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  • Open Access


    A Real-time Cutting Model Based on Finite Element and Order Reduction

    Xiaorui Zhang1,2,*, Wenzheng Zhang2, Wei Sun3, Hailun Wu2, Aiguo Song4, Sunil Kumar Jha5

    Computer Systems Science and Engineering, Vol.43, No.1, pp. 1-15, 2022, DOI:10.32604/csse.2022.024950

    Abstract Telemedicine plays an important role in Corona Virus Disease 2019 (COVID-19). The virtual surgery simulation system, as a key component in telemedicine, requires to compute in real-time. Therefore, this paper proposes a real-time cutting model based on finite element and order reduction method, which improves the computational speed and ensure the real-time performance. The proposed model uses the finite element model to construct a deformation model of the virtual lung. Meanwhile, a model order reduction method combining proper orthogonal decomposition and Galerkin projection is employed to reduce the amount of deformation computation. In addition, the More >

  • Open Access


    Design and Analysis of Novel Antenna for Millimeter-Wave Communication

    Omar A. Saraereh*

    Computer Systems Science and Engineering, Vol.43, No.1, pp. 413-422, 2022, DOI:10.32604/csse.2022.024202

    Abstract At present, the microwave frequency band bandwidth used for mobile communication is only 600 MHz. In 2020, the 5G mobile Communication required about 1 GHz of bandwidth, so people need to tap new spectrum resources to meet the development needs of mobile Internet traffic that will increase by 1,000 times in the next 10 years. Utilize the potentially large bandwidth (30∼300 GHz) of the millimeter wave frequency band to provide higher data rates is regarded as the potential development trend of the future wireless communication technology. A microstrip patch implementation approach based on electromagnetic coupling feeding… More >

  • Open Access


    Support Vector Machine Based Handwritten Hindi Character Recognition and Summarization

    Sunil Dhankhar1,*, Mukesh Kumar Gupta1, Fida Hussain Memon2,3, Surbhi Bhatia4, Pankaj Dadheech1, Arwa Mashat5

    Computer Systems Science and Engineering, Vol.43, No.1, pp. 397-412, 2022, DOI:10.32604/csse.2022.024059

    Abstract In today’s digital era, the text may be in form of images. This research aims to deal with the problem by recognizing such text and utilizing the support vector machine (SVM). A lot of work has been done on the English language for handwritten character recognition but very less work on the under-resourced Hindi language. A method is developed for identifying Hindi language characters that use morphology, edge detection, histograms of oriented gradients (HOG), and SVM classes for summary creation. SVM rank employs the summary to extract essential phrases based on paragraph position, phrase position,… More >

  • Open Access


    PAPR Reduction of NOMA Using Vandermonde Matrix-Particle Transmission Sequence

    Arun Kumar1,*, Sandeep Gupta2, Himanshu Sharma3, Mehedi Masud4

    Computer Systems Science and Engineering, Vol.43, No.1, pp. 193-201, 2022, DOI:10.32604/csse.2022.023991

    Abstract Non-Orthogonal Multiple Access (NOMA) is an ideal choice for 5G waveforms due to their characteristics such as high data rate, massive device connectivity, high spectral access, and effective frequency selective fading. Thus, it permits gigantic connectivity. The spectrum overlaps with NOMA, which consents several operators to segment the spectrum at the same frequency. These features make NOMA more suitable for use beyond 5G. Peak to Average Power (PAPR) is a major problem in Multi-Carrier Techniques (MCT) like NOMA and it also degrades the performance of the amplifier. The Partial Transmission Sequence (PTS) is a superior… More >

  • Open Access


    Breast Mammogram Analysis and Classification Using Deep Convolution Neural Network

    V. Ulagamuthalvi1, G. Kulanthaivel2,*, A. Balasundaram3, Arun Kumar Sivaraman4

    Computer Systems Science and Engineering, Vol.43, No.1, pp. 275-289, 2022, DOI:10.32604/csse.2022.023737

    Abstract One of the fast-growing disease affecting women’s health seriously is breast cancer. It is highly essential to identify and detect breast cancer in the earlier stage. This paper used a novel advanced methodology than machine learning algorithms such as Deep learning algorithms to classify breast cancer accurately. Deep learning algorithms are fully automatic in learning, extracting, and classifying the features and are highly suitable for any image, from natural to medical images. Existing methods focused on using various conventional and machine learning methods for processing natural and medical images. It is inadequate for the image… More >

  • Open Access


    Bayes Theorem Based Virtual Machine Scheduling for Optimal Energy Consumption

    R. Swathy*, B. Vinayagasundaram

    Computer Systems Science and Engineering, Vol.43, No.1, pp. 159-174, 2022, DOI:10.32604/csse.2022.023706

    Abstract This paper proposes an algorithm for scheduling Virtual Machines (VM) with energy saving strategies in the physical servers of cloud data centers. Energy saving strategy along with a solution for productive resource utilization for VM deployment in cloud data centers is modeled by a combination of “Virtual Machine Scheduling using Bayes Theorem” algorithm (VMSBT) and Virtual Machine Migration (VMMIG) algorithm. It is shown that the overall data center’s consumption of energy is minimized with a combination of VMSBT algorithm and Virtual Machine Migration (VMMIG) algorithm. Virtual machine migration between the active physical servers in the… More >

  • Open Access


    Energy-Efficient Cluster in Wireless Sensor Network Using Life Time Delay Clustering Algorithms

    V. Kumar1,*, N. Jayapandian2, P. Balasubramanie3

    Computer Systems Science and Engineering, Vol.43, No.1, pp. 77-86, 2022, DOI:10.32604/csse.2022.023481

    Abstract Through Wireless Sensor Networks (WSN) formation, industrial and academic communities have seen remarkable development in recent decades. One of the most common techniques to derive the best out of wireless sensor networks is to upgrade the operating group. The most important problem is the arrangement of optimal number of sensor nodes as clusters to discuss clustering method. In this method, new client nodes and dynamic methods are used to determine the optimal number of clusters and cluster heads which are to be better organized and proposed to classify each round. Parameters of effective energy use… More >

  • Open Access


    A Novel Approach Based on Hybrid Algorithm for Energy Efficient Cluster Head Identification in Wireless Sensor Networks

    C. Ram Kumar1,*, K. Murali Krishna2, Mohammad Shabbir Alam3, K. Vigneshwaran4, Sridharan Kannan5, C. Bharatiraja6

    Computer Systems Science and Engineering, Vol.43, No.1, pp. 259-273, 2022, DOI:10.32604/csse.2022.023477

    Abstract The Wireless Sensor Networks (WSN) is a self-organizing network with random deployment of wireless nodes that connects each other for effective monitoring and data transmission. The clustering technique employed to group the collection of nodes for data transmission and each node is assigned with a cluster head. The major concern with the identification of the cluster head is the consideration of energy consumption and hence this paper proposes an hybrid model which forms an energy efficient cluster head in the Wireless Sensor Network. The proposed model is a hybridization of Glowworm Swarm Optimization (GSO) and More >

  • Open Access


    Intrusion Detection System for Big Data Analytics in IoT Environment

    M. Anuradha1,*, G. Mani2, T. Shanthi3, N. R. Nagarajan4, P. Suresh5, C. Bharatiraja6

    Computer Systems Science and Engineering, Vol.43, No.1, pp. 381-396, 2022, DOI:10.32604/csse.2022.023321

    Abstract In the digital area, Internet of Things (IoT) and connected objects generate a huge quantity of data traffic which feeds big data analytic models to discover hidden patterns and detect abnormal traffic. Though IoT networks are popular and widely employed in real world applications, security in IoT networks remains a challenging problem. Conventional intrusion detection systems (IDS) cannot be employed in IoT networks owing to the limitations in resources and complexity. Therefore, this paper concentrates on the design of intelligent metaheuristic optimization based feature selection with deep learning (IMFSDL) based classification model, called IMFSDL-IDS for… More >

  • Open Access


    A Sensitive Wavebands Identification System for Smart Farming

    M. Kavitha*, M. Sujaritha

    Computer Systems Science and Engineering, Vol.43, No.1, pp. 245-257, 2022, DOI:10.32604/csse.2022.023320

    Abstract Sensing the content of macronutrients in the agricultural soil is an essential task in precision agriculture. It helps the farmers in the optimal use of fertilizers. It reduces the cost of food production and also the negative environmental impacts on atmosphere and water bodies due to indiscriminate dosage of fertilizers. The traditional chemical-based laboratory soil analysis methods do not serve the purpose as they are hardly suitable for site specific soil management. Moreover, the spectral range used in the chemical-based laboratory soil analysis may be of 350–2500 nm, which leads to redundancy and confusion. Developing sensors… More >

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