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  • Open Access

    ARTICLE

    Design of Intelligent Mosquito Nets Based on Deep Learning Algorithms

    Yuzhen Liu1,3, Xiaoliang Wang1,*, Xinghui She1, Ming Yi1, Yuelong Li1, Frank Jiang2

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2261-2276, 2021, DOI:10.32604/cmc.2021.015501

    Abstract An intelligent mosquito net employing deep learning has been one of the hotspots in the field of Internet of Things as it can reduce significantly the spread of pathogens carried by mosquitoes, and help people live well in mosquito-infested areas. In this study, we propose an intelligent mosquito net that can produce and transmit data through the Internet of Medical Things. In our method, decision-making is controlled by a deep learning model, and the proposed method uses infrared sensors and an array of pressure sensors to collect data. Moreover the ZigBee protocol is used to transmit the pressure map which… More >

  • Open Access

    ARTICLE

    Negotiation Based Combinatorial Double Auction Mechanism in Cloud Computing

    Zakir Ullah1, Asif Umer1, Mahdi Zaree2, Jamil Ahmad1, Faisal Alanazi3,*, Noor Ul Amin1, Arif Iqbal Umar1, Ali Imran Jehangiri1, Muhammad Adnan1

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2123-2140, 2021, DOI:10.32604/cmc.2021.015445

    Abstract Cloud computing is a demanding business platform for services related to the field of IT. The goal of cloud customers is to access resources at a sustainable price, while the goal of cloud suppliers is to maximize their services utilization. Previously, the customers would bid for every single resource type, which was a limitation of cloud resources allocation. To solve these issues, researchers have focused on a combinatorial auction in which the resources are offered by the providers in bundles so that the user bids for their required bundle. Still, in this allocation mechanism, some drawbacks need to be tackled,… More >

  • Open Access

    ARTICLE

    ANN Based Novel Approach to Detect Node Failure in Wireless Sensor Network

    Sundresan Perumal1, Mujahid Tabassum1, Ganthan Narayana2, Suresh Ponnan3,*, Chinmay Chakraborty4, Saju Mohanan5, Zeeshan Basit5, Mohammad Tabrez Quasim6

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1447-1462, 2021, DOI:10.32604/cmc.2021.014854

    Abstract A wireless sensor network (WSN) consists of several tiny sensor nodes to monitor, collect, and transmit the physical information from an environment through the wireless channel. The node failure is considered as one of the main issues in the WSN which creates higher packet drop, delay, and energy consumption during the communication. Although the node failure occurred mostly due to persistent energy exhaustion during transmission of data packets. In this paper, Artificial Neural Network (ANN) based Node Failure Detection (NFD) is developed with cognitive radio for detecting the location of the node failure. The ad hoc on-demand distance vector (AODV)… More >

  • Open Access

    ARTICLE

    A Novel Hybrid Clustering Based Transmission Protocol for Wireless Body Area Networks

    Neelam Sharma1,*, Harshita Chadha2, Karan Singh3, B. M. Singh4, Nitish Pathak5

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2459-2473, 2021, DOI:10.32604/cmc.2021.014305

    Abstract Wireless sensor networks are a collection of intelligent sensor devices that are connected to one another and have the capability to exchange information packets amongst themselves. In recent years, this field of research has become increasingly popular due to the host of useful applications it can potentially serve. A deep analysis of the concepts associated with this domain reveals that the two main problems that are to be tackled here are throughput enhancement and network security improvement. The present article takes on one of these two issues namely the throughput enhancement. For the purpose of improving network productivity, a hybrid… More >

  • Open Access

    ARTICLE

    Few-Shot Learning for Discovering Anomalous Behaviors in Edge Networks

    Merna Gamal1, Hala M. Abbas2, Nour Moustafa3,*, Elena Sitnikova3, Rowayda A. Sadek1

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1823-1837, 2021, DOI:10.32604/cmc.2021.012877

    Abstract Intrusion Detection Systems (IDSs) have a great interest these days to discover complex attack events and protect the critical infrastructures of the Internet of Things (IoT) networks. Existing IDSs based on shallow and deep network architectures demand high computational resources and high volumes of data to establish an adaptive detection engine that discovers new families of attacks from the edge of IoT networks. However, attackers exploit network gateways at the edge using new attacking scenarios (i.e., zero-day attacks), such as ransomware and Distributed Denial of Service (DDoS) attacks. This paper proposes new IDS based on Few-Shot Deep Learning, named CNN-IDS,… More >

  • Open Access

    ARTICLE

    Adaptive Relay Selection Scheme for Minimization of the Transmission Time

    Yu-Jin Na1, Ji-Sung Jung1, Young-Hwan You2, Hyoung-Kyu Song1,*

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1361-1373, 2021, DOI:10.32604/cmc.2021.018481

    Abstract As the installation of small cells increases, the use of relay also increases. The relay operates as a base station as well as just an amplifier. As the roles and types of relays become more diverse, appropriate relay selection technology is an effective way to improve communication performance. Many researches for relay selection have been studied to secure the reliability of relay communication. In this paper, the relay selection scheme is proposed for a cooperative system using decode-and-forward (DF) relaying scheme in the mobile communication system. To maintain the transmission rate, the proposed scheme classifies a candidate group considering the… More >

  • Open Access

    ARTICLE

    Breast Lesions Detection and Classification via YOLO-Based Fusion Models

    Asma Baccouche1,*, Begonya Garcia-Zapirain2, Cristian Castillo Olea2, Adel S. Elmaghraby1

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1407-1425, 2021, DOI:10.32604/cmc.2021.018461

    Abstract With recent breakthroughs in artificial intelligence, the use of deep learning models achieved remarkable advances in computer vision, ecommerce, cybersecurity, and healthcare. Particularly, numerous applications provided efficient solutions to assist radiologists for medical imaging analysis. For instance, automatic lesion detection and classification in mammograms is still considered a crucial task that requires more accurate diagnosis and precise analysis of abnormal lesions. In this paper, we propose an end-to-end system, which is based on You-Only-Look-Once (YOLO) model, to simultaneously localize and classify suspicious breast lesions from entire mammograms. The proposed system first preprocesses the raw images, then recognizes abnormal regions as… More >

  • Open Access

    ARTICLE

    Resource Assessment of Wind Energy Potential of Mokha in Yemen with Weibull Speed

    Abdulbaset El-Bshah1, Fahd N. Al-Wesabi2,3,*, Ameen M. Al-Kustoban4, Mohammad Alamgeer5, Nadhem Nemri5, Majdy M. Eltahir5, Hany Mahgoub6, Noha Negm7

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1123-1140, 2021, DOI:10.32604/cmc.2021.018427

    Abstract The increasing use of fossil fuels has a significant impact on the environment and ecosystem, which increases the rate of pollution. Given the high potential of renewable energy sources in Yemen and other Arabic countries, and the absence of similar studies in the region. This study aims to examine the potential of wind energy in Mokha region. This was done by analyzing and evaluating wind properties, determining available energy density, calculating wind energy extracted at different altitudes, and then computing the capacity factor for a few wind turbines and determining the best. Weibull speed was verified as the closest to… More >

  • Open Access

    ARTICLE

    Modeling of Heart Rate Variability Using Time-Frequency Representations

    Ghaylen Laouini1, Ibrahim Mahariq1, Thabet Abdeljawad2,3,4,*, Hasan Aksoy5

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1289-1299, 2021, DOI:10.32604/cmc.2021.018411

    Abstract The heart rate variability signal is highly correlated with the respiration even at high workload exercise. It is also known that this phenomenon still exists during increasing exercise. In the current study, we managed to model this correlation during increasing exercise using the time varying integral pulse frequency modulation (TVIPFM) model that relates the mechanical modulation (MM) to the respiration and the cardiac rhythm. This modulation of the autonomic nervous system (ANS) is able to simultaneously decrease sympathetic and increase parasympathetic activity. The TVIPFM model takes into consideration the effect of the increasing exercise test, where the effect of a… More >

  • Open Access

    ARTICLE

    Intelligent Multiclass Skin Cancer Detection Using Convolution Neural Networks

    Reham Alabduljabbar*, Hala Alshamlan

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 831-847, 2021, DOI:10.32604/cmc.2021.018402

    Abstract The worldwide mortality rate due to cancer is second only to cardiovascular diseases. The discovery of image processing, latest artificial intelligence techniques, and upcoming algorithms can be used to effectively diagnose and prognose cancer faster and reduce the mortality rate. Efficiently applying these latest techniques has increased the survival chances during recent years. The research community is making significant continuous progress in developing automated tools to assist dermatologists in decision making. The datasets used for the experimentation and analysis are ISBI 2016, ISBI 2017, and HAM 10000. In this work pertained models are used to extract the efficient feature. The… More >

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