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8th International Conference on Decision and Game Theory for Security, GameSec 2017

作者： Tosh, Deepak K. Vakilinia, Iman Shetty, Sachin Sengupta, Shamik Kamhoua, Charles A. Njilla, Laurent Kwiat, Kevin Department of Computer Science Norfolk State University NorfolkVA United States Department of Computer Science and Engineering University of Nevada RenoNV United States Virginia Modeling Analysis and Simulation Center Old Dominion University NorfolkVA United States Network Security Branch Army Research Laboratory AdelphiMD United States Cyber Assurance Branch Air Force Research Laboratory RomeNY United States

ISBN: (纸本)9783319687100

Cyber-threat landscape has become highly complex, due to which isolated attempts to understand, detect, and resolve cybersecurity issues are not feasible in making a time constrained decisions. Introduction of cyber-threat information (CTI) sharing has potential to handle this issue to some extent, where knowledge about security incidents is gathered, exchanged across organizations for deriving useful information regarding the threat actors and vulnerabilities. Although, sharing security information could allow organizations to make informed decision, it may not completely eliminate the risks. Therefore, organizations are also inclined toward considering cyber-insurance for transferring risks to the insurers. Also, in networked environment, adversaries may exploit the information sharing to successfully breach the participating organizations. In this paper, we consider these players, i.e. organizations, adversary, and insure, to model a three layer game, where players play sequentially to find out their optimal strategies. Organizations determine their optimal self-defense investment to make while participating in CTI sharing and cyber-insurance. The adversary looks for an optimal attack rate while the insurer targets to maximize its profit by offering suitable coverage level to the organizations. Using backward induction approach, we conduct subgame perfect equilibrium analysis to find optimal strategies for the involved players. We observe that when cyber-insurance is not considered, attacker prefers to increase its rate of attack. This motivates the organizations to consider cyber-insurance option for transferring the risks on their critical assets. © 2017, Springer International Publishing AG.

关键词： Game theory

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Discovering and visualizing underlying tra-c regions from vehicle trajectories withmulti-features

Discovering and visualizing underlying tra-c regions from ve...

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Video Surveillance and Transportation Imaging Applications 2016

作者： Yu, Dongjin Wang, Ruiting Wang, Jiaojiao Li, Wanqing College of Computer Hangzhou Dianzi University Hangzhou China Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education China

City traffic often exhibits regional characteristics, such as large trucks frequently appearing in the suburbs, and the paths to playgrounds on weekends generally being congested. Discovering and visualizing these hidden traffic regions inside which roads share similar characteristics of traffic conditions simplifies the modeling complexities of whole city traffic conditions and therefore contributes significantly toward city planning. Unfortunately, such traffic regions always have irregular shapes and are time varying, which makes their discovery extremely complicated. In addition, establishing a method to visualize and explore the traffic regions interactively still remains challenging. In this article, the authors propose a latent Dirichlet allocation (LDA)-based approach to the discovery of underlying traffic regions (or region topics) from vehicle trajectories captured by surveillance devices installed along roadsides. They treat vehicle trajectories as documents and the values of different traffic features, such as locations, directions, speeds and vehicle types, as the corresponding words. After applying the LDA model, they obtain a list of region topics with combined feature values, in which the different feature values are clustered with probabilistic assignments. Meanwhile, they build a prototype system to explore the surveillance-device-based vehicle trajectories according to the discovered region topics. The prototype system, which consists of map view, cloud view, treemap view and matrix-table view, visualizes the feature values of hidden traffic regions. The authors finally research a real case based on the traffic data in Wenzhou City, a large city in eastern China with a population of more than nine million. They investigate approximately 157 surveillance devices and 750,000 moving vehicles. The case demonstrates the effectiveness of both their proposed approach and the prototype system. © 2016 Society for Imaging Science and Technology.

关键词： Population statistics

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Using density peaks sentence clustering for update summary generation

Using density peaks sentence clustering for update summary g...

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2016 IEEE Canadian Conference on Electrical and computer Engineering, CCECE 2016

作者： Wu, Guohua Guo, Yutian Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education School of Computer Science and Technology Hangzhou Dianzi University China

ISBN: (纸本)9781467387217

Update summarization can be a daunting task in automatic text summarization. It aims to distill evolved messages from a collection of new articles, under the assumption that the reader has already browsed the previous articles. In this paper, a number of state-of-the-art approaches were reviewed for extracting update summarization and then a method called DPC-TS was proposed. This approach is derived from the DPC-based multi-documents summarization method, which was developed in 2015. In our study, a model was established by using the topic signature algorithm, to evaluate the novelty of sentences in update documents set. In addition, the scheme of calculating similarities between sentences and sentence selection approach was improved to ensure there are diversity topics in the summary. DPC-TS update documents summarization method is a simple and effective approach, which can be reproduced and deployed in real environment. © 2016 IEEE.

关键词： update summarization DPC topic signature dedicated physical channel signature algorithm Novelty Adjudication peaks

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Privacy Setting Recommendation for Image Sharing

Privacy Setting Recommendation for Image Sharing

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International Conference on Machine Learning and Applications (ICMLA)

作者： Jun Yu Zhenzhong Kuang Zhou Yu Dan Lin Jianping Fan Key Laboratory of Complex Systems Modeling and Simulation Hangzhou Dianzi University Hangzhou China Dept. of Computer Science Missouri University of S & T Rolla MO USA Dept. of Computer Science UNC-Charlotte Charlotte NC USA

This paper aims to simultaneously consider two inseparable issues for privacy setting recommendation: (1) sensitiveness of visual content of the images being shared; and (2) trustworthiness of users being granted. First, an object-based approach is developed for image content sensitiveness (privacy) representation. Secondly, the users on a social network are clustered into a set of representative social groups to generate a discriminative dictionary for user trustworthiness characterization. Finally, a tree classifier is trained hierarchically to recommend appropriate privacy settings for image sharing.

关键词： Privacy Social groups Visualization Object recognition Social network services Dictionaries Training

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Nonlocal and Gradient Theories of Piezoelectric Nanoplates

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Procedia Engineering 2017年 190卷 178-185页

作者： Jan Sladek Vladimir Sladek Jozef Kasala Ernian Pan Institute of Construction and Architecture Slovak Academy of Sciences 84503 Bratislava Slovakia Faculty of Special Technology Alexander Dubcek University of Trencin 91150 Trencin Slovakia Computer Modeling and Simulation Group Department of Civil Engineering University of Akron Akron OH 44325-3905 USA

Classical continuum models are unable to describe the size effect in nano/micro structures, even though this effect is observed experimentally. Therefore, modified continuum models are frequently applied for the investigation of nanomechanics due to their computational efficiency and capability of providing accurate results which are comparable to the atomistic models. In this paper, the Mindlin plate is extended to the piezoelectric nanoplate with nonlocal and gradient theories for size effect. The governing equations for bending moments, normal and shear stresses are derived via the Hamilton‘s principle. Differences between the two theories are described.

关键词： Nonlocal gradient elasticity Mindlin plate Hamilton‘s principle size effect

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Multi-modal factorized bilinear pooling with co-attention learning for visual question answering

arXiv

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arXiv 2017年

作者： Yu, Zhou Yu, Jun Fan, Jianping Tao, Dacheng Key Laboratory of Complex Systems Modeling and Simulation School of Computer Science and Technology Hangzhou Dianzi University China Department of Computer Science University of North Carolina Charlotte United States UBTECH Sydney AI Centre School of IT FEIT University of Sydney Australia

Visual question answering (VQA) is challenging because it requires a simultaneous understanding of both the visual content of images and the textual content of questions. The approaches used to represent the images and questions in a fine-grained manner and questions and to fuse these multimodal features play key roles in performance. Bilinear pooling based models have been shown to outperform traditional linear models for VQA, but their high-dimensional representations and high computational complexity may seriously limit their applicability in practice. For multimodal feature fusion, here we develop a Multi-modal Factorized Bilinear (MFB) pooling approach to efficiently and effectively combine multi-modal features, which results in superior performance for VQA compared with other bilinear pooling approaches. For fine-grained image and question representation, we develop a 'co-attention' mechanism using an end-to-end deep network architecture to jointly learn both the image and question attentions. Combining the proposed MFB approach with co-attention learning in a new network architecture provides a unified model for VQA. Our experimental results demonstrate that the single MFB with co-attention model achieves new state-of-theart performance on the real-world VQA dataset. Code available at https://***/yuzcccc/mfb. Copyright © 2017, The Authors. All rights reserved.

关键词： Network architecture

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Multivariate Covariance using Principal Component Analysis for Reconstruction of Bidirected Gene Regulatory Networks

Multivariate Covariance using Principal Component Analysis f...

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Frontiers of Information Technology (FIT)

作者： Mehrosh Khalid Sharifullah Khan Jamil Ahmad Muhammad Shaheryar School of Electrical Engineering and Computer Science (SEECS) National University of Sciences and Technology (NUST) Islamabad Pakistan Research Center for Modeling and Simulation (RCMS) National University of Sciences and Technology Islamabad Pakistan Department of Computer Science Capital University of Science and Technology (CUST) Islamabad Pakistan

Gene Regulatory Networks (GRNs) visualize the dynamic behavior of genetic components and their complex interactions. Reconstructing GRNs from gene expression data is in practice using multiple approaches. These approaches result in symmetrical and diagonal gene interaction matrices. However, they cannot predict all kinds of regulatory network motifs between gene pairs, such as activation, inhibition and self regulations. The proposed approach applies multivariate covariances and Principal Component Analysis (PCA) to identify asymmetric and non-diagonal gene interactions. The proposed approach generated bidirected GRNs holding all kinds of regulatory interactions. Moreover, the identified gene regulatory interactions have been verified from the literature.

关键词： Gene expression Covariance matrices Symmetric matrices Principal component analysis Reverse engineering Proteins

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High-performance flow visualization for effective data analysis

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Journal of Flow Visualization and Image Processing 2016年第1-2期23卷 41-57页

作者： Liu, Zhanping Moorhead, Robert J. Department of Modeling Simulation and Visualization Engineering Old Dominion University ODU-MSVE 1300 ECSB 4700 Elkhorn Avenue NorfolkVA23529 United States Department of Electrical and Computer Engineering Mississippi State University United States

As data grows at exponential rates toward exa-scale (1018) computing, it is necessary to exploit scientific visualization in the form of a visual, informative, and interactive methodology to help resolve daunting problems arising from a wide variety of disciplines that involve big data analysis. While novel visualization algorithms are investigated for effective as well as efficient exploration of surface and volume flows, there are signs of revisiting sparse geometry-based methods with further improvement, back from dense texture-based approaches, and resorting to parallel visualization. This paper presents our innovative research along this path in high-performance visualization of flow data for exploration, recognition, representation, and analysis of overall patt erns and salient features, with techniques from texture-based to geometry-based, flows from 2D to 3D, complexity from steady to unsteady, and computing from serial to parallel. Specifically, a high-level description is primarily focused on four algorithms, i.e., accelerated unsteady flow line integral convolution, its extension to time-varying volume flows, advanced evenly spaced streamline placement, and interactive view-driven evenly spaced streamline placement. Also introduced are four systems, i.e., ActiveLIC, ActiveIBFV, ActiveFLOVE, and DOXIV, which we developed for high-performance flow visualization coupled with applications to demonstrate the practical applicability. © 2016 by Begell House, Inc.

关键词： Data visualization

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Synthesizing and visualizing symmetric flows

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Journal of Flow Visualization and Image Processing 2016年第3-4期23卷 253-273页

There are frequent user studies in flow visualization for comparing different algorithms in the effectiveness. While much work is focused on statistical analysis of the collected results, considerable bias arising from both flow data and task design is seldom addressed, compromising and even invalidating the subsequent conclusion. This paper presents topology-based synthesis of symmetric flows for explicit data generation, which then facilitates implicit task design, so as to enable convincing user studies. This method can produce a large number of (x-/y-/center-)symmetric flows with different structures but with nearly the same degree of topological complexity, and geometrically symmetric yet topologically asymmetric flows. The wide variety of topological constitution requires local + global visual perception, comprehensive feature recognition, and discreet pattern classification to gain a proper understanding of such symmetric and asymmetric flows. To visualize these flows, we propose to use a set of representative techniques including sparse geometry-based methods (i.e., arrow plots and evenly spaced streamlines) and dense texture-based approaches (i.e., three variants of line integral convolution) coupled with two color map schemes (i.e., rainbow band and color wheel). This selection, out of a broad range of candidate techniques, is based on thorough investigation of the working mechanisms, in-depth analysis of perceptual factors, and extensive observation of the advances in flow visualization. Thus, the rationale helps identify strengths and weaknesses of the existing flow visualization methods and provides hints for designing new effective algorithms. © 2016 by Begell House, Inc.

关键词： Flow visualization

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Autonomous Navigation for an Unmanned Aerial Vehicle by the Decomposition Coordination Method 4

Autonomous Navigation for an Unmanned Aerial Vehicle by the ...

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International Conference on Electrical Engineering, computer Science and Informatics

作者： Chaimaa Jihane Hala El Ouarrak Mohamed Mestari Mostafa Rachik Laboratory of Signals Distributed Systems and Artificial Intelligence (SSDIA) Ecole Normale Suprieure d'Enseignement Technique Mohammedia Av Hassan II Mohammedia Morocco Department of Mathematics and Computer Sciences Laboratory of Analysis Modeling and Simulation (LAMS) Faculty of Science Ben M'Sik Av Driss El Harti B.P 7955 Sidi Othmane Casablanca Morocco

ISBN: (纸本)9781538605509;9781538605493

This paper introduces a new approach for solving the navigation problem of Unmanned Aerial Vehicles (UAV) by studying its rotational and translational dynamics and then solving the nonlinear model by the Decomposition Coordination method. The objective is to reach a destination goal by the mean of an autonomous computed optimal path calculated through optimal control sequence. Solving such complex systems often requires a great amount of computation. However, the approach considered herein is based on the Decomposition Coordination principle, which allows the nonlinearity to be treated at a local level, thus offering a low computing time. The stability of the method is discussed with sufficient conditions for convergence. A numerical application is given in consolidation the theoretical results.

关键词： considered herein Decomposition theoretical

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