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Shakeel Ahmed^*, Abdulaziz Alhumam
Computer Systems Science and Engineering, Vol.37, No.1, pp. 1-18, 2021, DOI:10.32604/csse.2021.015775 - 05 February 2021
Abstract This article evaluates the security techniques that are used to maintain the healthcare devices, and proposes a mathematical model to list these in the order of priority and preference. To accomplish the stated objective, the article uses the Fuzzy Analytic Network Process (ANP) integrated with Technical for Order Preference by Similarities to Ideal Solution (TOPSIS) to find the suitable alternatives of the security techniques for securing the healthcare devices from trespassing. The methodology is enlisted to rank the alternatives/ techniques based on their weights’ satisfaction degree. Thereafter, the ranks of the alternatives determine the order More >

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Kaisarul Islam¹, Tabia Hossain¹, Mohammad Monirujjaman Khan^1,*, Mehedi Masud², Roobaea Alroobaea²
Computer Systems Science and Engineering, Vol.37, No.1, pp. 19-32, 2021, DOI:10.32604/csse.2021.015528 - 05 February 2021
（This article belongs to the Special Issue: Sensors and Nano-sensors Technologies for Health-Care Applications)
Abstract In this paper performance of three different designs of a 60 GHz high gain antenna for body-centric communication has been evaluated. The basic structure of the antenna is a slotted patch consisting of a rectangular ring radiator with passive radiators inside. The variation of the design was done by changing the shape of these passive radiators. For free space performance, two types of excitations were used—waveguide port and a coaxial probe. The coaxial probe significantly improved both the bandwidth and radiation efficiency. The center frequency of all the designs was close to 60 GHz with… More >

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Sinil Mubarak¹, Mohamed Hadi Habaebi^1,*, Md Rafiqul Islam¹, Farah Diyana Abdul Rahman, Mohammad Tahir²
Computer Systems Science and Engineering, Vol.37, No.1, pp. 33-46, 2021, DOI:10.32604/csse.2021.014384 - 05 February 2021
Abstract An Intrusion Detection System (IDS) provides a front-line defense mechanism for the Industrial Control System (ICS) dedicated to keeping the process operations running continuously for 24 hours in a day and 7 days in a week. A well-known ICS is the Supervisory Control and Data Acquisition (SCADA) system. It supervises the physical process from sensor data and performs remote monitoring control and diagnostic functions in critical infrastructures. The ICS cyber threats are growing at an alarming rate on industrial automation applications. Detection techniques with machine learning algorithms on public datasets, suitable for intrusion detection of More >

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Mustafa M. M. Al Qudah, Ahmad S. A. Mohamed^*, Syaheerah L. Lutfi
Computer Systems Science and Engineering, Vol.37, No.1, pp. 47-62, 2021, DOI:10.32604/csse.2021.015222 - 05 February 2021
Abstract The thermal-based imaging technique has recently attracted the attention of researchers who are interested in the recognition of human affects due to its ability to measure the facial transient temperature, which is correlated with human affects and robustness against illumination changes. Therefore, studies have increasingly used the thermal imaging as a potential and supplemental solution to overcome the challenges of visual (RGB) imaging, such as the variation of light conditions and revealing original human affect. Moreover, the thermal-based imaging has shown promising results in the detection of psychophysiological signals, such as pulse rate and respiration… More >

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A. N. M. Alahmadi¹, Hegazy Rezk^2,3,*
Computer Systems Science and Engineering, Vol.37, No.1, pp. 63-71, 2021, DOI:10.32604/csse.2021.015029 - 05 February 2021
Abstract A robust single-sensor global maximum power point tracking (MPPT) strategy based on modern optimization for photovoltaic systems considering shading conditions is proposed in this work. The proposed strategy is designed for battery charging applications and direct current (DC) microgrids. Under normal operation, the curve of photovoltaic (PV) output power versus PV voltage contains only a single peak point. This point can be simply captured using any traditional tracking method like perturb and observe. However, this situation is completely different during the shadowing effect where several peaks appear on the power voltage curve. Most of these… More >

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Shahrul Nizam Ismail¹, Suraya Hamid^1,*, Muneer Ahmad¹, A. Alaboudi², Nz Jhanjhi³
Computer Systems Science and Engineering, Vol.37, No.1, pp. 73-87, 2021, DOI:10.32604/csse.2021.015261 - 05 February 2021
Abstract Learning analytics is a rapidly evolving research discipline that uses the insights generated from data analysis to support learners as well as optimize both the learning process and environment. This paper studied students’ engagement level of the Learning Management System (LMS) via a learning analytics tool, student’s approach in managing their studies and possible learning analytic methods to analyze student data. Moreover, extensive systematic literature review (SLR) was employed for the selection, sorting and exclusion of articles from diverse renowned sources. The findings show that most of the engagement in LMS are driven by educators. More >

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Huarui Wu^1,2,3, Huaji Zhu^1,2,3, Xiao Han^1,2,3,*, Wei Xu⁴
Computer Systems Science and Engineering, Vol.37, No.1, pp. 89-104, 2021, DOI:10.32604/csse.2021.015030 - 05 February 2021
Abstract When wireless sensor networks (WSN) are deployed in the vegetable greenhouse with dynamic connectivity and interference environment, it is necessary to increase the node transmit power to ensure the communication quality, which leads to serious network interference. To offset the negative impact, the transmit power of other nodes must also be increased. The result is that the network becomes worse and worse, and node energy is wasted a lot. Taking into account the irregular connection range in the cucumber greenhouse WSN, we measured the transmission characteristics of wireless signals under the 2.4 Ghz operating frequency.… More >

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Zhengqiu Weng^1,2, Timing Chen^1,*, Tiantian Zhu¹, Hang Dong¹, Dan Zhou¹, Osama Alfarraj³
Computer Systems Science and Engineering, Vol.37, No.1, pp. 105-119, 2021, DOI:10.32604/csse.2021.015074 - 05 February 2021
Abstract Internet traffic encryption is a very common traffic protection method. Most internet traffic is protected by the encryption protocol called transport layer security (TLS). Although traffic encryption can ensure the security of communication, it also enables malware to hide its information and avoid being detected. At present, most of the malicious traffic detection methods are aimed at the unencrypted ones. There are some problems in the detection of encrypted traffic, such as high false positive rate, difficulty in feature extraction, and insufficient practicability. The accuracy and effectiveness of existing methods need to be improved. In… More >

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Zihao Shen^1,2, Hui Wang^1,*, Kun Liu¹, Peiqian Liu¹, Menglong Ba¹, MengYao Zhao³
Computer Systems Science and Engineering, Vol.37, No.1, pp. 121-133, 2021, DOI:10.32604/csse.2021.014988 - 05 February 2021
Abstract The rapid progress of the Internet has exposed networks to an increased number of threats. Intrusion detection technology can effectively protect network security against malicious attacks. In this paper, we propose a ReliefF-P-Naive Bayes and softmax regression (RP-NBSR) model based on machine learning for network attack detection to improve the false detection rate and F1 score of unknown intrusion behavior. In the proposed model, the Pearson correlation coefficient is introduced to compensate for deficiencies in correlation analysis between features by the ReliefF feature selection algorithm, and a ReliefF-Pearson correlation coefficient (ReliefF-P) algorithm is proposed. Then, More >

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Xiaoyu Duan¹, Shi Ying^1,*, Wanli Yuan¹, Hailong Cheng¹, Xiang Yin²
Computer Systems Science and Engineering, Vol.37, No.1, pp. 135-148, 2021, DOI:10.32604/csse.2021.014030 - 05 February 2021
Abstract Detecting anomaly logs is a great significance step for guarding system faults. Due to the uncertainty of abnormal log types, lack of real anomaly logs and accurately labeled log datasets. Existing technologies cannot be enough for detecting complex and various log point anomalies by using human-defined rules. We propose a log anomaly detection method based on Generative Adversarial Networks (GAN). This method uses the Encoder-Decoder framework based on Long Short-Term Memory (LSTM) network as the generator, takes the log keywords as the input of the encoder, and the decoder outputs the generated log template. The More >

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