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Symposium on Theory of Modeling and Simulation - DEVS Integrative M and S Symposium, DEVS 2015, Part of the 2015 Spring Simulation Multi-Conference, SpringSim 2015

作者： Sarjoughian, Hessam S. Sundaramoorthi, Savitha Arizona Center for Integrative Modeling and Simulation School of Computing Informatics and Decision Systems Engineering Arizona State University TempeAZ United States

ISBN: (纸本)9781510810600

Many scientific and engineering applications generate data that are well-suited to be studied using time series charts. Two types of time series that define input, output, and state dynamics of DEVS models are piecewise constant and event charts. In this paper, time series capable of displaying both linear and superdense time segments and trajectories are conceptualized and formulated. These lend themselves for visualizing behavior of parallel atomic and coupled DEVS models. The concept of superdense time segments is realized as plug-ins as part of the Eclipse BIRT (Business Intelligence and Reporting Tool) framework. They can receive timebased alphanumerical data sets from external static and dynamic sources, including the DEVS-Suite simulator. As standalone plug-ins, time series can be used to create static plots and used in BIRT reports. These plug-ins are also integrated into the DEVS-Suite simulator where each model component's behavior can be customized and dynamically plotted. Time series charts simplify and complement tabular logging of data sets for developing simulation models that exhibit zero-time transitory state transitions. © 2015 Society for Modeling & Simulation International (SCS).

关键词： Time series

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Dimension reconstruction for visual exploration of subspace clusters in high-dimensional data

Dimension reconstruction for visual exploration of subspace ...

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Pacific (formerly Asia-Pacific APVIS) Visualization Symposium

作者： Fangfang Zhou Juncai Li Wei Huang Ying Zhao Xiaoru Yuan Xing Liang Yang Shi School of Information Science and Engineering Central South University School of Software Central South University Key Laboratory of Machine Perception (Ministry of Education) Peking University Informatics & Decision Systems Engineering Arizona State University

ISBN: (纸本)9781509014521

Subspace-based analysis has increasingly become the preferred method for clustering high-dimensional data. A visually interactive exploration of subspaces and clusters is a cyclic process. Every meaningful discovery will motivate users to re-search subspaces that can provide improved clustering results and reveal the relationships among clusters that can hardly coexist in the original subspaces. However, the combination of dimensions from the original subspaces is not always effective in finding the expected subspaces. In this study, we present an approach that enables users to reconstruct new dimensions from the data projections of subspaces to preserve interesting cluster information. The reconstructed dimensions are included into an analytical workflow with the original dimensions to help users construct target-oriented subspaces which clearly display informative cluster structures. We also provide a visualization tool that assists users in the exploration of subspace clusters by utilizing dimension reconstruction. Several case studies on synthetic and real-world data sets have been performed to prove the effectiveness of our approach. Lastly, further evaluation of the approach has been conducted via expert reviews.

关键词： Data visualization Visualization Clustering algorithms Minerals Data mining Algorithm design and analysis Pipelines

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Hierarchical active transfer learning

Hierarchical active transfer learning

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SIAM International Conference on Data Mining 2015, SDM 2015

作者： Kale, David Ghazvininejad, Marjan Ramakrishna, Anil He, Jingrui Liu, Yan Computer Science Department Viterbi School of Engineering University of Southern California United States School of Computing Informatics and Decision Systems Engineering Arizona State University United States

ISBN: (纸本)9781510811522

We describe a unified active transfer learning framework called Hierarchical Active Transfer Learning (HATL). HATL exploits cluster structure shared between different data domains to perform transfer learning by imputing labels for unlabeled target data and to generate effective label queries during active learning. The resulting framework is flexible enough to perform not only adaptive transfer learning and accelerated active learning but also unsupervised and semi-supervised transfer learning. We derive an intuitive and useful upper bound on HATL's error when used to infer labels for unlabeled target points. We also present results on synthetic data that confirm both intuition and our analysis. Finally, we demonstrate HATL's empirical effectiveness on a benchmark data set for sentiment classification. Copyright © SIAM.

关键词： Classification (of information)

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Network based models and path based features for gene prioritization

Network based models and path based features for gene priori...

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International Conference on Computer Supported Cooperative Work in Design

作者： Yuechang Liu Hanghang Tong Xie Lei Yong Tang School of Computer Science Jiaying University Meizhou Guangdong School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe AZ USA Computer Science Hunter College The City University of New York USA School of Computer Science South China Normal University Guangzhou Guangdong

ISBN: (纸本)9781509019168

Network analysis has been shown to be an effective and cheap way to screen genes that are associated to diseases and chemicals. The identification of features that are used to order potentially related genes is key to do this job. Though many network models and structure based features have been proposed in the literature, they do not perform well enough for such gene prioritization task, especially when the heterogeneity of such networks is taken account. In this paper, a type of heterogeneous network called Generalized Bi-relational Network (GBN) is formalized. A series of path based features on GBN are defined. Though some of the features have been used in other literature, it is the first time to evaluate them in both supervised and unsupervised learning models. The experiment on real chemical-disease-gene networks shows that the features proposed in this paper gain promising performance in both supervised and unsupervised framework.

关键词： Diseases Computational modeling Chemicals Computer science Electronic mail Social network services Bioinformatics

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Modeling programming learning in online discußion forums 7

Modeling programming learning in online discußion forums

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7th International Conference on Computer Supported Education, CSEDU 2015

作者： Hsiao, I-Han School of Computing Informatics and Decision Systems Engineering Arizona State University 699 S. Mill Ave. TempeAZ United States

ISBN: (纸本)9789897581083

In this paper, we modelled constructive engagement activities in an online programming discußion. We built a logistic regreßion model based on the underlined cognitive proceßes in constructive learning activities. The findings supported that there is paßive-proactive behaviour and suggested that detecting constructive content can be a helpful claßifier in discerning relevant information to the users and in turn creating opportunities to optimize learning. The results also confirmed the value of discußion forum content, disregarding the crowd approves or not.

关键词： Data mining

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INSIGHT: A semantic visual analytics for programming discussion forums

INSIGHT: A semantic visual analytics for programming discuss...

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1st International Workshop on Visual Aspects of Learning Analytics, VISLA 2015

作者： Awasthi, Piyush Hsaio, I-Han School of Computing Informatics and Decision Systems Engineering Arizona State University 699 S. Mill Ave. TempeAZ United States

This paper presents INSIGHT, a visual analytics web application, designed to induce & inspire programming language learning from discussion forums. The visual analytics, extracts and displays semantic content from 'Stack Exchange' in a form of bubble chart. The bubbles represent summarized semantic concepts from the forum posts and outlines the concept specificity of each individual post. The discussion forum content are modeled as concepts based on an innovative Topic Facet Modeling algorithm (a probabilistic topic model that assumes all words in single sentence are generated from one topic facet), and aimed to provide better understanding and solicitation of the increasing large volume of discussion content. We hypothesize that by navigating and interacting (browsing, sorting, searching etc.) with the Facets, will enhance learning. A comprehensive system design rationales and preliminary qualitative study are reported in this paper.

关键词： Semantics

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Assessment of communication, teamwork, and engineering motivation in inter-disciplinary projects implemented in an introduction to engineering course 122

Assessment of communication, teamwork, and engineering motiv...

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2015 122nd ASEE Annual Conference and Exposition

作者： Zhu, Haolin Meuth, Ryan J. Arizona State University Ira A. Fulton Schools of Engineering United States Arizona State University School of Computing Informatics and Decision Systems Engineering United States

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Cross-entropy optimization for neuromodulation

Cross-entropy optimization for neuromodulation

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Harleen K. Brar Yunpeng Pan Babak Mahmoudi Evangelos A. Theodorou Autonomous Control and Decision Systems Laboratory at the Daniel Guggenheim School of Aerospace Engineering Georgia Institute of Technology Atlanta GA USA Department of Biomedical Informatics Emory University School of Medicine Atlanta GA USA

ISBN: (纸本)9781457702198

This study presents a reinforcement learning approach for the optimization of the proportional-integral gains of the feedback controller represented in a computational model of epilepsy. The chaotic oscillator model provides a feedback control systems view of the dynamics of an epileptic brain with an internal feedback controller representative of the natural seizure suppression mechanism within the brain circuitry. Normal and pathological brain activity is simulated in this model by adjusting the feedback gain values of the internal controller. With insufficient gains, the internal controller cannot provide enough feedback to the brain dynamics causing an increase in correlation between different brain sites. This increase in synchronization results in the destabilization of the brain dynamics, which is representative of an epileptic seizure. To provide compensation for an insufficient internal controller an external controller is designed using proportional-integral feedback control strategy. A cross-entropy optimization algorithm is applied to the chaotic oscillator network model to learn the optimal feedback gains for the external controller instead of hand-tuning the gains to provide sufficient control to the pathological brain and prevent seizure generation. The correlation between the dynamics of neural activity within different brain sites is calculated for experimental data to show similar dynamics of epileptic neural activity as simulated by the network of chaotic oscillators.

关键词： Oscillators Brain modeling Correlation Couplings Pathology Computational modeling Epilepsy

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Visual commonsense for scene understanding using perception, semantic parsing and reasoning

Visual commonsense for scene understanding using perception,...

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2015 AAAI Spring Symposium

作者： Aditya, Somak Yang, Yezhou Baral, Chitta Fermuller, Cornelia Aloimonos, Yiannis School of Computing Informatics and Decision Systems Engineering Arizona State University United States Department of Computer Science University of Maryland College Park United States

ISBN: (纸本)9781577357087

In this paper we explore the use of visual common-sense knowledge and other kinds of knowledge (such as domain knowledge, background knowledge, linguistic knowledge) for scene understanding. In particular, we combine visual processing with techniques from natural language understanding (especially semantic parsing), common-sense reasoning and knowledge representation and reasoning to improve visual perception to reason about finer aspects of activities. © Copyright 2015, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： Semantics

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Thermodynamics of a time-dependent and dissipative oval billiard: A heat transfer and billiard approach

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Physical Review E 2016年第6期94卷 062211-062211页

作者： Edson D. Leonel Marcus Vinícius Camillo Galia Luiz Antonio Barreiro Diego F. M. Oliveira Center for Complex Networks and Systems Research School of Informatics and Computing Indiana University Bloomington Indiana USA Department of Chemical and Biological Engineering Northwestern University Evanston Illinois 60208 USA and Northwestern Institute on Complex Systems (NICO) Northwestern University Evanston Illinois 60208 USA

We study some statistical properties for the behavior of the average squared velocity—hence the temperature—for an ensemble of classical particles moving in a billiard whose boundary is time dependent. We assume the collisions of the particles with the boundary of the billiard are inelastic, leading the average squared velocity to reach a steady-state dynamics for large enough time. The description of the stationary state is made by using two different approaches: (i) heat transfer motivated by the Fourier law and (ii) billiard dynamics using either numerical simulations and theoretical description.

关键词： Thermodynamics Billiards

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