Home / Journals / CSSE / Vol.42, No.2, 2022
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    ARTICLE

    Contrast Enhancement Based Image Detection Using Edge Preserved Key Pixel Point Filtering

    Balakrishnan Natarajan1,*, Pushpalatha Krishnan2
    Computer Systems Science and Engineering, Vol.42, No.2, pp. 423-438, 2022, DOI:10.32604/csse.2022.022376
    Abstract In existing methods for segmented images, either edge point extraction or preservation of edges, compromising contrast images is so sensitive to noise. The Degeneration Threshold Image Detection (DTID) framework has been proposed to improve the contrast of edge filtered images. Initially, DTID uses a Rapid Bilateral Filtering process for filtering edges of contrast images. This filter decomposes input images into base layers in the DTID framework. With minimal filtering time, Rapid Bilateral Filtering handles high dynamic contrast images for smoothening edge preservation. In the DTID framework, Rapid Bilateral Filtering with Shift-Invariant Base Pass Domain Filter is insensitive to noise. This… More >

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    ARTICLE

    Modeling Rogowski Coils for Monitoring Surge Arrester Discharge Currents

    Nehmdoh A. Sabiha1,*, Hend I. Alkhammash2
    Computer Systems Science and Engineering, Vol.42, No.2, pp. 439-449, 2022, DOI:10.32604/csse.2022.022506
    (This article belongs to this Special Issue: Advances in Computational Intelligence and its Applications)
    Abstract Rogowski coils (RCs) are widely used to measure power or high frequency currents based on their design. In this paper, two types of RCs that are circular (traditional) and cylindrical shapes wound using wire covered by varnish are constructed. This construction is carried out to be suitable for monitoring the discharge current of the surge arrester installed in the distribution system. Concerning high frequency RC modeling for both types considering transfer function is introduced. Self-integrating for both types is attained. Therefore, the experimental tests using function generator for both coils are carried out to identify the parameters of the transfer… More >

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    ARTICLE

    SOINN-Based Abnormal Trajectory Detection for Efficient Video Condensation

    Chin-Shyurng Fahn1, Chang-Yi Kao2,*, Meng-Luen Wu3, Hao-En Chueh4
    Computer Systems Science and Engineering, Vol.42, No.2, pp. 451-463, 2022, DOI:10.32604/csse.2022.022368
    (This article belongs to this Special Issue: Advances in Computational Intelligence and its Applications)
    Abstract With the evolution of video surveillance systems, the requirement of video storage grows rapidly; in addition, safe guards and forensic officers spend a great deal of time observing surveillance videos to find abnormal events. As most of the scene in the surveillance video are redundant and contains no information needs attention, we propose a video condensation method to summarize the abnormal events in the video by rearranging the moving trajectory and sort them by the degree of anomaly. Our goal is to improve the condensation rate to reduce more storage size, and increase the accuracy in abnormal detection. As the… More >

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    ARTICLE

    Evaluation of Deep Learning Models for Person Authentication Based on Touch Gesture

    Asrar Bajaber1,*, Mai Fadel1, Lamiaa Elrefaei2
    Computer Systems Science and Engineering, Vol.42, No.2, pp. 465-481, 2022, DOI:10.32604/csse.2022.022003
    (This article belongs to this Special Issue: Advances in Computational Intelligence and its Applications)
    Abstract Touch gesture biometrics authentication system is the study of user's touching behavior on his touch device to identify him. The features traditionally used in touch gesture authentication systems are extracted using hand-crafted feature extraction approach. In this work, we investigate the ability of Deep Learning (DL) to automatically discover useful features of touch gesture and use them to authenticate the user. Four different models are investigated Long-Short Term Memory (LSTM), Gated Recurrent Unit (GRU), Convolutional Neural Network (CNN) combined with LSTM (CNN-LSTM), and CNN combined with GRU(CNN-GRU). In addition, different regularization techniques are investigated such as Activity Regularizer, Batch Normalization… More >

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    ARTICLE

    PAPR Reduction Using Advanced Partial Transmission Scheme for 5G Waveforms

    Arun Kumar1, Sumit Chakravarty2, S. Suganya3, Mehedi Masud4,*, Sultan Aljahdali4
    Computer Systems Science and Engineering, Vol.42, No.2, pp. 483-492, 2022, DOI:10.32604/csse.2022.022899
    Abstract The implementation of Peak Average to Power Ratio (PAPR) reduction technologies will play an important role in the regularization of Fifth Generation (5G) radio communication. PAPR reduction in the advanced waveform will be the key part of designing a 5G network for different applications. This work introduces the simulation of an Advanced Partial Transmission Sequence (A-PTS) reduction techniques for Orthogonal Frequency Division Multiplexing (OFDM) and Filter Bank Multi-Carrier (FBMC) transmission schemes. In the projected A-PTS, the FBMC signals are mapped into the number of sub-blocks and Inverse Fast Fourier transform (IFFT) is performed to estimate the high peak power in… More >

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    ARTICLE

    Inter-Purchase Time Prediction Based on Deep Learning

    Ling-Jing Kao1, Chih-Chou Chiu1,*, Yu-Fan Lin2, Heong Kam Weng1
    Computer Systems Science and Engineering, Vol.42, No.2, pp. 493-508, 2022, DOI:10.32604/csse.2022.022166
    Abstract Inter-purchase time is a critical factor for predicting customer churn. Improving the prediction accuracy can exploit consumer’s preference and allow businesses to learn about product or pricing plan weak points, operation issues, as well as customer expectations to proactively reduce reasons for churn. Although remarkable progress has been made, classic statistical models are difficult to capture behavioral characteristics in transaction data because transaction data are dependent and short-, medium-, and long-term data are likely to interfere with each other sequentially. Different from literature, this study proposed a hybrid inter-purchase time prediction model for customers of on-line retailers. Moreover, the analysis… More >

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    ARTICLE

    Diabetic Retinopathy Diagnosis Using ResNet with Fuzzy Rough C-Means Clustering

    R. S. Rajkumar*, A. Grace Selvarani
    Computer Systems Science and Engineering, Vol.42, No.2, pp. 509-521, 2022, DOI:10.32604/csse.2022.021909
    Abstract

    Diabetic Retinopathy (DR) is a vision disease due to the long-term prevalence of Diabetes Mellitus. It affects the retina of the eye and causes severe damage to the vision. If not treated on time it may lead to permanent vision loss in diabetic patients. Today’s development in science has no medication to cure Diabetic Retinopathy. However, if diagnosed at an early stage it can be controlled and permanent vision loss can be avoided. Compared to the diabetic population, experts to diagnose Diabetic Retinopathy are very less in particular to local areas. Hence an automatic computer-aided diagnosis for DR detection is… More >

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    ARTICLE

    Securing Privacy Using Optimization and Statistical Models in Cognitive Radio Networks

    R. Neelaveni1,*, B. Sridevi2, J. Sivasankari3
    Computer Systems Science and Engineering, Vol.42, No.2, pp. 523-533, 2022, DOI:10.32604/csse.2022.021433
    Abstract Cognitive Radio Networks (CRN) are the possible and ideal solution for meeting the spectrum needs of next-generation communication systems. CRN is a promising alternative approach that allows spectrum sharing in many applications. The licensed users considered Primary Users (PU) and unlicensed users as Secondary Users (SU). Time and power consumption on security issues are considered degrading factors in performance for improving the Quality of Service (QoS). Irrespective of using different optimization techniques, the same methodology is to be updated for the task. So that, learning and optimization go hand in hand. It ensures the security in CRN, risk factors in… More >

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    ARTICLE

    Efficient User Pairing for Performance Enhancement of Downlink NOMA Systems

    Fahad Alraddady*
    Computer Systems Science and Engineering, Vol.42, No.2, pp. 535-544, 2022, DOI:10.32604/csse.2022.021746
    (This article belongs to this Special Issue: Emergent Topics in Intelligent Computing and Communication Engineering)
    Abstract In this paper, the resource allocation problem for user pairing (UP) in downlink non-orthogonal multiple access (NOMA) systems is investigated. NOMA allows the use of one subcarrier for more than one user at the same time, thus increases the total capacity of the wireless communication system. However, users pairing is a challenging task in the NOMA systems, because a good channel quality subcarrier should be selected and allocated for the user to enhance the performance of NOMA systems. The proposed UP algorithm aims to enhance the sum rate of the paired users per subcarrier and consequently enhance the total sum… More >

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    ARTICLE

    Industrial Centric Node Localization and Pollution Prediction Using Hybrid Swarm Techniques

    R. Saravana Ram1,*, M. Vinoth Kumar2, N. Krishnamoorthy3, A. Baseera4, D. Mansoor Hussain5, N. Susila6
    Computer Systems Science and Engineering, Vol.42, No.2, pp. 545-460, 2022, DOI:10.32604/csse.2022.021681
    Abstract Major fields such as military applications, medical fields, weather forecasting, and environmental applications use wireless sensor networks for major computing processes. Sensors play a vital role in emerging technologies of the 20th century. Localization of sensors in needed locations is a very serious problem. The environment is home to every living being in the world. The growth of industries after the industrial revolution increased pollution across the environment. Owing to recent uncontrolled growth and development, sensors to measure pollution levels across industries and surroundings are needed. An interesting and challenging task is choosing the place to fit the sensors. Many… More >

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