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作者： Huiqun Wu Shenghui Zhao Xiaofeng Zhang Aimin Sang Jiancheng Dong Kui Jiang Department of Medical Informatics Medical School of Nantong University Nantong University The Key Laboratory of Cognitive Computing and Intelligent Information Processing of Fujian Education Institutions (Wuyi University) Department of Ophthalmology Affiliated Hospital of Nantong University

Purpose: We aim to develop a back-propagation artificial neural network（BPANN） improved by a priori knowledge and to compare its efficacy with other methods in early diabetic retinopathy（DR） detection. Methods: A total of 240 fundus images, composed of 120 early-stage DR and 120 normal images, were obtained with the same 45° field of view camera, with the macula at the center, as a cohort for further training. All retinal images were processed, and a priori knowledge features such as blood vessel width and tortuosity were semi-automatically extracted. An improved BP-ANN with a priori knowledge was developed, and its efficacy was compared with that of the traditional BP network and SVM. Besides, k-fold cross validation method was conducted to demonstrate the efficiency of the proposed methods. We also developed a graphical user interface of our proposed BP-ANN to aid in DR screening. Results: Our 10 randomization and 5-fold cross validation results of SVM, traditional BP, and improved BP were compared. The results indicated that the BP-ANN with a priori knowledge can achieve better detection results. Besides, our results were also comparable with other reported state-of-art algorithms. During the training stage, the epoch in the improved BP-ANN was less than that in the traditional BP group（109 vs 254）, indicating that the time cost was shorter when using our improved BP-ANN. Furthermore, the accuracy and epoch of both the traditional BP and our improved BP network obtained better performances when the number of hidden neurons was 20. Conclusions: A priori knowledge-based BP-ANN could be a promising measure for early DR detection.

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A Mix-model based Deep Learning for Text Sentiment Analysis

A Mix-model based Deep Learning for Text Sentiment Analysis

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

作者： Qingfeng Pan Xianghan Zheng Guolong Chen Fujian Key Laboratory of Network Computing and Intelligent Information Processing College of Mathematics and Computer Science Fuzhou China

ISBN: (纸本)9781728112787

In recent years, with the rapid development of the Internet, a large number of emotional color data on commodities, events and services contain great value of mining. Traditional text sentiment analysis has been unable to effectively deal with the increasingly rich semantic information and it relies much on feature engineering. Manual features extraction consumes a lot of effort and it's hard to cover all the information. Deep learning has strong ability to fit nonlinear functions, it can dig deeper features of language, describe the rich inner information, which has good applicability and powerful expression. Aim at the problems that single neural network model can't fully extract features, the paper construct a bidirectional dynamic mixed memory model of text sentiment analysis based on deep learning. Firstly, using word embedding to represent the ***, building the combination of convolutional neural network and recurrent neural network, through the model fusion and the cascade configuration of memory cells, extracting features from different dimensions. Finally, adding the attention mechanism to weighted mean for output, capture the key information of text. The results show that the model can better make full use of the context of text, extract deeper features, and improve the accuracy of text analysis.

关键词： convolutional neural nets feature extraction learning (artificial intelligence) recurrent neural nets sentiment analysis text analysis recurrent neural nets text processing Feature extraction texts Sentiment analysis cascade configuration nonlinear functions Weighted Average immunocytes

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Reversible data hiding based on reducing invalid shifting of pixels in histogram shifting

arXiv

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arXiv 2019年

作者： Jia, Yujie Yin, Zhaoxia Zhang, Xinpeng Luo, Yonglong Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei230601 China School of Computer Science Fudan University Shanghai201203 China Anhui Provincial Key Laboratory of Network and Information Security Wuhu Anhui240002 China

In recent years, reversible data hiding (RDH), a new research hotspot in the field of information security, has been paid more and more attention by researchers. Most of the existing RDH schemes do not fully take it into account that natural image's texture has influence on embedding distortion. The image distortion caused by embedding data in the image's smooth region is much smaller than that in the unsmooth region, essentially, it is because embedding additional data in the smooth region corresponds to fewer invalid shifting pixels (ISPs) in histogram shifting. Thus, we propose a RDH scheme based on the images texture to reduce invalid shifting of pixels in histogram shifting. Specifically, first, a cover image is divided into two sub-images by the checkerboard pattern, and then each sub-image's fluctuation values are calculated. Finally, additional data can be embedded into the region of sub-images with smaller fluctuation value preferentially. The experimental results demonstrate that the proposed method has higher capacity and better stego-image quality than some existing RDH schemes. Copyright © 2019, The Authors. All rights reserved.

关键词： Pixels

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Design and Realization of MATLAB-based Face Recognition System

Design and Realization of MATLAB-based Face Recognition Syst...

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1st International Conference on Advanced Algorithms and Control Engineering, ICAACE 2018

作者： Liu, Jianming College of Mathematics and Computer Science Quanzhou Normal University Fujian Quanzhou362000 China Key Laboratory of Intelligent Computing and Information Processing Fujian Province University Quanzhou Normal University Fujian Quanzhou362000 China

Through MATLAB, the paper makes a comparison between Principal Component Analysis (PCA)face recognition algorithm and Adaboost recognition algorithm and selects the algorithm with higher recognition rates to develop an auto face recognition system. The paper explicates primary techniques the system adopts and its specific realization process. By downloading face database online, the paper conducts an all-round test to the system, the result of which proves that this face recognition system is completely practical and feasible. © Published under licence by IOP Publishing Ltd.

关键词： Principal component analysis

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Self-Evolutionary Neuron Model for Fast-Response Spiking Neural networks

TechRxiv

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TechRxiv 2019年

作者： Zhang, Anguo Han, Ying Hu, Jing Niu, Yuzhen Gao, Yueming Chen, Zhizhang Zhao, Kai College of Physics and Information Engineering Fuzhou University Fujian350108 China The Key Laboratory of Medical Instrumentation Pharmaceutical Technology of Fujian Province Fuzhou350116 China Research Institute of Ruijie Ruijie Networks Co. Ltd Fujian350002 China School of Public Health Xiamen University Xiamen361102 China College of Information and Intelligent Transportation Fujian Chuanzheng Communications College Fuzhou350007 China Fujian Key Laboratory of Network Computing and Intelligent Information Processing College of Mathematics and Computer Science Fuzhou University The Key Laboratory of Spatial Data Mining and Information Sharing Ministry of Education Fujian350108 China College of Physics and information Engineering Fuzhou University the Key Laboratory of Medical Instrumentation Pharmaceutical Technology of Fujian Province Fujian350108 China College of Physics and Information Engineering Fuzhou University 350108 China Faculty of Science and Technology University of Macau 999078 China

We propose two simple and effective spiking neuron models to improve the response time of the conventional spiking neural network. The proposed neuron models adaptively tune the presynaptic input current depending on the input received from its presynapses and subsequent neuron firing events. We analyze and derive the firing activity homeostatic convergence of the proposed models. We experimentally verify and compare the models on MNIST handwritten digits and FashionMNIST classification tasks. We show that the proposed neuron models significantly increase the response speed to the input signal. Experiment codes are available at https://***/anvien/Evol-SNN. © 2019, CC0.

关键词： Neural networks

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A Genetic Algorithm Based Piecewise Linear Representation of Time Series

A Genetic Algorithm Based Piecewise Linear Representation of...

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International Conference on intelligent System and Knowledge Engineering, ISKE

作者： Xiyang Yang Changxin Zhai Fang Li Longshu Liu Youhua Zhang Key laboratory of Intelligent Computing and Information Processing of Fujian Province Quanzhou Normal University Quanzhou China School of Mathematics and Computer Science Quanzhou Normal University Quanzhou China School of Mathematical Science Beijing Normal University Beijing China

ISBN: (数字)9781728123486

ISBN: (纸本)9781728123493

Line Segment Representation (LSR) refers to represents a time series by a few of line segments, such that the original time series and the piecewise line segment series have shapes as similar as possible. Because of its simple expression, LSR based time series are often easier to be understood and computed for some time series datamining tasks than the original raw data. Two kinds of continuous LSR methods, namely, 1 1 trend filtering and mix-integer programming (MILP) method, are discussed in this paper. To overcome the poor representation ability of l 1 trend filtering, and the high computational complexity of MILP, this paper proposes a hybrid method combining GA and linear programming (GA-LP) to find the optimal LSR time series efficiently. In GA-LP, locations of the breakpoints of the piecewise linear segment are fixed by GA, and values on these locations are fixed by a LP method. Numerical experiments reveal that GA-LP can reduce representation error by comparisons with l 1 trend filtering and MILP method, and its computing time is much less than that of MILP.

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A chaotic artificial bee colony algorithm based on lévy search

A chaotic artificial bee colony algorithm based on lévy sea...

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作者： Lin, Shijie Dong, Chen Wang, Zhiqiang Guo, Wenzhong Chen, Zhenyi Ye, Yin College of Mathematics and Computer Science Fuzhou University Fuzhou350116 China Key Laboratory of Information Security of Network Systems Fuzhou350116 China Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou350116 China Department of Electrical Engineering University of South Florida TampaFL33620 United States

A Lévy search strategy based chaotic artificial bee colony algorithm (LABC) is proposed in this paper. The chaotic sequence, global optimal mechanism and Lévy flight mechanism were introduced respectively into the initialization, the employed bee search and the onlooker bee search. The experiments show that the proposed algorithm performed better in convergence speed, global search ability and optimization accuracy than other improved ABC. Copyright © 2018 The Institute of Electronics, information and Communication Engineers.

关键词： Evolutionary algorithms

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Web server security evaluation method based on multi-source data

Web server security evaluation method based on multi-source ...

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

作者： Kedong Wu Xiaoling Gao Yanhua Liu Provincial Key Laboratory of Network Computing and Intelligent Information Processing College of Mathematics and Computer Science Fuzhou University Fuzhou Fujian Fujian Fuzhou Fujian China

ISBN: (纸本)9781728112787

Traditional web security assessments are evaluated using a single data source, and the results of the calculations from different data sources are different. Based on multi-source data, this paper uses Analytic Hierarchy Process to construct an evaluation model, calculates the weight of each level of indicators in the web security evaluation model, analyzes and processes the data, calculates the host security threat assessment values at various levels, and visualizes the evaluation results through ECharts+WebGL technology.

关键词： Security Servers IP networks XML information processing Data models Safety

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Positioning and Pressing Elevator Button by Binocular Vision and Robot Manipulator

Positioning and Pressing Elevator Button by Binocular Vision...

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

作者： Fang, Tiyu Chen, Huiwu Shi, Jianjie Li, Jinping University of Jinan School of Information Science and Engineering Jinan250022 China Shandong Provincial Key Laboratory of Network Based Intelligent Computing University of Jinan Jinan Shandong250022 China Shandong College University Key Laboratory of Information Processing and Cognitive Computing in 13th Fiveyear Jinan Shandong250022 China

ISBN: (纸本)9781728105512

There are two key problems of anthropomorphic dual-arm robot up and down floors which are path planning and pressing buttons of elevator automatically. Our research group has solved the problem of robot path planning based on electronic map in early stage. As for the problem of pressing buttons automatically, two issues still need to be handled, including positioning elevator buttons in three-dimensional space and pressing specific button automatically by the manipulator of robot. At present, our research group has achieved the accurate detection and recognition of elevator target button in the image. Besides, for the core issue, a new method of pressing target button automatically by manipulator with binocular vision servo is proposed. First, the binocular measurement is applied to get the distance and declination relationships between robot itself and target button, then we shall find the precise position of target button in visual three-dimensional coordinate system and transform its position into the three-dimensional coordinate system which takes robot shoulder as the origin. Thus, the manipulator movement model can be established by constructing relationships between the declination of three degrees of freedom and the real-time coordinates of manipulator, which contains extension of shoulder joint, Internal rotation of shoulder joint and flexion-extension function of elbow joint, and each of them as a separate dimension. On the basis of this model, the PWM (Pulse Width Modulation) control technology is employed to make the manipulator terminal close to target button autonomously. Finally, with deviation relationships between the manipulator terminal and target button as well as the threshold which is set to modulate manipulator, the goal of pressing target button by manipulator can be achieved eventually. Furthermore, the algorithm was tested on medium-sized wheeled dual-arm robot Hawk and results obtained verify the feasibility of the method proposed above ca

关键词： Robot applications

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ANDROIDOFF:Offloading android application based on cost estimation

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Journal of Systems and Software 2019年 158卷 110418-000页

作者： Chen, Xing Chen, Jiaqing Liu, Bichun Ma, Yun Zhang, Ying Zhong, Hao College of Mathematics and Computer Science Fuzhou University Fuzhou350116 China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou350116 China School of Software Tsinghua University Beijing100084 China National Engineering Research Center of Software Engineering Peking University China Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai200240 China

Computation offloading is a promising way of improving the performance and reducing the battery power consumption, since it moves some time-consuming computation activities to nearby servers. Although various approaches have been proposed to support computation offloading, we argue that there is still sufficient space for improvements, since existing approaches cannot accurately estimate the execution costs. As a result, we find that their offloading plans are less optimized. To handle the problem, in this paper, given an Android application, we propose a novel approach, called ANDROIDOFF, that supports offloading at the granularity of objects. Supporting such capability is challenging due to the two reasons: (1) through dynamic execution, it is feasible to collect the execution costs of only partial methods, and (2) it is difficult to accurately estimate the execution costs of the remaining methods. To overcome the challenges, given an Android application, ANDROIDOFF first combines static and dynamic analysis to predict the execution costs of all its methods. After all the costs are estimated, ANDROIDOFF synthesizes an offloading plan, in which determines the offloading details. We evaluate ANDROIDOFF on a real-world application, with two mobile devices. Our results show that, compared with other approaches, ANDROIDOFF saves the response time by 8%–49% and reduces the energy consumption by 12%–49% on average for computation-intensive applications. © 2019 Elsevier Inc.

关键词： computation offloading

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