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  • Open Access

    ARTICLE

    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, numerical data, inverted comma, sentence… More >

  • Open Access

    ARTICLE

    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 algorithm for moderating the PAPR.… More >

  • Open Access

    ARTICLE

    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 where the coarse structure matters… More >

  • Open Access

    ARTICLE

    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 data center is carried out… More >

  • Open Access

    ARTICLE

    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 and the ability to decide… More >

  • Open Access

    ARTICLE

    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 Artificial Bee Colony (ABC) algorithm… More >

  • Open Access

    ARTICLE

    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 IoT networks. The proposed IMFSDL-IDS… More >

  • Open Access

    ARTICLE

    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 based on the discovery of… More >

  • Open Access

    ARTICLE

    Fuzzy-Based Secure Clustering with Routing Technique for VANETs

    T. S. Balaji1,2, S. Srinivasan3,*, S. Prasanna Bharathi4, B. Ramesh5

    Computer Systems Science and Engineering, Vol.43, No.1, pp. 291-304, 2022, DOI:10.32604/csse.2022.023269

    Abstract Due to the advanced developments in communication technologies, Internet of vehicles and vehicular adhoc networks (VANET) offers numerous opportunities for effectively managing transportation problems. On the other, the cloud environment needs to disseminate the emergency message to the vehicles which are consistently distributed on the roadway so that every vehicle gets the messages from closer vehicles in a straightforward way. To resolve this issue, clustering and routing techniques can be designed using computational intelligence approaches. With this motivation, this paper presents a new type-2 fuzzy sets based clustering with metaheuristic optimization based routing (T2FSC-MOR) technique for secure communication in VANET.… More >

  • Open Access

    ARTICLE

    Assessing Asian Economies Renewable Energy Consumption Efficiency Using DEA with Undesirable Output

    Chia-Nan Wang1, Ngoc-Ai-Thy Nguyen1,*, Thanh-Tuan Dang1,2, Jing-Wein Wang3

    Computer Systems Science and Engineering, Vol.43, No.1, pp. 347-362, 2022, DOI:10.32604/csse.2022.022941

    Abstract Along with vast non-fossil potential and significant expertise, there is a question of whether Asian nations are attaining efficient consumption and exploitation of renewable resources. From this perspective, the paper aims to evaluate the efficiency of 14 potential Asia countries in renewable energy consumption during the six-year periods (2014–2019). In analyzing the performance of the renewable energy sector, the data envelopment analysis (DEA) with an undesirable output model approach has been widely utilized to measure the efficiency of peer units compared with the best practice frontier. We consider four inputs and two outputs to a DEA-based efficiency model. Labor force,… More >

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