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arXiv 2020年

作者： Sun, Zemin Liu, Yanheng Wang, Jian Anil, Carie Cao, Dongpu College of Computer Science and Technology Key Laboratory of Symbolic Computation Knowledge Engineering of Ministry of Education Jilin University Changchun130012 China Engineering VIT-AP AmaravatiAndhra Pradesh522237 India College of Engineering Nanjing Agricultural University Nanjing210031 China Waterloo Cognitive Autonomous Driving Lab University of Waterloo N2L 3G1 Canada

—In the era of the Internet of Things (IoT), vehicles and other intelligent components in Intelligent Transportation System (ITS) are connected, forming the Vehicular Networks (VNs) that provide efficient and secure traffic, ubiquitous access to information, and various applications. However, as the number of connected nodes keeps increasing, it is challenging to satisfy various and large amounts of service requests with different Quality of Service (QoS) and security requirements in the highly dynamic VNs. Intelligent nodes in VNs can compete or cooperate for limited network resources so that either an individual or a group objectives can be achieved. Game theory, a theoretical framework designed for strategic interactions among rational decision-makers who faced with scarce resources, can be used to model and analyze individual or group behaviors of communication entities in VNs. This paper primarily surveys the recent advantages of GT used in solving various challenges in VNs. As VNs and GT have been extensively investigate34d, this survey starts with a brief introduction of the basic concept and classification of GT used in VNs. Then, a comprehensive review of applications of GT in VNs is presented, which primarily covers the aspects of QoS and security. Moreover, with the development of fifth-generation (5G) wireless communication, recent contributions of GT to diverse emerging technologies of 5G integrated into VNs are surveyed in this paper. Finally, several key research challenges and possible solutions for applying GT in VNs are outlined. Copyright © 2020, The Authors. All rights reserved.

关键词： Game theory

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BAENET: A Brain Age Estimation Network with 3D Skipping and Outlier Constraint Loss

BAENET: A Brain Age Estimation Network with 3D Skipping and ...

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IEEE International Symposium on Biomedical Imaging

作者： Taiping Qu Yangming Yue Qirui Zhang Cheng Wang Zhiqiang Zhang Guangming Lu Wei Du Xiuli Li Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education College of Computer Science and Technology Jilin University Changchun China Deepwise AI Lab Beijing China Jinling Hospital Medical School of Nanjing University Nanjing Jiangsu China

ISBN: (数字)9781538693308

ISBN: (纸本)9781538693315

The potential pattern changes in brain micro-structure can be used for the brain development assessment in children and adolescents by MRI scans. In this paper, we propose a highly accurate and efficient end-to-end brain age estimation network (BAENET) on T1-weighted MRI images. On the network, 3D skipping and outlier constraint loss are designed to accommodate deeper network and increase the robustness. Besides, we incorporate the neuroimaging domain knowledge into stratified sampling for better generalization ability for datasets with different age distributions, and gender learning for more gender-specific features during modeling. We verify the effectiveness of the proposed method on the public ABIDE2 and ADHD200 benchmark, consisting of 382 and 378 normal children scans respectively. Our BAENET achieves MAE of 1.11 and 1.16, significantly outperforming the best reported methods by 5.1 % and 9.4%.

关键词： Three-dimensional displays Brain modeling Estimation Solid modeling Feature extraction Magnetic resonance imaging Task analysis

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Black-box expectation propagation for Bayesian models

Black-box expectation propagation for Bayesian models

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2018 SIAM International Conference on Data Mining, SDM 2018

作者： Li, Ximing Li, Changchun Chi, Jinjin Ouyang, Jihong Wang, Wenting College of Computer Science and Technology Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University China College of Mathematics Jilin University China

In this paper, we develop a generic black-box expectation propagation (BBEP) algorithm that can be directly applied to Bayesian models without model-specific derivations. BBEP is built on the spirit of using Monte Carlo estimates, where the moment matching step in EP is replaced with Monte Carlo approximations. To avoid high variance, we employ importance sampling for variance reduction and analyze how to find an optimal proposal distribution. We compare BBEP against the state-of-the-art black-box algorithms on both synthetic and real-world data sets. The experimental results indicate that BBEP can reach better predictive performance than baseline algorithms, and even can be on a par with analytical solutions in some settings. © 2018 by SIAM.

关键词： Importance sampling

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Design of vehicle automatic braking systems considering drivers' braking characteristics

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International Journal of Performability engineering 2019年第9期15卷 2338-2345页

作者： Gao, Zhenhai Sun, Tianjun Hassan, MuHammad Wang, Liupu College of Automotive Engineering Jilin University Changchun130022 China College of Computer Science and Technology Jilin University Changchun130012 China Key Laboratory of Symbol Computation Knowledge Engineering of Ministry of Education Jilin University Changchun130012 China Cancer Hospital Attached Xinjiang Medical University Urumqi830000 China Department of Computer Science and Information Technology University of Malakand KP Pakistan

With the rapid development of advanced driver assistance systems (ADAS), an automatic braking system has become increasingly important when faced with complicated traffic. The conventional decision-making method for the braking system is focused on security but lacks consideration of drivers' characteristics, which generates feelings of fear and frustration. We propose an anthropomorphic braking method based on vehicle kinematic characteristics and dynamic theories to improve the original system and eliminate the sense of jerking. Furthermore, on the basis of the traditional time to collision (TTC) algorithm, we consider the random motion of the target vehicle and develop a dynamic time to collision (DTTC) algorithm to meet different drivers' braking requirements. Therefore, in this study, the braking model is optimized by a series of driving simulator and real-vehicle braking tests. Finally, the validity and feasibility of the method are verified through the simulations of different braking modes. © 2019 Totem Publisher, Inc. All rights reserved.

关键词： Advanced driver assistance systems

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computational Prediction of Human Body-Fluid Protein

Computational Prediction of Human Body-Fluid Protein

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IEEE International Conference on Bioinformatics and Biomedicine

作者： Dan Shao Xueteng Cui Lan Huang Kai He Yan Wang Yao Wang Key laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education College of Computer Science and Technology Jilin University College of Computer Science and Technology Changchun University Key laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education College of Computer Science and Technology Jilin University

ISBN: (纸本)9781728118680

Research on body fluid proteomes has led to the discoveries of context-dependent proteomics profiles and numerous novel disease biomarkers. Common challenges remain with current proteomics technologies about how to effectively handle the large variety of protein modifications in those fluids. To this end, computational efforts have shown early successes in identifying biomarker proteins in specific human diseases. In this article, we first reviewed published computational methods on this topic and then presented a new database system and a novel deep learning-based method for predicting body-fluid proteins in 16 types of human fluids. The results show that our new system outperforms existing methods and provides a highly promising tool to facilitate clinical proteomic discovery.

关键词： machine learning protein prediction body-fluid proteome deep learning Machine Learning Database systems Artificial Intelligence proteomics protein modifications Fluid Human Body maladjustment Learning-based method Biological Markers Body Fluids

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A Registration Method for Augmented Reality System Based on Visual SLAM

A Registration Method for Augmented Reality System Based on ...

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International Conference on Electronic engineering and Informatics (EEI)

作者： Zuoming Zhang Man Shu Zixuan Wang Hanwen Wang Xin Wang College of Software Engineering Jilin University Changchun China College of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineer of Ministry of Education Jilin University Changchun China

ISBN: (纸本)9781728140773

In augmented reality, smart devices need to sense their own position in real physical space and complex scene structure to achieve good virtual reality interaction and three-dimensional registration. This paper proposes a technical framework of visual SLAM, which uses VO and BA methods based on feature points to obtain pose, and applies it to the augmented reality system to realize pose estimation, registration, tracking, collision and other effects of intelligent equipment independent of artificial or natural landmarks.

关键词： augmented reality image registration pose estimation robot vision SLAM (robots) augmented reality pose estimation robot vision image registration supersonic low altitude missile Registration

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Design of a Daily Brief Business Report Generator based on Web Scraping with KNN Algorithm 2

Design of a Daily Brief Business Report Generator based on W...

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2nd International Conference on Computer Information Science and Application Technology, CISAT 2019

作者： Lin, Gang Liang, Yanchun Fu, Xiaoyang Chen, Guangshun Cai, Shaocan Zhuhai Laboratory of Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of Education Department of Computer Science and Technology School of Computer Science Zhuhai Guangdong519041 China Department of Computer Science and Technology School of Computer Science Zhuhai College Jilin University Zhuhai Guangdong519041 China

In order to generate a report for an enterprise where there is neither the API supporting from their existing website systems nor the granted database access rights approval, a daily business report generator system based on web scraping with k nearest neighbor (kNN) classification algorithm is proposed in this paper. It covers the web crawler technology that is to access existing website system and extract business data. The kNN algorithm is applied to identify the verification code on the login page, and the brief daily report generating in a spread-sheet style grid. Compared with some OCR engine for image recognition, the system in Python can automatically generate the brief daily business reports by the kNN algorithm, which is better than some library with default training set on validating the verification code. © Published under licence by IOP Publishing Ltd.

关键词： Report generators

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SNB-PPB: Social-network-based-privacy-preserving Broadcast for Vehicular Communications 4

SNB-PPB: Social-network-based-privacy-preserving Broadcast f...

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4th International Conference on Vehicle Technology and Intelligent Transport Systems, VEHITS 2018

作者： Liu, Yanheng Zhu, Haifeng Wang, Jian College of Computer Science and Technology Jilin University Changchun130012 China Key Laboratory of Symbolic Computation Knowledge Engineering of Ministry of Education Jilin University Changchun130012 China

ISBN: (纸本)9789897582936

Internet key Exchange (IKE) can be used in vehicular communications in vehicular ad hoc networks (VANETs), but it requires a stable communication procedure, which is usually difficult to achieve because of the highly dynamic context of a VANET. In this paper, we propose a new method named social-network-based-privacy-preserving broadcast (SNB-PPB) for secure vehicular communications, which can omit the key exchange procedure. It transfers the information of online social networks to offline vehicular communications, dividing messages into different privacy levels and vehicles into different trust levels based on trust relations on social networks. The sender uses attributes on social networks and the message’s privacy level to encrypt messages;only those receivers who satisfy the corresponding trust level can decrypt the broadcast *** the best of our knowledge, this is the first time that social networks have been applied in VANETs to achieve secure vehicular communications and privacy preservation. Our simulation results show that our method enables the sender to decide the amount and percentage of vehicles that can decrypt the received broadcast. Copyright © 2018 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

关键词： Vehicular ad hoc networks

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Model-based diagnosis of incomplete discrete-event system with rough set theory

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Science China(Information Sciences) 2017年第1期60卷 190-200页

作者： Xuena GENG Dantong OUYANG Yonggang ZHANG Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of EducationJilin University College of Computer Science and Technology Jilin University

Fault diagnosis of discrete-event system(DES) is important in the preventing of harmful events in the system. In an ideal situation, the system to be diagnosed is assumed to be complete; however, this assumption is rather restrictive. In this paper, a novel approach, which uses rough set theory as a knowledge extraction tool to deal with diagnosis problems of an incomplete model, is investigated. DESs are presented as information tables and decision tables. Based on the incomplete model and observations, an algorithm called Optimizing Incomplete Model is proposed in this paper in order to obtain the repaired model. Furthermore, a necessary and sufficient condition for a system to be diagnosable is given. In ensuring the diagnosability of a system, we also propose an algorithm to minimize the observable events and reduce the cost of sensor selection.

关键词： model-based diagnosis diagnosability discrete-event system finite state machine rough set theory

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Copy-Paste Detection Based on a SIFT Marked Graph Feature Vector

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Chinese Journal of Electronics 2017年第2期26卷 345-350页

作者： LYU Yingda SHEN Xuanjing CHEN Haipeng College of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University

To detect copy-paste tampering,an improved SIFT(Scale invariant feature transform)-based algorithm was *** angle is defined and a maximum angle-based marked graph is *** marked graph feature vector is provided to each SIFT key point via discrete polar coordinate *** points are matched to detect the copy-paste tampering *** experimental results show that the proposed algorithm can effectively identify and detect the rotated or scaled copy-paste regions,and in comparison with the methods reported previously,it is resistant to postprocessing,such as blurring,Gaussian white noise and JPEG *** proposed algorithm performs better than the existing algorithm to dealing with scaling transformation.

关键词： Copy-paste tampering Image forensics Marked graph Maximum angle

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