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  • Open Access


    Detection of Parkinson’s Disease with Multiple Feature Extraction Models and Darknet CNN Classification

    G. Prema Arokia Mary1,*, N. Suganthi2

    Computer Systems Science and Engineering, Vol.43, No.1, pp. 333-345, 2022, DOI:10.32604/csse.2022.021164

    Abstract Parkinson’s disease (PD) is a neurodegenerative disease in the central nervous system. Recently, more researches have been conducted in the determination of PD prediction which is really a challenging task. Due to the disorders in the central nervous system, the syndromes like off sleep, speech disorders, olfactory and autonomic dysfunction, sensory disorder symptoms will occur. The earliest diagnosing of PD is very challenging among the doctors community. There are techniques that are available in order to predict PD using symptoms and disorder measurement. It helps to save a million lives of future by early prediction.… More >

  • Open Access


    Secured Cloud Communication Using Lightweight Hash Authentication with PUF

    R. Padmavathy*, M. Newlin Rajkumar

    Computer Systems Science and Engineering, Vol.43, No.1, pp. 233-243, 2022, DOI:10.32604/csse.2022.021129

    Abstract Internet-of-Things (IoT) is an awaited technology in real-world applications to process daily tasks using intelligent techniques. The main process of data in IoT involves communication, integration, and coordination with other real-world applications. The security of transferred, stored, and processed data in IoT is not ensured in many constraints. Internet-enabled smart devices are widely used among populations for all types of applications, thus increasing the popularity of IoT among widely used server technologies. Smart grid is used in this article with IoT to manage large data. A smart grid is a collection of numerous users in… More >

  • Open Access


    Home Monitoring of Pets Based on AIoT

    Wen-Tsai Sung1, Sung-Jung Hsiao2,*

    Computer Systems Science and Engineering, Vol.43, No.1, pp. 59-75, 2022, DOI:10.32604/csse.2022.020745

    Abstract With technological and social development in recent decades, people have begun pursuing more comfortable lives that frequently feature household pets that are treated like members of the family. On average, one out of every three households has a pet. This has also led to the creation and growth of many businesses in the pet industry. A few companies have developed a system that allows busy office workers to remotely care for pets at home based on the Internet of Things and an intelligent adjustment function. As owners of two dogs, the authors of this study… More >

  • Open Access


    Feature Selection Using Grey Wolf Optimization with Random Differential Grouping

    R. S. Latha1,*, B. Saravana Balaji2, Nebojsa Bacanin3, Ivana Strumberger3, Miodrag Zivkovic3, Milos Kabiljo3

    Computer Systems Science and Engineering, Vol.43, No.1, pp. 317-332, 2022, DOI:10.32604/csse.2022.020487

    Abstract Big data are regarded as a tremendous technology for processing a huge variety of data in a short time and with a large storage capacity. The user’s access over the internet creates massive data processing over the internet. Big data require an intelligent feature selection model by addressing huge varieties of data. Traditional feature selection techniques are only applicable to simple data mining. Intelligent techniques are needed in big data processing and machine learning for an efficient classification. Major feature selection algorithms read the input features as they are. Then, the features are preprocessed and… More >

  • Open Access


    Document Clustering Using Graph Based Fuzzy Association Rule Generation

    P. Perumal*

    Computer Systems Science and Engineering, Vol.43, No.1, pp. 203-218, 2022, DOI:10.32604/csse.2022.020459

    Abstract With the wider growth of web-based documents, the necessity of automatic document clustering and text summarization is increased. Here, document summarization that is extracting the essential task with appropriate information, removal of unnecessary data and providing the data in a cohesive and coherent manner is determined to be a most confronting task. In this research, a novel intelligent model for document clustering is designed with graph model and Fuzzy based association rule generation (gFAR). Initially, the graph model is used to map the relationship among the data (multi-source) followed by the establishment of document clustering… More >

  • Open Access


    Early Diagnosis of Alzheimer’s Disease Based on Convolutional Neural Networks

    Atif Mehmood1,*, Ahed Abugabah1, Ahmed Ali AlZubi2, Louis Sanzogni3

    Computer Systems Science and Engineering, Vol.43, No.1, pp. 305-315, 2022, DOI:10.32604/csse.2022.018520

    Abstract Alzheimer’s disease (AD) is a neurodegenerative disorder, causing the most common dementia in the elderly peoples. The AD patients are rapidly increasing in each year and AD is sixth leading cause of death in USA. Magnetic resonance imaging (MRI) is the leading modality used for the diagnosis of AD. Deep learning based approaches have produced impressive results in this domain. The early diagnosis of AD depends on the efficient use of classification approach. To address this issue, this study proposes a system using two convolutional neural networks (CNN) based approaches for an early diagnosis of… More >

  • Open Access


    Flexible Task Scheduling Based on Edge Computing and Cloud Collaboration

    Suzhen Wang1,*, Wenli Wang1, Zhiting Jia1, Chaoyi Pang2

    Computer Systems Science and Engineering, Vol.42, No.3, pp. 1241-1255, 2022, DOI:10.32604/csse.2022.024021

    Abstract With the rapid development and popularization of 5G and the Internet of Things, a number of new applications have emerged, such as driverless cars. Most of these applications are time-delay sensitive, and some deficiencies were found during data processing through the cloud centric architecture. The data generated by terminals at the edge of the network is an urgent problem to be solved at present. In 5 g environments, edge computing can better meet the needs of low delay and wide connection applications, and support the fast request of terminal users. However, edge computing only has the… More >

  • Open Access


    Gray-Hole Attack Minimization in IoMT with 5G Based D2D Networks

    V. Balaji*, P. Selvaraj

    Computer Systems Science and Engineering, Vol.42, No.3, pp. 1289-1303, 2022, DOI:10.32604/csse.2022.023609

    Abstract Reliable transmission is vital to the success of the next generation of communications technologies and Fifth Generation (5G) networks. Many sensitive applications, such as eHealth and medical services, can benefit from a 5G network. The Internet of Medical Things (IoMT) is a new field that fosters the maintenance of trust among various IoMT Device to Device (D2D) modern technologies. In IoMT the medical devices have to be connected through a wireless network and constantly needs to be self-configured to provide consistent and efficient data transmission. The medical devices need to be connected with sophisticated protocols… More >

  • Open Access


    Conditional Probability Approach for Fault Detection in Photovoltaic Energy Farms

    Nagy I. Elkalashy1,*, Ibrahim B. M. Taha2

    Computer Systems Science and Engineering, Vol.42, No.3, pp. 1109-1120, 2022, DOI:10.32604/csse.2022.023509

    Abstract Detection of electric faults in photovoltaic (PV) farms enhances a sustainable service continuity of farm energy generation. In this paper, a probabilistic function is introduced to detect the faults in the PV farms. The conditional probability functions are adopted to detect different fault conditions such as internal string faults, string-to-string faults, and string-to-negative terminal faults. As the diodes are important to make the PV farms in-service safely during the faults, the distribution currents of these faults are evaluated with different concepts of diode consideration as well as without considering any diode installation. This part of… More >

  • Open Access


    CNN and Fuzzy Rules Based Text Detection and Recognition from Natural Scenes

    T. Mithila1,*, R. Arunprakash2, A. Ramachandran3

    Computer Systems Science and Engineering, Vol.42, No.3, pp. 1165-1179, 2022, DOI:10.32604/csse.2022.023308

    Abstract In today’s real world, an important research part in image processing is scene text detection and recognition. Scene text can be in different languages, fonts, sizes, colours, orientations and structures. Moreover, the aspect ratios and layouts of a scene text may differ significantly. All these variations appear assignificant challenges for the detection and recognition algorithms that are considered for the text in natural scenes. In this paper, a new intelligent text detection and recognition method for detectingthe text from natural scenes and forrecognizing the text by applying the newly proposed Conditional Random Field-based fuzzy rules… More >

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