Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (5)
  • Open Access

    ARTICLE

    Double DQN Method For Botnet Traffic Detection System

    Yutao Hu1, Yuntao Zhao1,*, Yongxin Feng2, Xiangyu Ma1

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 509-530, 2024, DOI:10.32604/cmc.2024.042216 - 25 April 2024

    Abstract In the face of the increasingly severe Botnet problem on the Internet, how to effectively detect Botnet traffic in real-time has become a critical problem. Although the existing deep Q network (DQN) algorithm in Deep reinforcement learning can solve the problem of real-time updating, its prediction results are always higher than the actual results. In Botnet traffic detection, although it performs well in the training set, the accuracy rate of predicting traffic is as high as%; however, in the test set, its accuracy has declined, and it is impossible to adjust its prediction strategy on… More >

  • Open Access

    ARTICLE

    An Efficient Scheme for Data Pattern Matching in IoT Networks

    Ashraf Ali*, Omar A. Saraereh

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2203-2219, 2022, DOI:10.32604/cmc.2022.025994 - 29 March 2022

    Abstract The Internet has become an unavoidable trend of all things due to the rapid growth of networking technology, smart home technology encompasses a variety of sectors, including intelligent transportation, allowing users to communicate with anybody or any device at any time and from anywhere. However, most things are different now. Background: Structured data is a form of separated storage that slows down the rate at which everything is connected. Data pattern matching is commonly used in data connectivity and can help with the issues mentioned above. Aim: The present pattern matching system is ineffective due… More >

  • Open Access

    ARTICLE

    COVID-19 Severity Prediction Using Enhanced Whale with Salp Swarm Feature Classification

    Nebojsa Budimirovic1, E. Prabhu2, Milos Antonijevic1, Miodrag Zivkovic1, Nebojsa Bacanin1,*, Ivana Strumberger1, K. Venkatachalam3

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1685-1698, 2022, DOI:10.32604/cmc.2022.023418 - 24 February 2022

    Abstract Computerized tomography (CT) scans and X-rays play an important role in the diagnosis of COVID-19 and pneumonia. On the basis of the image analysis results of chest CT and X-rays, the severity of lung infection is monitored using a tool. Many researchers have done in diagnosis of lung infection in an accurate and efficient takes lot of time and inefficient. To overcome these issues, our proposed study implements four cascaded stages. First, for pre-processing, a mean filter is used. Second, texture feature extraction uses principal component analysis (PCA). Third, a modified whale optimization algorithm is More >

  • Open Access

    ARTICLE

    Information Classification and Extraction on Official Web Pages of Organizations

    Jinlin Wang1, Xing Wang1, *, Hongli Zhang1, Binxing Fang1, Yuchen Yang1, Jianan Liu2

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 2057-2073, 2020, DOI:10.32604/cmc.2020.011158 - 30 June 2020

    Abstract As a real-time and authoritative source, the official Web pages of organizations contain a large amount of information. The diversity of Web content and format makes it essential for pre-processing to get the unified attributed data, which has the value of organizational analysis and mining. The existing research on dealing with multiple Web scenarios and accuracy performance is insufficient. This paper aims to propose a method to transform organizational official Web pages into the data with attributes. After locating the active blocks in the Web pages, the structural and content features are proposed to classify More >

  • Open Access

    ARTICLE

    Brake Fault Diagnosis Through Machine Learning Approaches – A Review

    Alamelu Manghai T.M.1, Jegadeeshwaran R2, Sugumaran V.3

    Structural Durability & Health Monitoring, Vol.11, No.1, pp. 43-67, 2017, DOI:10.3970/sdhm.2017.012.043

    Abstract Diagnosis is the recognition of the nature and cause of a certain phenomenon. It is generally used to determine cause and effect of a problem. Machine fault diagnosis is a field of finding faults arising in machines. To identify the most probable faults leading to failure, many methods are used for data collection, including vibration monitoring, thermal imaging, oil particle analysis, etc. Then these data are processed using methods like spectral analysis, wavelet analysis, wavelet transform, short-term Fourier transform, high-resolution spectral analysis, waveform analysis, etc., The results of this analysis are used in a root More >

Displaying 1-10 on page 1 of 5. Per Page