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  • Open Access

    ARTICLE

    Prediction of Covid-19 Based on Chest X-Ray Images Using Deep Learning with CNN

    Anika Tahsin Meem1, Mohammad Monirujjaman Khan1,*, Mehedi Masud2, Sultan Aljahdali2

    Computer Systems Science and Engineering, Vol.41, No.3, pp. 1223-1240, 2022, DOI:10.32604/csse.2022.021563

    Abstract The COVID-19 pandemic has caused trouble in people’s daily lives and ruined several economies around the world, killing millions of people thus far. It is essential to screen the affected patients in a timely and cost-effective manner in order to fight this disease. This paper presents the prediction of COVID-19 with Chest X-Ray images, and the implementation of an image processing system operated using deep learning and neural networks. In this paper, a Deep Learning, Machine Learning, and Convolutional Neural Network-based approach for predicting Covid-19 positive and normal patients using Chest X-Ray pictures is proposed. In this study, machine learning… More >

  • Open Access

    ARTICLE

    Proportional Fairness Based Energy Efficient Routing in Wireless Sensor Network

    Abolfazl Mehbodniya1, Surbhi Bhatia2, Arwa Mashat3, Mohanraj Elangovan4,*, Sudhakar Sengan5

    Computer Systems Science and Engineering, Vol.41, No.3, pp. 1071-1082, 2022, DOI:10.32604/csse.2022.021529

    Abstract Wireless Sensor Network (WSN) is an independent device that comprises a discrete collection of Sensor Nodes (SN) to sense environmental positions, device monitoring, and collection of information. Due to limited energy resources available at SN, the primary issue is to present an energy-efficient framework and conserve the energy while constructing a route path along with each sensor node. However, many energy-efficient techniques focused drastically on energy harvesting and reduced energy consumption but failed to support energy-efficient routing with minimal energy consumption in WSN. This paper presents an energy-efficient routing system called Energy-aware Proportional Fairness Multi-user Routing (EPFMR) framework in WSN.… More >

  • Open Access

    ARTICLE

    Analyzing the Implications of COVID-19 Pandemic through an Intelligent-Computing Technique

    Abhishek Kumar Pandey1, Jehad F. Al-Amri2, Ahmad F. Subahi3, Rajeev Kumar4,*, Raees Ahmad Khan1

    Computer Systems Science and Engineering, Vol.41, No.3, pp. 959-974, 2022, DOI:10.32604/csse.2022.021443

    Abstract The outbreak of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2 virus or COVID-19) disease was declared pandemic by the World Health Organization (WHO) on March 11, 2020. COVID-19 has already affected more than 211 nations. In such a bleak scenario, it becomes imperative to analyze and identify those regions in Saudi Arabia that are at high risk. A preemptive study done in the context of predicting the possible COVID-19 hotspots would facilitate in the implementation of prompt and targeted countermeasures against SARS-CoV-2, thus saving many lives. Working towards this intent, the present study adopts a decision making based methodology of… More >

  • Open Access

    ARTICLE

    Smart COVID-3D-SCNN: A Novel Method to Classify X-ray Images of COVID-19

    Ahed Abugabah1,*, Atif Mehmood2, Ahmad Ali AL Zubi3, Louis Sanzogni4

    Computer Systems Science and Engineering, Vol.41, No.3, pp. 997-1008, 2022, DOI:10.32604/csse.2022.021438

    Abstract The outbreak of the novel coronavirus has spread worldwide, and millions of people are being infected. Image or detection classification is one of the first application areas of deep learning, which has a significant contribution to medical image analysis. In classification detection, one or more images (detection) are usually used as input, and diagnostic variables (such as whether there is a disease) are used as output. The novel coronavirus has spread across the world, infecting millions of people. Early-stage detection of critical cases of COVID-19 is essential. X-ray scans are used in clinical studies to diagnose COVID-19 and Pneumonia early.… More >

  • Open Access

    ARTICLE

    An Effective and Secure Quality Assurance System for a Computer Science Program

    Mohammad Alkhatib*

    Computer Systems Science and Engineering, Vol.41, No.3, pp. 975-995, 2022, DOI:10.32604/csse.2022.021398

    Abstract Improving the quality assurance (QA) processes and acquiring accreditation are top priorities for academic programs. The learning outcomes (LOs) assessment and continuous quality improvement represent core components of the quality assurance system (QAS). Current assessment methods suffer deficiencies related to accuracy and reliability, and they lack well-organized processes for continuous improvement planning. Moreover, the absence of automation, and integration in QA processes forms a major obstacle towards developing efficient quality system. There is a pressing need to adopt security protocols that provide required security services to safeguard the valuable information processed by QAS as well. This research proposes an effective… More >

  • Open Access

    ARTICLE

    Optimal Load Balancing in Cloud Environment of Virtual Machines

    Fuad A.M. Al-Yarimi1,*, Sami Althahabi1, Majdy Mohammed Eltayeb2

    Computer Systems Science and Engineering, Vol.41, No.3, pp. 919-932, 2022, DOI:10.32604/csse.2022.021272

    Abstract Cloud resource scheduling is gaining prominence with the increasing trends of reliance on cloud infrastructure solutions. Numerous sets of cloud resource scheduling models were evident in the literature. Cloud resource scheduling refers to the distinct set of algorithms or programs the service providers engage to maintain the service level allocation for various resources over a virtual environment. The model proposed in this manuscript schedules resources of virtual machines under potential volatility aspects, which can be applied for any priority metric chosen by the server administrators. Also, the model can be flexible for any time frame-based analysis of the load factor.… More >

  • Open Access

    ARTICLE

    System Dynamics Forecasting on Taiwan Power Supply Chain

    Zhiqiu Yu1,*, Shuo-Yan Chou1, Phan Nguyen Ky Phuc2, Tiffany Hui-Kuang Yu3

    Computer Systems Science and Engineering, Vol.41, No.3, pp. 1191-1205, 2022, DOI:10.32604/csse.2022.021239

    Abstract This research aims to study the sustainability of Taiwan power supply chain based on system dynamics forecasting. The paper tries to investigate electricity shortage effects not only on the industrial side, but also from the standpoint of society. In our model, different forecasting methods such as linear regression, time series analysis, and gray forecasting are also considered to predict the parameters. Further tests such as the structure, dimension, historical fit, and sensitivity of the model are also conducted in this paper. Through analysis forecasting result, we believe that the demand for electricity in Taiwan will continue to increase to a… More >

  • Open Access

    ARTICLE

    Design of Miniature UWB-Based Antenna by Employing a Tri-Sectional SIR Feeder

    Ehab Dh. Hussein1,*, Yaqeen S. Mezaal2, Oguz Bayat1

    Computer Systems Science and Engineering, Vol.41, No.3, pp. 1157-1172, 2022, DOI:10.32604/csse.2022.021205

    Abstract A novel ultra-wideband (UWB)-based microstrip antenna is presented in this work by using a slotted patch resonator, a tri-sectional stepped impedance resonator (SIR) feeder, as well as a reduced ground plane. The whole structure was realized on an FR4 substrate. The impact of incorporating several cases of ground planes on the input reflection has been thoroughly investigated under the same tri-sectional SIR feeder and by employing a slotted patch radiator. Since the complete ground plane presents an inadequate frequency response, by reducing the ground plane, the induced UWB responses are apparent while the antenna exhibits higher impedance bandwidth. The impact… More >

  • Open Access

    ARTICLE

    A Hybrid Heuristic Algorithm for Solving COVID-19’s Social Distancing at Universities Campus

    Hassan Al-Tarawneh1, Khalid Al-Kaabneh1, Aysh Alhroob2, Hazem Migdady3, Issam Alhadid4,*

    Computer Systems Science and Engineering, Vol.41, No.3, pp. 933-944, 2022, DOI:10.32604/csse.2022.021078

    Abstract Social distancing during COVID-19 has become one of the most important measures in reducing the risks of the spread of the virus. Implementing these measures at universities is crucial and directly related to the physical attendance of the populations of students, professors, employees, and other members on campus. This research proposes an automated scheduling approach that can help universities and schools comply with the social distancing regulations by providing assistance in avoiding huge assemblages of people. Furthermore, this paper proposes a novel course timetable-scheduling scheme based on four main constraints. First, a distance of two meters must be maintained between… More >

  • Open Access

    ARTICLE

    Cost Effective Decentralized Key Management Framework for IoT

    Raja Lavanya*, K. Sundarakantham, S. Mercy Shalinie

    Computer Systems Science and Engineering, Vol.41, No.3, pp. 1057-1070, 2022, DOI:10.32604/csse.2022.021052

    Abstract Security is a primary concern in communication for reliable transfer of information between the authenticated members, which becomes more complex in a network of Internet of Things (IoT). To provide security for group communication a key management scheme incorporating Bilinear pairing technique with Multicast and Unicast key management protocol (BMU-IOT) for decentralized networks has been proposed. The first part of the proposed work is to divide the network into clusters where sensors are connected to and is administered by cluster head. Each sensor securely shares its secret keys with the cluster head using unicast. Based on these decryption keys, the… More >

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