Digital Commons Network^™

Hierarchical Fuzzy Logic System For Implementing Maintenance Schedules Of Offshore Power Systems, C. S. Chang, Zhaoxia Wang, Fan Yang, W. W. Tan

Research Collection School Of Computing and Information Systems

Smart grid provides the technology for modernizing electricity delivery systems by using distributed and computer-based remote sensing, control and automation, and two-way communications. Potential benefits of the technology are that the smart grid's central control will now be able to control and operate many remote power plant, optimize the overall asset utilization and operational efficiently. In this paper, we propose an innovative approach for the smart grid to handle uncertainties arising from condition monitoring and maintenance of power plant. The approach uses an adaptive maintenance advisor and a system-maintenance optimizer for designing/implementing optimized condition-based maintenance activities, and collectively handles operational …

Improved Duplicate Bug Report Identification, Yuan Tian, Chengnian Sun, David Lo

Research Collection School Of Computing and Information Systems

Bugs are prevalent in software systems. To improve the reliability of software systems, developers often allow end users to provide feedback on bugs that they encounter. Users could perform this by sending a bug report in a bug report management system like Bugzilla. This process however is uncoordinated and distributed, which means that many users could submit bug reports reporting the same problem. These are referred to as duplicate bug reports. The existence of many duplicate bug reports may cause much unnecessary manual efforts as often a triager would need to manually tag bug reports as being duplicates. Recently, there …

Commit Patterns And Threats To Validity In Analysis Of Open Source Software Repositories, Alexander Curtis Maclean

Theses and Dissertations

In the course of studying the effects of programming in multiple languages, we unearthed troubling trends in SourceForge artifacts. Our initial studies suggest that programming in multiple languages concurrently negatively affects developer productivity. While addressing our initial question of interest, we discovered a pattern of monolithic commits in the SourceForge community. Consequently, we also report on the effects that this pattern of commits can have when using SourceForge as a data-source for temporal analysis of open source projects or for studies of individual developers.

Manipulation Of Online Reviews: An Analysis Of Ratings, Readability, And Sentiments, Nan Hu, Indranil Bose, Noi Sian Koh, Ling Liu

Research Collection School Of Computing and Information Systems

As consumers become increasingly reliant on online reviews to make purchase decisions, the sales of the product becomes dependent on the word of mouth (WOM) that it generates. As a result, there can be attempts by firms to manipulate online reviews of products to increase their sales. Despite the suspicion on the existence of such manipulation, the amount of such manipulation is unknown, and deciding which reviews to believe in is largely based on the reader's discretion and intuition. Therefore, the success of the manipulation of reviews by firms in generating sales of products is unknown. In this paper, we …

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 …

Emotion Detection In Suicide Notes Using Maximum Entropy Classification, Richard H. Wicentowski, M. R. Sydes

Computer Science Faculty Works

An ensemble of supervised maximum entropy classifiers can accurately detect and identify sentiments expressed in suicide notes. Using lexical and syntactic features extracted from a training set of externally annotated suicide notes, we trained separate classifiers for each of fifteen pre-specified emotions. This formed part of the 2011 i2b2 NLP Shared Task, Track 2. The precision and recall of these classifiers related strongly with the number of occurrences of each emotion in the training data. Evaluating on previously unseen test data, our best system achieved an F 1 score of 0.534.

Run Your Research: On The Effectiveness Of Lightweight Mechanization, Casey Klein, John Clements, Christos Dimoulas, Carl Eastlund, Matthias Felleisen, Matthew Flatt, Jay A. Mccarthy, Jon Rafkind, Sam Tobin-Hochstadt, Robert Bruce Findler

Computer Science and Software Engineering

Formal models serve in many roles in the programming language community. In its primary role, a model communicates the idea of a language design; the architecture of a language tool; or the essence of a program analysis. No matter which role it plays, however, a faulty model doesn't serve its purpose.

One way to eliminate flaws from a model is to write it down in a mechanized formal language. It is then possible to state theorems about the model, to prove them, and to check the proofs. Over the past nine years, PLT has developed and explored a lightweight version …

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 …

A Scalable Distributed Syntactic, Semantic And Lexical Language Model, Ming Tan, Wenli Zhou, Lei Zheng, Shaojun Wang

Kno.e.sis Publications

This paper presents an attempt at building a large scale distributed composite language model that is formed by seamlessly integrating an n-gram model, a structured language model, and probabilistic latent semantic analysis under a directed Markov random field paradigm to simultaneously account for local word lexical information, mid-range sentence syntactic structure, and long-span document semantic content. The composite language model has been trained by performing a convergent N-best list approximate EM algorithm and a follow-up EM algorithm to improve word prediction power on corpora with up to a billion tokens and stored on a supercomputer. The large scale distributed composite …

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.

Correct Reasoning: Essays On Logic-Based Ai In Honour Of Vladimir Lifschitz, Esta Erdem, Joohyung Lee, Yuliya Lierler, David Pearce

Faculty Books and Monographs

Co-edited by Yuliya Lierler, UNO faculty member.

Essay, Parsing Combinatory Categorial Grammar via Planning in Answer Set Programming, co-authored by Yuliya Lierler, UNO faculty member.

This Festschrift published in honor of Vladimir Lifschitz on the occasion of his 65th birthday presents 39 articles by colleagues from all over the world with whom Vladimir Lifschitz had cooperation in various respects. The 39 contributions reflect the breadth and the depth of the work of Vladimir Lifschitz in logic programming, circumscription, default logic, action theory, causal reasoning and answer set programming.

Object Recognition Based On Shape And Function: Inspired By Children's Word Acquisition, Akihiro Eguchi

Inquiry: The University of Arkansas Undergraduate Research Journal

This paper explores a new approach to computational object recognition by borrowing an idea from child language acquisition studies in developmental psychology. Whereas previous image recognition research used shape to recognize and label a target object, the model proposed in this study added the function of the object resulting in a more accurate recognition. This study makes use of new gaming technology, Microsoft’s Kinect, in implementing the proposed new object recognition model. A demonstration of the model developed in this project properly infers different names for similarly shaped objects and the same name for differently shaped objects.

Algorithms For Community Identification In Complex Networks, Mahadevan Vasudevan

Electronic Theses and Dissertations

First and foremost, I would like to extend my deepest gratitude to my advisor, Professor Narsingh Deo, for his excellent guidance and encouragement, and also for introducing me to this wonderful science of complex networks. Without his support this dissertation would not have been possible. I would also like to thank the members of my research committee, professors Charles Hughes, Ratan Guha, Mainak Chatterjee and Yue Zhao for their advice and guidance during the entire process. I am indebted to the faculty and the staff of the Department of Electrical Engineering and Computer Science for providing me the resources and …

Simulation Visualization Rhetoric And It's Practical Implications, D'An Knowles Ball, Andrew J. Collins

Engineering Management & Systems Engineering Faculty Publications

Modeling and simulation has moved far beyond simple data representation into the world of visual communication over the past 15 years; ultimately, the acceptance of M&S within mainstream science and society will depend on the results that are produced visually. A simulation’s function is of primary importance to its end result, but it cannot be denied that the discipline of M&S now prizes fancy graphics to communicate. Rhetorical methodological decisions have the greatest impact on the end user, and considerations that bring visual rhetoric to modeling and simulation should be examined as a necessity to application. This paper will expose …

Beefmoves: Dissemination, Diversity, And Dynamics Of English Borrowings In A German Hip Hop Forum, Matt Garley, Julia Hockenmaier

Publications and Research

We investigate how novel English-derived words (anglicisms) are used in a German-language Internet hip hop forum, and what factors contribute to their uptake.

Storyspace: A Story-Driven Approach For Creating Musuem Narratives, Annika Wolff, Paul Mulholland, Tevor Collins

Publications

In a curated exhibition of a museum or art gallery, a selection of heritage objects and associated information is presented to a visitor for the purpose of telling a story about them. The same underlying story can be presented in a number of different ways. This paper describes techniques for creating multiple alternative narrative structures from a single underlying story, by selecting different organising principles for the events and plot structures of the story. These authorial decisions can produce different dramatic effects. Storyspace is a web interface to an ontology for describing curatorial narratives. We describe how the narrative component …

Effects Of Diacritics On Turkish Information Retrieval, Adi̇l Alpkoçak, Meltem Ceylan

Turkish Journal of Electrical Engineering and Computer Sciences

We investigate the effects of improper use of diacritics in the Turkish alphabet on information retrieval. A diacritic is simply a supplementary sign added to a letter to change the sound value of the letter, and the Turkish alphabet has 5 special letters derived from Latin by adding different diacritics. The statistical analysis performed in this study shows that retrieval performance significantly decreases when documents and queries contain letters with different forms, such that documents consist of letters with diacritics while queries consist of standard Latin letters and vice versa. In order to tackle this challenge, we propose 3 approaches: …

A Comparative Study Of Blind And Nonblind Trainings In A Single-Carrier Wimax (Ieee 802.16-2004) Radio, Ali̇ Özen

Turkish Journal of Electrical Engineering and Computer Sciences

Experimental and theoretical bit error rate performance evaluations of blind and nonblind training techniques are obtained by using a single-carrier WiMAX (IEEE 802.16-2004) radio for high-order quadrature amplitude modulation channels. Instead of using a certain type of channel profile, this study concentrates on true frequency-selective Rayleigh fading channels and also evaluates the fast fading scenario of Rayleigh channels in a real-time WiMAX radio environment around 3.5 GHz. The popular least mean squares (LMS) learning algorithm and constant modulus learning algorithm (CMA) are used as benchmarks in an investigation of nonblind and blind trainings, namely recursive least squares (RLS), modified-CMA, normalized-CMA, …

Cascade Fuzzy Logic Control Of A Single-Link Flexible-Joint Manipulator, İsmai̇l Hakki Akyüz, Zafer Bi̇ngül, Selçuk Ki̇zi̇r

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents the design and control of a single-link flexible-joint robot manipulator. A cascade fuzzy logic controller (FLC) was used to remove link vibrations and to obtain fast trajectory tracking performance. The cascade FLC structure includes 3 different FLCs. The input variables of the first and the second FLCs are the motor rotation angle error, its derivative, and the end-point deflection error its derivative, respectively. The outputs of these controllers are the inputs of the third FLC, which yields the control signal to the flexible robot arm. All of the FLCs were embedded in a DS1103 real-time control board. …

Broken Rotor Bar Fault Detection In Inverter-Fed Squirrel Cage Induction Motors Using Stator Current Analysis And Fuzzy Logic, Mehmet Akar, İlyas Çankaya

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents the implementation of broken rotor bar fault detection in an inverter-fed induction motor using motor current signal analysis (MCSA) and prognosis with fuzzy logic. Recently, inverter-fed induction motors have become very popular because of their adjustable speed drive. They have been used in many vital control applications such as rolling mills, variable speed compressors, pumps, and fans. The condition monitoring of these motors can significantly reduce the cost of maintenance in the early detection of faults. In this study, MCSA is applied to an inverter-fed induction motor to detect broken rotor bar faults. The diagnosis of a …

Model Selection And Score Normalization For Text-Dependent Single Utterance Speaker Verification, Osman Büyük, Mustafa Levent Arslan

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we investigate model selection and channel variability issues on a text-dependent single utterance (TDSU) speaker verification application. Due to the lack of an appropriate database for the task, a multichannel speaker recognition database, which consists of multiple recordings of a single Turkish utterance, is collected. The first set of experiments is devoted to model selection. Phonetic hidden Markov model (HMM)-based, sentence HMM-based, and Gaussian mixture model (GMM)-based methods are compared to find the most appropriate modeling approach for the target application. Based on the experimental results, the HMM-based methods outperform the GMM. The sentence HMM yields the …

Using A Game-Based Learning Model As A New Teaching Strategy For Computer Engineering, Kristijan Kuk, Dragica Jovanovic, Dusan Jokanovic, Petar Spalevic, Marko Caric, Stefan Panic

Turkish Journal of Electrical Engineering and Computer Sciences

Interactive multimedia simulations and computer game elements can be successfully combined in order to create new advanced educational resources for teaching today's generation of students. Such a learning environment, a game-based learning model (GBLm), has been designed as a research prototype. This paper describes one type of GBLm for computer engineering, which we have used in the subject of computer graphics for the teaching unit Z-buffer algorithm, in order to facilitate the learning process. The implementation of a GBLm for graphical algorithms (GBL4CAl) is presented in detail as a multimedia interactive learning module designed to motivate students by making learning …

Ontology Management For Universities, Roland Böving

Theses

What is the 'knowledge' of a university? It is the sum of all experiences and all contributions of students and staff. Knowledge ultimately exists, among other things, in the form of theses, articles, lectures and research reports. The largest knowledge pool of a university is made up, however, of the knowledge and expertise of every single member of the university. As a result of the high rate of turnover of people, knowledge and expertise are on the one hand constantly being lost, but this is replaced by a fresh intake of upcoming young students and lecturers reflecting the spirit of …

Semantic Inference On Heterogeneous E-Marketplace Activities, Jingzhi Guo, Lida Xu, Zhiguo Gong, Chin-Pang Che, Sohail S. Chaudry

Information Technology & Decision Sciences Faculty Publications

An electronic marketplace (e-marketplace) is a common business information space populated with many entities of different system types. Each of them has its own context of how to process activities. This leads to heterogeneous e-marketplace activities, which are difficult to make interoperable and inferred from one entity to another. This study solves this problem by proposing a concept of separation strategy and implementing it through providing a semantic inference engine with a novel inference algorithm. The solution, called the RuleXPM approach, enables one to semantically infer a next e-marketplace activity across multiple contexts/domains. Experiments show that the cross-context/cross-domain semantic inference …

Assessing Metacognitive Skills Using Adaptive Neural Networks, Anderson Justin, Kouider Mokhtari, Arun Kulkarni

Computer Science Faculty Publications and Presentations

The assessment of student's levels of metacognitive knowledge and skills is critical in determining their ability to effectively perform complex cognitive tasks such as solving mathematics or reading comprehension problems. In this paper, we use an adaptive multiplayer perceptron model to categorize participants based on their metacognitive awareness and perceived use of reading strategies while reading. Eight hundred and sixty-five middle school students participated in the study. All participants completed a 30-item instrument- the Metacognitive Awareness-of-Reading Strategies Inventory (MARSI). We used adaptive multi-layer perceptron models to classify participants into three groups based on their metacognitive strategy awareness levels using thirteen …

A Tarskian Informal Semantics For Answer Set Programming, Marc Denecker, Yuliya Lierler, Miroslaw Truszczyński, Joost Vennekens

Computer Science Faculty Proceedings & Presentations

In their seminal papers on stable model semantics, Gelfond and Lifschitz introduced ASP by casting programs as epistemic theories, in which rules represent statements about the knowledge of a rational agent. To the best of our knowledge, theirs is still the only published systematic account of the intuitive meaning of rules and programs under the stable semantics. In current ASP practice, however, we find numerous applications in which rational agents no longer seem to play any role. Therefore, we propose here an alternative explanation of the intuitive meaning of ASP programs, in which they are not viewed as statements about …

Surviving Solver Sensitivity: An Asp Practitioner’S Guide, Bryan Silverthorn, Yuliya Lierler, Marius Schneider

Computer Science Faculty Proceedings & Presentations

Answer set programming (ASP) is a declarative programming formalism that allows a practitioner to specify a problem without describing an algorithm for solving it. In ASP, the tools for processing problem specifications are called answer set solvers. Because specified problems are often NP complete, these systems often require significant computational effort to succeed. Furthermore, they offer different heuristics, expose numerous parameters, and their running time is sensitive to the configuration used. Portfolio solvers and automatic algorithm configuration systems are recent attempts to automate the problem of manual parameter tuning, and to mitigate the burden of identifying the right solver configuration. …

Security Specialists Are From Mars; Healthcare Practitioners Are From Venus: The Case For A Community-Of-Practice Approach To Security Architectures For Healthcare, Elizabeth Coles-Kemp, Patricia Williams

Australian eHealth Informatics and Security Conference

Information security is a necessary requirement of information sharing in the healthcare environment. Research shows that the application of security in this setting is sometimes subject to work-arounds where healthcare practitioners feel forced to incorporate practices that they have not had an input into and with which they have not engaged with. This can result in a sense of security practitioners and healthcare practitioners being culturally very different in their approach to information systems. As a result such practices do not constitute part of their community of practice nor their identity. In order to respond to this, systems designers typically …

Direct Optimization Of Ranking Measures For Learning To Rank Models, Li Li Guo

Browse all Theses and Dissertations

The main challenge in learning-to-rank for information retrieval is the difficulty to di- rectly optimize ranking measures to automatically construct a ranking model from training data. It is mainly due to the fact that the ranking measures are determined by the order of ranked documents rather than the specific values of ranking model scores, thus they are non-convex, nondifferentiable and discontinuous. To address this issue, listwise approaches have been proposed where loss functions are defined either by exploiting a probabilistic model or by optimizing upper bounds or smoothed approximations of ranking measures. Even though very promising results have been achieved, …