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作者： Li, Zuoyong Yu, Zhaochai Liu, Weixia Xu, Yong Zhang, Daoqiang Cheng, Yong Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350121 China The Fujian College's Research Base of Humanities and Social Science for Internet Innovation Research Center Minjiang University Fuzhou350121 China Straits Institute Minjiang University Fuzhou350121 China Bio-Computing Research Center Shenzhen Graduate School Harbin Institute of Technology Shenzhen518055 China Department of Computer Science and Engineering Nanjing University of Aeronautics and Astronautics Nanjing210016 China School of Communication Engineering Nanjing Institute of Technology Nanjing211167 China

Tongue image segmentation is a crucial step in developing an automatic tongue diagnosis system. After exploring characteristics of image thresholding in different color spaces, we propose a simple and effective tongue image segmentation method. Specifically, the proposed method first extracts an initial tongue body region by performing image thresholding on the transformed hue component in HSI (Hue, Saturation, and Intensity) color space. Then, one of two image thresholding results on the red component of an original tongue image is adaptively selected to find the gap region between the tongue body root and the upper lip. Finally, the initial tongue body region is refined by removing fake object regions such as the upper lip to obtain final tongue image segmentation result. Experimental results on a tongue image dataset containing 200 subjects demonstrate the effectiveness of the proposed method. © 2018 John Wiley & Sons, Ltd.

关键词： Image segmentation

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Camera Abnormal Movement and Foreign Object Invasion Detection Based on Cumulative Edge Distribution Probability Model

Camera Abnormal Movement and Foreign Object Invasion Detecti...

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2018 International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2018

作者： Yu, Xiangru Cai, Fudong Dou, Yimin Li, Jinping Institute of Pattern Recognition and Intelligent System School of Information Science and Engineering University of Jinan Jinan China Shandong Provincial Key Laboratory of Network Based Intelligent Computing Jinan China Shandong College University Key Laboratory of Information Processing and Cognitive Computing in 13th Five-year University of Jinan Jinan China Shandong Senter Electronic Co. Ltd Zibo China

ISBN: (纸本)9781728105512

In practice, there often exist some occasions where video surveillance can only be realized by using rechargeable batteries due to the high cost of power supply. In order to extend the battery life, images can only be taken at a certain interval. Obviously, image difference is an important method to obtain various changes in this case. Among these changes, foreign invasion is one of the focuses. However, due to bolt shedding, abnormal weather and other factors, the camera may have abnormal movement which may seriously affect the detection effect of image difference method. Therefore, it is an urgent issue to find an effective way to detect the abnormal movement of camera and improve the detection accuracy of foreign invasion. Considering the characteristics of this kind of image sequences, we propose an effective algorithm to detect the camera abnormal movement and foreign object invasion based on a cumulative edge distribution probability model. Since sky region is relatively simple, we only discuss changes in sky region to detect camera abnormal movement. Our algorithm has 6 basic steps: firstly, segment the sky region;secondly, extract the edge information of the current image and the preceding adjacent image in the image sequence;thirdly, determine if the edge information of two adjacent images coincide. If consistent, then go to the next step, otherwise, it indicates that the camera has abnormal movement, then alarm;fourthly, calculate the cumulative edge probability distribution model in the sky region by using the historical image sequence;fifthly, by using adaptive Parzen window, determine if foreign object invasion exists by comparing the probability model of cumulative edge distribution with edge distribution of the current image;sixthly, update the cumulative edge distribution probability model in sky region. The algorithm achieves good results in practical applications. Through the test of thousands of images taken in the wild, the detection accuracy of

关键词： Cameras

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Research on Futures Programmed Trading Based on Deep Reinforcement Learning

Research on Futures Programmed Trading Based on Deep Reinfor...

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International Conference on Cloud computing, Big Data and Blockchain (ICCBB)

作者： Weipeng Xie Xianghan Zheng College of Mathematics and Computer Science Fuzhou University Fuzhou China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou China

ISBN: (纸本)9781728112787

There are many categories in the financial market, and futures market plays a very important role. How to make the most profit in futures market is a problem that investors, fund organizations and private placement teams have been studying all along. This paper constructs a futures investment decision model based on intensive learning model theory, makes graphical conversion according to historical time series data, defines the return of strategies for local strategy banks, trains a DQN network, automatically switches strategies, and ensures the maximization of gains.

关键词： Market research Switches Reinforcement learning Investment Data models Wavelet analysis Contracts

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A Data Placement Strategy for Scientific Workflow in Hybrid Cloud

A Data Placement Strategy for Scientific Workflow in Hybrid ...

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IEEE International Conference on Cloud computing, CLOUD

作者： Zhanghui Liu Tao Xiang Bing Lin Xinshu Ye Haijiang Wang Ying Zhang Xing Chen Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou China College of Physics and Energy Fujian Normal University College of Mathematics and Computer Science Fuzhou University

In cloud computing environments, data centers can provide high-performance computing resources and distributed storage space. Scientific workflows often need to be implemented across multiple data centers, where copious amounts of application data are stored. Moving data across geographically distributed data centers leads to intolerable delays and hinders the efficient execution of scientific workflows, which are large-scale data-intensive. Reasonable data placement can reduce data scheduling between the data centers effectively. In this paper, an adaptive discrete particle swarm optimization (PSO) algorithm based on genetic algorithm has been proposed to decrease the number of data transmissions across data centers. The algorithm overcame the premature convergence defect of PSO by introducing the mutation and crossover of genetic algorithm. Moreover, it effectively improved the diversity in the process of population evolution. Compared with the previous work, the simulation results showed that the proposed strategy greatly reduced the volume of data transfer while reducing the number of data movement across data centers.

关键词： Data centers Task analysis Cloud computing Genetic algorithms Data communication Layout Particle swarm optimization

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Integrating MOOCs with Traditional Classroom Instruction to Improve Teaching Effectiveness

Integrating MOOCs with Traditional Classroom Instruction to ...

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2017 2nd International Seminar on Education Innovation and Economic Management(SEIEM 2017)

作者： Xiaodong Wu Yuzhu Zeng Faculty of Mathematics and Computer Science Quanzhou Normal University Fujian Provincial Key Laboratory of Data Intensive Computing Key Laboratory of Intelligent Computing and Information Processing Fujian Province University

Massive Open Online Course(MOOC) is a new teaching mode appeared in recent years and its emergence has constituted some challenge to the traditional teaching. However, MOOCs teaching mode has both advantages and disadvantages. In this paper, both the merits and the demerits of MOOC education are analyzed. We point out that the MOOC education mode and the traditional face-to-face classroom instruction should be combined together so as to improve the teaching effectiveness in modern education. Finally, how to blend the MOOC mode and the traditional classroom teaching and further utilize the network platform to improve the teaching efficiency in several learning phases are examined.

关键词： MOOCs face-to-face teaching traditional teaching network teaching platform

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The Order and Failure Estimation of Redundancy System Based on Cobweb Model 4th

The Order and Failure Estimation of Redundancy System Based ...

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4th Euro-China Conference on intelligent Data Analysis and Applications, ECC 2017

作者： Xie, Chao-Fan Xu, Lin Xu, Lu-Xiong Zhang, Fuquan Network Center Fuqing Branch of Fujian Normal University Fuqing FuzhouFujian China Economic Institute Fujian Normal University Fuqing FuzhouFujian China Electronic Information and Engineering Institute Fuqing Branch of Fujian Normal University Fuqing FuzhouFujian China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350121 China School of Software Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9783319685267

In order to improve the reliability and life of components, product providers often take the form of redundant backup. The lower the failure rate of the product itself and the more the number of redundant backups, the more reliable and stable system is, but the number of redundant backups will greatly increase the cost of the product. Moreover, the product can not be detected through dismantling products to achieve, This provides the provider with the possibility of speculation, so the provider will provide a lower degree of redundancy of products or secondary products with high-level redundancy is a huge problem faced by buyers. The study will use the method of truncation estimation to make a asymptotic estimation, provide statistic reference formula and feasible calculation method for the purchaser, which can greatly reduce the cost of the demand and the reliability of the system operation. © 2018, Springer International Publishing AG.

关键词： Redundancy

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Correction to: Underwater image enhancement using an edge-preserving filtering Retinex algorithm

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Multimedia Tools and Applications 2020年第25期79卷 17279-17279页

作者： Peixian Zhuang Xinghao Ding Jiangsu Key Laboratory of Meteorological Observation and Information Processing Jiangsu Technology and Engineering Center of Meteorological Sensor Network School of Electronic and Information Engineering Nanjing University of Information Science and Technology Nanjing China Fujian Key Laboratory of Sensing and Computing for Smart City School of Information Science and Engineering Xiamen University Xiamen China

In the original publication, Equations were incorrectly presented. The original article has been corrected.

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Refactoring Java Code for Automatic API Generation

Refactoring Java Code for Automatic API Generation

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International Conference on Cloud computing, Big Data and Blockchain (ICCBB)

作者： Genggeng Liu Chuanshumin Hu Shihong Chen Ying Zhang Xing Chen Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou China National Engineering Research Center of Software Engineering Peking University Beijing China

ISBN: (纸本)9781728112787

With the development of the Internet, a large number of computer applications have emerged, and the quantity is still growing rapidly. These applications contain a lot of useful data and functions, however, as most of them are not available and couldn't interact with each other, so the data and functions are difficult to shared and reused, resulting in a huge waste of resources. In order to solve this problem, secondary development is needed on the basis of the source system. For example, it is necessary to collect data from client applications or integrate their functions. Therefore, a framework of automatic encapsulation API based on the client system is proposed in this paper. Firstly, using a design pattern to reconstruct the runtime software architecture. Secondly, an algorithm is proposed for parameter matching to automatically construct API template. Thirdly, a framework is implemented to support design patterns and matching algorithms. In conclusion, we experimented with a real client system, and the results show that in most cases our method can effectively encapsulate and reduce the execution time of the functions.

关键词： application program interfaces Java software architecture software maintenance Application programming interfaces Software maintenance Software architecture Java Java programming language API AXIAL POWER INDICATOR American Petroleum Institute execution time AUTOMATIC APPLIED COMPUTER SCIENCE Clients design pattern

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Identification and Prediction of key Nucleotide Sites Using Machine Learning in Bioinformatics: A Brief Overview

Identification and Prediction of Key Nucleotide Sites Using ...

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IEEE International Conference on Big Data and Cloud computing (BdCloud)

作者： Jianhua Cai Leyi Wei Kun Zeng Guobao Xiao Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou P.R. China College of Mathematics and Computer Science Fuzhou University Fuzhou P.R. China College of Intelligence and Computing Tianjin University Tianjin P.R. China

ISBN: (数字)9781728143286

ISBN: (纸本)9781728143293

Nowadays, the burgeon of machine learning has promoted its wide application in various fields. In Bioinformatics, machine learning computational method has become an indispensable part. Its efficiency and simplicity break the expensive and inefficient barriers of previous experimental methods. This article briefly reviews the application and development of machine learning in identifying and predicting key nucleotide sites (such as 6mA, 5mC, 4mC, etc.) in DNA or RNA. Among them, supervised learning is one of the main methods to this work. Its wide application has provided great convenience for the development of identification and prediction of key nucleotides in Bioinformatics.

关键词： Bioinformatics Feature extraction Machine learning Predictive models Computational modeling DNA Prediction algorithms

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Video rain/snow removal by transformed online multiscale convolutional sparse coding

arXiv

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arXiv 2019年

作者： Li, Minghan Cao, Xiangyong Zhao, Qian Zhang, Lei Gao, Chenqiang Meng, Deyu School of Mathematics and Statistics Ministry of Education Key Lab of Intelligent Networks and Network Security Xi'an Jiaotong University Shaanxi China Department of Computing Hong Kong Polytechnic University Hung Hom Hong Kong Chongqing Key Laboratory of Signal and Information Processing Chongqing University of Posts and Telecommunications Chongqing400065 China

Video rain/snow removal from surveillance videos is an important task in the computer vision community since rain/snow existed in videos can severely degenerate the performance of many surveillance system. Various methods have been investigated extensively, but most only consider consistent rain/snow under stable background scenes. Rain/snow captured from practical surveillance camera, however, is always highly dynamic in time with the background scene transformed occasionally. To this issue, this paper proposes a novel rain/snow removal approach, which fully considers dynamic statistics of both rain/snow and background scenes taken from a video sequence. Specifically, the rain/snow is encoded as an online multi-scale convolutional sparse coding (OMS-CSC) model, which not only finely delivers the sparse scattering and multi-scale shapes of real rain/snow, but also well encodes their temporally dynamic configurations by real-time ameliorated parameters in the model. Furthermore, a transformation operator imposed on the background scenes is further embedded into the proposed model, which finely conveys the dynamic background transformations, such as rotations, scalings and distortions, inevitably existed in a real video sequence. The approach so constructed can naturally better adapt to the dynamic rain/snow as well as background changes, and also suitable to deal with the streaming video attributed its online learning mode. The proposed model is formulated in a concise maximum a posterior (MAP) framework and is readily solved by the ADMM algorithm. Compared with the state-of-the-art online and offline video rain/snow removal methods, the proposed method achieves better performance on synthetic and real videos datasets both visually and quantitatively. Specifically, our method can be implemented in relatively high efficiency, showing its potential to real-time video rain/snow removal. Copyright © 2019, The Authors. All rights reserved.

关键词： Convolution

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