Computer Sciences Commons^™

Logic Programs Vs. First-Order Formulas In Textual Inference, Yuliya Lierler, Vladimir Lifschitz

Computer Science Faculty Proceedings & Presentations

In the problem of recognizing textual entailment, the goal is to decide, given a text and a hypothesis expressed in a natural language, whether a human reasoner would call the hypothesis a consequence of the text. One approach to this problem is to use a first-order reasoning tool to check whether the hypothesis can be derived from the text conjoined with relevant background knowledge, after expressing all of them by first-order formulas. Another possibility is to express the hypothesis, the text, and the background knowledge in a logic programming language, and use a logic programming system. We discuss the relation …

Abstract Modular Systems And Solvers, Yuliya Lierler, Miroslaw Truszczyński

Computer Science Faculty Proceedings & Presentations

Integrating diverse formalisms into modular knowledge representation systems offers increased expressivity, modeling convenience and computational benefits. We introduce concepts of abstract modules and abstract modular systems to study general principles behind the design and analysis of modelfinding programs, or solvers, for integrated heterogeneous multi-logic systems. We show how abstract modules and abstract modular systems give rise to transition systems, which are a natural and convenient representation of solvers pioneered by the SAT community. We illustrate our approach by showing how it applies to answer set programming and propositional logic, and to multi-logic systems based on these two formalisms.

Hybrid Automated Reasoning Tools: From Black-Box To Clear-Box Integration, Marcello Balduccini, Yuliya Lierler

Computer Science Faculty Proceedings & Presentations

Recently, researchers in answer set programming and constraint programming spent significant efforts in the development of hybrid languages and solving algorithms combining the strengths of these traditionally separate fields. These efforts resulted in a new research area: constraint answer set programming (CASP). CASP languages and systems proved to be largely successful at providing efficient solutions to problems involving hybrid reasoning tasks, such as scheduling problems with elements of planning. Yet, the development of CASP systems is difficult, requiring non-trivial expertise in multiple areas. This suggests a need for a study identifying general development principles of hybrid systems. Once these principles …

Making Solution Pluralism In Policy Making Accessible: Optimization Of Design And Services For Constituent Well-Being, Margeret A. Hall, Steven O. Kimbrough, Wibke Michalk, Jefff Schneider, Christof Weinhardt

Interdisciplinary Informatics Faculty Proceedings & Presentations

Policy makers are increasingly turning to computational support mechanisms for managing uncertainty, and constituent focused-decisions. Utilization and standardization of human-computer interaction principles to create solution pluralism (the condition of having a consideration set containing a multiplicity of credible solutions) is a fundamental to fulfilling this need. There is a need for standardized applications and user interfaces to deliver a higher quality of service, which assists policy makers in maintaining or increasing constituent well-being.

A Parallel Template For Implementing Filters For Biological Correlation Networks, Kathryn Dempsey Cooper, Vladimir Ufimtsev, Sanjukta Bhowmick, Hesham Ali

Interdisciplinary Informatics Faculty Publications

High throughput biological experiments are critical for their role in systems biology – the ability to survey the state of cellular mechanisms on the broad scale opens possibilities for the scientific researcher to understand how multiple components come together, and what goes wrong in disease states. However, the data returned from these experiments is massive and heterogeneous, and requires intuitive and clever computational algorithms for analysis. The correlation network model has been proposed as a tool for modeling and analysis of this high throughput data; structures within the model identified by graph theory have been found to represent key players …

Real-Time Embodied Agent Adaptation, Ryan M. Schuetzler, David W. Wilson

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

This paper reports on initial investigation of two emerging technologies, FaceFX and Smartbody, capable of creating life-like animations for embodied conversational agents (ECAs) such as the AVATAR agent. Real-time rendering and animation generation technologies can enable rapid adaptation of ECAs to changing circumstances. The benefits of each package are discussed.

Information And Communication Technologies Effects On Economic Growth, Nancy Jimenez, Lotfollah Najjar, Sajda Qureshi, Dwight Haworth

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

While Information and Communication Technologies (ICTs) are seen to be drivers of economic growth, it is unclear how this change takes place, especially since social and human factors are often seen to change as a result of ICTs. This paper investigates the effects of ICTs, and social and human factors in terms of skills, education, and labor, on economic growth. An augmented production function is used to quantify the effects that infodensity levels, defined as the combination of ICT networks and skills, education, and labor, have on the economic growth of high and low-to-middle income economies. This research draws upon …

Factors That Affect Information And Communication Technology Adoption By Small Businesses In China, Jie Xiong, Sajda Qureshi, Lotfollah Najjar

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

Emerging economies appear to be powering growth in their regions. While China is seen to lead growth in the emerging markets of Asia, 98% of its manufacturing and production base is powered by small businesses. These businesses represent the majority of all businesses in emerging countries and their growth increases with their successful adoption of Information Technology. As the driving force behind the economic growth of China, Information and Communications Technologies (ICTs) are shaping the ways in which small businesses are able to grow. The majority of current research into the user acceptance and adoption of ICTs focusses on the …

The Role Of Human Capital In Information And Communication Technology Adoption For Development: Evidence From China, Jie Xiong, Sajda Qureshi, Lotfollah Najjar

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

Emerging economies, in particular China, are powering growth in Asia. While China is seen to lead growth in the emerging markets of Asia, 98% of its manufacturing and production base is powered by small businesses. These businesses represent the majority of all businesses in emerging countries and the growth of these businesses increases with their successful adoption of Information Technology. This paper uses a well-known model in Information Systems Adoption to analyze ICT usage, the effect ICT usage and human capital in the development of the small businesses in China. The reason this model is used is to find out …

A Model Of Icts Adoption For Sustainable Development: An Investigation Of Small Business In The United States And China, Jie Xiong, Sajda Qureshi

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

No abstract provided.

Virtual Phd Courses – A New Mode Of Phd Education?, Bjørn Erik Munkvold, Ilze Zigurs, Deepak Khazanchi

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

This paper presents experiences from a joint virtual PhD course for doctoral students at a Norwegian and a US university. Based on an experiential learning approach, the course focused on practices for virtual research collaboration. Through six synchronous online sessions, interspersed with interaction in sub-teams, the participants worked on developing a joint conference publication. This gave the PhD students first-hand experience with working in a virtual research team. Based on our analysis of the experiences from the course, we discuss challenges of the virtual course setting and present guidelines for the design and conduct of similar virtual courses. Our results …

Multi-Level Opinion Dynamics Under Bounded Confidence, Gang Kou, Yiyi Zhao, Yi Peng, Yong Shi

Information Systems and Quantitative Analysis Faculty Publications

Opinion dynamics focuses on the opinion evolution in a social community. Recently, some models of continuous opinion dynamics under bounded confidence were proposed by Deffuant and Krause, et al. In the literature, agents were generally assumed to have a homogeneous confidence level. This paper proposes an extended model for a group of agents with heterogeneous confidence levels. First, a social differentiation theory is introduced and a social group is divided into opinion subgroups with distinct confidence levels. Second, a multi-level heterogeneous opinion formation model is formulated under the framework of bounded confidence. Finally, computer simulations are conducted to study the …

Constraint Answer Set Programming, Yuliya Lierler

Computer Science Faculty Publications

Constraint answer set programming (CASP) is a novel, promising direction of research whose roots go back to propositional satisfiability (SAT). SAT solvers are efficient tools for solving boolean constraint satisfaction problems that arise in different areas of computer science, including software and hardware verification. Some constraints are more naturally expressed by non-boolean constructs. Satisfiability modulo theories (SMT) extends boolean satisfiability by the integration of non-boolean symbols defined by a background theory in another formalism, such as a constraint processing language. Answer set programming (ASP) extends computational methods of SAT in yet another way, inspired by ideas from knowledge representation, logic …

The Future Of Citizen Science: Emerging Technologies And Shifting Paradigms, Greg Newman, Andrea Wiggins, Alycia Crall, Eric Graham, Sarah Newman, Kevin Crowston

Information Systems and Quantitative Analysis Faculty Publications

Citizen science creates a nexus between science and education that, when coupled with emerging technologies, expands the frontiers of ecological research and public engagement. Using representative technologies and other examples, we examine the future of citizen science in terms of its research processes, program and participant cultures, and scientific communities. Future citizen‐science projects will likely be influenced by sociocultural issues related to new technologies and will continue to face practical programmatic challenges. We foresee networked, open science and the use of online computer/video gaming as important tools to engage non‐traditional audiences, and offer recommendations to help prepare project managers for …

Ethical Considerations For Virtual Worlds, Alanah Mitchell, Deepak Khazanchi

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

Metaverses, like Second Life and Teleplace, and the inherent technology capabilities that they offer continue to be of interest for researchers, practitioners, and educators. Due to this trend, and the uncertainty regarding immersive virtual experiences as contrasted with face-to-face experiences, there is a need to further understand the ethical challenges associated with this virtual context. This paper presents a starting point for discussing ethics in virtual worlds. Specifically, we review virtual worlds and their unique technology capabilities as well as the ethical considerations that arise due to these unique capabilities.

An Approach In Defining Information Assurance Patterns Based On Security Ontology And Meta-Modeling, Aniruddha Bhaumik

Student Work

We have to realizing that information is the most important asset. We are at a stage where the information is not only becoming a valuable asset but also the volume of it is increasing at a rapid rate. Modern Enterprises are now working hard to ensure the proper storage, availability and integrity of this information. So we are having the information assurance discipline which is focusing on preservation of information confidentiality, integrity and availability in all of the informations’ various state. We have the information security patterns. But we have to realize that we have to design the Information assurance …

A Semantic Approach For Keyword Search On Relational Databases, Rajvardhan Patil

Student Work

Today’s search engines make it easier for the user to browse and query the online available data. But when it comes to structured data, the queries have to be structured too, in order to retrieve the data. This makes it difficult for novice users, with no knowledge of the underlying schema or query language, to access the relational data. Therefore, to query the structured data in an unstructured language of web, there is a need to map the user keyword queries to their equivalent SQL format. This research is intended to bridge the gap by introducing a framework named STRUCT. …

Understanding The Adaptive Use Of Virtual World Technology Capabilities And Trust In Virtual Teams, Dawn Owens

Student Work

In an environment of global competition and constant technological change, the use of virtual teams has become commonplace for many organizations. Virtual team members are geographically and temporally dispersed, experience cultural diversity, and lack shared social context and face-to-face encounters considered as irreplaceable for building and maintaining trust. Previous research has established that higher trusting teams have better cooperation and experience improved outcomes; however, trust building in a team where members are from different backgrounds, time zones and cultures is a considerable challenge. Virtual teams (VTs) rely heavily on technology to facilitate coordination, communication, and control in the team. One …

A Multicriteria Decision Making Approach For Estimating The Number Of Clusters In A Data Set, Yi Peng, Yong Zhang, Gang Kou, Yong Shi

Information Systems and Quantitative Analysis Faculty Publications

Determining the number of clusters in a data set is an essential yet difficult step in cluster analysis. Since this task involves more than one criterion, it can be modeled as a multiple criteria decision making (MCDM) problem. This paper proposes a multiple criteria decision making (MCDM)-based approach to estimate the number of clusters for a given data set. In this approach, MCDM methods consider different numbers of clusters as alternatives and the outputs of any clustering algorithm on validity measures as criteria. The proposed method is examined by an experimental study using three MCDM methods, the well-known clustering algorithm–k-means, …

An Energy-Aware Bioinformatics Application For Assembling Short Reads In High Performance Computing Systems, Julia Warnke, Sachin Pawaskar, Hesham Ali

Computer Science Faculty Proceedings & Presentations

Current biomedical technologies are producing massive amounts of data on an unprecedented scale. The increasing complexity and growth rate of biological data has made bioinformatics data processing and analysis a key and computationally intensive task. High performance computing (HPC) has been successfully applied to major bioinformatics applications to reduce computational burden. However, a naïve approach for developing parallel bioinformatics applications may achieve a high degree of parallelism while unnecessarily expending computational resources and consuming high levels of energy. As the wealth of biological data and associated computational burden continues to increase, there has become a need for the development of …

Energy Aware Algorithms For Managing Wireless Sensor Networks, Abhishek Karpate

Student Work

While the majority of the current Wireless Sensor Networks (WSNs) research has prioritized either the coverage of the monitored area or the energy efficiency of the network, it is clear that their relationship must be further studied in order to find optimal solutions that balance the two factors. Higher degrees of redundancy can be attained by increasing the number of active sensors monitoring a given area which results in better performance. However, this in turn increases the energy being consumed. In our research, we focus on attaining a solution that considers several optimization parameters such as the percentage of coverage, …

Identifying Core Components In Software Systems, Phillip Meyer

Student Work

As large software systems are highly complex, they can be difficult for a developer to understand. If a core subset of a software system could be extracted which contains the most important classes and connections of the larger system, studying this core would be useful for efficiently understanding the overall system. In this research we examine research into core/periphery structures in networks, primarily focusing on the use of k-core decomposition. The extracted dependencies of three open source Java software systems provide the inputs, with forty different versions of these systems analyzed in total. We derive inter-class dependencies from these releases …

Representing First-Order Causal Theories By Logic Programs, Paolo Ferrarris, Joohyung Lee, Yuliya Lierler, Vladimir Lifschitz, Fangkai Yang

Computer Science Faculty Publications

Nonmonotonic causal logic, introduced by McCain and Turner (McCain, N. and Turner, H. 1997. Causal theories of action and change. In Proceedings of National Conference on Artificial Intelligence (AAAI), Stanford, CA, 460–465) became the basis for the semantics of several expressive action languages. McCain's embedding of definite propositional causal theories into logic programming paved the way to the use of answer set solvers for answering queries about actions described in such languages. In this paper we extend this embedding to nondefinite theories and to the first-order causal logic.

Discontinuities And Best Practices In Virtual Research Collaboration, Vipin Arora, Deepak Khazanchi, Bjørn Erik Munkvold, Dawn Owens, Karen Stendal, Alvin Tarrell, Adeola Wale-Kolade, Sofi Westin, Ilze Zigurs

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

Research collaboration has become increasingly global, as collaboration technologies continue to advance and as research problems become more interdisciplinary and global. Virtual research teams have processes and challenges that are unique from a typical virtual team, and we need a better understanding of how such teams can utilize virtual research environments to their advantage. We examine this question from a review of the relevant literature and an analysis of experiences and reflections from a doctoral seminar that studied and experienced the process of virtual research collaboration.

Parallel Adaptive Algorithms For Sampling Large Scale Networks, Kanimathi Duraisamy

Student Work

The study of real-world systems, represented as networks, has important application in many disciplines including social sciences [1], bioinformatics [2] and software engineering [3]. These networks are extremely large, and analyzing them is very expensive. Our research work involves developing parallel graph sampling methods for efficient analysis of gene correlation networks. Our sampling algorithms maintain important structural and informational properties of large unstructured networks. We focus on preserving the relative importance, based on combinatorial metrics, rather than the exact measures. We use a special subgraph technique, based on finding triangles called maximal chordal subgraphs, which maintains the highly connected portions …

Wraps – A System For Determining The Probability Of Prokaryotic Protein Annotation Correctness, Benjamin K. Nelson

Student Work

Advances in sequencing technology have resulted in the sequencing of whole genomes from many simple organisms such as fungi and bacteria, while allowing the assembly of much more complex genomes like humans and chimpanzees. Consequently, association of segments of newly sequenced genomes to specific function (i.e. annotation) is being completed by comparative study of protein coding regions from previously annotated genome data. While this is an ideal procedure to process and annotate huge number of available genomic sequences, this approach can potentially lead to propagating erroneous annotation in a public sequence repository and vastly diminish the integrity of these new …

Architecture-Based Reliability Analysis Of Web Services, Cobra Mariam Rahmani

Student Work

In a Service Oriented Architecture (SOA), the hierarchical complexity of Web Services (WS) and their interactions with the underlying Application Server (AS) create new challenges in providing a realistic estimate of WS performance and reliability. The current approaches often treat the entire WS environment as a black-box. Thus, the sensitivity of the overall reliability and performance to the behavior of the underlying WS architectures and AS components are not well-understood. In other words, the current research on the architecture-based analysis of WSs is limited.

This dissertation presents a novel methodology for modeling the reliability and performance of web services. WSs …

Taxonomic Classification Of Media Reports In The Cyber Attack Domain, Jinhua Zhang

Student Work

Cyber-attacks have become a huge threat to the information age. In a previous study, cyber-attacks associated with events in Social, Political, Economic and Cultural (SPEC) dimensions were analyzed [6]. The task of this research is to construct an automated classifier that can classify media reports related to past and current cyber-attack events according to the SPEC taxonomy. The classifier was built on a machine learning principle incorporated with approaches focused on 1) document indexing; 2) calculation of classification thresholds; 3) definition of classification effectiveness; and 4) calculation of precision and recall. The classifier is expected to perform with acceptable effectiveness …

Weighted-Sequence Problem: Asp Vs Casp And Declarative Vs Problem-Oriented Solving, Yuliya Lierler, Shaden Smith

Computer Science Faculty Proceedings & Presentations

Search problems with large variable domains pose a challenge to current answer-set programming (ASP) systems as large variable domains make grounding take a long time, and lead to large ground theories that may make solving infeasible. To circumvent the “grounding bottleneck” researchers proposed to integrate constraint solving techniques with ASP in an approach called constraint ASP (CASP). In the paper, we evaluate an ASP system clingo and a CASP system clingcon on a handcrafted problem involving large integer domains that is patterned after the database task of determining the optimal join order. We find that search methods used by clingo …

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.