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  • Open Access

    ARTICLE

    Automatic PV Grid Fault Detection System with IoT and LabVIEW as Data Logger

    Rohit Samkria1, Mohammed Abd-Elnaby2, Rajesh Singh3, Anita Gehlot3, Mamoon Rashid4,*, Moustafa H. Aly5, Walid El-Shafai6

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1709-1723, 2021, DOI:10.32604/cmc.2021.018525

    Abstract Fault detection of the photovoltaic (PV) grid is necessary to detect serious output power reduction to avoid PV modules’ damage. To identify the fault of the PV arrays, there is a necessity to implement an automatic system. In this IoT and LabVIEW-based automatic fault detection of 3 × 3 solar array, a PV system is proposed to control and monitor Internet connectivity remotely. Hardware component to automatically reconfigure the solar PV array from the series-parallel (SP) to the complete cross-linked array underneath partial shading conditions (PSC) is centered on the Atmega328 system to achieve maximum power. In the LabVIEW environment,… More >

  • Open Access

    ARTICLE

    Adaptive Error Curve Learning Ensemble Model for Improving Energy Consumption Forecasting

    Prince Waqas Khan, Yung-Cheol Byun*

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1893-1913, 2021, DOI:10.32604/cmc.2021.018523

    Abstract Despite the advancement within the last decades in the field of smart grids, energy consumption forecasting utilizing the metrological features is still challenging. This paper proposes a genetic algorithm-based adaptive error curve learning ensemble (GA-ECLE) model. The proposed technique copes with the stochastic variations of improving energy consumption forecasting using a machine learning-based ensembled approach. A modified ensemble model based on a utilizing error of model as a feature is used to improve the forecast accuracy. This approach combines three models, namely CatBoost (CB), Gradient Boost (GB), and Multilayer Perceptron (MLP). The ensembled CB-GB-MLP model’s inner mechanism consists of generating… More >

  • Open Access

    ARTICLE

    Cluster Analysis for IR and NIR Spectroscopy: Current Practices to Future Perspectives

    Simon Crase1,2, Benjamin Hall2, Suresh N. Thennadil3,*

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1945-1965, 2021, DOI:10.32604/cmc.2021.018517

    Abstract Supervised machine learning techniques have become well established in the study of spectroscopy data. However, the unsupervised learning technique of cluster analysis hasn’t reached the same level maturity in chemometric analysis. This paper surveys recent studies which apply cluster analysis to NIR and IR spectroscopy data. In addition, we summarize the current practices in cluster analysis of spectroscopy and contrast these with cluster analysis literature from the machine learning and pattern recognition domain. This includes practices in data pre-processing, feature extraction, clustering distance metrics, clustering algorithms and validation techniques. Special consideration is given to the specific characteristics of IR and… More >

  • Open Access

    ARTICLE

    An Efficient Method for Covid-19 Detection Using Light Weight Convolutional Neural Network

    Saddam Bekhet1,*, Monagi H. Alkinani2, Reinel Tabares-Soto3, M. Hassaballah4

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2475-2491, 2021, DOI:10.32604/cmc.2021.018514

    Abstract The COVID-19 pandemic is a significant milestone in the modern history of civilization with a catastrophic effect on global wellbeing and monetary. The situation is very complex as the COVID-19 test kits are limited, therefore, more diagnostic methods must be developed urgently. A significant initial step towards the successful diagnosis of the COVID-19 is the chest X-ray or Computed Tomography (CT), where any chest anomalies (e.g., lung inflammation) can be easily identified. Most hospitals possess X-ray or CT imaging equipments that can be used for early detection of COVID-19. Motivated by this, various artificial intelligence (AI) techniques have been developed… More >

  • Open Access

    ARTICLE

    A Time-Domain Comparator Based Skipping-Window SAR ADC

    Liangbo Xie1, Yan Ren1, Mu Zhou1, Xiaolong Yang1,*, Zhengwen Huang2

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1597-1609, 2021, DOI:10.32604/cmc.2021.018502

    Abstract This paper presents an energy efficient successive-approximation register (SAR) analog-to-digital converter (ADC) for low-power applications. To improve the overall energy-efficiency, a skipping-window technique is used to bypass corresponding conversion steps when the input falls in a window indicated by a time-domain comparator, which can provide not only the polarity of the input, but also the amount information of the input. The time-domain comparator, which is based on the edge pursing principle, consists of delay cells, two NAND gates, two D-flip-flop register-based phase detectors and a counter. The digital characteristic of the comparator makes the design more flexible, and the comparator… More >

  • Open Access

    ARTICLE

    Towards Machine Learning Based Intrusion Detection in IoT Networks

    Nahida Islam1, Fahiba Farhin1, Ishrat Sultana1, M. Shamim Kaiser1, Md. Sazzadur Rahman1, Mufti Mahmud2, A. S. M. Sanwar Hosen3, Gi Hwan Cho3,*

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1801-1821, 2021, DOI:10.32604/cmc.2021.018466

    Abstract The Internet of Things (IoT) integrates billions of self-organized and heterogeneous smart nodes that communicate with each other without human intervention. In recent years, IoT based systems have been used in improving the experience in many applications including healthcare, agriculture, supply chain, education, transportation and traffic monitoring, utility services etc. However, node heterogeneity raised security concern which is one of the most complicated issues on the IoT. Implementing security measures, including encryption, access control, and authentication for the IoT devices are ineffective in achieving security. In this paper, we identified various types of IoT threats and shallow (such as decision… More >

  • Open Access

    ARTICLE

    Energy Optimization in Multi-UAV-Assisted Edge Data Collection System

    Bin Xu1,2,3, Lu Zhang1, Zipeng Xu1, Yichuan Liu1, Jinming Chai1, Sichong Qin4, Yanfei Sun1,*

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1671-1686, 2021, DOI:10.32604/cmc.2021.018395

    Abstract In the IoT (Internet of Things) system, the introduction of UAV (Unmanned Aerial Vehicle) as a new data collection platform can solve the problem that IoT devices are unable to transmit data over long distances due to the limitation of their battery energy. However, the unreasonable distribution of UAVs will still lead to the problem of the high total energy consumption of the system. In this work, to deal with the problem, a deployment model of a mobile edge computing (MEC) system based on multi-UAV is proposed. The goal of the model is to minimize the energy consumption of the… More >

  • Open Access

    ARTICLE

    An Optimized Design of Antenna Arrays for the Smart Antenna Systems

    Fahd N. Al-Wesabi1,2,*, Murad A. A. Almekhlafi3, Huda G. Iskandar2,4, Adnan Zain5, Saleh Alzahrani6, Mohammed Alamgeer6, Nadhem Nemri6, Sami Dhabi6, Mohammad Medani6, Ali. M. Al-Sharafi2,7

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1979-1994, 2021, DOI:10.32604/cmc.2021.018390

    Abstract In recent years, there has been an increasing demand to improve cellular communication services in several aspects. The aspect that received the most attention is improving the quality of coverage through using smart antennas which consist of array antennas. this paper investigates the main characteristics and design of the three types of array antennas of the base station for better coverage through simulation (MATLAB) which provides field and strength patterns measured in polar and rectangular coordinates for a variety of conditions including broadsides, ordinary End-fire, and increasing directivity End-fire which is typically used in smart antennas. The method of analysis… More >

  • Open Access

    ARTICLE

    ECC: Edge Collaborative Caching Strategy for Differentiated Services Load-Balancing

    Fang Liu1,*, Zhenyuan Zhang2, Zunfu Wang1, Yuting Xing3

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2045-2060, 2021, DOI:10.32604/cmc.2021.018303

    Abstract Due to the explosion of network data traffic and IoT devices, edge servers are overloaded and slow to respond to the massive volume of online requests. A large number of studies have shown that edge caching can solve this problem effectively. This paper proposes a distributed edge collaborative caching mechanism for Internet online request services scenario. It solves the problem of large average access delay caused by unbalanced load of edge servers, meets users’ differentiated service demands and improves user experience. In particular, the edge cache node selection algorithm is optimized, and a novel edge cache replacement strategy considering the… More >

  • Open Access

    ARTICLE

    Multi-Criteria Prediction Mechanism for Vehicular Wi-Fi Offloading

    Mahmoud Alawi1, Raed Alsaqour2, Abdi Abdalla3, Maha Abdelhaq4,*, Mueen Uddin5

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2313-2337, 2021, DOI:10.32604/cmc.2021.018282

    Abstract The growing demands of vehicular network applications, which have diverse networking and multimedia capabilities that passengers use while traveling, cause an overload of cellular networks. This scenario affects the quality of service (QoS) of vehicle and non-vehicle users. Nowadays, wireless fidelity access points Wi-Fi access point (AP) and fourth generation long-term evolution advanced (4G LTE-A) networks are broadly accessible. Wi-Fi APs can be utilized by vehicle users to stabilize 4G LTE-A networks. However, utilizing the opportunistic Wi-Fi APs to offload the 4G LTE-A networks in a vehicular ad hoc network environment is a relatively difficult task. This condition is due… More >

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