Home / Journals / CSSE / Vol.43, No.1, 2022
  • Open Access

    ARTICLE

    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 cutting path is formed according… More >

  • Open Access

    ARTICLE

    Enhanced Route Optimization for Wireless Networks Using Meta-Heuristic Engineering

    S. Navaneetha Krishnan1, P. Sundara Vadivel2,*, D. Yuvaraj3, T. Satyanarayana Murthy4, Sree Jagadeesh Malla5, S. Nachiyappan6, S. Shanmuga Priya7
    Computer Systems Science and Engineering, Vol.43, No.1, pp. 17-26, 2022, DOI:10.32604/csse.2022.021590
    Abstract Wireless Sensor Networks (WSN) are commonly used to observe and monitor precise environments. WSNs consist of a large number of inexpensive sensor nodes that have been separated and distributed in different environments. The base station received the amount of data collected by the numerous sensors. The current developments designate that the attentFgion in applications of WSNs has been increased and extended to a very large scale. The Trust-Based Adaptive Acknowledgement (TRAACK) Intrusion-Detection System for Wireless Sensor Networks (WSN) is described based on the number of active positive deliveries and The Kalman filter used in Modified Particle Swarm Optimization (MPSO) has… More >

  • Open Access

    ARTICLE

    A Fast Panoptic Segmentation Network for Self-Driving Scene Understanding

    Abdul Majid1, Sumaira Kausar1,*, Samabia Tehsin1, Amina Jameel2
    Computer Systems Science and Engineering, Vol.43, No.1, pp. 27-43, 2022, DOI:10.32604/csse.2022.022590
    Abstract In recent years, a gain in popularity and significance of science understanding has been observed due to the high paced progress in computer vision techniques and technologies. The primary focus of computer vision based scene understanding is to label each and every pixel in an image as the category of the object it belongs to. So it is required to combine segmentation and detection in a single framework. Recently many successful computer vision methods has been developed to aid scene understanding for a variety of real world application. Scene understanding systems typically involves detection and segmentation of different natural and… More >

  • Open Access

    ARTICLE

    QKD in Cloud-Fog Computing for Personal Health Record

    L. Arulmozhiselvan*, E. Uma
    Computer Systems Science and Engineering, Vol.43, No.1, pp. 45-57, 2022, DOI:10.32604/csse.2022.022024
    Abstract Cloud computing is a rapid growing technology which delivers computing services such as servers, storage, database, networking, software and analytics. It has brought a new way to securely store and share information and data with multiple users. When authorized person access these clouds, the released data should not compromise any individual’s privacy and identity should not be revealed. Fog Computing is the extension of cloud with decentralized structure which stores the data in locations somewhere between the data source and cloud. The goal of fog computing is to provide high security, improve performance and network efficiency. We use quantum key… More >

  • Open Access

    ARTICLE

    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 observed their pets’ living habits… 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

    Cancelable Speaker Identification System Based on Optical-Like Encryption Algorithms

    Safaa El-Gazar1, Walid El-Shafai2,3,*, Ghada El-Banby4, Hesham F. A. Hamed1, Gerges M. Salama1, Mohammed Abd-Elnaby5, Fathi E. Abd El-Samie2,6
    Computer Systems Science and Engineering, Vol.43, No.1, pp. 87-102, 2022, DOI:10.32604/csse.2022.022722
    Abstract Biometric authentication is a rapidly growing trend that is gaining increasing attention in the last decades. It achieves safe access to systems using biometrics instead of the traditional passwords. The utilization of a biometric in its original format makes it usable only once. Therefore, a cancelable biometric template should be used, so that it can be replaced when it is attacked. Cancelable biometrics aims to enhance the security and privacy of biometric authentication. Digital encryption is an efficient technique to be used in order to generate cancelable biometric templates. In this paper, a highly-secure encryption algorithm is proposed to ensure… More >

  • Open Access

    ARTICLE

    Cooperative Detection Method for DDoS Attacks Based on Blockchain

    Jieren Cheng1,2, Xinzhi Yao1,2,*, Hui Li3, Hao Lu4, Naixue Xiong5, Ping Luo1,2, Le Liu1,2, Hao Guo1,2, Wen Feng1,2
    Computer Systems Science and Engineering, Vol.43, No.1, pp. 103-117, 2022, DOI:10.32604/csse.2022.025668
    Abstract Distributed Denial of Service (DDoS) attacks is always one of the major problems for service providers. Using blockchain to detect DDoS attacks is one of the current popular methods. However, the problems of high time overhead and cost exist in the most of the blockchain methods for detecting DDoS attacks. This paper proposes a blockchain-based collaborative detection method for DDoS attacks. First, the trained DDoS attack detection model is encrypted by the Intel Software Guard Extensions (SGX), which provides high security for uploading the DDoS attack detection model to the blockchain. Secondly, the service provider uploads the encrypted model to… More >

  • Open Access

    ARTICLE

    Pattern Analysis and Regressive Linear Measure for Botnet Detection

    B. Padmavathi1,2,*, B. Muthukumar3
    Computer Systems Science and Engineering, Vol.43, No.1, pp. 119-139, 2022, DOI:10.32604/csse.2022.021431
    Abstract Capturing the distributed platform with remotely controlled compromised machines using botnet is extensively analyzed by various researchers. However, certain limitations need to be addressed efficiently. The provisioning of detection mechanism with learning approaches provides a better solution more broadly by saluting multi-objective constraints. The bots’ patterns or features over the network have to be analyzed in both linear and non-linear manner. The linear and non-linear features are composed of high-level and low-level features. The collected features are maintained over the Bag of Features (BoF) where the most influencing features are collected and provided into the classifier model. Here, the linearity… More >

  • Open Access

    ARTICLE

    An Efficient Stabbing Based Intrusion Detection Framework for Sensor Networks

    A. Arivazhagi1,*, S. Raja Kumar2
    Computer Systems Science and Engineering, Vol.43, No.1, pp. 141-157, 2022, DOI:10.32604/csse.2022.021851
    Abstract Intelligent Intrusion Detection System (IIDS) for networks provide a resourceful solution to network security than conventional intrusion defence mechanisms like a firewall. The efficiency of IIDS highly relies on the algorithm performance. The enhancements towards these methods are utilized to enhance the classification accuracy and diminish the testing and training time of these algorithms. Here, a novel and intelligent learning approach are known as the stabbing of intrusion with learning framework (SILF), is proposed to learn the attack features and reduce the dimensionality. It also reduces the testing and training time effectively and enhances Linear Support Vector Machine (l-SVM). It… 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

    Efficient Supply Current Control Strategies for Bridgeless Interleaved AC-DC Converter

    R. Sasikala1,*, R. Seyezhai2
    Computer Systems Science and Engineering, Vol.43, No.1, pp. 175-191, 2022, DOI:10.32604/csse.2022.022386
    Abstract This paper presents an efficient supply current wave shaping technique for bridgeless interleaved Single Ended Primary Inductor Converter (SEPIC). The SEPIC converter converts an Alternating Current (AC) to Direct Current (DC) with the boost converter. Power Factor Correction (PFC) is progressively significant to achieve high energy efficiency. The overall system efficiency can be increased as the bridgeless topology has less conduction losses from rectifying bridges. Also, the bridgeless and interleaved techniques are incorporated in this study to achieve better performance. The performance of the system is analyzed on both current control and sensor-less techniques. Different controllers such as Proportional Integral… 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

    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 with the generation of association… More >

  • Open Access

    ARTICLE

    Early Rehabilitation of Orthopedic Internal Fixation Removal in Daytime Ward

    Lanlan Ni1, Lanzheng Bian2, Rugang Lu1, Ting Chen1,*, Jinyue Xia3
    Computer Systems Science and Engineering, Vol.43, No.1, pp. 219-231, 2022, DOI:10.32604/csse.2022.026594
    Abstract Children's fractures are very common, and many children's fractures need internal fixation. When the children are treated and recovered, it needs to be internally fixed and then taken out. With the development of internal fixation materials, the research of surgical methods and the improvement of surgical skills, postoperative removal of orthopedic surgery patients has gradually been included in daytime surgery. While ensuring the safety of children's surgery, it is necessary to shorten the postoperative limb and joint function recovery time, promote the recovery of limb and joint function, the healing of wounds and bones, and reduce the occurrence of these… More >

  • Open Access

    ARTICLE

    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 the network with the fastest… 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

    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

    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

    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

    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 AD automatically. In the proposed… More >

  • Open Access

    ARTICLE

    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 classified. Here, an algorithm does… More >

  • Open Access

    ARTICLE

    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. In this article, the early… 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 >

  • Open Access

    ARTICLE

    MRI Brain Tumor Segmentation with Intuitionist Possibilistic Fuzzy Clustering and Morphological Operations

    J. Anitha*, M. Kalaiarasu
    Computer Systems Science and Engineering, Vol.43, No.1, pp. 363-379, 2022, DOI:10.32604/csse.2022.022402
    Abstract Digital Image Processing (DIP) is a well-developed field in the biological sciences which involves classification and detection of tumour. In medical science, automatic brain tumor diagnosis is an important phase. Brain tumor detection is performed by Computer-Aided Diagnosis (CAD) systems. The human image creation is greatly achieved by an approach namely medical imaging which is exploited for medical and research purposes. Recently Automatic brain tumor detection from MRI images has become the emerging research area of medical research. Brain tumor diagnosis mainly performed for obtaining exact location, orientation and area of abnormal tissues. Cancer and edema regions inference from brain… 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

    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

    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 is presented to increase the… More >

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