun Ren1,2, Kui Zhu1,2, Yuqiu Gao3, Jinyue Xia4,*, Shi Zhou1,2, Ruiguo Hu1,2, Xiujuan Feng5

    CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 3271-3287, 2021, DOI:10.32604/cmc.2021.011153

    Abstract Under the co-promotion of the wave of urbanization and the rise of data science, smart cities have become the new concept and new practice of urban development. Smart cities are the combination of information technology represented by the Internet of Things, cloud computing, mobile networks and big data, and urbanization. How to effectively achieve the long-term preservation of massive, heterogeneous, and multi-source digital electronic records in smart cities is a key issue that must be solved. Digital continuity can ensure the accessibility, integrity and availability of information. The quality management of electronic record, like the More >

  • Open Access


    Multi-Scale Blind Image Quality Predictor Based on Pyramidal Convolution

    Feng Yuan, Xiao Shao*

    Journal on Big Data, Vol.2, No.4, pp. 167-176, 2020, DOI:10.32604/jbd.2020.015357

    Abstract Traditional image quality assessment methods use the hand-crafted features to predict the image quality score, which cannot perform well in many scenes. Since deep learning promotes the development of many computer vision tasks, many IQA methods start to utilize the deep convolutional neural networks (CNN) for IQA task. In this paper, a CNN-based multi-scale blind image quality predictor is proposed to extract more effectivity multi-scale distortion features through the pyramidal convolution, which consists of two tasks: A distortion recognition task and a quality regression task. For the first task, image distortion type is obtained by More >

  • Open Access


    An Improved Distributed Query for Large-Scale RDF Data

    Aoran Li1, Xinmeng Wang1, Xueliang Wang4, Bohan Li1,2,3,*

    Journal on Big Data, Vol.2, No.4, pp. 157-166, 2020, DOI:10.32604/jbd.2020.010358

    Abstract The rigid structure of the traditional relational database leads to data redundancy, which seriously affects the efficiency of the data query and cannot effectively manage massive data. To solve this problem, we use distributed storage and parallel computing technology to query RDF data. In order to achieve efficient storage and retrieval of large-scale RDF data, we combine the respective advantage of the storage model of the relational database and the distributed query. To overcome the disadvantages of storing and querying RDF data, we design and implement a breadth-first path search algorithm based on the keyword More >

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