Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (549)
  • Open Access

    ARTICLE

    Improving POI Recommendation via Non-Convex Regularized Tensor Completion

    Ming Zhao*, Tao Liu

    Journal of Information Hiding and Privacy Protection, Vol.2, No.3, pp. 125-134, 2020, DOI:10.32604/jihpp.2020.010211 - 18 December 2020

    Abstract The problem of low accuracy of POI (Points of Interest) recommendation in LBSN (Location-Based Social Networks) has not been effectively solved. In this paper, a POI recommendation algorithm based on nonconvex regularized tensor completion is proposed. The fourth-order tensor is constructed by using the current location category, the next location category, time and season, the regularizer is added to the objective function of tensor completion to prevent over-fitting and reduce the error of the model. The proximal algorithm is used to solve the objective function, and the adaptive momentum is introduced to improve the efficiency More >

  • Open Access

    ARTICLE

    A Data-Aware Remote Procedure Call Method for Big Data Systems

    Jin Wang1,2, Yaqiong Yang1, Jingyu Zhang1,3,*, Xiaofeng Yu4, Osama Alfarraj5, Amr Tolba5,6

    Computer Systems Science and Engineering, Vol.35, No.6, pp. 523-532, 2020, DOI:10.32604/csse.2020.35.523

    Abstract In recent years, big data has been one of the hottest development directions in the information field. With the development of artificial intelligence technology, mobile smart terminals and high-bandwidth wireless Internet, various types of data are increasing exponentially. Huge amounts of data contain a lot of potential value, therefore how to effectively store and process data efficiently becomes very important. Hadoop Distributed File System (HDFS) has emerged as a typical representative of dataintensive distributed big data file systems, and it has features such as high fault tolerance, high throughput, and can be deployed on low-cost… More >

  • Open Access

    ARTICLE

    A Position Self-Adaptive Method to Detect Fake Access Points

    Ping Lu1,2,*

    Journal of Quantum Computing, Vol.2, No.2, pp. 119-127, 2020, DOI:10.32604/jqc.2020.09433 - 19 October 2020

    Abstract In recent years, with the maturity and popularity of Wi-Fi technology, wireless hotspots have been deployed on a large scale in public places. But at the same time, it brings many security issues that cannot be ignored. Among them, the fake access point attack is a very serious threat in wireless local area network. In this paper, we propose a method to detect fake access points in wireless local area network. First, our detection method is passive, which means there is almost no additional traffic will be generated during the program’s operation. Second, different from More >

  • Open Access

    ARTICLE

    A Subsynchronous Oscillation Suppression Method Based on Self-Adaptive Auto Disturbance Rejection Proportional Integral Control of Voltage Source Converter Based Multi-Terminal Direct Current System with Doubly-Fed Induction Generator-Based Wind Farm Access

    Miaohong Su1, Haiying Dong1,2,*, Kaiqi Liu1, Weiwei Zou1

    Energy Engineering, Vol.117, No.6, pp. 439-452, 2020, DOI:10.32604/EE.2020.011805 - 16 October 2020

    Abstract A subsynchronous oscillation suppression strategy based on self-adaptive auto disturbance rejection proportional integral controller is proposed for doublyfed induction generator-based wind farm integrated into grid through voltage source converter based multi-terminal direct current. In this strategy, the nonlinear PI controller is constructed by fal function to replace the traditional linear PI controller, and then the tracking differentiator is used to arrange the appropriate transition process in combination with the idea of active disturbance rejection control, and the self-adaptive auto disturbance rejection proportional integral controller is designed. By applying the controller to the inner loop of the… More >

  • Open Access

    ARTICLE

    A Novel Forgery Detection in Image Frames of the Videos Using Enhanced Convolutional Neural Network in Face Images

    S. Velliangiri1,*, J. Premalatha2

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 625-645, 2020, DOI:10.32604/cmes.2020.010869 - 12 October 2020

    Abstract Different devices in the recent era generated a vast amount of digital video. Generally, it has been seen in recent years that people are forging the video to use it as proof of evidence in the court of justice. Many kinds of researches on forensic detection have been presented, and it provides less accuracy. This paper proposed a novel forgery detection technique in image frames of the videos using enhanced Convolutional Neural Network (CNN). In the initial stage, the input video is taken as of the dataset and then converts the videos into image frames. More >

  • Open Access

    ARTICLE

    Reversible Data Hiding in Encrypted Images Based on Prediction and Adaptive Classification Scrambling

    Lingfeng Qu1, Hongjie He1, Shanjun Zhang2, Fan Chen1, *

    CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2623-2638, 2020, DOI:10.32604/cmc.2020.09723 - 16 September 2020

    Abstract Reversible data hiding in encrypted images (RDH-EI) technology is widely used in cloud storage for image privacy protection. In order to improve the embedding capacity of the RDH-EI algorithm and the security of the encrypted images, we proposed a reversible data hiding algorithm for encrypted images based on prediction and adaptive classification scrambling. First, the prediction error image is obtained by a novel prediction method before encryption. Then, the image pixel values are divided into two categories by the threshold range, which is selected adaptively according to the image content. Multiple high-significant bits of pixels More >

  • Open Access

    ARTICLE

    Research on Prediction Methods of Prevalence Perception under Information Exposure

    Weijin Jiang1, 2, 3, 4, Fang Ye1, 2, *, Wei Liu2, 3, Xiaoliang Liu1, 2, Guo Liang5, Yuhui Xu2, 3, Lina Tan1, 2

    CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2263-2275, 2020, DOI:10.32604/cmc.2020.010082 - 16 September 2020

    Abstract With the rapid development of information technology, the explosive growth of data information has become a common challenge and opportunity. Social network services represented by WeChat, Weibo and Twitter, drive a large amount of information due to the continuous spread, evolution and emergence of users through these platforms. The dynamic modeling, analysis, and network information prediction, has very important research and application value, and plays a very important role in the discovery of popular events, personalized information recommendation, and early warning of bad information. For these reasons, this paper proposes an adaptive prediction algorithm for More >

  • Open Access

    ARTICLE

    Adaptive Binary Coding for Scene Classification Based on Convolutional Networks

    Shuai Wang1, Xianyi Chen2, *

    CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2065-2077, 2020, DOI:10.32604/cmc.2020.09857 - 16 September 2020

    Abstract With the rapid development of computer technology, millions of images are produced everyday by different sources. How to efficiently process these images and accurately discern the scene in them becomes an important but tough task. In this paper, we propose a novel supervised learning framework based on proposed adaptive binary coding for scene classification. Specifically, we first extract some high-level features of images under consideration based on available models trained on public datasets. Then, we further design a binary encoding method called one-hot encoding to make the feature representation more efficient. Benefiting from the proposed More >

  • Open Access

    ARTICLE

    Developing an Adaptation Process for Real-Coded Genetic Algorithms

    Ridvan Saraçoğlu*, Ahmet Fatih Kazankaya

    Computer Systems Science and Engineering, Vol.35, No.1, pp. 13-19, 2020, DOI:10.32604/csse.2020.35.013

    Abstract The genetic algorithm (GA) is a metaheuristic method which simulates the life cycle and the survival of the fittest in the nature for solving optimization problems. This study aimed to develop enhanced operation by modifying the current GA. This development process includes an adaptation method that contains certain developments and adds a new process to the classic algorithm. Individuals of a population will be trialed to adapt to the current solution of the problem by taking them separately for each generation. With this adaptation method, it is more likely to get better results in a More >

  • Open Access

    ARTICLE

    Optimized PID Controller Using Adaptive Differential Evolution with Meanof-pbest Mutation Strategy

    Ti-Hung Chen1, Ming-Feng Yeh2,*

    Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 407-420, 2020, DOI:10.32604/iasc.2020.013917

    Abstract On the basis of JADE (adaptive differential evolution with optional external archive) and the modified differential evolution with p-best crossover (MDE_pBX), this study attempts to propose a modified mutation strategy termed "DE/(pbest)/1" for the differential evolution (DE) algorithm, where “(pbest)” represents the mean of p top-best vectors. Two modified parameter adaptation mechanisms are also proposed to update the crossover rate and the scale factor, respectively, in an adaptive manner. The DE variant with the proposed mutation strategy and two modified adaptation mechanisms is termed adaptive differential evolution with mean-of-pbest mutation strategy, denoted by ADE_pBM is comparable to or More >

Displaying 421-430 on page 43 of 549. Per Page