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  • Open Access

    ARTICLE

    Entropy-Based Approach to Detect DDoS Attacks on Software Defined Networking Controller

    Mohammad Aladaileh1, Mohammed Anbar1,*, Iznan H. Hasbullah1, Yousef K. Sanjalawe1,2, Yung-Wey Chong1

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 373-391, 2021, DOI:10.32604/cmc.2021.017972

    Abstract The Software-Defined Networking (SDN) technology improves network management over existing technology via centralized network control. The SDN provides a perfect platform for researchers to solve traditional network’s outstanding issues. However, despite the advantages of centralized control, concern about its security is rising. The more traditional network switched to SDN technology, the more attractive it becomes to malicious actors, especially the controller, because it is the network’s brain. A Distributed Denial of Service (DDoS) attack on the controller could cripple the entire network. For that reason, researchers are always looking for ways to detect DDoS attacks against the controller with higher… More >

  • Open Access

    ARTICLE

    Video Analytics Framework for Human Action Recognition

    Muhammad Attique Khan1, Majed Alhaisoni2, Ammar Armghan3, Fayadh Alenezi3, Usman Tariq4, Yunyoung Nam5,*, Tallha Akram6

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3841-3859, 2021, DOI:10.32604/cmc.2021.016864

    Abstract Human action recognition (HAR) is an essential but challenging task for observing human movements. This problem encompasses the observations of variations in human movement and activity identification by machine learning algorithms. This article addresses the challenges in activity recognition by implementing and experimenting an intelligent segmentation, features reduction and selection framework. A novel approach has been introduced for the fusion of segmented frames and multi-level features of interests are extracted. An entropy-skewness based features reduction technique has been implemented and the reduced features are converted into a codebook by serial based fusion. A custom made genetic algorithm is implemented on… More >

  • Open Access

    ARTICLE

    Eye Gaze Detection Based on Computational Visual Perception and Facial Landmarks

    Debajit Datta1, Pramod Kumar Maurya1, Kathiravan Srinivasan2, Chuan-Yu Chang3,*, Rishav Agarwal1, Ishita Tuteja1, V. Bhavyashri Vedula1

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2545-2561, 2021, DOI:10.32604/cmc.2021.015478

    Abstract The pandemic situation in 2020 brought about a ‘digitized new normal’ and created various issues within the current education systems. One of the issues is the monitoring of students during online examination situations. A system to determine the student’s eye gazes during an examination can help to eradicate malpractices. In this work, we track the users’ eye gazes by incorporating twelve facial landmarks around both eyes in conjunction with computer vision and the HAAR classifier. We aim to implement eye gaze detection by considering facial landmarks with two different Convolutional Neural Network (CNN) models, namely the AlexNet model and the… More >

  • Open Access

    ARTICLE

    Alcoholism Detection by Wavelet Energy Entropy and Linear Regression Classifier

    Xianqing Chen1,2, Yan Yan3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.127, No.1, pp. 325-343, 2021, DOI:10.32604/cmes.2021.014489

    Abstract Alcoholism is an unhealthy lifestyle associated with alcohol dependence. Not only does drinking for a long time leads to poor mental health and loss of self-control, but alcohol seeps into the bloodstream and shortens the lifespan of the body’s internal organs. Alcoholics often think of alcohol as an everyday drink and see it as a way to reduce stress in their lives because they cannot see the damage in their bodies and they believe it does not affect their physical health. As their drinking increases, they become dependent on alcohol and it affects their daily lives. Therefore, it is important… More >

  • Open Access

    ARTICLE

    Kernel Entropy Based Extended Kalman Filter for GPS Navigation Processing

    Dah-Jing Jwo*, Jui-Tao Lee

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 857-876, 2021, DOI:10.32604/cmc.2021.016894

    Abstract This paper investigates the kernel entropy based extended Kalman filter (EKF) as the navigation processor for the Global Navigation Satellite Systems (GNSS), such as the Global Positioning System (GPS). The algorithm is effective for dealing with non-Gaussian errors or heavy-tailed (or impulsive) interference errors, such as the multipath. The kernel minimum error entropy (MEE) and maximum correntropy criterion (MCC) based filtering for satellite navigation system is involved for dealing with non-Gaussian errors or heavy-tailed interference errors or outliers of the GPS. The standard EKF method is derived based on minimization of mean square error (MSE) and is optimal only under… More >

  • Open Access

    ARTICLE

    Second Law Analysis of Magneto Radiative GO-MoS2/H2O–(CH2OH)2 Hybrid Nanofluid

    Adnan1, Umar Khan2, Naveed Ahmed3, Syed Tauseef Mohyud-Din4, Dumitru Baleanu5,6,7, Kottakkaran Sooppy Nisar8, Ilyas Khan9,*

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 213-228, 2021, DOI:10.32604/cmc.2021.014383

    Abstract Entropy Generation Optimization (EGO) attained huge interest of scientists and researchers due to its numerous applications comprised in mechanical engineering, air conditioners, heat engines, thermal machines, heat exchange, refrigerators, heat pumps and substance mixing etc. Therefore, the study of radiative hybrid nanofluid (GO-MoS2/C2H6O2–H2O) and the conventional nanofluid (MoS2/C2H6O2–H2O) is conducted in the presence of Lorentz forces. The flow configuration is modeled between the parallel rotating plates in which the lower plate is permeable. The models which govern the flow in rotating system are solved numerically over the domain of interest and furnished the results for the temperature, entropy generation and… More >

  • Open Access

    ARTICLE

    Entropy-Based Watermarking Approach for Sensitive Tamper Detection of Arabic Text

    Fahd N. Al-Wesabi1,2,*

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3635-3648, 2021, DOI:10.32604/cmc.2021.015865

    Abstract The digital text media is the most common media transferred via the internet for various purposes and is very sensitive to transfer online with the possibility to be tampered illegally by the tampering attacks. Therefore, improving the security and authenticity of the text when it is transferred via the internet has become one of the most difficult challenges that researchers face today. Arabic text is more sensitive than other languages due to Harakat’s existence in Arabic diacritics such as Kasra, and Damma in which making basic changes such as modifying diacritic arrangements can lead to change the text meaning. In… More >

  • Open Access

    ARTICLE

    Minimum Error Entropy Based EKF for GPS Code Tracking Loop

    Dah-Jing Jwo1,*, Jen-Hsien Lai2

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 2883-2898, 2021, DOI:10.32604/cmc.2021.015102

    Abstract This paper investigates the minimum error entropy based extended Kalman filter (MEEKF) for multipath parameter estimation of the Global Positioning System (GPS). The extended Kalman filter (EKF) is designed to give a preliminary estimation of the state. The scheme is designed by introducing an additional term, which is tuned according to the higher order moment of the estimation error. The minimum error entropy criterion is introduced for updating the entropy of the innovation at each time step. According to the stochastic information gradient method, an optimal filer gain matrix is obtained. The mean square error criterion is limited to the… More >

  • Open Access

    ARTICLE

    Deep Learning-Based Hookworm Detection in Wireless Capsule Endoscopic Image Using AdaBoost Classifier

    K. Lakshminarayanan1, N. Muthukumaran1, Y. Harold Robinson2, Vimal Shanmuganathan3, Seifedine Kadry4, Yunyoung Nam5,*

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3045-3055, 2021, DOI:10.32604/cmc.2021.014370

    Abstract Hookworm is an illness caused by an internal sponger called a roundworm. Inferable from deprived cleanliness in the developing nations, hookworm infection is a primary source of concern for both motherly and baby grimness. The current framework for hookworm detection is composed of hybrid convolutional neural networks; explicitly an edge extraction framework alongside a hookworm classification framework is developed. To consolidate the cylindrical zones obtained from the edge extraction framework and the trait map acquired into the hookworm scientific categorization framework, pooling layers are proposed. The hookworms display different profiles, widths, and bend directions. These challenges make it difficult for… More >

  • Open Access

    ARTICLE

    Fractional Rényi Entropy Image Enhancement for Deep Segmentation of Kidney MRI

    Hamid A. Jalab1, Ala’a R. Al-Shamasneh1, Hadil Shaiba2, Rabha W. Ibrahim3,4,*, Dumitru Baleanu5,6,7

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2061-2075, 2021, DOI:10.32604/cmc.2021.015170

    Abstract Recently, many rapid developments in digital medical imaging have made further contributions to health care systems. The segmentation of regions of interest in medical images plays a vital role in assisting doctors with their medical diagnoses. Many factors like image contrast and quality affect the result of image segmentation. Due to that, image contrast remains a challenging problem for image segmentation. This study presents a new image enhancement model based on fractional Rényi entropy for the segmentation of kidney MRI scans. The proposed work consists of two stages: enhancement by fractional Rényi entropy, and MRI Kidney deep segmentation. The proposed… More >

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