Computer Sciences Commons^™

Design Of A Flexible Component Gathering Algorithm For Converting Cell-Based Models To Graph Representations For Use In Evolutionary Search, Marianna Budnikova, Jeffrey W. Habig, Daniel Lobo, Nicolas Cornia, Michael Levin, Tim Andersen

Computer Science Faculty Publications and Presentations

Background

The ability of science to produce experimental data has outpaced the ability to effectively visualize and integrate the data into a conceptual framework that can further higher order understanding. Multidimensional and shape-based observational data of regenerative biology presents a particularly daunting challenge in this regard. Large amounts of data are available in regenerative biology, but little progress has been made in understanding how organisms such as planaria robustly achieve and maintain body form. An example of this kind of data can be found in a new repository (PlanformDB) that encodes descriptions of planaria experiments and morphological outcomes using a …

Flipping The Classroom In An Academic Writing Course, Marion Engin, Senem Donanci

All Works

This article describes a series of video lessons the authors prepared using the iPad application Educreations to teach elements of the academic essay in an English-medium university in the United Arab Emirates. The authors give a brief introduction to the topic, a rationale for flipping the classroom, and provide a step-by-step account of how the academic writing course progressed.

Information Security As A Determinant Of Nation’S Networked Readiness: A Country Level Analysis, Manal Yunis, Madison Ngafeeson, Kai Koong

Conference Papers in Published Proceedings

No abstract provided.

Inference Of Snp-Gene Regulatory Networks By Integrating Gene Expressions And Genetic Perturbations, Dongchul Kim, Jiao Wang, Chunyu Liu, Jean Gao

Computer Science Faculty Publications

In order to elucidate the overall relationships between gene expressions and genetic perturbations, we propose a network inference method to infer gene regulatory network where single nucleotide polymorphism (SNP) is involved as a regulator of genes. In the most of the network inferences named as SNP-gene regulatory network (SGRN) inference, pairs of SNP-gene are given by separately performing expression quantitative trait loci (eQTL) mappings. In this paper, we propose a SGRN inference method without predefined eQTL information assuming a gene is regulated by a single SNP at most. To evaluate the performance, the proposed method was applied to random data …

Effective Detection Of Vulnerable And Malicious Browser Extensions, Hossain Shahriar, Komminist Weldemariam, Mohammad Zulkernine, Thibaud Lutellier

Faculty Articles

Unsafely coded browser extensions can compromise the security of a browser, making them attractive targets for attackers as a primary vehicle for conducting cyber-attacks. Among others, the three factors making vulnerable extensions a high-risk security threat for browsers include: i) the wide popularity of browser extensions, ii) the similarity of browser extensions with web applications, and iii) the high privilege of browser extension scripts. Furthermore, mechanisms that specifically target to mitigate browser extension-related attacks have received less attention as opposed to solutions that have been deployed for common web security problems (such as SQL injection, XSS, logic flaws, client-side vulnerabilities, …

Application Sharing From Mobile Devices With A Collaborative Shared Display, Richard S. Shurtz

Theses and Dissertations

With the increasing ubiquity of smartphones, tablets, and large pixel-rich displays, there are many exciting new possibilities for using these devices for collaborative work. While there already exist hardware and software that support communication and interaction between mobile devices and shared displays, application sharing in these scenarios is still limited and inflexible. We present a new method of application sharing which allows collaborators to download clips or snapshots of each other's applications. These snapshots can be used to re-launch and resume the shared application back to the state it was in when it was shared. We have built a system …

On Non-Cooperative Multiple-Target Tracking With Wireless Sensor Networks, Ye Zhu, A. Vikram, Huirong Fu, Yong Guan

Electrical and Computer Engineering Faculty Publications

In this paper, we propose an approach to track multiple non-cooperative targets with wireless sensor networks. Most existing tracking algorithms can not be directly applied to non-cooperative target tracking because they assume the access to signals from individual targets for tracking by assuming that: 1) there is only one target in a field; 2) signals from different co-operative targets can be differentiated; or 3) interference caused by signals from other targets is negligible because of attenuation. We propose a general approach for tracking non-cooperative targets. The tracking algorithm first separates the aggregate signals from multiple indistinguishable targets via the blind …

Libraries Respond To Mobile Ubiquity: Research And Assessment Of Mobile Device Usage Trends For Academic And Medical Libraries, Megan M. Hurst, Eleanor I. Cook, J. Michael Lindsay, Martha F. Earl

Charleston Library Conference

The authors consider trends in mobile device usage for the Internet as a whole, for EBSCO Discovery Service across all client libraries, and at two specific libraries: Preston Medical Library, serving the University of Tennessee (UT) Graduate School of Medicine and UT Medical Center, and the Joyner Library at East Carolina University, serving students and faculty on the main campus. Librarians at Preston Medical Library conducted a survey to determine which mobile devices, platforms, and apps were used by their patrons in 2012. East Carolina University piloted an iPad and e-reader lending program in 2010–2011. The results of each are …

Outsourceable Two-Party Privacy-Preserving Biometric Authentication, Hu Chun, Yousef Elmehdwi, Feng Li, Prabir Bhattacharya, Wei Jiang

Computer Science Faculty Research & Creative Works

Biometric authentication, a key component for many secure protocols and applications, is a process of authenticating a user by matching her biometric data against a biometric database stored at a server managed by an entity. If there is a match, the user can log into her account or obtain the services provided by the entity. Privacy-preserving biometric authentication (PPBA) considers a situation where the biometric data are kept private during the authentication process. That is the user's biometric data record is never disclosed to the entity, and the data stored in the entity's biometric database are never disclosed to the …

Musical Motif Discovery In Non-Musical Media, Daniel S. Johnson

Theses and Dissertations

Many music composition algorithms attempt to compose music in a particular style. The resulting music is often impressive and indistinguishable from the style of the training data, but it tends to lack significant innovation. In an effort to increase innovation in the selection of pitches and rhythms, we present a system that discovers musical motifs by coupling machine learning techniques with an inspirational component. The inspirational component allows for the discovery of musical motifs that are unlikely to be produced by a generative model, while the machine learning component harnesses innovation. Candidate motifs are extracted from non-musical media such as …

Temporal Information Extraction And Knowledge Base Population, Taylor Cassidy

Dissertations, Theses, and Capstone Projects

Temporal Information Extraction (TIE) from text plays an important role in many Natural Language Processing and Database applications. Many features of the world are time-dependent, and rich temporal knowledge is required for a more complete and precise understanding of the world. In this thesis we address aspects of two core tasks in TIE. First, we provide a new corpus of labeled temporal relations between events and temporal expressions, dense enough to facilitate a change in research directions from relation classification to identification, and present a system designed to address corresponding new challenges. Second, we implement a novel approach for the …

Automated Classification Of Argument Stance In Student Essays: A Linguistically Motivated Approach With An Application For Supporting Argument Summarization, Adam Robert Faulkner

Dissertations, Theses, and Capstone Projects

This study describes a set of document- and sentence-level classification models designed to automate the task of determining the argument stance (for or against) of a student argumentative essay and the task of identifying any arguments in the essay that provide reasons in support of that stance. A suggested application utilizing these models is presented which involves the automated extraction of a single-sentence summary of an argumentative essay. This summary sentence indicates the overall argument stance of the essay from which the sentence was extracted and provides a representative argument in support of that stance.

A novel set …

The Lived Experience Of Young Adult Burn Survivors' Use Of Social Media, Marie S. Giordano

Dissertations, Theses, and Capstone Projects

The purpose of this phenomenological study was to illuminate the meaning of social media use by young adult burn survivors. Five females and four males, aged 20-25, who sustained burns > 25%, were interviewed. Van Manen's (1999) phenomenological methodology provided the framework for this study. The meaning of the context of the lived experience is described in the five essential themes of identity, connectivity, social support, making meaning, and privacy. These young adult burn survivors, having experienced the traumatic effects of a burn during adolescence, use social media as a way of expressing their identity, while being cautious about privacy. Part …

Echolocation: Using Word-Burst Analysis To Rescore Keyword Search Candidates In Low-Resource Languages, Justin Richards

Dissertations, Theses, and Capstone Projects

State of the art technologies for speech recognition are very accurate for heavily studied languages like English. They perform poorly, though, for languages wherein the recorded archives of speech data available to researchers are relatively scant. In the context of these low-resource languages, the task of keyword search within recorded speech is formidable. We demonstrate a method that generates more accurate keyword search results on low-resource languages by studying a pattern not exploited by the speech recognizer. The word-burst, or burstiness, pattern is the tendency for word utterances to appear together in bursts as conversational topics fluctuate. We give evidence …

Cutting Wi-Fi Scan Tax For Smart Devices, Tianxing Li

Dartmouth College Master’s Theses

Today most popular mobile apps and location-based services require near always-on Wi-Fi connectivity (e.g., Skype, Viber, Wi-Fi Finder). The Wi-Fi power drain resulting from frequent Wi-Fi active scans is undermining the battery performance of smart devices and causing users to remove apps or disable important services. We collectively call this the scan tax problem. The main reason for this problem is that the main processor has to be active during Wi-Fi active scans and hence consumes a significant and disproportionate amount of energy during scan periods. We propose a simple and effective architectural change, where the main processor periodically computes …

Bass In Your Face: A Case-Study Exploration Of Networked Culture, Samantha Phyllis Kretmar

Dissertations, Theses, and Capstone Projects

Using dubstep DJ Bassnectar as a case-study example, this thesis explores the impact of social networks and mobile connectivity. As evidenced by Bassnectar's digitally based approach to experiencing, distributing, and consuming music, these developments have contributed to the shift to a new model I describe as Networked Culture.

Figure 1 is a video highlighting the Bassnectar concert experience. Figure 2 is an audio clip illustrating the "drop" in dubstep. Figure 3 is another audio clip demonstrating the dubstep sound. Figure 4 is an image of an Ableton Live sound library. Figure 5 is an image of Ableton Live's functionality. Figure …

Designing A Goal Journaling Application, Kevin Lufkin

Liberal Arts and Engineering Studies

Achieving a personal goal and making a positive change in one’s life can be a difficult and elusive task. Everyday people are creating and setting new goals for themselves, but more often than not these goals are never realized. Motivation, determination, and discipline are all key elements when it comes to accomplishing a goal, but if there is no clear idea as to how to connect the dots from where one is to where one wants to be these important qualities lose their effectiveness.

The applications that exist today largely fit in the realm of goal/task management and planners. This …

Numerical Investigation Of Pyrolysis Gas Blowing Pattern And Thermal Response Using Orthotropic Charring Ablative Material, Haoyue Weng, Alexandre Martin

Mechanical Engineering Faculty Publications

An orthotropic material model is implemented in a three-dimensional material response code, and numerically studied for charring ablative material. Model comparison is performed using an iso-Q sample geometry. The comparison is presented using pyrolysis gas streamlines and time series of temperature at selected virtual thermocouples. Results show that orthotropic permeability affects both pyrolysis gas flow and thermal response, but orthotropic thermal conductivity essentially changes the thermal performance of the material. The effect of orthotropic properties may have practical use such that the material performance can be manipulated by altering the angle of orthotropic orientation.

Numerical Study Of Spallation Phenomenon In An Arc-Jet Environment, Raghava Davuluri, Alexandre Martin

Mechanical Engineering Faculty Publications

The spallation phenomenon might affect the aerodynamic heating rates of re-entry vehicles. To investigate spallation effects, a code is developed to compute the dynamics of spalled particles. The code uses a finite-rate chemistry model to study the chemical interactions of the particles with the flow field. The spallation code is one-way coupled to a CFD solver that models the hypersonic flow field around an ablative sample. Spalled particles behavior is numerically studied for argon and air flow field. The chemistry model is compared with that of Park's model which complies with oxidation and sublimation and shows disagreement for nitridation.

A Constrained, Possibilistic Logical Approach For Software System Survivability Evaluation, Yanjun Zuo

Accountancy Faculty Publications

In this paper, we present a logical framework to facilitate users in assessing a software system in terms of the required survivability features. Survivability evaluation is essential in linking foreign software components to an existing system or obtaining software systems from external sources. It is important to make sure that any foreign components/systems will not compromise the current system’s survivability properties. Given the increasing large scope and complexity of modern software systems, there is a need for an evaluation framework to accommodate uncertain, vague, or even ill-known knowledge for a robust evaluation based on multi-dimensional criteria. Our framework incorporates user-defined …

How To Assign Weights To Different Factors In Vulnerability Analysis: Towards A Justification Of A Heuristic Technique, Beverly Rivera, Irbis Gallegos, Vladik Kreinovich

Departmental Technical Reports (CS)

The main objective of vulnerability analysis is to select the alternative which is the least vulnerable. To make this selection, we must describe the vulnerability of each alternative by a single number -- then we will select the alternative with the smallest value of this vulnerability index. Usually, there are many aspects of vulnerability: vulnerability of a certain asset to a storm, to a terrorist attack, to hackers' attack, etc. For each aspect, we can usually gauge the corresponding vulnerability, the difficulty is how to combine these partial vulnerabilities into a single weighted value. In our previous research, we proposed …

Dealing With Uncertainties In Computing: From Probabilistic And Interval Uncertainty To Combination Of Different Types Of Uncertainty, Vladik Kreinovich

Departmental Technical Reports (CS)

To predict values of future quantities, we apply algorithms to the current and past measurement results. Because of the measurement errors and model inaccuracy, the resulting estimates are, in general, different from the desired values of the corresponding quantities. There exist methods for estimating this difference, but these methods have been mainly developed for the two extreme cases: the case when we know the exact probability distributions of all the measurement errors and the interval case, when we only know the bounds on the measurement errors. In practice, we often have some partial information about the probability distributions which goes …

R-Bounded Fuzzy Measures Are Equivalent To Epsilon-Possibility Measures, Karen A. Richart-Ruiz, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Traditional probabilistic description of uncertainty is based on additive probability measures. To describe non-probabilistic uncertainty, it is therefore reasonable to consider non-additive measures. An important class of non-additive measures are possibility measures, for which m(A union B) = max(m(A), m(B)). In this paper, we show that possibility measures are, in some sense, universal approximators: for every epsilon > 0, every non-additive measure which satisfies a certain reasonable boundedness property is equivalent to a measure which is epsilon-close to a possibility measure.

How To Estimate Relative Spatial Resolution Of Different Maps Or Images Of The Same Area?, Christian Servin, A A. Velasco, Vladik Kreinovich

Departmental Technical Reports (CS)

In this paper, we describe how to estimate relative spatial resolution of different maps or images of the same area under uncertainty. We consider probabilistic and fuzzy approaches and we show that both approaches lead to the same estimates -- which makes us more confident that this joint result is reasonable.

Shared Roots: Regularizing Deep Neural Networks Through Multitask Learning, Piotr Teterwak

Dartmouth College Undergraduate Theses

In this paper, we propose to regularize deep neural nets with a new type of multitask learning where the auxiliary task is formed by agglomerating classes into super-classes. As such, it is possible to jointly train the network on the class-based classification problem AND super-class based classification problem. We study this in settings where the training set is small and show that , concurrently with a regularization scheme of randomly reinitializing weights in deeper layers, this leads to competitive results on the ImageNet and Caltech-256 datasets and state-of-the-art results on CIFAR-100.

Active Learning With Efficient Feature Weighting Methods For Improving Data Quality And Classification Accuracy, Justin Martineau, Lu Chen, Doreen Cheng, Amit P. Sheth

Kno.e.sis Publications

Many machine learning datasets are noisy with a substantial number of mislabeled instances. This noise yields sub-optimal classification performance. In this paper we study a large, low quality annotated dataset, created quickly and cheaply using Amazon Mechanical Turk to crowdsource annotations. We describe computationally cheap feature weighting techniques and a novel non-linear distribution spreading algorithm that can be used to iteratively and interactively correcting mislabeled instances to significantly improve annotation quality at low cost. Eight different emotion extraction experiments on Twitter data demonstrate that our approach is just as effective as more computationally expensive techniques. Our techniques save a considerable …

Semantic Modelling Of Smart City Data, Stefan Bischof, Athanasios Karapantelakis, Cosmin-Septimiu Nechifor, Amit P. Sheth, Alessandra Mileo, Payam Barnaghi

Kno.e.sis Publications

Cities present an opportunity for rendering Web of Things-enabled services. According to the World Health Organization, population in cities will double by the middle of this century, while cities deal with increasingly pressing issues such as environmental sustainability, economic growth and citizen mobility. In this paper, we propose a discussion around the need for common semantic descriptions for smart city data to facilitate future services in "smart cities". We present examples of data that can be collected from cities, discuss issues around this data and put forward some preliminary thoughts for creating a semantic description model to describe and help …

New A*Star-Smu Centre Combines High-Powered Computing And Behavioural Sciences To Study People-Centric Issues, Singapore Management University

SMU Press Releases and News

The Agency for Science, Technology and Research (A*STAR) and the Singapore Management University (SMU) will establish a Centre for Technology and Social-Behavioural Insights (CTSBI) to tap on high performance computing technology, big data analytics and behavioural sciences to study people-centric issues and human behaviour including how people think, feel and act in different settings. Such information can be used to enhance planning and address issues in different areas such as retail, logistics, urban planning, education and community development.

Games People Play: Exploring Depaul's Top-Rated Computer Game Development Program

DePaul Magazine

In March 2014, the Princeton Review, in conjunction with PC Gamer magazine, named the top 25 schools to study game design in the United States and Canada. DePaul's undergraduate program ranked 20th, a considerable leap from 2013’s honorable mention. The graduate program came in at 12th. DePaul's strong ranking reflects the game development program's extension of its basic game development, software engineering and programming to include art, design and storytelling, as well as computer graphics technology, networking, artificial intelligence and human-computer interaction. Examples of the award-winning games developed by students and now marketed by such going concerns as Sony PlayStation …

Pre-R: Making Health Care Healthier, Grant Ramil, Mark Corpuz, Eliot Mestre, Akshay Rangnekar, Alex Lin

Computer Engineering

The Pre-R project provides a central database of medical service fees offered by hospitals across the United States. The database is crowdsourced and all data points are provided by end users or by hospital providers themselves. The fees are searchable through a website (www.pre-r.com) and iOS and Android applications. The mobile applications also provide a way for users to capture a picture of any medical bill and upload it for analysis and entry to our database.