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  • Open Access

    ARTICLE

    Implications COVID-19 on Performance and Energy Management in the Production Electricity

    Noor Shakir Mahmood1, Ahmed Ali Ajmi1, Shamsul Sarip2,*, Khairur Rijal Jamaludin2, Hazilah Mad Kaidi2, Hayati Abdul Talib2

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 895-911, 2021, DOI:10.32604/cmc.2021.018012

    Abstract The COVID-19 pandemic has directly impacted the electric power industry; the energy sector has experienced huge losses in electricity production. These losses have also affected the reliability of communication and employees’ performance, hence destabilizing the electric power system. This article aims at achieving two objectives. First, analyzing the impact of the COVID-19 pandemic on the communication of performance (human error and human factors) and energy management in electricity production. Second, to develop a conceptual framework model to alleviate effects of the pandemic on the power sector and then improve energy management and human performance. This paper involves investigating the influence… More >

  • 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

    Probabilistic and Hierarchical Quantum Information Splitting Based on the Non-Maximally Entangled Cluster State

    Gang Xu1, Rui-Ting Shan2, Xiu-Bo Chen2, Mianxiong Dong3, Yu-Ling Chen4,*

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 339-349, 2021, DOI:10.32604/cmc.2021.017968

    Abstract With the emergence of classical communication security problems, quantum communication has been studied more extensively. In this paper, a novel probabilistic hierarchical quantum information splitting protocol is designed by using a non-maximally entangled four-qubit cluster state. Firstly, the sender Alice splits and teleports an arbitrary one-qubit secret state invisibly to three remote agents Bob, Charlie, and David. One agent David is in high grade, the other two agents Bob and Charlie are in low grade. Secondly, the receiver in high grade needs the assistance of one agent in low grade, while the receiver in low grade needs the aid of… More >

  • Open Access

    ARTICLE

    GAN-GLS: Generative Lyric Steganography Based on Generative Adversarial Networks

    Cuilin Wang1, Yuling Liu1,*, Yongju Tong1, Jingwen Wang2

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1375-1390, 2021, DOI:10.32604/cmc.2021.017950

    Abstract Steganography based on generative adversarial networks (GANs) has become a hot topic among researchers. Due to GANs being unsuitable for text fields with discrete characteristics, researchers have proposed GAN-based steganography methods that are less dependent on text. In this paper, we propose a new method of generative lyrics steganography based on GANs, called GAN-GLS. The proposed method uses the GAN model and the large-scale lyrics corpus to construct and train a lyrics generator. In this method, the GAN uses a previously generated line of a lyric as the input sentence in order to generate the next line of the lyric.… More >

  • Open Access

    ARTICLE

    Deep Learning and Entity Embedding-Based Intrusion Detection Model for Wireless Sensor Networks

    Bandar Almaslukh*

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1343-1360, 2021, DOI:10.32604/cmc.2021.017914

    Abstract Wireless sensor networks (WSNs) are considered promising for applications such as military surveillance and healthcare. The security of these networks must be ensured in order to have reliable applications. Securing such networks requires more attention, as they typically implement no dedicated security appliance. In addition, the sensors have limited computing resources and power and storage, which makes WSNs vulnerable to various attacks, especially denial of service (DoS). The main types of DoS attacks against WSNs are blackhole, grayhole, flooding, and scheduling. There are two primary techniques to build an intrusion detection system (IDS): signature-based and data-driven-based. This study uses the… More >

  • Open Access

    ARTICLE

    Hybrid Segmentation Scheme for Skin Features Extraction Using Dermoscopy Images

    Jehyeok Rew, Hyungjoon Kim, Eenjun Hwang*

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 801-817, 2021, DOI:10.32604/cmc.2021.017892

    Abstract Objective and quantitative assessment of skin conditions is essential for cosmeceutical studies and research on skin aging and skin regeneration. Various handcraft-based image processing methods have been proposed to evaluate skin conditions objectively, but they have unavoidable disadvantages when used to analyze skin features accurately. This study proposes a hybrid segmentation scheme consisting of Deeplab v3+ with an Inception-ResNet-v2 backbone, LightGBM, and morphological processing (MP) to overcome the shortcomings of handcraft-based approaches. First, we apply Deeplab v3+ with an Inception-ResNet-v2 backbone for pixel segmentation of skin wrinkles and cells. Then, LightGBM and MP are used to enhance the pixel segmentation… More >

  • Open Access

    ARTICLE

    Stress Distribution in Composites with Co-Phase Periodically Curved Two Neighboring Hollow Fibers

    Resat Kosker1,*, Ismail Gulten2

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 967-983, 2021, DOI:10.32604/cmc.2021.017857

    Abstract In this paper, stress distribution is examined in the case where infinite length co-phase periodically curved two neighboring hollow fibers are contained by an infinite elastic body. The midline of the fibers is assumed to be in the same plane. Using the three-dimensional geometric linear exact equations of the elasticity theory, research is carried out by use of the piecewise homogeneous body model. Moreover, the body is assumed to be loaded at infinity by uniformly distributed normal forces along the hollow fibers. On the inter-medium between the hollow fibers and matrix surfaces, complete cohesion conditions are satisfied. The boundary form… More >

  • Open Access

    ARTICLE

    Multi-Class Sentiment Analysis of Social Media Data with Machine Learning Algorithms

    Galimkair Mutanov, Vladislav Karyukin*, Zhanl Mamykova

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 913-930, 2021, DOI:10.32604/cmc.2021.017827

    Abstract The volume of social media data on the Internet is constantly growing. This has created a substantial research field for data analysts. The diversity of articles, posts, and comments on news websites and social networks astonishes imagination. Nevertheless, most researchers focus on posts on Twitter that have a specific format and length restriction. The majority of them are written in the English language. As relatively few works have paid attention to sentiment analysis in the Russian and Kazakh languages, this article thoroughly analyzes news posts in the Kazakhstan media space. The amassed datasets include texts labeled according to three sentiment… More >

  • Open Access

    ARTICLE

    A Novel Features Prioritization Mechanism for Controllers in Software-Defined Networking

    Jehad Ali1, Byungkyu Lee2, Jimyung Oh2, Jungtae Lee3, Byeong-hee Roh1,*

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 267-282, 2021, DOI:10.32604/cmc.2021.017813

    Abstract The controller in software-defined networking (SDN) acts as strategic point of control for the underlying network. Multiple controllers are available, and every single controller retains a number of features such as the OpenFlow version, clustering, modularity, platform, and partnership support, etc. They are regarded as vital when making a selection among a set of controllers. As such, the selection of the controller becomes a multi-criteria decision making (MCDM) problem with several features. Hence, an increase in this number will increase the computational complexity of the controller selection process. Previously, the selection of controllers based on features has been studied by… More >

  • Open Access

    ARTICLE

    Complex Problems Solution as a Service Based on Predictive Optimization and Tasks Orchestration in Smart Cities

    Shabir Ahmad1, Jehad Ali2, Faisal Jamil3, Taeg Keun Whangbo1, DoHyeun Kim3,*

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1271-1288, 2021, DOI:10.32604/cmc.2021.017773

    Abstract Smart cities have different contradicting goals having no apparent solution. The selection of the appropriate solution, which is considered the best compromise among the candidates, is known as complex problem-solving. Smart city administrators face different problems of complex nature, such as optimal energy trading in microgrids and optimal comfort index in smart homes, to mention a few. This paper proposes a novel architecture to offer complex problem solutions as a service (CPSaaS) based on predictive model optimization and optimal task orchestration to offer solutions to different problems in a smart city. Predictive model optimization uses a machine learning module and… More >

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