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Search Results (131)
  • Open Access

    ARTICLE

    Cryptographic Lightweight Encryption Algorithm with Dimensionality Reduction in Edge Computing

    D. Jerusha*, T. Jaya

    Computer Systems Science and Engineering, Vol.42, No.3, pp. 1121-1132, 2022, DOI:10.32604/csse.2022.022997

    Abstract Edge Computing is one of the radically evolving systems through generations as it is able to effectively meet the data saving standards of consumers, providers and the workers. Requisition for Edge Computing based items have been increasing tremendously. Apart from the advantages it holds, there remain lots of objections and restrictions, which hinders it from accomplishing the need of consumers all around the world. Some of the limitations are constraints on computing and hardware, functions and accessibility, remote administration and connectivity. There is also a backlog in security due to its inability to create a trust between devices involved in… More >

  • Open Access

    ARTICLE

    N-SVRG: Stochastic Variance Reduction Gradient with Noise Reduction Ability for Small Batch Samples

    Haijie Pan, Lirong Zheng*

    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 493-512, 2022, DOI:10.32604/cmes.2022.019069

    Abstract The machine learning model converges slowly and has unstable training since large variance by random using a sample estimate gradient in SGD. To this end, we propose a noise reduction method for Stochastic Variance Reduction gradient (SVRG), called N-SVRG, which uses small batches samples instead of all samples for the average gradient calculation, while performing an incremental update of the average gradient. In each round of iteration, a small batch of samples is randomly selected for the average gradient calculation, while the average gradient is updated by rounding of the past model gradients during internal iterations. By suitably reducing the… More >

  • Open Access

    ARTICLE

    STRASS Dehazing: Spatio-Temporal Retinex-Inspired Dehazing by an Averaging of Stochastic Samples

    Zhe Yu1, Bangyong Sun1,3,*, Di Liu2, Vincent Whannou de Dravo1, Margarita Khokhlova4, Siyuan Wu3

    Journal of Renewable Materials, Vol.10, No.5, pp. 1381-1395, 2022, DOI:10.32604/jrm.2022.018262

    Abstract In this paper, we propose a neoteric and high-efficiency single image dehazing algorithm via contrast enhancement which is called STRASS (Spatio-Temporal Retinex-Inspired by an Averaging of Stochastic Samples) dehazing, it is realized by constructing an efficient high-pass filter to process haze images and taking the influence of human vision system into account in image dehazing principles. The novel high-pass filter works by getting each pixel using RSR and computes the average of the samples. Then the low-pass filter resulting from the minimum envelope in STRESS framework has been replaced by the average of the samples. The final dehazed image is… More >

  • Open Access

    ARTICLE

    Gaining-Sharing Knowledge Based Algorithm for Solving Stochastic Programming Problems

    Prachi Agrawal1, Khalid Alnowibet2, Ali Wagdy Mohamed3,4,*

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2847-2868, 2022, DOI:10.32604/cmc.2022.023126

    Abstract This paper presents a novel application of metaheuristic algorithms for solving stochastic programming problems using a recently developed gaining sharing knowledge based optimization (GSK) algorithm. The algorithm is based on human behavior in which people gain and share their knowledge with others. Different types of stochastic fractional programming problems are considered in this study. The augmented Lagrangian method (ALM) is used to handle these constrained optimization problems by converting them into unconstrained optimization problems. Three examples from the literature are considered and transformed into their deterministic form using the chance-constrained technique. The transformed problems are solved using GSK algorithm and… More >

  • Open Access

    ARTICLE

    Stochastic Gradient Boosting Model for Twitter Spam Detection

    K. Kiruthika Devi1,*, G. A. Sathish Kumar2

    Computer Systems Science and Engineering, Vol.41, No.2, pp. 849-859, 2022, DOI:10.32604/csse.2022.020836

    Abstract

    In today’s world of connectivity there is a huge amount of data than we could imagine. The number of network users are increasing day by day and there are large number of social networks which keeps the users connected all the time. These social networks give the complete independence to the user to post the data either political, commercial or entertainment value. Some data may be sensitive and have a greater impact on the society as a result. The trustworthiness of data is important when it comes to public social networking sites like facebook and twitter. Due to the large… More >

  • Open Access

    ARTICLE

    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 >

  • Open Access

    ARTICLE

    VISPNN: VGG-Inspired Stochastic Pooling Neural Network

    Shui-Hua Wang1, Muhammad Attique Khan2, Yu-Dong Zhang3,*

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3081-3097, 2022, DOI:10.32604/cmc.2022.019447

    Abstract Aim Alcoholism is a disease that a patient becomes dependent or addicted to alcohol. This paper aims to design a novel artificial intelligence model that can recognize alcoholism more accurately. Methods We propose the VGG-Inspired stochastic pooling neural network (VISPNN) model based on three components: (i) a VGG-inspired mainstay network, (ii) the stochastic pooling technique, which aims to outperform traditional max pooling and average pooling, and (iii) an improved 20-way data augmentation (Gaussian noise, salt-and-pepper noise, speckle noise, Poisson noise, horizontal shear, vertical shear, rotation, Gamma correction, random translation, and scaling on both raw image and its horizontally mirrored image).… More >

  • Open Access

    ARTICLE

    Deterministic and Stochastic Fractional-Order Hastings-Powell Food Chain Model

    Moustafa El-Shahed1,*, Asmaa M. Al-Dububan2

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2277-2296, 2022, DOI:10.32604/cmc.2022.019314

    Abstract In this paper, a deterministic and stochastic fractional-order model of the tri-trophic food chain model incorporating harvesting is proposed and analysed. The interaction between prey, middle predator and top predator population is investigated. In order to clarify the characteristics of the proposed model, the analysis of existence, uniqueness, non-negativity and boundedness of the solutions of the proposed model are examined. Some sufficient conditions that ensure the local and global stability of equilibrium points are obtained. By using stability analysis of the fractional-order system, it is proved that if the basic reproduction number , the predator free equilibrium point is globally… More >

  • Open Access

    ARTICLE

    Deterministic and Stochastic Fractional Order Model for Lesser Date Moth

    Moustafa El-shahed1,*, Asmaa M. Al-Dububan2

    Computer Systems Science and Engineering, Vol.40, No.2, pp. 749-764, 2022, DOI:10.32604/csse.2022.019655

    Abstract In this paper, a deterministic and stochastic fractional order model for lesser date moth (LDM) using mating disruption and natural enemies is proposed and analysed. The interaction between LDM larvae, fertilized LDM female, unfertilized LDM female, LDM male and the natural enemy is investigated. In order to clarify the characteristics of the proposed deterministic fractional order model, the analysis of existence, uniqueness, non-negativity and boundedness of the solutions of the proposed fractional-order model are examined. In addition, some sufficient conditions are obtained to ensure the local and global stability of equilibrium points. The occurrence of local bifurcation near the equilibrium… More >

  • Open Access

    ARTICLE

    Two-Stage Production Planning Under Stochastic Demand: Case Study of Fertilizer Manufacturing

    Chia-Nan Wang1, Shao-Dong Syu1,2,*, Chien-Chang Chou3, Viet Tinh Nguyen4, Dang Van Thuy Cuc5

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1195-1207, 2022, DOI:10.32604/cmc.2022.019890

    Abstract Agriculture is a key facilitator of economic prosperity and nourishes the huge global population. To achieve sustainable agriculture, several factors should be considered, such as increasing nutrient and water efficiency and/or improving soil health and quality. Using fertilizer is one of the fastest and easiest ways to improve the quality of nutrients inland and increase the effectiveness of crop yields. Fertilizer supplies most of the necessary nutrients for plants, and it is estimated that at least 30%–50% of crop yields is attributable to commercial fertilizer nutrient inputs. Fertilizer is always a major concern in achieving sustainable and efficient agriculture. Applying… More >

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