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2014

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Articles 181 - 210 of 1965

Full-Text Articles in Computer Sciences

A New Transfer Impedance Based System Equivalent Model For Voltage Stability Analysis, Yang Wang, Caisheng Wang, Feng Lin, Wenyuan Li, Le Yi Wang, Junhui Zhao Nov 2014

A New Transfer Impedance Based System Equivalent Model For Voltage Stability Analysis, Yang Wang, Caisheng Wang, Feng Lin, Wenyuan Li, Le Yi Wang, Junhui Zhao

Electrical & Computer Engineering and Computer Science Faculty Publications

This paper presents a new transfer impedance based system equivalent model (TISEM) for voltage stability analysis. The TISEM can be used not only to identify the weakest nodes (buses) and system voltage stability, but also to calculate the amount of real and reactive power transferred from the generator nodes to the vulnerable node causing voltage instability. As a result, a full-scale view of voltage stability of the whole system can be presented in front of system operators. This useful information can help operators take proper actions to avoid voltage collapse. The feasibility and effectiveness of the TISEM are further validated …

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Feasibility Of Scalable Quantum Computers, Benjamin N. Goodberry Nov 2014

Feasibility Of Scalable Quantum Computers, Benjamin N. Goodberry

Selected Honors Theses

No abstract provided.

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A Privacy Risk Scoring Framework For Mobile, Jedidiah Spencer Montgomery Nov 2014

A Privacy Risk Scoring Framework For Mobile, Jedidiah Spencer Montgomery

Theses and Dissertations

Protecting personal privacy has become an increasingly important issue as computers become a more integral part of everyday life. As people begin to trust more personal information to be contained in computers they will question if that information is safe from unwanted intrusion and access. With the rise of mobile devices (e.g., smartphones, tablets, wearable technology) users have enjoyed the convenience and availability of stored personal information in mobile devices, both in the operating system and within applications.For a mobile application to function correctly it needs permission or privileges to access and control various resources and controls on the mobile …

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Cubic Spline Interpolation By Solving A Recurrence Equation Instead Of A Tridiagonal Matrix, Peter Revesz Nov 2014

Cubic Spline Interpolation By Solving A Recurrence Equation Instead Of A Tridiagonal Matrix, Peter Revesz

School of Computing: Conference and Workshop Papers

The cubic spline interpolation method is proba- bly the most widely-used polynomial interpolation method for functions of one variable. However, the cubic spline method requires solving a tridiagonal matrix-vector equation with an O(n) computational time complexity where n is the number of data measurements. Even an O(n) time complexity may be too much in some time-ciritical applications, such as continuously estimating and updating the flight paths of moving objects. This paper shows that under certain boundary conditions the tridiagonal matrix solving step of the cubic spline method could be entirely eliminated and instead the coefficients of the unknown cubic polynomials …

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An Analysis Of Mayo Clinic Search Query Logs For Cardiovascular Diseases, Ashutosh Sopan Jadhav, Amit P. Sheth, Jyotishman Pathak Nov 2014

An Analysis Of Mayo Clinic Search Query Logs For Cardiovascular Diseases, Ashutosh Sopan Jadhav, Amit P. Sheth, Jyotishman Pathak

Kno.e.sis Publications

Increasingly, individuals are taking active participation in learning and managing their health by leveraging online resources. Understanding online health information searching behavior can help us to study what health topics users search for and how search queries are formulated. In this work, we analyzed 10 million cardiovascular diseases (CVD) related search queries from MayoClinic.com. We performed semantic analysis on the queries using UMLS MetaMap and analyzed structural and textual properties as well as linguistic characteristics of the queries.

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Combining Multiple Kernel Methods On Riemannian Manifold For Emotion Recognition In The Wild, M. Liu, R. Wang, S. Li, S. Shan, Zhiwu Huang, X. Chen Nov 2014

Combining Multiple Kernel Methods On Riemannian Manifold For Emotion Recognition In The Wild, M. Liu, R. Wang, S. Li, S. Shan, Zhiwu Huang, X. Chen

Research Collection School Of Computing and Information Systems

In this paper, we present the method for our submission to the Emotion Recognition in the Wild Challenge (EmotiW 2014). The challenge is to automatically classify the emotions acted by human subjects in video clips under realworld environment. In our method, each video clip can be represented by three types of image set models (i.e. linear subspace, covariance matrix, and Gaussian distribution) respectively, which can all be viewed as points residing on some Riemannian manifolds. Then different Riemannian kernels are employed on these set models correspondingly for similarity/distance measurement. For classification, three types of classifiers, i.e. kernel SVM, logistic regression, …

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Scalable Visual Instance Mining With Threads Of Features, Wei Zhang, Hongzhi Li, Chong-Wah Ngo, Shih-Fu Chang Nov 2014

Scalable Visual Instance Mining With Threads Of Features, Wei Zhang, Hongzhi Li, Chong-Wah Ngo, Shih-Fu Chang

Research Collection School Of Computing and Information Systems

We address the problem of visual instance mining, which is to extract frequently appearing visual instances automatically from a multimedia collection. We propose a scalable mining method by exploiting Thread of Features (ToF). Specifically, ToF, a compact representation that links consistent features across images, is extracted to reduce noises, discover patterns, and speed up processing. Various instances, especially small ones, can be discovered by exploiting correlated ToFs. Our approach is significantly more effective than other methods in mining small instances. At the same time, it is also more efficient by requiring much fewer hash tables. We compared with several state-of-the-art …

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Click-Through-Based Subspace Learning For Image Search, Yingwei Pan, Ting Yao, Xinmei Tian, Houqiang Li, Chong-Wah Ngo Nov 2014

Click-Through-Based Subspace Learning For Image Search, Yingwei Pan, Ting Yao, Xinmei Tian, Houqiang Li, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

One of the fundamental problems in image search is to rank image documents according to a given textual query. We address two limitations of the existing image search engines in this paper. First, there is no straightforward way of comparing textual keywords with visual image content. Image search engines therefore highly depend on the surrounding texts, which are often noisy or too few to accurately describe the image content. Second, ranking functions are trained on query-image pairs labeled by human labelers, making the annotation intellectually expensive and thus cannot be scaled up. We demonstrate that the above two fundamental challenges …

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Linguistic Analysis Of Toxic Behavior In An Online Video Game, Haewoon Kwak, Telefonica Nov 2014

Linguistic Analysis Of Toxic Behavior In An Online Video Game, Haewoon Kwak, Telefonica

Research Collection School Of Computing and Information Systems

In this paper we explore the linguistic components of toxic behavior by using crowdsourced data from over 590 thousand cases of accused toxic players in a popular match-based competition game, League of Legends. We perform a series of linguistic analyses to gain a deeper understanding of the role communication plays in the expression of toxic behavior. We characterize linguistic behavior of toxic players and compare it with that of typical players in an online competition game. We also find empirical support describing how a player transitions from typical to toxic behavior. Our findings can be helpful to automatically detect and …

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Web Application Vulnerability Prediction Using Hybrid Program Analysis And Machine Learning, Lwin Khin Shar, Lionel Briand, Hee Beng Kuan Tan Nov 2014

Web Application Vulnerability Prediction Using Hybrid Program Analysis And Machine Learning, Lwin Khin Shar, Lionel Briand, Hee Beng Kuan Tan

Research Collection School Of Computing and Information Systems

Due to limited time and resources, web software engineers need support in identifying vulnerable code. A practical approach to predicting vulnerable code would enable them to prioritize security auditing efforts. In this paper, we propose using a set of hybrid (staticþdynamic) code attributes that characterize input validation and input sanitization code patterns and are expected to be significant indicators of web application vulnerabilities. Because static and dynamic program analyses complement each other, both techniques are used to extract the proposed attributes in an accurate and scalable way. Current vulnerability prediction techniques rely on the availability of data labeled with vulnerability …

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A Parallel Genetic Algorithm For Tuning Neural Networks, Nathan Chadderdon, Ben Harsha, Steven Bogaerts Nov 2014

A Parallel Genetic Algorithm For Tuning Neural Networks, Nathan Chadderdon, Ben Harsha, Steven Bogaerts

Annual Student Research Poster Session

One challenge in using artificial neural networks is how to determine appropriate parameters for network structure and learning. Often parameters such as learning rate or number of hidden units are set arbitrarily or with a general "intuition" as to what would be most effective. The goal of this project is to use a genetic algorithm to tune a population of neural networks to determine the best structure and parameters. This paper considers a genetic algorithm to tune the number of hidden units, learning rate, momentum, and number of examples viewed per weight update. Experiments and results are discussed for two …

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Ironfox: Securing The Web, Stephen Mcmurtry, William Johnson, Khadija Stewart (Advisor) Nov 2014

Ironfox: Securing The Web, Stephen Mcmurtry, William Johnson, Khadija Stewart (Advisor)

Annual Student Research Poster Session

No abstract provided.

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Correction To “Master Regulators, Regulatory Networks, And Pathways Of Glioblastoma Subtypes”, Serdar Bozdag, Aiguo Li, Mehmet Baysan, Howard A. Fine Nov 2014

Correction To “Master Regulators, Regulatory Networks, And Pathways Of Glioblastoma Subtypes”, Serdar Bozdag, Aiguo Li, Mehmet Baysan, Howard A. Fine

Mathematics, Statistics and Computer Science Faculty Research and Publications

No abstract provided.

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Client/Server Data Synchronization In Ios Development, Dmitry Tumanov Nov 2014

Client/Server Data Synchronization In Ios Development, Dmitry Tumanov

Undergraduate Honors Theses

Electronic gadgets such as touchpads and smartphones are becoming more popular in business and everyday life. The main advantage of mobile devices over personal computers is their portability. Cellular data plans allow Internet access without having permanent access point. There is a number of web-based applications available for gadgets. The primary goal of these apps is to provide their services through constant Internet access. However, it may affect the operation of both devices and applications. The objective of this thesis is to find a better way of client/server data synchronization in iOS development that can reduce the negative consequences of …

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Large-Scale Mechanical Buckle Fold Development And The Initiation Of Tensile Fractures, Andreas Eckert, Peter Connolly, Xiaolong Liu Nov 2014

Large-Scale Mechanical Buckle Fold Development And The Initiation Of Tensile Fractures, Andreas Eckert, Peter Connolly, Xiaolong Liu

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Tensile failure associated with buckle folding is commonly associated to the distribution of outer arc extension but has also been observed on fold limbs. This study investigates whether tensile stresses and associated failure can be explained by the process of buckling under realistic in situ stress conditions. A 2-D plane strain finite element modeling approach is used to study single-layer buckle folds with a Maxwell viscoelastic rheology. A variety of material parameters are considered and their influence on the initiation of tensile stresses during the various stages of deformation is analyzed. It is concluded that the buckling process determines the …

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Using Variations Of Shape And Appearance In Alignment Methods For Classifying Human Actions, Sultan Mohammad Almotairi Nov 2014

Using Variations Of Shape And Appearance In Alignment Methods For Classifying Human Actions, Sultan Mohammad Almotairi

Theses and Dissertations

In this dissertation, we address the problem of recognizing human-action from videos. The recognition aims at recovering action information from the image sequences using different features such as variations of the human shape. Approaches based on such features often use sequence-alignment methods. We propose two novel methods for human-action recognition. We also propose an elliptical-shaped band for the Dynamic Time Warping (DTW) that provides a good compromise between alignment accuracy and computational speed. First, we study the applicability of the pairwise shape-similarity measurements for human-action recognition. Since action can be seen as a sequence of shapes of silhouette poses, there …

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Remarks On Characterizations Of Malinowska And Szynal, Gholamhossein Hamedani, Z. Javanshiri, Mehdi Maadooliat, A. Yazdani Nov 2014

Remarks On Characterizations Of Malinowska And Szynal, Gholamhossein Hamedani, Z. Javanshiri, Mehdi Maadooliat, A. Yazdani

Mathematics, Statistics and Computer Science Faculty Research and Publications

The problem of characterizing a distribution is an important problem which has recently attracted the attention of many researchers. Thus, various characterizations have been established in many different directions. An investigator will be vitally interested to know if their model fits the requirements of a particular distribution. To this end, one will depend on the characterizations of this distribution which provide conditions under which the underlying distribution is indeed that particular distribution. In this work, several characterizations of Malinowska and Szynal (2008) for certain general classes of distributions are revisited and simpler proofs of them are presented. These characterizations are …

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Quantification Of The Statistical Effects Of Spatiotemporal Processing Of Nontask Fmri Data, M. Muge Karaman, Andrew S. Nencka, Iain P. Bruce, Daniel B. Rowe Nov 2014

Quantification Of The Statistical Effects Of Spatiotemporal Processing Of Nontask Fmri Data, M. Muge Karaman, Andrew S. Nencka, Iain P. Bruce, Daniel B. Rowe

Mathematics, Statistics and Computer Science Faculty Research and Publications

Nontask functional magnetic resonance imaging (fMRI) has become one of the most popular noninvasive areas of brain mapping research for neuroscientists. In nontask fMRI, various sources of “noise” corrupt the measured blood oxygenation level-dependent signal. Many studies have aimed to attenuate the noise in reconstructed voxel measurements through spatial and temporal processing operations. While these solutions make the data more “appealing,” many commonly used processing operations induce artificial correlations in the acquired data. As such, it becomes increasingly more difficult to derive the true underlying covariance structure once the data have been processed. As the goal of nontask fMRI studies …

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Localization Of Near-Field Radio Controlled Unintended Emitting Sources In The Presence Of Multipath Fading, Nurbanu Guzey, Hao Xu, Sarangapani Jagannathan Nov 2014

Localization Of Near-Field Radio Controlled Unintended Emitting Sources In The Presence Of Multipath Fading, Nurbanu Guzey, Hao Xu, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

Localization of near-field unintended emitting radio controlled (RC) devices under a multipath environment is considered in this paper using a uniform linear array (ULA). Since received signals are dependent on both angle of arrival (AoA) and distance from the RC devices to the ULA in the near-field scenario, traditional localization schemes based on received signal strength indicator, time difference in arrival, which only estimate either AoA or distance, are unsuitable. Therefore, a novel smooth 2-D multiple signal classification (MUSIC) near-field localization scheme is developed to locate RC devices under a multipath environment with a possible location error of 0.5 m. …

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The Evolution Of Research On Multimedia Travel Guide Search And Recommender Systems, Junge Shen, Zhiyong Cheng, Jialie Shen, Tao Mei, Xinbo Gao Nov 2014

The Evolution Of Research On Multimedia Travel Guide Search And Recommender Systems, Junge Shen, Zhiyong Cheng, Jialie Shen, Tao Mei, Xinbo Gao

Research Collection School Of Computing and Information Systems

The importance of multimedia travel guide search and recommender systems has led to a substantial amount of research spanning different computer science and information system disciplines in recent years. The five core research streams we identify here incorporate a few multimedia computing and information retrieval problems that relate to the alternative perspectives of algorithm design for optimizing search/recommendation quality and different methodological paradigms to assess system performance at large scale. They include (1) query analysis, (2) diversification based on different criteria, (3) ranking and reranking, (4) personalization and (5) evaluation. Based on a comprehensive discussion and analysis of these streams, …

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Deep Learning For Content-Based Image Retrieval: A Comprehensive Study, Ji Wan, Dayong Wang, Steven C. H. Hoi, Pengcheng Wu, Jianke Zhu, Yongdong Zhang, Jintao Li Nov 2014

Deep Learning For Content-Based Image Retrieval: A Comprehensive Study, Ji Wan, Dayong Wang, Steven C. H. Hoi, Pengcheng Wu, Jianke Zhu, Yongdong Zhang, Jintao Li

Research Collection School Of Computing and Information Systems

Learning effective feature representations and similarity measures are crucial to the retrieval performance of a content-based image retrieval (CBIR) system. Despite extensive research efforts for decades, it remains one of the most challenging open problems that considerably hinders the successes of real-world CBIR systems. The key challenge has been attributed to the well-known "semantic gap" issue that exists between low-level image pixels captured by machines and high-level semantic concepts perceived by human. Among various techniques, machine learning has been actively investigated as a possible direction to bridge the semantic gap in the long term. Inspired by recent successes of deep …

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Player Acceptance Of Human Computation Games: An Aesthetic Perspective, Xiaohui Wang, Dion Hoe Lian Goh, Ee Peng Lim, Adrian Wei Liang Vu Nov 2014

Player Acceptance Of Human Computation Games: An Aesthetic Perspective, Xiaohui Wang, Dion Hoe Lian Goh, Ee Peng Lim, Adrian Wei Liang Vu

Research Collection School Of Computing and Information Systems

Human computation games (HCGs) are applications that use games to harness human intelligence to perform computations that cannot be effectively done by software systems alone. Despite their increasing popularity, insufficient research has been conducted to examine the predictors of player acceptance for HCGs. In particular, prior work underlined the important role of game enjoyment in predicting acceptance of entertainment technology without specifying its driving factors. This study views game enjoyment through a taxonomy of aesthetic experiences and examines the effect of aesthetic experience, usability and information quality on player acceptance of HCGs. Results showed that aesthetic experience and usability were …

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Exploiting Geographical Neighborhood Characteristics For Location Recommendation, Yong Liu, Wei Wei, Aixin Sun, Chunyan Miao Nov 2014

Exploiting Geographical Neighborhood Characteristics For Location Recommendation, Yong Liu, Wei Wei, Aixin Sun, Chunyan Miao

Research Collection School Of Computing and Information Systems

Geographical characteristics derived from the historical check-in data have been reported effective in improving location recommendation accuracy. However, previous studies mainly exploit geographical characteristics from a user’s perspective, via modeling the geographical distribution of each individual user’s check-ins. In this paper, we are interested in exploiting geographical characteristics from a location perspective, by modeling the geographical neighborhood of a location. The neighborhood is modeled at two levels: the instance-level neighborhood defined by a few nearest neighbors of the location, and the region-level neighborhood for the geographical region where the location exists. We propose a novel recommendation approach, namely Instance-Region Neighborhood …

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Designing A Bayer Filter With Smooth Hue Transition Interpolation Using The Xilinx System Generator, Zhiqiang Li, Peter Revesz Nov 2014

Designing A Bayer Filter With Smooth Hue Transition Interpolation Using The Xilinx System Generator, Zhiqiang Li, Peter Revesz

School of Computing: Conference and Workshop Papers

This paper describes the design of a Bayer filter with smooth hue transition using the System Generator for DSP. We describe and compare experimentally two different designs, one based on a MATLAB implementation and the other based on a modification of the Bayer filter using bilinear interpolation.

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A Game-Theoretic Analysis Of The Nuclear Non-Proliferation Treaty, Peter Revesz Nov 2014

A Game-Theoretic Analysis Of The Nuclear Non-Proliferation Treaty, Peter Revesz

School of Computing: Conference and Workshop Papers

Although nuclear non-proliferation is an almost universal human desire, in practice, the negotiated treaties appear unable to prevent the steady growth of the number of states that have nuclear weapons. We propose a computational model for understanding the complex issues behind nuclear arms negotiations, the motivations of various states to enter a nuclear weapons program and the ways to diffuse crisis situations.

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Estimating The Flight Path Of Moving Objects Based On Acceleration Data, Peter Revesz Nov 2014

Estimating The Flight Path Of Moving Objects Based On Acceleration Data, Peter Revesz

School of Computing: Conference and Workshop Papers

Inertial navigation is the problem of estimating the flight path of a moving object based on only acceleration measurements. This paper describes and compares two approaches for inertial navigation. Both approaches estimate the flight path of the moving object using cubic spline interpolation, but they find the coefficients of the cubic spline pieces by different methods. The first approach uses a tridiagonal matrix, while the second approach uses recurrence equations. They also require different boundary conditions. While both approaches work in O(n) time where n is the number of given acceleration measurements, the recurrence equation-based method can be easier updated …

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Online Passive Aggressive Active Learning And Its Applications, Jing Lu, Peilin Zhao, Steven C. H. Hoi Nov 2014

Online Passive Aggressive Active Learning And Its Applications, Jing Lu, Peilin Zhao, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

We investigate online active learning techniques for classification tasks in data stream mining applications. Unlike traditional learning approaches (either batch or online learning) that often require to request the class label of each incoming instance, online active learning queries only a subset of informative incoming instances to update the classification model, which aims to maximize classification performance using minimal human labeling effort during the entire online stream data mining task. In this paper, we present a new family of algorithms for online active learning called Passive-Aggressive Active (PAA) learning algorithms by adapting the popular Passive-Aggressive algorithms in an online active …

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Perspectives On Task Ownership In Mobile Operating System Development [Invited Talk], Subhajit Datta Nov 2014

Perspectives On Task Ownership In Mobile Operating System Development [Invited Talk], Subhajit Datta

Research Collection School Of Computing and Information Systems

There can be little contention about Stroustrup's epigrammatic remark: our civilization runs on software. However a caveat is increasingly due, much of the software that runs our civilization, runs on mobile devices today. Mobile operating systems have come to play a preeminent role in the ubiquity and utility of such devices. The development ecosystem of Android - one of the most popular mobile operating systems - presents an interesting context for studying whether and how collaboration dynamics in mobile development differ from conventional software development. In this paper, we examine factors that influence task ownership in Android development. Our results …

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Celelabel: An Interactive System For Annotating Celebrities In Web Videos, Zhineng Chen, Jinfeng Bai, Chong-Wah Ngo, Bailan Feng, Bo Xu Nov 2014

Celelabel: An Interactive System For Annotating Celebrities In Web Videos, Zhineng Chen, Jinfeng Bai, Chong-Wah Ngo, Bailan Feng, Bo Xu

Research Collection School Of Computing and Information Systems

Manual annotation of celebrities in Web videos is an essential task in many people-related Web services. The task, however, poses a significant challenge even to skillful annotators, mainly due to the large quantity of unfamiliar and greatly varied celebrities, and the lack of a customized system for it. This work develops CeleLabel, an interactive system for manually annotating celebrities in the Web video domain. The peculiarity of CeleLabel is to exploit and display multiple types of information that could assist the annotation, including video content, context surrounding and within a video, celebrity images on the Web, and human factors. Using …

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Amulet: A Secure Architecture For Mhealth Applications For Low-Power Wearable Devices, Andrés Molina-Markham, Ronald Peterson, Joseph Skinner, Tianlong Yun, Bhargav Golla, Kevin Freeman, Travis Peters, Jacob Sorber, Ryan Halter, David Kotz Nov 2014

Amulet: A Secure Architecture For Mhealth Applications For Low-Power Wearable Devices, Andrés Molina-Markham, Ronald Peterson, Joseph Skinner, Tianlong Yun, Bhargav Golla, Kevin Freeman, Travis Peters, Jacob Sorber, Ryan Halter, David Kotz

Dartmouth Scholarship

Interest in using mobile technologies for health-related applications (mHealth) has increased. However, none of the available mobile platforms provide the essential properties that are needed by these applications. An mHealth platform must be (i) secure; (ii) provide high availability; and (iii) allow for the deployment of multiple third-party mHealth applications that share access to an individual's devices and data. Smartphones may not be able to provide property (ii) because there are activities and situations in which an individual may not be able to carry them (e.g., while in a contact sport). A low-power wearable device can provide higher availability, remaining …

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