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A random finite set based joint probabilistic data association filter with non-homogeneous Markov chain

Frontiers of Information technology & Electronic Engineering 2021年第8期22卷 1114-1126页

作者： Yun ZHU Shuang LIANG Xiaojun WU Honghong YANG Key Laboratory of Modern Teaching Technology Ministry of EducationXi’an 710062China School of Computer Science Shaanxi Normal UniversityXi’an 710119China Academy of Advanced Interdisciplinary Research Xidian UniversityXi’an 710071China

We demonstrate a heuristic approach for optimizing the posterior density of the data association tracking algorithm via the random finite set(RFS)***,we propose an adjusted version of the joint probabilistic data association(JPDA)filter,known as the nearest-neighbor set JPDA(NNSJPDA).The target labels in all possible data association events are switched using a novel nearest-neighbor method based on the Kullback-Leibler divergence,with the goal of improving the accuracy of the ***,the distribution of the target-label vector is *** transition matrix of the target-label vector can be obtained after the switching of the posterior *** transition matrix varies with time,causing the propagation of the distribution of the target-label vector to follow a non-homogeneous Markov *** show that the chain is inherently doubly stochastic and deduce corresponding *** examples and simulations,the effectiveness of NNSJPDA is *** results can be easily generalized to other data association approaches under the same RFS framework.

关键词： Target tracking Filtering theory Random finite set theory Bayes methods Markov chain

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A Differential Privacy Incentive Compatible Mechanism and Equilibrium Analysis

A Differential Privacy Incentive Compatible Mechanism and Eq...

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International Conference on Networking and Network Applications (NaNA)

作者： Hai Liu Zhenqiang Wu Lin Zhang Key Laboratory of Modern Teaching Technology Shannxi Normal University Xi'an China Shangluo university Shangluo China

ISBN: (纸本)9781467398046

In data analysis with interactive or non-interactive framework, the common assumption is that the data curators are credible. However, it is not reliable in reality. To that end, we propose, according to the incentive compatible mechanism, a differential privacy truthful mechanism, and in the mechanism, we analyze data privacy, utility and incentive compatible properties. Through analysis our scheme addresses the problem that data curator is not trust, and show it satisfies privacy and utility, and obtains the truthful tell. Another, differential privacy and availability is at odds with each other, the research of balance of between differential privacy and availability has been extensively developed, and availability is formulated as a quality of service. In this paper, to the balance problem of between differential privacy and availability, we only need to directly depend on utility function of the availability related to differential privacy budget, so we construct a game with respect to them and analyze the equilibrium of differential privacy and availability by using linear programming.

关键词： Privacy Data privacy Games Cost accounting Databases Reliability Mechanical factors

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Hippocampal μ-opioid receptors on GABAergic neurons mediate stress-induced impairment of memory retrieval

Hippocampal μ-opioid receptors on GABAergic neurons mediate...

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2019中国生理学会学术年会暨张锡钧基金第十五届全国青年优秀生理学学术论文交流会及第十三届全国青年生理学工作者学术会议

作者：师梅梅 Ka-Min Fan Yan-Ning Qiao Li-Juan Qiu Wei Ren Zhi-Qiang Liu MOE Key Laboratory of Modern Teaching Technology Center for Teacher Professional Ability DevelopmentShaanxi Normal University

Stressful life events induce abnormalities in emotional and cognitive *** endogenous opioid system plays an essential role in stress adaptation and coping *** particular, theμ-opioid receptor (μR), one of the major opioid receptors, strongly influences memory processing in that alterations inμR signalling are associated with various neuropsychiatric ***, it

关键词： Hippocampal opioid receptors on GABAergic neurons mediate stress-induced impairment of memory retrieval

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A Regularized Hypergraph Recommendation Algorithm with Attention Mechanism

A Regularized Hypergraph Recommendation Algorithm with Atten...

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IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS)

作者： Tingting Zhu Jianrui Chen Zhihui Wang Meixia He The Key Laboratory of Modern Teaching Technology Ministry of Education Xi’an China Shaanxi Normal University Xi’an China

ISBN: (纸本)9781665441506

Collaborative filtering is one of the most commonly used recommendation technologies in recommender systems. However, it has the problems of sparse score data and low recommendation accuracy. To address these problems, we propose a regularized hypergraph recommendation algorithm with attention mechanism. We can fully mine the high-order relationships in the hyperedges without loss of information. In addition, we apply users’ attributes information to calculate the attraction of an item to the attributes, and then get the similarity between items. In order to calculate the similarity more accurately, the relations of items to attributes are divided into two cases: likes and dislikes. Moreover, according to the different attention of users to different items, we introduce the attention mechanism. Finally, we build and optimize the regularization function to obtain the predictive scores and recommendation lists. Experimental results on Movielens-100K and Movielens-1M demonstrate the effectiveness of our proposed algorithm.

关键词： Cloud computing Heuristic algorithms Conferences Collaborative filtering Prediction algorithms Time measurement Intelligent systems

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An efficient privacy preserving data aggregation approach for mobile sensing

An efficient privacy preserving data aggregation approach fo...

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作者： Zhang, Lichen Wang, Xiaoming Lu, Junling Li, Peng Cai, Zhipeng Ministry of Education Key Laboratory for Modern Teaching Technology Shaanxi Normal University Xi'an710119 China School of Computer Science Shaanxi Normal University Xi'an710119 China Department of Computer Science Geogia State University Atlanta30303 Afghanistan

The advances in sensing capabilities of smartphones give rise to a variety of mobile participatory sensing applications that collect users' personal data. Because of the existence of both sensitive, private personal data, and untrusted aggregator, serious privacy concerns on users arise. Currently, existing privacy preserving data collection methods either require bidirectional communications between an untrusted aggregator and mobile users in every aggregation period, or have high computation or communication overhead. To address these problems, we propose an efficient data aggregation approach by which an untrusted aggregator in mobile sensing can collect the statistics over the data contributed by multiple mobile users, while supporting privacy preservation of each user and data integrity verification. In this approach, information hiding and homomorphic encryption are applied to guarantee the data privacy of mobile users. In detail, a breadth-first search tree is first constructed at the initial phase among the mobile users, and then the original datum of each user is perturbed among its neighbors in ciphertext space by using information hiding and homomorphic encryption. The evaluations of our approach show that our protocol requires lower communication and computation overhead and thus more feasible for the computation constrained mobile devices. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

关键词： Sensitive data

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Image analysis based system for assessing malaria 3rd

Image analysis based system for assessing malaria

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3rd International Conference on Cyberspace Data and Intelligence, Cyber DI 2019, and the International Conference on Cyber-Living, Cyber-Syndrome, and Cyber-Health, CyberLife 2019

作者： Manning, Kyle Zhai, Xiaojun Yu, Wangyang School of Computer Science and Electronic Engineering University of Essex ColchesterCO4 3SQ United Kingdom Key Laboratory of Modern Teaching Technology Ministry of Education School of Computer Science Shaanxi Normal University Xi’an China

ISBN: (纸本)9789811519246

Malaria, a not only widespread but also a potentially fatal disease that can be found mainly in tropical regions of the world, with the World Health Organization reporting an estimated 219 million cases worldwide as of 2017 of which 435,000 were mortal. Diagnosis currently involves taking a blood sample from a patient who is presumed to be infected, which is examined under a microscope by trained experts, although reliable the process is tedious. This disease is an ever-increasing problem thereby creating a need for an automated solution to the diagnosis of malaria. The primary objective of this project is to design a tool that can diagnose malaria from an image of a blood smear that has been stained with the commonly used Giemsa stain (which highlights the parasites in a red blood cell by turning them dark purple). In this paper, we have developed a graphical user interface to assist with the separation of red blood cells and extraction of the cells infected with the malaria parasite as well as an ANN (Artificial Neural Network) for cell classification. The graphical user interface allows the user to analyse the blood sample by running a series of image processing techniques followed by the extraction of infected cells, the results have shown that these techniques could be potentially used to detect malaria. Currently, the achieved results shown that the proposed system has 92% accuracy of a database contains a large number of ground-truth images. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Diagnosis

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Radar Health Management System Based on Multi-agent

Radar Health Management System Based on Multi-agent

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2020 Global Reliability and Prognostics and Health Management, PHM-Shanghai 2020

作者： Zhang, Qixiao Yang, Jianjun Dong, Peng Cai, Yi Department of Management Engineering and Equipment Economics Wuhan430033 China Key Laboratory of Modern Manufacturing Quality Engineering Hubei University of Technology Wuhan430033 China Air Force Early Warning Academy Teaching and Research Support Center Wuhan430019 China

ISBN: (纸本)9781728159454

In order to maintain the operational readiness of radar, the article builds a multi-agent-based radar health management system based on the radar system structure. The system elaborated the three-level structure and work flow of system-component-part, and defined the functions and interrelationships of agents in health management systems at all levels. Based on the extensibility of the agent, the article takes the TR module (part) of the antenna feeder system (component) as an example to implement the function. And it is shown that the health management system is targeted to provide a efficient model for radar system. © 2020 IEEE.

关键词： Multi agent systems

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Detection of social groups in class by affinity propagation

Detection of social groups in class by affinity propagation

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2019 IEEE International Conferences on Ubiquitous Computing and Communications and Data Science and Computational Intelligence and Smart Computing, Networking and Services, IUCC/DSCI/SmartCNS 2019

作者： Wang, Yajie Peng, Qiyang Pei, Zhao Ma, Miao Chen, Yuli Leng, Chengcai Yang, Honghong School of Information Engineering Shaanxi Xueqian Normal University Xi'an China Key Laboratory of Modern Teaching Technology Ministry of Education Xi'an China School of Computer Science Shaanxi Normal University Xi'an China School of Mathematics Northwest University Xi'an China

ISBN: (纸本)9781728152097

The social groups often represent the groups within which are dense connections and between which are sparse connections. The social groups are actually the clusters. In this paper, we propose a simple but powerful method to combine the content and link information of the social network in the class, and analyze the results of different graph clustering algorithms, our experimental result shows that social groups detection by Affinity Propagation algorithm outperforms than the other clustering algorithms. In addition, we analyze the centrality of the detected communities and find the groups detected can significantly help to improve the quality of the teaching and learning. © 2019 IEEE.

关键词： Clustering algorithms

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ERP Evidence for the Effect of Facial Expression on the Attentional Blink

ERP Evidence for the Effect of Facial Expression on the Atte...

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2017 IEEE 国际医学影像物理和工程大会暨第八届中国医学影像物理学术年会

作者： Suqin Lin Yuecui Kan Xuewei Wang Haijun Duan School of Education Shaanxi Normal University Key Laboratory of Modern Teaching Technology Ministry of Education Shaanxi Normal University

***: The major aim of this study was to explore the time course of the effect of emotional valence on attentional blink from ERP experiments. ***: This study examined the temporal characteristics of visual attention towards facial expressions by presenting a rapid serial visual presentation(RSVP) paradigm to undergraduates(n=32, 16 females). Neutral facial stimuli were presented as the first target(T1), and emotional faces(neutral, happy, angry) as the second target(T2). We presented 2 or 6 facial expression pictures between T1 and T2. We mainly analyzed ERP elicited by emotional T2. The epoch for ERP was 1000 ms including a 200 ms prestimulus baseline. In this study, N1, P3 components were measured and analyzed the peak latencies and ***: ANOVAs revealed that response accuracy was significantly affected by lag(p < 0.01) and facial expression(p < 0.01). Subjects performed at the highest accuracy in the angry expressions condition. Angry faces elicited larger N100 amplitudes than happy(p < 0.05) and neutral faces(p < 0.001). P300 amplitudes showed significant main effect at lag(p < 0.01) and facial expression(p < 0.01). ***: Both N1 and P3 components can be modulated by emotion facial expression. In pre-perceptual stage, N1 had a processing bias for angry faces. While P3 further distinguished between facial expression images.

关键词： attentional blink RSVP facial expression time course temporal attention

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Rcovery of student scores based on singular value decomposition

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Journal of Computational Information Systems 2014年第8期10卷 3155-3162页

作者： Liu, Shigang Xin, Xiaomeng Peng, Yali Cao, Han Key Laboratory of Modern Teaching Technology Ministry of Education Xi'an 710062 China School of Computer Science Shaanxi Normal University Xi'an 710062 China

In order to effectively recover the student score data, this paper proposes an iterative singular value decomposition. We take the student score as a matrix which is low rank. When the initial values of missing data are given, the approximate values solved by the singular value decomposition are more close to the real values than the initial ones and replace the initial values. Finally, the real values can obtained after several iterations. Our method takes advantage of all the known data to recover the missing data. At the same time, all the data are treated uniformly. Simulation and real experimental results show that the method can effectively recover the student scores. © 2014 Binary Information Press.

关键词： Students

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