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  • Open Access

    ARTICLE

    Blockchain Data Privacy Access Control Based on Searchable Attribute Encryption

    Tao Feng1,*, Hongmei Pei1, Rong Ma1, Youliang Tian2, Xiaoqin Feng3

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 871-890, 2021, DOI:10.32604/cmc.2020.012146

    Abstract Data privacy is important to the security of our society, and enabling authorized users to query this data efficiently is facing more challenge. Recently, blockchain has gained extensive attention with its prominent characteristics as public, distributed, decentration and chronological characteristics. However, the transaction information on the blockchain is open to all nodes, the transaction information update operation is even more transparent. And the leakage of transaction information will cause huge losses to the transaction party. In response to these problems, this paper combines hierarchical attribute encryption with linear secret sharing, and proposes a blockchain data privacy protection control scheme based… More >

  • Open Access

    ARTICLE

    Qualitative Analysis of a Fractional Pandemic Spread Model of the Novel Coronavirus (COVID-19)

    Ali Yousef1,*, Fatma Bozkurt1,2, Thabet Abdeljawad3,4,5

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 843-869, 2021, DOI:10.32604/cmc.2020.012060

    Abstract In this study, we classify the genera of COVID-19 and provide brief information about the root of the spread and the transmission from animal (natural host) to humans. We establish a model of fractional-order differential equations to discuss the spread of the infection from the natural host to the intermediate one, and from the intermediate one to the human host. At the same time, we focus on the potential spillover of bat-borne coronaviruses. We consider the local stability of the co-existing critical point of the model by using the Routh–Hurwitz Criteria. Moreover, we analyze the existence and uniqueness of the… More >

  • Open Access

    ARTICLE

    A Convolutional Neural Network Classifier VGG-19 Architecture for Lesion Detection and Grading in Diabetic Retinopathy Based on Deep Learning

    V. Sudha1,*, T. R. Ganeshbabu2

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 827-842, 2021, DOI:10.32604/cmc.2020.012008

    Abstract Diabetic Retinopathy (DR) is a type of disease in eyes as a result of a diabetic condition that ends up damaging the retina, leading to blindness or loss of vision. Morphological and physiological retinal variations involving slowdown of blood flow in the retina, elevation of leukocyte cohesion, basement membrane dystrophy, and decline of pericyte cells, develop. As DR in its initial stage has no symptoms, early detection and automated diagnosis can prevent further visual damage. In this research, using a Deep Neural Network (DNN), segmentation methods are proposed to detect the retinal defects such as exudates, hemorrhages, microaneurysms from digital… More >

  • Open Access

    ARTICLE

    Nonlinear Time Series Analysis of Pathogenesis of COVID-19 Pandemic Spread in Saudi Arabia

    Sunil Kumar Sharma1, Shivam Bhardwaj2,*, Rashmi Bhardwaj3, Majed Alowaidi1

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 805-825, 2021, DOI:10.32604/cmc.2020.011937

    Abstract This article discusses short–term forecasting of the novel Corona Virus (COVID-19) data for infected and recovered cases using the ARIMA method for Saudi Arabia. The COVID-19 data was obtained from the Worldometer and MOH (Ministry of Health, Saudi Arabia). The data was analyzed for the period from March 2, 2020 (the first case reported) to June 15, 2020. Using ARIMA (2, 1, 0), we obtained the short forecast up to July 02, 2020. Several statistical parameters were tested for the goodness of fit to evaluate the forecasting methods. The results show that ARIMA (2, 1, 0) gave a better forecast… More >

  • Open Access

    ARTICLE

    Hospital Bed Allocation Strategy Based on Queuing Theory during the COVID-19 Epidemic

    Jing Hu1, Gang Hu2,*, Jiantao Cai3, Lipeng Xu2, Qirun Wang4

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 793-803, 2021, DOI:10.32604/cmc.2020.011110

    Abstract During the current epidemic, it is necessary to ensure the rehabilitation treatment of children with serious illness. At the same time, however, it is essential to effectively prevent cross-infection and prevent infections from occurring within the hospital setting. To resolve this contradiction, the rehabilitation department of Nanjing Children’s Hospital adjusted its bed allocation based on the queuing model, with reference to the regional source and classification of the children’s conditions in the rehabilitation department ward. The original triple rooms were transformed into a double room to enable the treatment of severely sick children coming from other places. A M/G/2 queuing… More >

  • Open Access

    ARTICLE

    Privacy-Preserving Recommendation Based on Kernel Method in Cloud Computing

    Tao Li1, Qi Qian2, Yongjun Ren3,*, Yongzhen Ren4, Jinyue Xia5

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 779-791, 2021, DOI:10.32604/cmc.2020.010424

    Abstract The application field of the Internet of Things (IoT) involves all aspects, and its application in the fields of industry, agriculture, environment, transportation, logistics, security and other infrastructure has effectively promoted the intelligent development of these aspects. Although the IoT has gradually grown in recent years, there are still many problems that need to be overcome in terms of technology, management, cost, policy, and security. We need to constantly weigh the benefits of trusting IoT products and the risk of leaking private data. To avoid the leakage and loss of various user data, this paper developed a hybrid algorithm of… More >

  • Open Access

    ARTICLE

    Anomaly Classification Using Genetic Algorithm-Based Random Forest Model for Network Attack Detection

    Adel Assiri*

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 767-778, 2021, DOI:10.32604/cmc.2020.013813

    Abstract Anomaly classification based on network traffic features is an important task to monitor and detect network intrusion attacks. Network-based intrusion detection systems (NIDSs) using machine learning (ML) methods are effective tools for protecting network infrastructures and services from unpredictable and unseen attacks. Among several ML methods, random forest (RF) is a robust method that can be used in ML-based network intrusion detection solutions. However, the minimum number of instances for each split and the number of trees in the forest are two key parameters of RF that can affect classification accuracy. Therefore, optimal parameter selection is a real problem in… More >

  • Open Access

    ARTICLE

    Towards Interference-Aware ZigBee Transmissions in Heterogeneous Wireless Networks

    Sangsoon Lim1, Sanghyun Seo2,*

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 751-765, 2021, DOI:10.32604/cmc.2020.013430

    Abstract Cross-technology interference (CTI) from diverse wireless networks such as ZigBee, Bluetooth, and Wi-Fi has become a severe problem in the 2.4 GHz Industrial Scientific and Medical (ISM) band. Especially, low power and lossy networks are vulnerable to the signal interferences from other aggressive wireless networks when they perform low power operations to conserve the energy consumption. This paper presents CoSense, which accurately detects ZigBee signals with a reliable signal correlation scheme in the presence of the CTI. The key concept of CoSense is to reduce false wake-ups of low power listening (LPL) by identifying the pre-defined ZigBee signatures. Our scheme… More >

  • Open Access

    ARTICLE

    Emergency Prioritized and Congestion Handling Protocol for Medical Internet of Things

    Sabeen Tahir*, Sheikh Tahir Bakhsh, Rayed AlGhamdi

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 733-749, 2021, DOI:10.32604/cmc.2020.013261

    Abstract Medical Internet of Things (MIoTs) is a collection of small and energyefficient wireless sensor devices that monitor the patient’s body. The healthcare networks transmit continuous data monitoring for the patients to survive them independently. There are many improvements in MIoTs, but still, there are critical issues that might affect the Quality of Service (QoS) of a network. Congestion handling is one of the critical factors that directly affect the QoS of the network. The congestion in MIoT can cause more energy consumption, delay, and important data loss. If a patient has an emergency, then the life-critical signals must transmit with… More >

  • Open Access

    ARTICLE

    Artificial Intelligence-Based Semantic Segmentation of Ocular Regions for Biometrics and Healthcare Applications

    Rizwan Ali Naqvi1, Dildar Hussain2, Woong-Kee Loh3,*

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 715-732, 2021, DOI:10.32604/cmc.2020.013249

    Abstract Multiple ocular region segmentation plays an important role in different applications such as biometrics, liveness detection, healthcare, and gaze estimation. Typically, segmentation techniques focus on a single region of the eye at a time. Despite the number of obvious advantages, very limited research has focused on multiple regions of the eye. Similarly, accurate segmentation of multiple eye regions is necessary in challenging scenarios involving blur, ghost effects low resolution, off-angles, and unusual glints. Currently, the available segmentation methods cannot address these constraints. In this paper, to address the accurate segmentation of multiple eye regions in unconstrainted scenarios, a lightweight outer… More >

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