Computer Sciences Commons^™

An Estimation Theory Approach To Detection And Ranging Of Obscured Targets In 3-D Ladar Data, Charles R. Burris

Theses and Dissertations

The purpose of this research is to develop an algorithm to detect obscured images in 3-D LADAR data. The real data used for this research was gathered using a FLASH LADAR system under development at AFRL/SNJM. The system transmits light with a wavelength of 1.55 micrometers and produces 20 128 X 128 temporally resolved images from the return pulse separated by less than 2 nanoseconds in time. New algorithms for estimating the range to a target in 3-D FLASH LADAR data were developed. Results from processing real data are presented and compared to the traditional correlation receiver for extracting ranges …

Bda Enhancement Methodology Using Situational Parameter Adjustments, Michael V. Carras Jr.

Theses and Dissertations

In the context of close ground combat, the perception of Battle Damage Assessment (BDA) is closely linked with a soldier’s engagement decisions and has significant effects on the battlefield. Perceived BDA is also one of the most complex and uncertain processes facing the soldier in live combat. As a result, the modeling and simulation community has yet to adequately model the perceived BDA process in combat models. This research effort examines the BDA process from a perception standpoint and proposes a methodology to collect the pertinent data and model this perception in the Army’s current force-on-force model, CASTFOREM. A subject …

Visual Ontology Modeling For Electronic Markets, Saartje Brockmans, Andreas Geyer-Schulz, Pascal Hitzler, Rudi Studer

Computer Science and Engineering Faculty Publications

The research program, Information Management and Market Engineering, focuses on the analysis and the design of electronic markets. Taking a holistic view of the conceptualization and realization of solutions, the research integrates the disciplines business administration, economics, computer science, and law. Topics of interest range from the implementation, quality assurance, and further development of electronic markets to their integration into business processes, innovative business models, and legal frameworks.

Taxaminer: Improving Taxonomy Label Quality Using Latent Semantic Indexing, Cartic Ramakrishnan, Christopher Thomas, Vipul Kashyap, Amit P. Sheth

Kno.e.sis Publications

The development of taxonomies/ontologies is a human intensive process requiring prohibitively large resource commitments in terms of time and cost. In our previous work we have identified an experimentation framework for semi-automatic taxonomy/hierarchy generation from unstructured text. In the preliminary results presented, the taxonomy/hierarchy quality was lower than we had anticipated. In this paper, we present two variations of our experimentation framework, viz. Latent semantic Indexing (LSI) for document indexing and the use of term vectors to prune labels assigned to nodes in the final taxonomy/hierarchy. Using our previous results of taxonomy/hierarchy quality as the baseline we present results that …

Data Processing In Space, Time, And Semantics Dimensions, Farshad Hakimpour, Boanerges Aleman-Meza, Matthew Perry, Amit P. Sheth

Kno.e.sis Publications

This work presents an experimental system for data processing in space, time and semantics dimensions using current Semantic Web technologies. The paper describes how we obtain geographic and event data from Internet sources and also how we integrate them into an RDF store. We briefly introduce a set of functionalities in space, time and semantics dimensions. These functionalities are implemented based on our existing technology for main-memory based RDF data processing developed in the LSDIS Lab. A number of these functionalities are exposed as REST Web services. We present two sample client side applications that are developed using a combination …

Data Mining Techniques To Study Therapy Success With Autistic Children, Gondy A. Leroy, Annika Irmscher, Marjorie H. Charlop

CGU Faculty Publications and Research

Autism spectrum disorder has become one of the most prevalent developmental disorders, characterized by a wide variety of symptoms. Many children need extensive therapy for years to improve their behavior and facilitate integration in society. However, few systematic evaluations are done on a large scale that can provide insights into how, where, and how therapy has an impact. We describe how data mining techniques can be used to provide insights into behavioral therapy as well as its effect on participants. To this end, we are developing a digital library of coded video segments that contains data on appropriate and inappropriate …

Semi-Supervised Conditional Random Fields For Improved Sequence Segmentation And Labeling, Feng Jiao, Shaojun Wang, Chi-Hoon Lee, Russell Greiner, Dale Schuurmans

Kno.e.sis Publications

We present a new semi-supervised training procedure for conditional random fields (CRFs) that can be used to train sequence segmentors and labelers from a combination of labeled and unlabeled training data. Our approach is based on extending the minimum entropy regularization framework to the structured prediction case, yielding a training objective that combines unlabeled conditional entropy with labeled conditional likelihood. Although the training objective is no longer concave, it can still be used to improve an initial model (e.g. obtained from supervised training) by iterative ascent. We apply our new training algorithm to the problem of identifying gene and protein …

An Investigation Of Codon Usage Bias Including Visualization And Quantification In Organisms Exhibiting Multiple Biases, Douglas W. Raiford, Travis E. Doom, Dan E. Krane, Michael L. Raymer

Kno.e.sis Publications

Prokaryotic genomic sequence data provides a rich resource for bioinformatic analytic algorithms. Information can be extracted in many ways from the sequence data. One often overlooked process involves investigating an organism’s codon usage. Degeneracy in the genetic code leads to multiple codons coding for the same amino acids. Organism’s often preferentially utilize specific codons when coding for an amino acid. This biased codon usage can be a useful trait when predicting a gene’s expressivity or whether the gene originated from horizontal transfer. There can be multiple biases at play in a genome causing errors in the predictive process. For this …

A Semantic Future For Ai, Rudi Studer, Anupriya Ankolekar, Pascal Hitzler

Computer Science and Engineering Faculty Publications

In our modern information society, people need to manage ever-increasing numbers of personal devices and conduct more of their work and activities online, often making use of heterogeneous services. The amount of information to be processed by each individual is constantly growing, making it increasingly difficult to control, channel, share and make constructive use of it. To mitigate this, computing needs to become much more human-centered, e.g. by presenting personalised information to users and by respecting personal preferences in controlling multiple devices or invoking various services. Appropriate representation of the semantics of the information and functionality of devices and services …

Foreign-Born Population In Selected Ohio Cities, 1870 To 2000 A Brief Descriptive Report, Mark Salling, Ellen Cyran

All Maxine Goodman Levin School of Urban Affairs Publications

No abstract provided.

Predicting Domain Specific Entities With Limited Background Knowledge, Christopher Thomas, Amit P. Sheth

Kno.e.sis Publications

This paper proposes a framework for automatic recognition of domain-specific entities from text, given limited background knowledge, e.g. in form of an ontology. The algorithm exploits several lightweight natural language processing techniques, such as tokenization and stemming, as well as statistical techniques, such as singular value decomposition (SVD) to suggest domain relatedness of unknown entities.

Using Query-Specific Variance Estimates To Combine Bayesian Classifiers, Chi-Hoon Lee, Russell Greiner, Shaojun Wang

Kno.e.sis Publications

Many of today's best classification results are obtained by combining the responses of a set of base classifiers to produce an answer for the query. This paper explores a novel "query specific" combination rule: After learning a set of simple belief network classifiers, we produce an answer to each query by combining their individual responses, using weights based inversely on their respective variances around their responses. These variances are based on the uncertainty of the network parameters, which in turn depend on the training datasample. In essence, this variance quantifies the base classifier's confidence of its response to this query. …

Clustering Similarity Comparison Using Density Profiles, Eric Bae, James Bailey, Guozhu Dong

Kno.e.sis Publications

The unsupervised nature of cluster analysis means that objects can be clustered in many ways, allowing different clustering algorithms to generate vastly different results. To address this, clustering comparison methods have traditionally been used to quantify the degree of similarity between alternative clusterings. However, existing techniques utilize only the point memberships to calculate the similarity, which can lead to unintuitive results. They also cannot be applied to analyze clusterings which only partially share points, which can be the case in stream clustering. In this paper we introduce a new measure named ADCO, which takes into account density profiles for each …

An Online Discriminative Approach To Background Subtraction, Li Cheng, Shaojun Wang, Terry Caelli

Kno.e.sis Publications

We present a simple, principled approach to detecting foreground objects in video sequences in real-time. Our method is based on an on-line discriminative learning technique that is able to cope with illumination changes due to discontinuous switching, or illumination drifts caused by slower processes such as varying time of the day. Starting from a discriminative learning principle, we derive a training algorithm that, for each pixel, computes a weighted linear combination of selected past observations with time-decay. We present experimental results that show the proposed approach outperforms existing methods on both synthetic sequences and real video data.

Driving Deep Semantics In Middleware And Networks: What, Why And How?, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

Knowledge Modeling And Its Application In Life Sciences: A Tale Of Two Ontologies, Satya S. Sahoo, Christopher Thomas, Amit P. Sheth, William S. York, Samir Tartir

Kno.e.sis Publications

High throughput glycoproteomics, similar to genomics and proteomics, involves extremely large volumes of distributed, heterogeneous data as a basis for identification and quantification of a structurally diverse collection of biomolecules. The ability to share, compare, query for and most critically correlate datasets using the native biological relationships are some of the challenges being faced by glycobiology researchers. As a solution for these challenges, we are building a semantic structure, using a suite of ontologies, which supports management of data and information at each step of the experimental lifecycle. This framework will enable researchers to leverage the large scale of glycoproteomics …

Show Me What You Mean! Exploiting Domain Semantics In Ontology Visualization, Ravi Pavagada, Christopher Thomas, Amit P. Sheth, William S. York

Kno.e.sis Publications

Ontologies build the backbone for many life-sciences applications. These ontologies, however, are represented in XML based languages that are meant for machine-consumption and hence are difficult for humans to comprehend. For a meaningful visualization of these ontologies, it is important that the display of entities and relationships captures the cognitive representation of the domain as perceived by the domain experts. In this paper we present OntoVista, an ontology visualization tool that is adaptable to the needs of different domains, especially in the life sciences. While keeping the graph structures as the predominant model, we provide a semantically enhanced graph display …

Using The Census Bureau's Public Use Microdata For Migration Analysis, Mark Salling, Ellen Cyran

All Maxine Goodman Levin School of Urban Affairs Publications

Using the Census Bureau's Public Use Microdata for Migration Analysis, Proceedings of the annual conference of the Urban and Regional Information Systems Association, Vancouver, BC, Canada, September 2006, pp.336-348.

Comparison Of Selected Survey Instruments For Software Team Communication Research, Raghava G. Gowda, Donald J. Polzella

Psychology Faculty Publications

One of the factors that influence task productivity is communication pertaining to task, resources, and organizational issues. The objective of this research is to explore the availability of validated survey instruments in the area of organizational and team communication and assess their applicability in software development team research. Based on past studies, we have selected six comprehensive instruments. This paper provides a brief summary of the instruments and the various dimensions that they cover. The instruments are classified using a Group Variable Classification System (GVCS - input-process - output - feedback) model for team research. As most of the instruments …

Evaluating The Impact Of Peer Review And Participation Awareness In An Online Collaborative Document Authoring Environment, Greg Baatard

Theses : Honours

Online Learning Environments (OLEs) have been widely adopted by higher education facilities, offering distance education with the potential to support the social and collaborative aspects deemed crucial to modern constructivist pedagogy. Groupware, a form of software which aims to facilitate group work, has been the subject of much research, from both educational and enterprise perspectives. This research introduced Reportal, an online groupware system designed to facilitate the collaborative authoring of a document. Reportal's peer review and participation awareness features were the focus of this research, and their impact was measured against the elements of online collaboration, a typology established by …

Book Review: Digital Crime And Forensic Science In Cyberspace, Gary C. Kessler

Journal of Digital Forensics, Security and Law

This issue presents the first Book Review column for the JDFSL. It is an experiment to broaden the services that the journal provides to readers, so we are anxious to get your reaction. Is the column useful and interesting? Should we include more than one review per issue? Should we also review products? Do you have suggested books/products for review and/or do you want to write a review? All of this type of feedback -- and more -- is appreciated. Please feel free to send comments to Gary Kessler ([email protected]) or Glenn Dardick ([email protected]).

Alphaco: A Teaching Case On Information Technology Audit And Security, Hüseyin Tanriverdi, Joshua Bertsch, Jonathan Harrison, Po-Ling Hsiao, Ketan S. Mesuria, David Hendrawirawan

Journal of Digital Forensics, Security and Law

Recent regulations in the United States (U.S.) such as the Sarbanes-Oxley Act of 2002 require top management of a public firm to provide reasonable assurance that they institute internal controls that minimize risks over the firm’s operations and financial reporting. External auditors are required to attest to the management’s assertions over the effectiveness of those internal controls. As firms rely more on information technology (IT) in conducting business, they also become more vulnerable to IT related risks. IT is critical for initiating, recording, processing, summarizing and reporting accurate financial and non-financial data. Thus, understanding IT related risks and instituting internal …

Table Of Contents

Journal of Digital Forensics, Security and Law

No abstract provided.

Designing A Data Warehouse For Cyber Crimes, Il-Yeol Song, John D. Maguire, Ki Jung Lee, Namyoun Choi, Xiaohua Hu, Peter Chen

Journal of Digital Forensics, Security and Law

One of the greatest challenges facing modern society is the rising tide of cyber crimes. These crimes, since they rarely fit the model of conventional crimes, are difficult to investigate, hard to analyze, and difficult to prosecute. Collecting data in a unified framework is a mandatory step that will assist the investigator in sorting through the mountains of data. In this paper, we explore designing a dimensional model for a data warehouse that can be used in analyzing cyber crime data. We also present some interesting queries and the types of cyber crime analyses that can be performed based on …

A Forensic Log File Extraction Tool For Icq Instant Messaging Clients, Kim Morfitt, Craig Valli

Journal of Digital Forensics, Security and Law

Instant messenger programs such as ICQ are often used by hackers and criminals for illicit purposes and consequently the log files from such programs are of interest in a forensic investigation. This paper outlines research that has resulted in the development of a tool for the extraction of ICQ log file entries. Detailed reconstruction of data from log files was achieved with a number of different ICQ software. There are several limitations with the current design including timestamp information not adjusted for the time zone, data could be altered, and conversations must be manually reconstructed. Future research will aim to …

The Design Of An Undergraduate Degree Program In Computer & Digital Forensics, Gary C. Kessler, Michael E. Schirling

Journal of Digital Forensics, Security and Law

Champlain College formally started an undergraduate degree program in Computer & Digital Forensics in 2003. The underlying goals were that the program be multidisciplinary, bringing together the law, computer technology, and the basics of digital investigations; would be available as on online and oncampus offering; and would have a process-oriented focus. Success of this program has largely been due to working closely with practitioners, maintaining activity in events related to both industry and academia, and flexibility to respond to ever-changing needs. This paper provides an overview of how this program was conceived, developed, and implemented; its evolution over time; and …

The Role Of Power And Negotiation In Online Deception, Chad Albrecht, Conan C. Albrecht, Jonathan Wareham, Paul Fox

Journal of Digital Forensics, Security and Law

The purpose of this paper is to advance theoretical understanding of the important role of both power and negotiation during online deception. By so doing, the paper provides insight into the relationship between perpetrator and victim in Internet fraud. The growing prevalence of Internet Fraud continues to be a burden to both society and individuals. In an attempt to better understand Internet fraud and online deception, this article attempts to build an interactive model, based upon the dimensions of power and negotiation from the management and psychology literature. Using the model presented, the article examines the effects of the Internet …

A Curriculum For Teaching Information Technology Investigative Techniques For Auditors, Grover S. Kearns

Journal of Digital Forensics, Security and Law

Recent prosecutions of highly publicized white-collar crimes combined with public outrage have resulted in heightened regulation of financial reporting and greater emphasis on systems of internal control. Because both white-collar and cybercrimes are usually perpetrated through computers, internal and external auditors’ knowledge of information technology (IT) is now more vital than ever. However, preserving digital evidence and investigative techniques, which can be essential to fraud examinations, are not skills frequently taught in accounting programs and instruction in the use of computer assisted auditing tools and techniques – applications that might uncover fraudulent activity – is limited. Only a few university-level …

Development Of A National Repository Of Digital Forensic Intelligence, Mark Weiser, David P. Biros, Greg Mosier

Journal of Digital Forensics, Security and Law

Many people do all of their banking online, we and our children communicate with peers through computer systems, and there are many jobs that require near continuous interaction with computer systems. Criminals, however, are also “connected”, and our online interaction provides them a conduit into our information like never before. Our credit card numbers and other fiscal information are at risk, our children's personal information is exposed to the world, and our professional reputations are on the line.

The discipline of Digital Forensics in law enforcement agencies around the nation and world has grown to match the increased risk and …

Electronic Data Discovery: Integrating Due Process Into Cyber Forensic Practice, John W. Bagby, John C. Ruhnka

Journal of Digital Forensics, Security and Law

Most organizations and government agencies regularly become engaged in litigation with suppliers, customers, clients, employees, competitors, shareholders, prosecutors or regulatory agencies that nearly assures the need to organize, retain, find and produce business records and correspondence, emails, accounting records or other data relevant to disputed issues. This article discusses some high visibility cases that constrain how metadata and content is routinely made available to opposing parties in civil litigation, to prosecutors in criminal prosecutions and to agency staff in regulatory enforcement litigation. Public policy, as implemented in the rules of evidence and pretrial discovery, restrict electronic data discovery (EDD) as …