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  • Open Access

    ARTICLE

    A Fully Adaptive Active Queue Management Method for Congestion Prevention at the Router Buffer

    Ali Alshahrani1, Ahmad Adel Abu-Shareha2,*, Qusai Y. Shambour2, Basil Al-Kasasbeh1

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1679-1698, 2023, DOI:10.32604/cmc.2023.043545

    Abstract Active queue management (AQM) methods manage the queued packets at the router buffer, prevent buffer congestion, and stabilize the network performance. The bursty nature of the traffic passing by the network routers and the slake behavior of the existing AQM methods leads to unnecessary packet dropping. This paper proposes a fully adaptive active queue management (AAQM) method to maintain stable network performance, avoid congestion and packet loss, and eliminate unnecessary packet dropping. The proposed AAQM method is based on load and queue length indicators and uses an adaptive mechanism to adjust the dropping probability based on the buffer status. The… More >

  • Open Access

    ARTICLE

    Classification Model for IDS Using Auto Cryptographic Denoising Technique

    N. Karthikeyan2, P. Sivaprakash1,*, S. Karthik2

    Computer Systems Science and Engineering, Vol.45, No.1, pp. 671-685, 2023, DOI:10.32604/csse.2023.029984

    Abstract Intrusion detection systems (IDS) are one of the most promising ways for securing data and networks; In recent decades, IDS has used a variety of categorization algorithms. These classifiers, on the other hand, do not work effectively unless they are combined with additional algorithms that can alter the classifier’s parameters or select the optimal sub-set of features for the problem. Optimizers are used in tandem with classifiers to increase the stability and with efficiency of the classifiers in detecting invasion. These algorithms, on the other hand, have a number of limitations, particularly when used to detect new types of threats.… More >

  • Open Access

    ARTICLE

    Experimental Performance Measures of Recycled Insulation Concrete Blocks from Construction and Demolition Waste

    Doudou Liu1,*, Liang Qiao2,3, Guozhong Li4

    Journal of Renewable Materials, Vol.10, No.6, pp. 1675-1691, 2022, DOI:10.32604/jrm.2022.018397

    Abstract Construction and demolition (C&D) waste has seriously affected the ecological environment. The utilization of C&D waste resources can greatly alleviate this problem, and it is an important way to help achieve the goal of zero carbon in 2050. In this study, insulation concrete blocks were developed with recycled aggregates, cement, fly ash as main raw materials, expanded polystyrene (EPS) insulation boards as block insulation filling material, and self-developed construction waste composite activator, interface enhancer, surface modifier and other additives. Through experimental research and performance test analysis, the best mix ratio of the product and the mechanism of each additive were… More >

  • Open Access

    ARTICLE

    Texture Segmentation based on Multivariate Generalized Gaussian Mixture Model

    K. Naveen Kumar1, K. Srinivasa Rao2, Y. Srinivas3, Ch. Satyanarayana4

    CMES-Computer Modeling in Engineering & Sciences, Vol.107, No.3, pp. 201-221, 2015, DOI:10.3970/cmes.2015.107.201

    Abstract Texture Analysis is one of the prime considerations for image analysis and processing. Texture segmentation gained lot of importance due to its ready applicability in automation of scene identification and computer vision. Several texture segmentation methods have been developed and analysed with the assumption that the feature vector associated with the texture of the image region is modelled as Gaussian mixture model. Due to the limitations of the Gaussian model being meso kurtic, it may not characterise the texture of all image regions accurately. Hence in this paper, a texture segmentation algorithm is developed and analysed with the assumption that… More >

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