Home / Journals / CSSE / Vol.44, No.1, 2023
  • Open AccessOpen Access

    ARTICLE

    Metaheuristics Based Node Localization Approach for Real-Time Clustered Wireless Networks

    R. Bhaskaran1, P. S. Sujith Kumar2, G. Shanthi3, L. Raja4, Gyanendra Prasad Joshi5, Woong Cho6,*
    Computer Systems Science and Engineering, Vol.44, No.1, pp. 1-17, 2023, DOI:10.32604/csse.2023.024973
    Abstract In recent times, real time wireless networks have found their applicability in several practical applications such as smart city, healthcare, surveillance, environmental monitoring, etc. At the same time, proper localization of nodes in real time wireless networks helps to improve the overall functioning of networks. This study presents an Improved Metaheuristics based Energy Efficient Clustering with Node Localization (IM-EECNL) approach for real-time wireless networks. The proposed IM-EECNL technique involves two major processes namely node localization and clustering. Firstly, Chaotic Water Strider Algorithm based Node Localization (CWSANL) technique to determine the unknown position of the nodes. Secondly, an Oppositional Archimedes Optimization… More >

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    ARTICLE

    Design of Hierarchical Classifier to Improve Speech Emotion Recognition

    P. Vasuki*
    Computer Systems Science and Engineering, Vol.44, No.1, pp. 19-33, 2023, DOI:10.32604/csse.2023.024441
    Abstract Automatic Speech Emotion Recognition (SER) is used to recognize emotion from speech automatically. Speech Emotion recognition is working well in a laboratory environment but real-time emotion recognition has been influenced by the variations in gender, age, the cultural and acoustical background of the speaker. The acoustical resemblance between emotional expressions further increases the complexity of recognition. Many recent research works are concentrated to address these effects individually. Instead of addressing every influencing attribute individually, we would like to design a system, which reduces the effect that arises on any factor. We propose a two-level Hierarchical classifier named Interpreter of responses… More >

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    ARTICLE

    A Hybrid Regularization-Based Multi-Frame Super-Resolution Using Bayesian Framework

    Mahmoud M. Khattab1,2,*, Akram M Zeki1, Ali A. Alwan3, Belgacem Bouallegue2, Safaa S. Matter4, Abdelmoty M. Ahmed2
    Computer Systems Science and Engineering, Vol.44, No.1, pp. 35-54, 2023, DOI:10.32604/csse.2023.025251
    Abstract The prime purpose for the image reconstruction of a multi-frame super-resolution is to reconstruct a higher-resolution image through incorporating the knowledge obtained from a series of relevant low-resolution images, which is useful in numerous fields. Nevertheless, super-resolution image reconstruction methods are usually damaged by undesirable restorative artifacts, which include blurring distortion, noises, and stair-casing effects. Consequently, it is always challenging to achieve balancing between image smoothness and preservation of the edges inside the image. In this research work, we seek to increase the effectiveness of multi-frame super-resolution image reconstruction by increasing the visual information and improving the automated machine perception,… More >

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    ARTICLE

    Efficient Centralized Cooperative Spectrum Sensing Techniques for Cognitive Networks

    P. Gnanasivam1, G. T. Bharathy1,*, V. Rajendran2, T. Tamilselvi1
    Computer Systems Science and Engineering, Vol.44, No.1, pp. 55-65, 2023, DOI:10.32604/csse.2023.023374
    Abstract Wireless Communication is a system for communicating information from one point to other, without utilizing any connections like wire, cable, or other physical medium. Cognitive Radio (CR) based systems and networks are a revolutionary new perception in wireless communications. Spectrum sensing is a vital task of CR to avert destructive intrusion with licensed primary or main users and discover the accessible spectrum for the efficient utilization of the spectrum. Centralized Cooperative Spectrum Sensing (CSS) is a kind of spectrum sensing. Most of the test metrics designed till now for sensing the spectrum is produced by using the Sample Covariance Matrix… More >

  • Open AccessOpen Access

    ARTICLE

    Enforcing a Source-end Cooperative Multilevel Defense Mechanism to Counter Flooding Attack

    Saraswathi Shunmuganathan*
    Computer Systems Science and Engineering, Vol.44, No.1, pp. 67-79, 2023, DOI:10.32604/csse.2023.023858
    Abstract The exponential advancement in telecommunication embeds the Internet in every aspect of communication. Interconnections of networks all over the world impose monumental risks on the Internet. A Flooding Attack (FA) is one of the major intimidating risks on the Internet where legitimate users are prevented from accessing network services. Irrespective of the protective measures incorporated in the communication infrastructure, FA still persists due to the lack of global cooperation. Most of the existing mitigation is set up either at the traffic starting point or at the traffic ending point. Providing mitigation at one or the other end may not be… More >

  • Open AccessOpen Access

    ARTICLE

    Histogram Matched Chest X-Rays Based Tuberculosis Detection Using CNN

    Joe Louis Paul Ignatius1,*, Sasirekha Selvakumar1, Kavin Gabriel Joe Louis Paul2, Aadhithya B. Kailash1, S. Keertivaas1, S. A. J. Akarvin Raja Prajan1
    Computer Systems Science and Engineering, Vol.44, No.1, pp. 81-97, 2023, DOI:10.32604/csse.2023.025195
    Abstract Tuberculosis (TB) is a severe infection that mostly affects the lungs and kills millions of people’s lives every year. Tuberculosis can be diagnosed using chest X-rays (CXR) and data-driven deep learning (DL) approaches. Because of its better automated feature extraction capability, convolutional neural networks (CNNs) trained on natural images are particularly effective in image categorization. A combination of 3001 normal and 3001 TB CXR images was gathered for this study from different accessible public datasets. Ten different deep CNNs (Resnet50, Resnet101, Resnet152, InceptionV3, VGG16, VGG19, DenseNet121, DenseNet169, DenseNet201, MobileNet) are trained and tested for identifying TB and normal cases. This… More >

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    ARTICLE

    Improved Load-Balanced Clustering for Energy-Aware Routing (ILBC-EAR) in WSNs

    D. Loganathan1,*, M. Balasubramani1, R. Sabitha2, S. Karthik2
    Computer Systems Science and Engineering, Vol.44, No.1, pp. 99-112, 2023, DOI:10.32604/csse.2023.023120
    Abstract Sensors are considered as important elements of electronic devices. In many applications and service, Wireless Sensor Networks (WSNs) are involved in significant data sharing that are delivered to the sink node in energy efficient manner using multi-hop communications. But, the major challenge in WSN is the nodes are having limited battery resources, it is important to monitor the consumption rate of energy is very much needed. However, reducing energy consumption can increase the network lifetime in effective manner. For that, clustering methods are widely used for optimizing the rate of energy consumption among the sensor nodes. In that concern, this… More >

  • Open AccessOpen Access

    ARTICLE

    Fuzzy User Access Trust Model for Cloud Access Control

    Aakib Jawed Khan*, Shabana Mehfuz
    Computer Systems Science and Engineering, Vol.44, No.1, pp. 113-128, 2023, DOI:10.32604/csse.2023.023378
    Abstract Cloud computing belongs to a set of policies, protocols, technologies through which one can access shared resources such as storage, applications, networks, and services at relatively low cost. Despite the tremendous advantages of cloud computing, one big threat which must be taken care of is data security in the cloud. There are a dozen of threats that we are being exposed to while availing cloud services. Insufficient identity and access management, insecure interfaces and Applications interfaces (APIs), hijacking, advanced persistent threats, data threats, and many more are certain security issues with the cloud platform. APIs and service providers face a… More >

  • Open AccessOpen Access

    ARTICLE

    Arrhythmia Prediction on Optimal Features Obtained from the ECG as Images

    Fuad A. M. Al-Yarimi*
    Computer Systems Science and Engineering, Vol.44, No.1, pp. 129-142, 2023, DOI:10.32604/csse.2023.024297
    Abstract A critical component of dealing with heart disease is real-time identification, which triggers rapid action. The main challenge of real-time identification is illustrated here by the rare occurrence of cardiac arrhythmias. Recent contributions to cardiac arrhythmia prediction using supervised learning approaches generally involve the use of demographic features (electronic health records), signal features (electrocardiogram features as signals), and temporal features. Since the signal of the electrical activity of the heartbeat is very sensitive to differences between high and low heartbeats, it is possible to detect some of the irregularities in the early stages of arrhythmia. This paper describes the training… More >

  • Open AccessOpen Access

    ARTICLE

    An Efficient Framework for Utilizing Underloaded Servers in Compute Cloud

    M. Hema1,*, S. Kanaga Suba Raja2
    Computer Systems Science and Engineering, Vol.44, No.1, pp. 143-156, 2023, DOI:10.32604/csse.2023.024895
    Abstract In cloud data centers, the consolidation of workload is one of the phases during which the available hosts are allocated tasks. This phenomenon ensures that the least possible number of hosts is used without compromise in meeting the Service Level Agreement (SLA). To consolidate the workloads, the hosts are segregated into three categories: normal hosts, under-loaded hosts, and overloaded hosts based on their utilization. It is to be noted that the identification of an extensively used host or underloaded host is challenging to accomplish. Threshold values were proposed in the literature to detect this scenario. The current study aims to… More >

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