Zhibin Zhang^1,2,*, Ping Li^1,3, Shuailing Zhao^1,2, Zhimin Lv^1,2, Fang Du^1,2, Yajian An^1,2

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 1043-1056, 2021, DOI:10.32604/cmc.2020.012517 - 30 October 2020

Abstract As the agricultural internet of things (IoT) technology has evolved, smart agricultural robots needs to have both flexibility and adaptability when moving in complex field environments. In this paper, we propose the concept of a vision-based navigation system for the agricultural IoT and a binocular vision navigation algorithm for smart agricultural robots, which can fuse the edge contour and the height information of rows of crop in images to extract the navigation parameters. First, the speeded-up robust feature (SURF) extracting and matching algorithm is used to obtain featuring point pairs from the green crop row… More >

Muhammad Adnan Khan^1,*, Mubashar Habib¹, Shazia Saqib¹, Tahir Alyas¹, Khalid Masood Khan¹, Mohammed A. Al Ghamdi², Sultan H. Almotiri²

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 691-706, 2021, DOI:10.32604/cmc.2020.012542 - 30 October 2020

Abstract The innovation and development in data science have an impact in all trades of life. The commercialization of sport has encouraged players, coaches, and other concerns to use technology to be in better position than r their opponents. In the past, the focus was on improved training techniques for better physical performance. These days, sports analytics identify the patterns in the performance and highlight strengths and weaknesses of potential players. Sports analytics not only predict the performance of players in the near future but it also performs predictive modeling for a particular behavior of a… More >

Qianqian Li¹, Meng Li², Lei Guo^3,*, Zhen Zhang⁴

Journal of Information Hiding and Privacy Protection, Vol.2, No.4, pp. 199-205, 2020, DOI:10.32604/jihpp.2020.016299 - 07 January 2021

Abstract On-site programming big data refers to the massive data generated in the process of software development with the characteristics of real-time, complexity and high-difficulty for processing. Therefore, data cleaning is essential for on-site programming big data. Duplicate data detection is an important step in data cleaning, which can save storage resources and enhance data consistency. Due to the insufficiency in traditional Sorted Neighborhood Method (SNM) and the difficulty of high-dimensional data detection, an optimized algorithm based on random forests with the dynamic and adaptive window size is proposed. The efficiency of the algorithm can be More >

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 >

Jin Wang^1,2, Yaqiong Yang¹, Jingyu Zhang^1,3,*, Xiaofeng Yu⁴, Osama Alfarraj⁵, Amr Tolba^5,6

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 >

Ping Lu^1,2,*

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 >

Miaohong Su¹, Haiying Dong^1,2,*, 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 >

S. Velliangiri^1,*, 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 >

Lingfeng Qu¹, Hongjie He¹, Shanjun Zhang², Fan Chen^{1, *}

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 >

Weijin Jiang^{1, 2, 3, 4}, Fang Ye^{1, 2, *}, Wei Liu^{2, 3}, Xiaoliang Liu^{1, 2}, Guo Liang⁵, Yuhui Xu^{2, 3}, Lina Tan^{1, 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 >