Journals / CMC / Vol.,
Table of Content

Research Article

BEST PAPER 2021

Machine Learning Empowered Secure Computing for Intelligent Systems


Submission Deadline: 28 February 2022

Abstract

This article has no abstract.

Keywords

Suggested topics include, but are not limited to, the following:
• Cybersecurity
• Spam Detection
• Secure online social networks
• Anomaly and intrusion detection in the network
• Malware analysis and detection
• Security models based AI for protecting IoT networks
• Intrusion Detection for IoT systems
• Distributed AI Systems and Architectures
• eBusiness, eCommerce, eHealth, eLearning
• Finance and AI
• Extreme Machine Learning
• Applications of neural networks in data analytics
• CNN, LSTM
• Automation and control system
• Smart mobility and transportation
• Signal and Image Processing
  • Research Article

    BEST PAPER 2021

    Defocus Blur Segmentation Using Local Binary Patterns with Adaptive Threshold

    Usman Ali, Muhammad Tariq Mahmood* CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1597-1611, 2022, DOI:10.32604/cmc.2022.022219
    Abstract Enormous methods have been proposed for the detection and segmentation of blur and non-blur regions of the images. Due to the limited available information about blur type, scenario and the level of blurriness, detection and segmentation is a challenging task. Hence, the performance of the blur measure operator is an essential factor and needs improvement to attain perfection. In this paper, we propose an effective blur measure based on local binary pattern (LBP) with adaptive threshold for blur detection. The sharpness metric developed based on LBP used a fixed threshold irrespective of the type and level of blur, that may… More >

    Graphic Abstract

  • Research Article

    BEST PAPER 2021

    DDoS Detection in SDN using Machine Learning Techniques

    Muhammad Waqas Nadeem, Hock Guan Goh*, Vasaki Ponnusamy, Yichiet Aun CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 771-789, 2022, DOI:10.32604/cmc.2022.021669
    Abstract Software-defined network (SDN) becomes a new revolutionary paradigm in networks because it provides more control and network operation over a network infrastructure. The SDN controller is considered as the operating system of the SDN based network infrastructure, and it is responsible for executing the different network applications and maintaining the network services and functionalities. Despite all its tremendous capabilities, the SDN face many security issues due to the complexity of the SDN architecture. Distributed denial of services (DDoS) is a common attack on SDN due to its centralized architecture, especially at the control layer of the SDN that has a… More >

    Graphic Abstract

  • Research Article

    BEST PAPER 2021

    Estimating Fuel-Efficient Air Plane Trajectories Using Machine Learning

    Jaiteg Singh1, Gaurav Goyal1, Farman Ali2, Babar Shah3, Sangheon Pack4,* CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 6189-6204, 2022, DOI:10.32604/cmc.2022.021657
    Abstract Airline industry has witnessed a tremendous growth in the recent past. Percentage of people choosing air travel as first choice to commute is continuously increasing. Highly demanding and congested air routes are resulting in inadvertent delays, additional fuel consumption and high emission of greenhouse gases. Trajectory planning involves creation identification of cost-effective flight plans for optimal utilization of fuel and time. This situation warrants the need of an intelligent system for dynamic planning of optimized flight trajectories with least human intervention required. In this paper, an algorithm for dynamic planning of optimized flight trajectories has been proposed. The proposed algorithm… More >

    Graphic Abstract

  • Research Article

    BEST PAPER 2021

    A Novel Auto-Annotation Technique for Aspect Level Sentiment Analysis

    Muhammad Aasim Qureshi1,*, Muhammad Asif1, Mohd Fadzil Hassan2, Ghulam Mustafa1, Muhammad Khurram Ehsan1, Aasim Ali1, Unaza Sajid1 CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4987-5004, 2022, DOI:10.32604/cmc.2022.020544
    Abstract In machine learning, sentiment analysis is a technique to find and analyze the sentiments hidden in the text. For sentiment analysis, annotated data is a basic requirement. Generally, this data is manually annotated. Manual annotation is time consuming, costly and laborious process. To overcome these resource constraints this research has proposed a fully automated annotation technique for aspect level sentiment analysis. Dataset is created from the reviews of ten most popular songs on YouTube. Reviews of five aspects—voice, video, music, lyrics and song, are extracted. An N-Gram based technique is proposed. Complete dataset consists of 369436 reviews that took 173.53… More >

    Graphic Abstract

Share Link

WeChat scan