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  • Open Access

    ARTICLE

    Medical Feature Selection Approach Based on Generalized Normal Distribution Algorithm

    Mohamed Abdel-Basset1, Reda Mohamed1, Ripon K. Chakrabortty2, Michael J. Ryan2, Yunyoung Nam3,*, Mohamed Abouhawwash4,5

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 2883-2901, 2021, DOI:10.32604/cmc.2021.017854

    Abstract This paper proposes a new pre-processing technique to separate the most effective features from those that might deteriorate the performance of the machine learning classifiers in terms of computational costs and classification accuracy because of their irrelevance, redundancy, or less information; this pre-processing process is often known as feature selection. This technique is based on adopting a new optimization algorithm known as generalized normal distribution optimization (GNDO) supported by the conversion of the normal distribution to a binary one using the arctangent transfer function to convert the continuous values into binary values. Further, a novel restarting strategy (RS) is proposed… More >

  • Open Access

    ARTICLE

    Implementation of Legendre Neural Network to Solve Time-Varying Singular Bilinear Systems

    V. Murugesh1, B. Saravana Balaji2,*, Habib Sano Aliy3, J. Bhuvana4, P. Saranya5, Andino Maseleno6, K. Shankar7, A. Sasikala8

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3685-3692, 2021, DOI:10.32604/cmc.2021.017836

    Abstract Bilinear singular systems can be used in the investigation of different types of engineering systems. In the past decade, considerable attention has been paid to analyzing and synthesizing singular bilinear systems. Their importance lies in their real world application such as economic, ecological, and socioeconomic processes. They are also applied in several biological processes, such as population dynamics of biological species, water balance, temperature regulation in the human body, carbon dioxide control in lungs, blood pressure, immune system, cardiac regulation, etc. Bilinear singular systems naturally represent different physical processes such as the fundamental law of mass action, the DC motor,… More >

  • Open Access

    ARTICLE

    Classification of Retroviruses Based on Genomic Data Using RVGC

    Khalid Mahmood Aamir1, Muhammad Bilal2, Muhammad Ramzan1,3, Muhammad Attique Khan4, Yunyoung Nam5,*, Seifedine Kadry6

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3829-3844, 2021, DOI:10.32604/cmc.2021.017835

    Abstract Retroviruses are a large group of infectious agents with similar virion structures and replication mechanisms. AIDS, cancer, neurologic disorders, and other clinical conditions can all be fatal due to retrovirus infections. Detection of retroviruses by genome sequence is a biological problem that benefits from computational methods. The National Center for Biotechnology Information (NCBI) promotes science and health by making biomedical and genomic data available to the public. This research aims to classify the different types of rotavirus genome sequences available at the NCBI. First, nucleotide pattern occurrences are counted in the given genome sequences at the preprocessing stage. Based on… More >

  • Open Access

    ARTICLE

    Multi-Layered Deep Learning Features Fusion for Human Action Recognition

    Sadia Kiran1, Muhammad Attique Khan1, Muhammad Younus Javed1, Majed Alhaisoni2, Usman Tariq3, Yunyoung Nam4,*, Robertas Damaševičius5, Muhammad Sharif6

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 4061-4075, 2021, DOI:10.32604/cmc.2021.017800

    Abstract Human Action Recognition (HAR) is an active research topic in machine learning for the last few decades. Visual surveillance, robotics, and pedestrian detection are the main applications for action recognition. Computer vision researchers have introduced many HAR techniques, but they still face challenges such as redundant features and the cost of computing. In this article, we proposed a new method for the use of deep learning for HAR. In the proposed method, video frames are initially pre-processed using a global contrast approach and later used to train a deep learning model using domain transfer learning. The Resnet-50 Pre-Trained Model is… More >

  • Open Access

    ARTICLE

    An Intelligent Graph Edit Distance-Based Approach for Finding Business Process Similarities

    Abid Sohail1, Ammar Haseeb1, Mobashar Rehman2,*, Dhanapal Durai Dominic3, Muhammad Arif Butt4

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3603-3618, 2021, DOI:10.32604/cmc.2021.017795

    Abstract There are numerous application areas of computing similarity between process models. It includes finding similar models from a repository, controlling redundancy of process models, and finding corresponding activities between a pair of process models. The similarity between two process models is computed based on their similarity between labels, structures, and execution behaviors. Several attempts have been made to develop similarity techniques between activity labels, as well as their execution behavior. However, a notable problem with the process model similarity is that two process models can also be similar if there is a structural variation between them. However, neither a benchmark… More >

  • Open Access

    ARTICLE

    Effect of Weather on the Spread of COVID-19 Using Eigenspace Decomposition

    Manar A. Alqudah1, Thabet Abdeljawad2,3,4,*, Anwar Zeb5, Izaz Ullah Khan5, Fatma Bozkurt6

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3047-3063, 2021, DOI:10.32604/cmc.2021.017752

    Abstract Since the end of 2019, the world has suffered from a pandemic of the disease called COVID-19. WHO reports show approximately 113 M confirmed cases of infection and 2.5 M deaths. All nations are affected by this nightmare that continues to spread. Widespread fear of this pandemic arose not only from the speed of its transmission: a rapidly changing “normal life” became a fear for everyone. Studies have mainly focused on the spread of the virus, which showed a relative decrease in high temperature, low humidity, and other environmental conditions. Therefore, this study targets the effect of weather in considering… More >

  • Open Access

    ARTICLE

    A Compromise Programming to Task Assignment Problem in Software Development Project

    Ngo Tung Son1,2,*, Jafreezal Jaafar1, Izzatdin Abdul Aziz1, Bui Ngoc Anh2, Hoang Duc Binh2, Muhammad Umar Aftab3

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3429-3444, 2021, DOI:10.32604/cmc.2021.017710

    Abstract The scheduling process that aims to assign tasks to members is a difficult job in project management. It plays a prerequisite role in determining the project’s quality and sometimes winning the bidding process. This study aims to propose an approach based on multi-objective combinatorial optimization to do this automatically. The generated schedule directs the project to be completed with the shortest critical path, at the minimum cost, while maintaining its quality. There are several real-world business constraints related to human resources, the similarity of the tasks added to the optimization model, and the literature’s traditional rules. To support the decision-maker… More >

  • Open Access

    ARTICLE

    Mango Leaf Disease Identification Using Fully Resolution Convolutional Network

    Rabia Saleem1, Jamal Hussain Shah1,*, Muhammad Sharif1, Ghulam Jillani Ansari2

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3581-3601, 2021, DOI:10.32604/cmc.2021.017700

    Abstract Due to the high demand for mango and being the king of all fruits, it is the need of the hour to curb its diseases to fetch high returns. Automatic leaf disease segmentation and identification are still a challenge due to variations in symptoms. Accurate segmentation of the disease is the key prerequisite for any computer-aided system to recognize the diseases, i.e., Anthracnose, apical-necrosis, etc., of a mango plant leaf. To solve this issue, we proposed a CNN based Fully-convolutional-network (FrCNnet) model for the segmentation of the diseased part of the mango leaf. The proposed FrCNnet directly learns the features… More >

  • Open Access

    ARTICLE

    FastAFLGo: Toward a Directed Greybox Fuzzing

    Chunlai Du1, Tong Jin1, Yanhui Guo2,*, Binghao Jia1, Bin Li3

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3845-3855, 2021, DOI:10.32604/cmc.2021.017697

    Abstract While the size and complexity of software are rapidly increasing, not only is the number of vulnerabilities increasing, but their forms are diversifying. Vulnerability has become an important factor in network attack and defense. Therefore, automatic vulnerability discovery has become critical to ensure software security. Fuzzing is one of the most important methods of vulnerability discovery. It is based on the initial input, i.e., a seed, to generate mutated test cases as new inputs of a tested program in the next execution loop. By monitoring the path coverage, fuzzing can choose high-value test cases for inclusion in the new seed… More >

  • Open Access

    ARTICLE

    An Intelligent Forwarding Strategy in SDN-Enabled Named-Data IoV

    Asadullah Tariq1, Irfan ud din1, Rana Asif Rehman2, Byung-Seo Kim3,*

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 2949-2966, 2021, DOI:10.32604/cmc.2021.017658

    Abstract Internet of Vehicles (IoV), a rapidly growing technology for efficient vehicular communication and it is shifting the trend of traditional Vehicular Ad Hoc Networking (VANET) towards itself. The centralized management of IoV endorses its uniqueness and suitability for the Intelligent Transportation System (ITS) safety applications. Named Data Networking (NDN) is an emerging internet paradigm that fulfills most of the expectations of IoV. Limitations of the current IP internet architecture are the main motivation behind NDN. Software-Defined Networking (SDN) is another emerging networking paradigm of technology that is highly capable of efficient management of overall networks and transforming complex networking architectures… More >

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