Prohim Tam¹, Sa Math¹, Seokhoon Kim^1,2,*

Computer Systems Science and Engineering, Vol.45, No.2, pp. 2141-2154, 2023, DOI:10.32604/csse.2023.030984 - 03 November 2022

Abstract Edge intelligence brings the deployment of applied deep learning (DL) models in edge computing systems to alleviate the core backbone network congestions. The setup of programmable software-defined networking (SDN) control and elastic virtual computing resources within network functions virtualization (NFV) are cooperative for enhancing the applicability of intelligent edge softwarization. To offer advancement for multi-dimensional model task offloading in edge networks with SDN/NFV-based control softwarization, this study proposes a DL mechanism to recommend the optimal edge node selection with primary features of congestion windows, link delays, and allocatable bandwidth capacities. Adaptive partial task offloading policy… More >

Fuat Türk^*

Computer Systems Science and Engineering, Vol.45, No.2, pp. 1357-1373, 2023, DOI:10.32604/csse.2023.030772 - 03 November 2022

Abstract Covid-19 is a deadly virus that is rapidly spread around the world towards the end of the 2020. The consequences of this virus are quite frightening, especially when accompanied by an underlying disease. The novelty of the virus, the constant emergence of different variants and its rapid spread have a negative impact on the control and treatment process. Although the new test kits provide almost certain results, chest X-rays are extremely important to detect the progression and degree of the disease. In addition to the Covid-19 virus, pneumonia and harmless opacity of the lungs also… More >

G. Nallasivan^1,*, V. Ramachandran², Roobaea Alroobaea³, Jasem Almotiri⁴

Computer Systems Science and Engineering, Vol.45, No.2, pp. 1655-1677, 2023, DOI:10.32604/csse.2023.030697 - 03 November 2022

Abstract An ultrasonic filter detects signs of malignant tumors by analysing the image’s pixel quality fluctuations caused by a liver ailment. Signs of malignant growth proximity are identified in an ultrasound filter through image pixel quality variations from a liver’s condition. Those changes are more common in alcoholic liver conditions than in other etiologies of cirrhosis, suggesting that the cause may be alcohol instead of liver disease. Existing Two-Dimensional (2D) ultrasound data sets contain an accuracy rate of 85.9% and a 2D Computed Tomography (CT) data set of 91.02%. The most recent work on designing a… More >

Anwer Mustafa Hilal^1,*, Amal Al-Rasheed², Jaber S. Alzahrani³, Majdy M. Eltahir⁴, Mesfer Al Duhayyim⁵, Nermin M. Salem⁶, Ishfaq Yaseen¹, Abdelwahed Motwakel¹

Computer Systems Science and Engineering, Vol.45, No.2, pp. 1249-1263, 2023, DOI:10.32604/csse.2023.030603 - 03 November 2022

Abstract Sleep plays a vital role in optimum working of the brain and the body. Numerous people suffer from sleep-oriented illnesses like apnea, insomnia, etc. Sleep stage classification is a primary process in the quantitative examination of polysomnographic recording. Sleep stage scoring is mainly based on experts’ knowledge which is laborious and time consuming. Hence, it can be essential to design automated sleep stage classification model using machine learning (ML) and deep learning (DL) approaches. In this view, this study focuses on the design of Competitive Multi-verse Optimization with Deep Learning Based Sleep Stage Classification (CMVODL-SSC)… More >

Karthick Panneerselvam^1,2,*, K. Mahesh¹, V. L. Helen Josephine³, A. Ranjith Kumar²

Computer Systems Science and Engineering, Vol.45, No.2, pp. 1047-1061, 2023, DOI:10.32604/csse.2023.030513 - 03 November 2022

Abstract Deep learning has reached many successes in Video Processing. Video has become a growing important part of our daily digital interactions. The advancement of better resolution content and the large volume offers serious challenges to the goal of receiving, distributing, compressing and revealing high-quality video content. In this paper we propose a novel Effective and Efficient video compression by the Deep Learning framework based on the flask, which creatively combines the Deep Learning Techniques on Convolutional Neural Networks (CNN) and Generative Adversarial Networks (GAN). The video compression method involves the layers are divided into different… More >

Muhammad Junaid Umer¹, Muhammad Sharif¹, Majed Alhaisoni², Usman Tariq³, Ye Jin Kim⁴, Byoungchol Chang^5,*

Computer Systems Science and Engineering, Vol.45, No.2, pp. 1001-1016, 2023, DOI:10.32604/csse.2023.030463 - 03 November 2022

Abstract Breast cancer (BC) is a most spreading and deadly cancerous malady which is mostly diagnosed in middle-aged women worldwide and effecting beyond a half-million people every year. The BC positive newly diagnosed cases in 2018 reached 2.1 million around the world with a death rate of 11.6% of total cases. Early diagnosis and detection of breast cancer disease with proper treatment may reduce the number of deaths. The gold standard for BC detection is biopsy analysis which needs an expert for correct diagnosis. Manual diagnosis of BC is a complex and challenging task. This work… More >

Anwer Mustafa Hilal^1,*, Eatedal Alabdulkreem², Jaber S. Alzahrani³, Majdy M. Eltahir⁴, Mohamed I. Eldesouki⁵, Ishfaq Yaseen¹, Abdelwahed Motwakel¹, Radwa Marzouk⁶

Computer Systems Science and Engineering, Vol.45, No.2, pp. 1129-1143, 2023, DOI:10.32604/csse.2023.030080 - 03 November 2022

Abstract Biomedical image processing is widely utilized for disease detection and classification of biomedical images. Tongue color image analysis is an effective and non-invasive tool for carrying out secondary detection at anytime and anywhere. For removing the qualitative aspect, tongue images are quantitatively inspected, proposing a novel disease classification model in an automated way is preferable. This article introduces a novel political optimizer with deep learning enabled tongue color image analysis (PODL-TCIA) technique. The presented PODL-TCIA model purposes to detect the occurrence of the disease by examining the color of the tongue. To attain this, the More >

V. Divya^1,*, S. Sendil Kumar², V. Gokula Krishnan³, Manoj Kumar⁴

Computer Systems Science and Engineering, Vol.45, No.2, pp. 1869-1886, 2023, DOI:10.32604/csse.2023.029762 - 03 November 2022

Abstract Signal processing based research was adopted with Electroencephalogram (EEG) for predicting the abnormality and cerebral activities. The proposed research work is intended to provide an automatic diagnostic system to determine the EEG signal in order to classify the brain function which shows whether a person is affected with schizophrenia or not. Early detection and intervention are vital for better prognosis. However, the diagnosis of schizophrenia still depends on clinical observation to date. Without reliable biomarkers, schizophrenia is difficult to detect in its early phase and hence we have proposed this idea. In this work, the… More >

K. Madumathi^1,*, S. Chandrasekar²

Computer Systems Science and Engineering, Vol.45, No.2, pp. 1821-1836, 2023, DOI:10.32604/csse.2023.029561 - 03 November 2022

Abstract Artificial intelligence, machine learning and deep learning algorithms have been widely used for Maximum Power Point Tracking (MPPT) in solar systems. In the traditional MPPT strategies, following of worldwide Global Maximum Power Point (GMPP) under incomplete concealing conditions stay overwhelming assignment and tracks different nearby greatest power focuses under halfway concealing conditions. The advent of artificial intelligence in MPPT has guaranteed of accurate following of GMPP while expanding the significant performance and efficiency of MPPT under Partial Shading Conditions (PSC). Still the selection of an efficient learning based MPPT is complex because each model has… More >

P. Sumathi^1,*, V. V. Karthikeyan², M. S. Kavitha³, S. Karthik³

Computer Systems Science and Engineering, Vol.45, No.2, pp. 1545-1559, 2023, DOI:10.32604/csse.2023.027580 - 03 November 2022

Abstract Soil is the major source of infinite lives on Earth and the quality of soil plays significant role on Agriculture practices all around. Hence, the evaluation of soil quality is very important for determining the amount of nutrients that the soil require for proper yield. In present decade, the application of deep learning models in many fields of research has created greater impact. The increasing soil data availability of soil data there is a greater demand for the remotely avail open source model, leads to the incorporation of deep learning method to predict the soil… More >