Physical Sciences and Mathematics Commons^™

Stochastic Analysis Of Horizontal Ip Scanning, Derek Leonard, Zhongmei Yao, Xiaoming Wang, Dmitri Loguinov

Computer Science Faculty Publications

Intrusion Detection Systems (IDS) have become ubiquitous in the defense against virus outbreaks, malicious exploits of OS vulnerabilities, and botnet proliferation. As attackers frequently rely on host scanning for reconnaissance leading to penetration, IDS is often tasked with detecting scans and preventing them. However, it is currently unknown how likely an IDS is to detect a given Internet-wide scan pattern and whether there exist sufficiently fast scan techniques that can remain virtually undetectable at large-scale. To address these questions, we propose a simple analytical model for the window-expiration rules of popular IDS tools (i.e., Snort and Bro) and utilize a …

On Superposition Of Heterogeneous Edge Processes In Dynamic Random Graphs, Zhongmei Yao, Daren B. H. Cline, Dmitri Loguinov

Computer Science Faculty Publications

This paper builds a generic modeling framework for analyzing the edge-creation process in dynamic random graphs in which nodes continuously alternate between active and inactive states, which represent churn behavior of modern distributed systems. We prove that despite heterogeneity of node lifetimes, different initial out-degree, non-Poisson arrival/failure dynamics, and complex spatial and temporal dependency among creation of both initial and replacement edges, a superposition of edge-arrival processes to a live node under uniform selection converges to a Poisson process when system size becomes sufficiently large. Due to the convoluted dependency and non-renewal nature of various point processes, this result significantly …

Localized Deconvolution: Characterizing Nmr-Based Metabolomics Spectroscopic Data Using Localized High-Throughput Deconvolution, Paul E. Anderson, Ajith H. Ranabahu, Deirdre A. Mahle, Nicholas V. Reo, Michael L. Raymer, Amit P. Sheth, Nicholas J. Delraso

Kno.e.sis Publications

The interpretation of nuclear magnetic resonance (NMR) experimental results for metabolomics studies requires intensive signal processing and multivariate data analysis techniques. Standard quantification techniques attempt to minimize effects from variations in peak positions caused by sample pH, ionic strength, and composition. These techniques fail to account for adjacent signals which can lead to drastic quantification errors. Attempts at full spectrum deconvolution have been limited in adoption and development due to the computational resources required. Herein, we develop a novel localized deconvolution algorithm for general purpose quantification of NMR-based metabolomics studies. Localized deconvolution decreases average absolute quantification error by 97% and …

Quality And Leniency In Online Collaborative Rating Systems, Hady W. Lauw, Ee Peng Lim, Ke Wang

Research Collection School Of Computing and Information Systems

The emerging trend of social information processing has resulted in Web users’ increased reliance on user-generated content contributed by others for information searching and decision making. Rating scores, a form of user-generated content contributed by reviewers in online rating systems, allow users to leverage others’ opinions in the evaluation of objects. In this article, we focus on the problem of summarizing the rating scores given to an object into an overall score that reflects the object’s quality. We observe that the existing approaches for summarizing scores largely ignores the effect of reviewers exercising different standards in assigning scores. Instead of …

Road: A New Spatial Object Search Framework For Road Networks, Ken C. K. Lee, Wang-Chien Lee, Baihua Zheng, Yuan Tian

Research Collection School Of Computing and Information Systems

In this paper, we present a new system framework called ROAD for spatial object search on road networks. ROAD is extensible to diverse object types and efficient for processing various location-dependent spatial queries (LDSQs), as it maintains objects separately from a given network and adopts an effective search space pruning technique. Based on our analysis on the two essential operations for LDSQ processing, namely, network traversal and object lookup, ROAD organizes a large road network as a hierarchy of interconnected regional subnetworks (called Rnets). Each Rnet is augmented with 1) shortcuts and 2) object abstracts to accelerate network traversals and …

Designer Satellite Collisions From Covert Cyber War, Jan Kallberg

Jan Kallberg

Outer space has enjoyed two decades of fairly peaceful development since the Cold War, but once again it is becoming more competitive and contested, with increased militarization. Therefore, it is important the United States maintain its space superiority to ensure it has the capabilities required by modern warfare for successful operations. Today is different from earlier periods of space development,1 because there is not a blatantly overt arms race in space,2 but instead a covert challenge to US interests in maintaining superiority, resilience, and capability. A finite number of states consider themselves geopolitical actors; however, as long as the United …

Framework For The Analysis Of Coordination In Crisis Response, Hemant Purohit, Andrew Hampton, Valerie L. Shalin, Amit P. Sheth, John M. Flach

Kno.e.sis Publications

Social Media play a critical role during crisis events, revealing a natural coordination dynamic. We propose a computational framework guided by social science principles to measure, analyze, and understand coordination among the different types of organizations and actors in crisis response. The analysis informs both the scientific account of cooperative behavior and the design of applications and protocols to support crisis management.

Extreme Learning Machine Terrain-Based Navigation For Unmanned Aerial Vehicles, Ee May Kan, Meng Hiot Lim, Yew Soon Ong, Ah-Hwee Tan, Swee Ping Yeo

Research Collection School Of Computing and Information Systems

Unmanned aerial vehicles (UAVs) rely on global positioning system (GPS) information to ascertain its position for navigation during mission execution. In the absence of GPS information, the capability of a UAV to carry out its intended mission is hindered. In this paper, we learn alternative means for UAVs to derive real-time positional reference information so as to ensure the continuity of the mission. We present extreme learning machine as a mechanism for learning the stored digital elevation information so as to aid UAVs to navigate through terrain without the need for GPS. The proposed algorithm accommodates the need of the …

The Social Network Of Software Engineering Research, Subhajit Datta, Nishant Kumar, Santonu Sarkar

Research Collection School Of Computing and Information Systems

The social network perspective has served as a useful framework for studying scientific research collaboration in different disciplines. Although collaboration in computer science research has received some attention, software engineering research collaboration has remained unexplored to a large extent. In this paper, we examine the collaboration networks based on co-authorship information of papers from ten software engineering publication venues over the 1976-2010 time period. We compare time variations of certain parameters of these networks with corresponding parameters of collaboration networks from other disciplines. We also explore whether software engineering collaboration networks manifest symptoms of the small-world phenomenon, conform to the …

Mitigating The True Cost Of Advertisement-Supported "Free" Mobile Applications, Azeem J. Khan, Vigneshwaran Subbaraju, Archan Misra, Srinivasan Seshan

Research Collection School Of Computing and Information Systems

The dominant, "ad-supported free application" model for consumer-oriented mobile computing is seemingly imperiled by the growing global adoption of metered data pricing plans by mobile operators. In this paper, we explore the opportunities for addressing this emerging conflict by enabling more intelligent ad delivery to such mobile devices. One especially promising path is leveraging the increasing availability of heterogeneous wireless access technologies (e.g., WiFi, femtocells) that offer less restrictive and more energy-efficient transport substrates for such data traffic. To understand the possibilities that exist, we first profile the advertisement traffic characteristics for some of the most popular advertisement-supported consumer applications, …

An Examination Of Coordination Among Friends And Strangers From A Coordination Theory Perspective, Christopher D. Wamble

Theses

Within mobile social coordination, there is a field of study known as outeraction, the communicative processes used by people to manage future interactions. It is an important area of research because it identifies how informal interactions support complex collaboration between individuals and groups. Outeraction is primarily conducted through the interpersonal communication channels of texting, instant messaging (IM), face-to-face, and mobile phone or Skype conversations. Currently this area of research in mobile outeraction support systems is weak. It lacks a firm foundation in system building, has very few if any conceptual frameworks, and little empirical knowledge of user requirements and attitudes …

Discovering Fine-Grained Sentiment In Suicide Notes, Wenbo Wang, Lu Chen, Ming Tan, Shaojun Wang, Amit P. Sheth

Kno.e.sis Publications

This paper presents our solution for the i2b2 sentiment classification challenge. Our hybrid system consists of machine learning and rule-based classifiers. For the machine learning classifier, we investigate a variety of lexical, syntactic and knowledge-based features, and show how much these features contribute to the performance of the classifier through experiments. For the rule-based classifier, we propose an algorithm to automatically extract effective syntactic and lexical patterns from training examples. The experimental results show that the rule-based classifier outperforms the baseline machine learning classifier using unigram features. By combining the machine learning classifier and the rule-based classifier, the hybrid system …

A Semantic Problem Solving Environment For Integrative Parasite Research: Identification Of Intervention Targets For Trypanosoma Cruzi, Priti Parikh, Todd Minning, Vinh Nguyen, Sarasi Lalithsena, Amir H. Asiaee, Satya S. Sahoo, Prashant Doshi, Rick L. Tarleton, Amit P. Sheth

Kno.e.sis Publications

Background: Research on the biology of parasites requires a sophisticated and integrated computational platform to query and analyze large volumes of data, representing both unpublished (internal) and public (external) data sources. Effective analysis of an integrated data resource using knowledge discovery tools would significantly aid biologists in conducting their research, for example, through identifying various intervention targets in parasites, and in deciding the future direction of ongoing as well as planned projects. A key challenge in achieving this objective is the heterogeneity between the internal lab data, usually stored as flat files, Excel spreadsheets or custom-built databases, and the external …

Responses To The 11/4/11 Ostp Data Rfi, David Lowe

Published Works

On November 3, 2011, OSTP released a Request for Information (RFI) soliciting public input on long-term preservation of, and public access to, the results of federally funded research, including digital data ,as required in the America COMPETES Reauthorization Act of 2010. Published here are the responses from David Lowe, Preservation Librarian and Digital Programs Team Leader at the University of Connecticut Libraries.

Establishing A Foundation For Automated Human Credibility Screening, Jay F. Nunamaker Jr., Judee K. Burgoon, Nathan W. Twyman, Jeffrey Gainer Proudfoot, Ryan M. Schuetzler, Justin Scott Giboney

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

Automated human credibility screening is an emerging research area that has potential for high impact in fields as diverse as homeland security and accounting fraud detection. Systems that conduct interviews and make credibility judgments can provide objectivity, improved accuracy, and greater reliability to credibility assessment practices, need to be built. This study establishes a foundation for developing automated systems for human credibility screening.

Countermeasures And Eye Tracking Deception Detection, Ryan M. Schuetzler

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

A new development in the field of deception detection is been the development of rapid, noncontact tools for automated detection. This research in progress paper describes a method for assessing the robustness of eye tracker-based deception detection to countermeasures employed by knowledgeable participants.

Can Information And Communication Technologies Lead To Community Capital? An Analysis Of Development, Dave Kocsis, Sajda Qureshi, Jie Xiong

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

While it is widely accepted that the increasing interconnectedness of the world economy has been fueled by the innovative uses of Information and Communication Technologies (ICTs), little attention has been paid to the increasing inequalities within developed and developing countries. These inequalities manifest themselves in the form of communities in which incomes are considerably below the rest of the country and there is a rise in poverty. This paper investigates this trend by taking a community capital perspective to investigate how ICTs may or may not enable businesses to grow. As micro-enterprises are seen to contribute to the growth of …

Factors Affecting Information And Communications Technology Adoption Of Small Businesses: Studies In China And United States, Jie Xiong, Sajda Qureshi

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

Small businesses in China and United States generate the largest share of economic activity and employment. As the driving force behind the economic growth of both countries, Information and Communications Technology (ICTs) has fundamentally shaped the two countries. This research-in-progress paper reports the research model we conduct to analyze the factors that will affect ICTs adoption of small businesses in both countries. The purpose of the paper is to (1) report proposals of the current status of the research project (2) build an understanding of ICTs adoption in both countries (3) build the framework to explore the relationship between ICTs …

Analysis Of Information And Communications Technology Adoption Between Small Businesses In China And The United States, Jie Xiong, Sajda Qureshi

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

This paper reports on two case studies, the Information and Communications Technology (ICT) adoption among small businesses conducted in both United States and China. One small business from Nebraska (United States of America) and one small business from Sichuan (China) were chosen for comparison. The purpose of this paper is to conduct a comparative case study based on the ICT adoption among small businesses in China and the United States. This paper will: (i) build an understanding of small business ICT in both areas, (ii) explore the relationship between the ICT development in less cutting-edge areas of China and the …

Cognitive Approaches For The Semantic Web, Dedre Gentner, Frank Van Harmelen, Pascal Hitzler, Krzysztof Janowicz, Kai-Uwe Kuhnberger

Computer Science and Engineering Faculty Publications

A major focus in the design of Semantic Web ontology languages used to be on finding a suitable balance between the expressivity of the language and the tractability of reasoning services defined over this language. This focus mirrors the original vision of a Web composed of machine readable and understandable data. Similarly to the classical Web a few years ago, the attention is recently shifting towards a user-centric vision of the Semantic Web. Essentially, the information stored on the Web is from and for humans. This new focus is not only reflected in the fast growing Linked Data Web but …

Ontology–Based Representation Of Simulation Models, Katarina Grolinger, Miriam A.M. Capretz, José R. Marti, Krishan D. Srivastava

Electrical and Computer Engineering Publications

Ontologies have been used in a variety of domains for multiple purposes such as establishing common terminology, organizing domain knowledge and describing domain in a machine-readable form. Moreover, ontologies are the foundation of the Semantic Web and often semantic integration is achieved using ontology. Even though simulation demonstrates a number of similar characteristics to Semantic Web or semantic integration, including heterogeneity in the simulation domain, representation and semantics, the application of ontology in the simulation domain is still in its infancy. This paper proposes an ontology-based representation of simulation models. The goal of this research is to facilitate comparison among …

An Exploratory Study Of The Nature And Composition Of Current Library And Information Science Programs In Indian State Universities, Bharat Mehra, Devendra Potnis, Jennifer Morden

Faculty Publications and Other Works -- EECS

This brief article explores the current state of library and information science (LIS) programs in terms of their nature and composition in state universities in India. Preliminary findings were based on a content analysis of representative information regarding LIS education available on the websites of all state universities and colleges that offer LIS programs in India. Findings indicated broad trends in administrative structuring and nomenclature of LIS programs which requires standardization. The type of degrees awarded, the composition of faculty positions, student places per year and student-faculty ratios was also found to be varied among the different institutions. The lack …

Role Of Semantic Web In Health Informatics, Satya S. Sahoo, Guo-Qiang Zhang, Amit P. Sheth

Kno.e.sis Publications

This tutorial weaves together three themes and the associated topics: [1] The role of biomedical ontologies [2] Key Semantic Web technologies with focus on Semantic provenance and integration [3] In-practice tools and real world use cases built to serve the needs of sleep medicine researchers, cardiologists involved in clinical practice, and work on vaccine development for human pathogens.

Resident Identification Using Kinect Depth Image Data And Fuzzy Clustering Techniques, Tanvi Banerjee, James M. Keller, Marjorie Skubic

Kno.e.sis Publications

As a part of our passive fall risk assessment research in home environments, we present a method to identify older residents using features extracted from their gait information from a single depth camera. Depth images have been collected continuously for about eight months from several apartments at a senior housing facility. Shape descriptors such as bounding box information and image moments were extracted from silhouettes of the depth images. The features were then clustered using Possibilistic C Means for resident identification. This technology will allow researchers and health professionals to gather more information on the individual residents by filtering out …

Modeling The Longitudinality Of User Acceptance Of Technology With An Evidence-Adaptive Clinical Decision Support System, Michael P. Johnson Jr., Kai Zheng, Rema Padman

Public Policy and Public Affairs Faculty Publication Series

This paper presents multiple innovations associated with an electronic health record system developed to support evidence-based medicine practice, and highlights a new construct, based on the technology acceptance model, to explain end users’ acceptance of this technology through a lens of continuous behavioral adaptation and change. We show that this new conceptualization of technology acceptance reveals a richer level of detail of the developmental course whereby individuals adjust their behavior gradually to assimilate technology use. We also show that traditional models such as technology acceptance model (TAM) are not capable of delineating this longitudinal behavioral development process. Our TAM-derived analysis …

An Approach To The Virtual Flora Of Mongolia – From A Data Repository To An Expert System, Http://Greif.Uni-Greifswald.De/Floragreif/, Jörg Hartleib, Martin Schnittler, Sabrina Rilke, Anne Zemmrich, Bernd Bobertz, Ulrike Najmi, Reinhard Zölitz, Susanne Starke

Erforschung biologischer Ressourcen der Mongolei / Exploration into the Biological Resources of Mongolia, ISSN 0440-1298

FloraGREIF is an internet accessible information system providing taxonomic, phytogeographic and ecological information on Mongolia’s flora in terms of descriptions, high-resolution plant images and an interactive WebGIS application. Organised along an updated checklist of the approx. 3000 Mongolian vascular plants that serves as a taxonomic backbone, information is split into the taxon level, referring to plant species, and the record level, referring to record or a collected plant specimen. At the latter level, images of living plants, scans of herbarium sheets, habitat photos and further notes can be found. Both data levels are linked by the name of the respective …

A Natural Language Interface Plug-In For Cooperative Query Answering In Biological Databases, Hasan M. Jamil

Wayne State University Associated BioMed Central Scholarship

Abstract

Background

One of the many unique features of biological databases is that the mere existence of a ground data item is not always a precondition for a query response. It may be argued that from a biologist's standpoint, queries are not always best posed using a structured language. By this we mean that approximate and flexible responses to natural language like queries are well suited for this domain. This is partly due to biologists' tendency to seek simpler interfaces and partly due to the fact that questions in biology involve high level concepts that are open to interpretations computed …

Using Data Mining Technique To Predict Cause Of Accident And Accident Prone Locations On Highway, Dr. Dipo Theophilus Akomolafe Mbcs, Mncs, Mcpn,

Dr. Dipo Theophilus Akomolafe MBCS, MNCS, MCPN,

Road accident is a special case of trauma that constitutes a major cause of disability, untimely death and loss of loved ones as well as family bread winners. Therefore, predicting the likelihood of road accident on high ways with particular emphasis on Lagos – Ibadan express road, Nigeria in order to prevent accident is very important. Various attempts had been made to identify the cause(s) of accidents on highways using different techniques and system and to reduce accident on the roads but the rate of accident keep on increasing. In this study, the various techniques used to analyse the causes …

The Information Technology Workforce: A Comparision Of Critical Skills Of Clients And Service Providers, Stephen Hawk, Kate M. Kaiser, Tim Goles, Christine V. Bullen

Business Faculty Publications

In this article the authors explore similarities and differences in skill needs of IT service providers and the firms that providers service (clients). The results show that providers and clients are more similar than different with regard to desired skills. Client firms emphasize technical skills for new hires more than providers do despite saying that these are the skills they would outsource to providers. The results have implications for organizations’ recruiting and retention, for individuals’ career development, and for educational programs.

Privacy-Preserving Data Sharing In High Dimensional Regression And Classification Settings, Stephen E. Fienberg, Jiashun Jin

LARC Research Publications

We focus on the problem of multi-party data sharing in high dimensional data settings where the number of measured features (or the dimension) p is frequently much larger than the number of subjects (or the sample size) n, the so-called p>> n scenario that has been the focus of much recent statistical research. Here, we consider data sharing for two interconnected problems in high dimensional data analysis, namely the feature selection and classification. We characterize the notions of “cautious", “regular", and “generous" data sharing in terms of their privacy-preserving implications for the parties and their share of data, with focus …