Physical Sciences and Mathematics Commons^™

Learning The Structure Of Gene Regulatory Networks From Time Series Gene Expression Data, Haoni Li, Nan Wang, Ping Gong, Edward J. Perkins, Chaoyang Zhang

Faculty Publications

Background: Dynamic Bayesian Network (DBN) is an approach widely used for reconstruction of gene regulatory networks from time-series microarray data. Its performance in network reconstruction depends on a structure learning algorithm. REVEAL (REVerse Engineering ALgorithm) is one of the algorithms implemented for learning DBN structure and used to reconstruct gene regulatory networks (GRN). However, the two-stage temporal Bayes network (2TBN) structure of DBN that specifies correlation between time slices cannot be obtained by score metrics used in REVEAL.

Methods: In this paper, we study a more sophisticated score function for DBN first proposed by Nir Friedman for stationary …

Multi- Autonomous Vehicle Insertion-Extraction System (Mavies), Jamie C. Macbeth, Manal Habib, Armen Mkrtchyan, Missy Cummings

Computer Science: Faculty Publications

MAVIES (Multi-Autonomous Vehicle Insertion-Extraction System) is the culmination of a year-long multi-stakeholder e ort between UTRC and the Humans and Automation Lab at MIT to design a human inter- face for insertion and extraction missions with multiple UAVs and option- ally piloted rotorcraft. The design process is a successful application of the Hybrid Cognitive Task Analysis (hCTA) process that tracks dozens of tasks, decision-making processes and their associated situation aware- ness requirements to determine the proper allocation of responsibilities between the human operator and the automated mission planner.

This paper discusses the various accomplishments through several phases of a disciplined …

Hyperspectral Data Processing In A High Performance Computing Environment: A Parallel Best Band Selection Algorithm, Stefan Robila, Gerald Busardo

Department of Computer Science Faculty Scholarship and Creative Works

Hyperspectral data are characterized by a richness of information unique among various visual representations of a scene by representing the information in a collection of grayscale images with each image corresponding to a narrow interval in the electromagnetic spectrum. Such detail allows for precise identification of materials in the scene and promises to support advances in imaging beyond the visible range. However, hyperspectral data are considerably large and cumbersome to process and efficient computing solutions based on high performance computing are needed. In this paper we first provide an overview of hyperspectral data and the current state of the art …

Towards Node Cooperation In Mobile Opportunistic Networks, Abderrahmen Mtibaa, Khaled Harras

Computer Science Faculty Works

Mobile devices such as smart-phones and tablets are becoming ubiquitous, with ever increasing communication capabilities. In situations where the necessary infrastructure is unavailable, costly, or overloaded, opportunistically connecting theses devices becomes a challenging area of research. Data is disseminated using nodes that store-carry-and-forward messages across the network. In such networks, node cooperation is fundamental for the message delivery process. Therefore, the lack of node cooperation (e.g., a node may refuse to act as a relay and settle for sending and receiving its own data) causes considerable degradation in the network. In order to ensure node cooperation in such networks, we …

A Perceptual Metric For Photo Retouching, Eric Kee, Hany Farid

Dartmouth Scholarship

In recent years, advertisers and magazine editors have been widely criticized for taking digital photo retouching to an extreme. Impossibly thin, tall, and wrinkle- and blemish-free models are routinely splashed onto billboards, advertisements, and magazine covers. The ubiquity of these unrealistic and highly idealized images has been linked to eating disorders and body image dissatisfaction in men, women, and children. In response, several countries have considered legislating the labeling of retouched photos. We describe a quantitative and perceptually meaningful metric of photo retouching. Photographs are rated on the degree to which they have been digitally altered by explicitly modeling and …

A Speculative Approach To Parallelization In Particle Swarm Optimization, Matthew Gardner, Andrew Mcnabb, Kevin Seppi

Faculty Publications

Particle swarm optimization (PSO) has previously been parallelized primarily by distributing the computation corresponding to particles across multiple processors. In these approaches, the only benefit of additional processors is an increased swarm size. However, in many cases this is not efficient when scaled to very large swarm sizes (on very large clusters). Current methods cannot answer well the question: “How can 1000 processors be fully utilized when 50 or 100 particles is the most efficient swarm size?” In this paper we attempt to answer that question with a speculative approach to the parallelization of PSO that we refer to as …

Drift Detection Using Uncertainty Distribution Divergence, Patrick Lindstrom, Brian Mac Namee, Sarah Jane Delany

Conference papers

Concept drift is believed to be prevalent inmost data gathered from naturally occurring processes andthus warrants research by the machine learning community.There are a myriad of approaches to concept drift handlingwhich have been shown to handle concept drift with varyingdegrees of success.

However, most approaches make the keyassumption that the labelled data will be available at nolabelling cost shortly after classification, an assumption whichis often violated. The high labelling cost in many domainsprovides a strong motivation to reduce the number of labelledinstances required to handle concept drift. Explicit detectionapproaches that do not require labelled instances to detectconcept drift show great …

User Choice Between Traditional And Computerized Methods: An Activity Perspective, Jun Sun

Information Systems Faculty Publications and Presentations

Numerous computerized methods emerge to replace traditional methods in people’s personal, work and social lives, but many are hesitant to make the transition. This study examines the factors that influence human choice between different methods. According to Activity Theory, traditional and computerized methods are both tools that a person uses for a certain task. The situated experiences with various methods shape people’s attitude toward using them later in terms of tool readiness. The understanding leads to hypothesized relationships between user-, method- and task-specific factors and the dependent variable. The results from an empirical study support that method experiences have strong …

A Study Of Correlations Between The Definition And Application Of The Gene Ontology, Yuji Mo

Computer and Electronics Engineering: Dissertations, Theses, and Student Research

When using the Gene Ontology (GO), nucleotide and amino acid sequences are annotated by terms in a structured and controlled vocabulary organized into relational graphs. The usage of the vocabulary (GO terms) in the annotation of these sequences may diverge from the relations defined in the ontology. We measure the consistency of the use of GO terms by comparing GO's defined structure to the terms' application. To do this, we first use synthetic data with different characteristics to understand how these characteristics influence the correlation values determined by various similarity measures. Using these results as a baseline, we found that …

Personality Dimensions And Temperaments Of Engineering Professors And Students – A Survey, Arif Raza, Zaka Ulmustafa, Luiz Fernando Capretz

Electrical and Computer Engineering Publications

This research work aims to study personality profiles and temperaments of Pakistani software engineering professors and students. In this survey we have collected personality profiles of 18 professors and 92 software engineering students. According to the Myers-Briggs Type Indicator (MBTI) instrument, the most prominent personality type among professors as well as among students is a combination of Introversion, Sensing, Thinking, and Judging (ISTJ). The study shows ITs (Introverts and Thinking) and IJs (Introverts and Judging) are the leading temperaments among the professors. About the students’ data, the results of the study indicate SJs (Sensing and Judging) and ISs (Introverts and …

Overview Of Contrast Data Mining As A Field And Preview Of An Upcoming Book, Guozhu Dong, James Bailey

Kno.e.sis Publications

This report provides an overview of the field of contrast data mining and its applications, and offers a preview of an upcoming book on the topic. The importance of contrasting is discussed and a brief survey is given covering the following topics: general definitions and terminology for contrast patterns, representative contrast pattern mining algorithms, applications of contrast mining for fundamental data mining tasks such as classification and clustering, applications of contrast mining in bioinformatics, medicine, blog analysis, image analysis and subgroup mining, results on contrast based dataset similarity measure, and on analyzing item interaction in contrast patterns, and open research …

Mobile Phone Graph Evolution: Findings, Model And Interpretation, Siyuan Liu, Lei Li, Christos Faloutsos, Lionel M. Ni

LARC Research Publications

What are the features of mobile phone graph along the time? How to model these features? What are the interpretation for the evolutional graph generation process? To answer the above challenging problems, we analyze a massive who-call-whom networks as long as a year, gathered from records of two large mobile phone communication networks both with 2 million users and 2 billion of calls. We examine the calling behavior distribution at multiple time scales (e.g. day, week, month and quarter), and find that the distribution is not only skewed with a heavy tail, but also changing at different time scales. How …

Stability And Classification Performance Of Feature Selection Techniques, Huanjing Wang, Taghi Khoshgoftaar, Qianhui Liang

Computer Science Faculty Publications

Feature selection techniques can be evaluated based on either model performance or the stability (robustness) of the technique. The ideal situation is to choose a feature selec- tion technique that is robust to change, while also ensuring that models built with the selected features perform well. One domain where feature selection is especially important is software defect prediction, where large numbers of met- rics collected from previous software projects are used to help engineers focus their efforts on the most faulty mod- ules. This study presents a comprehensive empirical ex- amination of seven filter-based feature ranking techniques (rankers) applied to …

Outlier Detection Using Modified-Ranks And Other Variants, Huaming Huang, Kishan Mehrotra, Chilukuri K. Mohan

Electrical Engineering and Computer Science - Technical Reports

Rank based algorithms provide a promising approach for outlier detection, but currently used rank-based measures of outlier detection suffer from two deficiencies: first they take a large value from an object whose density is high even though the object may not be an outlier and second the distance between the object and its nearest cluster plays a mild role though its rank with respect to its neighbor. To correct for these deficiencies we introduce the concept of modified-rank and propose new algorithms for outlier detection based on this concept.

Computing Inconsistency Measure Based On Paraconsistent Semantics, Pascal Hitzler, Yue Ma, Guilin Qi

Computer Science and Engineering Faculty Publications

Measuring inconsistency in knowledge bases has been recognized as an important problem in several research areas. Many methods have been proposed to solve this problem and a main class of them is based on some kind of paraconsistent semantics. However, existing methods suffer from two limitations: (i) they are mostly restricted to propositional knowledge bases; (ii) very few of them discuss computational aspects of computing inconsistency measures. In this article, we try to solve these two limitations by exploring algorithms for computing an inconsistency measure of first-order knowledge bases. After introducing a four-valued semantics for first-order logic, we define an …

Design And Implementation Of An Open Framework For Ubiquitous Carbon Footprint Calculator Applications, Farzana Rahman, Casey O'Brien, Sheikh Iqbal Ahamed, He Zhang, Lin Liu

Mathematics, Statistics and Computer Science Faculty Research and Publications

As climate change is becoming an important global issue, more and more people are beginning to pay attention to reducing greenhouse gas emissions. To measure personal or household carbon dioxide emission, there are already plenty of carbon footprint calculators available on the web. Most of these calculators use quantitative models to estimate carbon emission caused by a user's activities. Although these calculators can promote public awareness regarding carbon emission due to an individual's behavior, there are concerns about the consistency and transparency of these existing CO₂ calculators. Apart from a small group of smart phone based carbon footprint calculator …

Sensitivity Of The Frozen/Melted Basal Boundary To Perturbations Of Basal Traction And Geothermal Heat Flux : Isunnguata Sermia, Western Greenland, Douglas John Brinkerhoff, Toby Warren Meierbachtol, Jesse Johnson, Joel T. Harper

Computer Science Faculty Publications

A full-stress, thermomechanically coupled, numerical model is used to explore the interaction between basal thermal conditions and motion of a terrestrially terminating section of the west Greenland ice sheet. The model domain is a two-dimensional flowline profile extending from the ice divide to the margin. We use data-assimilation techniques based on the adjoint model in order to optimize the basal traction field, minimizing the difference between modeled and observed surface velocities. We monitor the sensitivity of the frozen/melted boundary (FMB) to changes in prescribed geothermal heat flux and sliding speed by applying perturbations to each of these parameters. The FMB …

Modeling 5 Years Of Subglacial Lake Activity In The Macayeal Ice Stream (Antarctica) Catchment Through Assimilation Of Icesat Laser Altimetry, Sasha P. Carter, Helen A. Fricker, Donald D. Blankenship, Jesse V. Johnson, William Lipscomb, Stephen F. Price, Duncan A. Young

Computer Science Faculty Publications

Subglacial lakes beneath Antarctica’s fast-moving ice streams are known to undergo ~1km³ volume changes on annual timescales. Focusing on the MacAyeal Ice Stream (MacIS) lake system, we create a simple model for the response of subglacial water distribution to lake discharge events through assimilation of lake volume changes estimated from Ice, Cloud and land Elevation Satellite (ICESat) laser altimetry. We construct a steady-state water transport model in which known subglacial lakes are treated as either sinks or sources depending on the ICESat-derived filling or drainingrates. The modeled volume change rates of five large subglacial lakes in the downstream portion …

Assessing The Impact Of Recommendation Agents On On-Line Consumer Unplanned Purchase Behavior, R. Eric Hostler, Victoria Y. Yoon, Zhiling Guo, Tor Guimaraes, Guisseppi Forgionne

Research Collection School Of Computing and Information Systems

Recommendation agents (RAs) have been used by many Internet businesses such as Amazon and Netflix. However, few authors have studied how consumer behavior is affected by those that make suggestions to online consumers based on their recent shopping behavior. Fewer still have examined the role that RAs play in influencing impulse purchasing decisions online. Our study developed a theoretical model to illustrate the impact of RAs on online consumer behavior. The model was tested through an online shopping simulation which used a collaborative filtering based product RA. Particular attention was paid to the effects of an RA on consumer behavior; …

Retrieval-Based Face Annotation By Weak Label Regularized Local Coordinate Coding, Dayong Wang, Steven C. H. Hoi, Ying He, Jianke Zhu

Research Collection School Of Computing and Information Systems

Retrieval-based face annotation is a promising paradigm in mining massive web facial images for automated face annotation. Such an annotation paradigm usually encounters two key challenges. The first challenge is how to efficiently retrieve a short list of most similar facial images from facial image databases, and the second challenge is how to effectively perform annotation by exploiting these similar facial images and their weak labels which are often noisy and incomplete. In this paper, we mainly focus on tackling the second challenge of the retrieval-based face annotation paradigm. In particular, we propose an effective Weak Label Regularized Local Coordinate …

Automated Removal Of Cross Site Scripting Vulnerabilities In Web Applications, Lwin Khin Shar, Hee Beng Kuan Tan

Research Collection School Of Computing and Information Systems

Context: Cross site scripting (XSS) vulnerability is among the top web application vulnerabilities according to recent surveys. This vulnerability occurs when a web application uses inputs received from users in web pages without properly checking them. This allows an attacker to inject malicious scripts in web pages via such inputs such that the scripts perform malicious actions when a client visits the exploited web pages. Such an attack may cause serious security violations such as account hijacking and cookie theft. Current approaches to mitigate this problem mainly focus on effective detection of XSS vulnerabilities in the programs or prevention of …

Wsm 2011: Third Acm Workshop On Social Media, Steven C. H. Hoi, Michal Jacovi, Ioannis Kompatsiaris, Jiebo Luo, Konstantinos Tserpes

Research Collection School Of Computing and Information Systems

The Third Workshop on Social Media (WSM2011) continues the series of Workshops on Social Media in 2009 and 2010 and has been established as a platform for the presentation and discussion of the latest, key research issues in social media analysis, exploration, search, mining, and emerging new social media applications. It is held in conjunction with the ACM International Multimedia Conference (MM'11) at Scottsdale, Arizona, USA, 2011 and has attracted contributions on various aspects of social media including data mining from social media, content organization, geo-localization, personalization, recommendation systems, user experience, machine learning and social media approaches and architectures for …

Towards Textually Describing Complex Video Contents With Audio-Visual Concept Classifiers, Chun Chet Tan, Yu-Gang Jiang, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Automatically generating compact textual descriptions of complex video contents has wide applications. With the recent advancements in automatic audio-visual content recognition, in this paper we explore the technical feasibility of the challenging issue of precisely recounting video contents. Based on cutting-edge automatic recognition techniques, we start from classifying a variety of visual and audio concepts in video contents. According to the classification results, we apply simple rule-based methods to generate textual descriptions of video contents. Results are evaluated by conducting carefully designed user studies. We find that the state-of-the-art visual and audio concept classification, although far from perfect, is able …

Cross Media Hyperlinking For Search Topic Browsing, Song Tan, Chong-Wah Ngo, Hung-Khoon Tan, Lei Pang

Research Collection School Of Computing and Information Systems

With the rapid growth of social media, there are plenty of information sources freely available online for use. Nevertheless, how to synchronize and leverage these diverse forms of information for multimedia applications remains a problem yet to be seriously studied. This paper investigates the synchronization of multiple media content in the physical form of hyperlinking them. The ultimate goal is to develop browsing systems that author search results with rich media information mined from various knowledge sources. The authoring enables the vivid visualization and exploration of different information landscapes inherent in search results. Several key techniques are studied in this …

Vireo@Trecvid 2011: Instance Search, Semantic Indexing, Multimedia Event Detection And Known-Item Search, Chong-Wah Ngo, Shi-Ai Zhu, Wei Zhang, Chun-Chet Tan, Ting Yao, Lei Pang, Hung-Khoon Tan

Research Collection School Of Computing and Information Systems

The vireo group participated in four tasks: instance search, semantic indexing, multimedia event detection and known-item search. In this paper,we will present our approaches and discuss the evaluation results.

Quantifying Computer Network Security, Ian Burchett

Masters Theses & Specialist Projects

Simplifying network security data to the point that it is readily accessible and usable by a wider audience is increasingly becoming important, as networks become larger and security conditions and threats become more dynamic and complex, requiring a broader and more varied security staff makeup. With the need for a simple metric to quantify the security level on a network, this thesis proposes: simplify a network’s security risk level into a simple metric. Methods for this simplification of an entire network’s security level are conducted on several characteristic networks. Identification of computer network port vulnerabilities from NIST’s Network Vulnerability Database …

Chernoff Dimensionality Reduction-Where Fisher Meets Fkt, Jing Peng, Guna Seetharaman, Wei Fan, Stefan Robila, Aparna Varde

Department of Computer Science Faculty Scholarship and Creative Works

Well known linear discriminant analysis (LDA) based on the Fisher criterion is incapable of dealing with heteroscedasticity in data. However, in many practical applications we often encounter heteroscedastic data, i.e., within-class scatter matrices can not be expected to be equal. A technique based on the Chernoff criterion for linear dimensionality reduction has been proposed recently. The technique extends well-known Fisher's LDA and is capable of exploiting information about heteroscedasticity in the data. While the Chernoff criterion has been shown to outperform the Fisher's, a clear understanding of its exact behavior is lacking. In addition, the criterion, as introduced, is rather …

Edge-Guarding Orthogonal Polyhedra, Nadia M. Benbernou, Erik D. Demaine, Martin L. Demaine, Anastasia Kurdia, Joseph O'Rourke, Godfried Toussaint, Jorge Urrutia, Giovanni Viglietta

Computer Science: Faculty Publications

We address the question: How many edge guards are needed to guard an orthogonal polyhedron of e edges, r of which are reflex? It was previously established [3] that e/12 are sometimes necessary and e/6 always suf- fice. In contrast to the closed edge guards used for these bounds, we introduce a new model, open edge guards (excluding the endpoints of the edge), which we argue are in some sense more natural in this context. After quantifying the relationship between closed and open edge guards, we improve the upper bound to show that, asymptotically, (11/72)e (open or closed) edge guards …

Value Relevance Of Blog Visibility, Nan Hu, Ling Liu, Arindam Tripathy, Lee J. Yao

Research Collection School Of Computing and Information Systems

This study empirically examines the effect of a non-traditional information source, namely a firm's blog visibility on the capital market valuation of firms. After controlling for earnings, book value of equity and other value relevant variables, such as traditional media exposure, R&D spending, and advertising expense, we find a positive association between a firm's blog visibility and its capital market valuation. In addition, we find blog visibility Grange causes trading, not vice versa. Our findings indicate that non-traditional information sources such as blogs help disseminate information and influence consumers' investment decisions by capturing their attention.

From Primordial Soup To Platform-Based Competition: Exploring The Emergence Of Products, Systems, And Platforms, C. Jason Woodard, Eric K. Clemons

Research Collection School Of Computing and Information Systems

We use an agent-based NK model to explore the conditions under which standard platforms emerge among competing products. Our findings were inconclusive. We find that the usual Darwinian conditions needed for the emergence of complexity are sufficient to yield a limited reliance upon platforms with a core of common components, simply because evolution causes the population to converge on a set of products that contain combinations that "work well," yielding what we call "coincidental platform emergence." Economies of scale yield more use of common components, or "production platform emergence." Positive participation externalities initially induce the highest degree of platform emergence …