Digital Commons Network^™

Modeling Human Group Behavior In Virtual Worlds, Fahad Shah

Electronic Theses and Dissertations

Virtual worlds and massively-multiplayer online games are rich sources of information about large-scale teams and groups, offering the tantalizing possibility of harvesting data about group formation, social networks, and network evolution. They provide new outlets for human social interaction that differ from both face-to-face interactions and non-physically-embodied social networking tools such as Facebook and Twitter. We aim to study group dynamics in these virtual worlds by collecting and analyzing public conversational patterns of users grouped in close physical proximity. To do this, we created a set of tools for monitoring, partitioning, and analyzing unstructured conversations between changing groups of participants …

Two-Language, Two-Paradigm Introductory Computing Curriculum Model And Its Implementation, Vladimir Zanev, Atanas Radenski

Mathematics, Physics, and Computer Science Faculty Articles and Research

This paper analyzes difficulties with the introduction of object-oriented concepts in introductory computing education and then proposes a two-language, two-paradigm curriculum model that alleviates such difficulties. Our two-language, two-paradigm curriculum model begins with teaching imperative programming using Python programming language, continues with teaching object-oriented computing using Java, and concludes with teaching object-oriented data structures with Java.

Determining A Patient Recovery From A Total Knee Replacement Using Fuzzy Logic And Active Databases, Robert Azarbod

All Graduate Theses, Dissertations, and Other Capstone Projects

The purpose of the knowledge-based system is to predict the rehabilitation timeline of a patient in physical therapy for a total knee replacement. All patients have various attributes that contribute to their rehabilitation rate such as: weight, gender, smoking habit, medications, physical ability, or other medical problems. A combination of any one or several of these attributes will affect the recovery process. The proposed FRTP (Fuzzy Rehabilitation Timeline Predictor) is a fuzzy data mining model that can predict the recovery length of a patient in physical therapy for a total knee replacement and provide feedback to experts for revision of …

A Web Based Fuzzy Data Mining Using Combs Inference Method And Decision Predictor, Shajia Akhter Sharmin

All Graduate Theses, Dissertations, and Other Capstone Projects

Fuzzy logic has become a very popular method of reasoning a system with approximate input system instead of a precise one. When qualitative variables are used to determine the decisions then we have to create some specific functions where the membership values of the input can be any number between 0 to 1 instead of 1 or 0 which is used in binary logic. When number of input attribute increases it the combinatorial rules increases exponentially, and diminishes performance of the system. The problem is generally known as “combinatorial rule explosion”. The Information Technology Department of Minnesota State University, Mankato …

Scholarship In International Technical Communication, 1950-1989: A Historical Study, Xiaoyan Huang

Masters Theses

"This thesis is a study of the published scholarship in international technical communication from 1950 to 1989. It provides insight into the four decades' worth of scholarship as well as a resource for the development of present and future scholarship in international technical communication. It attempts to answer the following research questions: What did scholars of international technical communication study in each decade? What are the similarities and differences among the four decades in terms of scholarship in international technical communication? What are the strengths and weaknesses of the relevant scholarship in the four decades? What can we learn from …

Security Risk Management: A Psychometric Map Of Expert Knowledge Structure, David Brooks

Research outputs 2011

The security industry operates within a diverse and multi-disciplined knowledge base, with risk management as a fundamental knowledge domain within security to mitigate its risks. Nevertheless, there has been limited research in understanding and mapping security expert knowledge structures within security risk management to consider if parts of security risk management are unique from more general risk management. This interpretive study applied a technique of multidimensional scaling (MDS) to develop and present a psychometric map within the knowledge domain of security risk management, validated with expert interviews. The psychometric MDS security risk management concept map presented the expert knowledge structure …

A Strategy To Articulate The Facility Management Knowledge Categories Within The Built Environment, Robert Doleman, David J. Brooks

Australian Security and Intelligence Conference

Security is applied in the built environment and this requires a close relationship with facility managers. Therefore, this study puts forward an approach to establish the facility management knowledge categories within the built environment. In part, the significance of the study stemmed from research undertaken into the compliance to Australian fire door maintenance within nursing homes, which demonstrated 87 percent noncompliance. This high level of non-compliance appeared to identify a lack of facility management knowledge, among other issues (Doleman & Brooks, 2011). The article uses a method to test the supposition of facility management knowledge construct in a three-phase Grounded …

Applying Text Timing In Corporate Spin-Off Disclosure Statement Analysis: Understanding The Main Concerns And Recommendation Of Appropriate Term Weights, Aravindh Sekar

Masters Theses

"Text mining helps in extracting knowledge and useful information from unstructured data. It detects and extracts information from mountains of documents and allowing in selecting data related to a particular data.

In this study, text mining is applied to the 10-12b filings done by the companies during Corporate Spin-off. The main purposes are (1) To investigate potential and/or major concerns found from these financial statements filed for corporate spin-off and (2) To identify appropriate methods in text mining which can be used to reveal these major concerns.

10-12b filings from thirty-four companies were taken and only the "Risk Factors" category …

Optimization Of Textual Affect Entity Relation Models, Ajith Cherukad Jose

Masters Theses

"Affective computing is a recent research area in computer science which deals with the design and development of systems that can recognize, interpret and process human affects/emotions. Various research projects in the past have focused on affect sensing and processing raw textual data. One such research effort conducted at the Oak Ridge National Laboratory (ORNL) has introduced an affect propagation algorithm which can generate affective relationships between entities contained in a given textual document. The algorithm depends upon a set of real-valued numeric parameters for which the best possible values are unknown. This thesis describes three different contributions to ORNL's …

Automatic Annotation Of Referring Expression In Situated Dialogues, Niels Schütte, John D. Kelleher, Brian Mac Namee

Articles

To apply machine learning techniques to the production and interpretation of natural language, we need large amounts of annotated language data. Manual annotation, however, is an expensive and time consuming process since it involves human annotators looking at the data and explicitly adding information that is implicitly contained in the data, based on their judgment. This work presents an approach to automatically annotating referring expressions in situated dialogues by exploiting the interpretation of language by the participants in the dia- logue. We associate instructions concerning objects in the environment with automatically detected events involving these objects and predict the referents …

Visual Learning Styles Among Digital Natives, Eric Palmer

Department of Computer Graphics Technology Degree Theses

This study explored the concept of digital nativity and its educational implications, including application of the learning styles hypothesis. The concept of digital natives, first put forth by Marc Prensky, introduced the notion that individuals raised in a technological environment have developed in such a way as to utilize information differently than the non-native generations before them. This study examined the possibility that these differences may include an increased efficiency in the utilization of narrative imagery versus textual information. The potential benefit of utilizing narrative imagery as an instructional tool is discussed. An experimental test application was developed for the …

The Effect Of Interactive Technology On Informal Learning And Performance In A Social Setting, Timothy Clay Boileau

Wayne State University Dissertations

This study is based on a qualitative multiple case study research design using a mixed methods approach to provide insight into the effect of interactive technology on informal learning and performance in a social business setting inhabited by knowledge workers. The central phenomenon examined is the variance in behavioral intention towards interactive Web 2.0 technologies in learning and performance-related activities, depending on social and cultural setting, observable in individual and group usage patterns.

The theoretical foundation for this study is drawn primarily from the activity theory model developed by Engeström (1987) and related research enabled by an ongoing review of …

Semi-Supervised Contrafold For Rna Secondary Structure Prediction: A Maximum Entropy Approach, Jianping Feng

Browse all Theses and Dissertations

A novel probabilistic discriminative model based on conditional random fields, CONTRAfold, has recently been proposed for single sequence RNA secondary structure prediction. By incorporating most of the features which closely mirror the local interaction terms of thermodynamics-based models, the CONTRAfold model has outperformed both probabilistic and physics-based techniques, and received the highest single sequence prediction accuracies. CONTRAfold, like most other RNA secondary structure prediction techniques, requires a collection of RNA sequences with known secondary structure to serve as training data for the algorithm. Manual annotation of RNA sequences is both expensive and time-consuming, and there remains a great deal more …

Seniors Language Paradigms: 21st Century Jargon And The Impact On Computer Security And Financial Transactions For Senior Citizens, David M. Cook, Patryk Szewczyk, Krishnun Sansurooah

Australian Information Security Management Conference

Senior Citizens represent a unique cohort of computer users insomuch as they have come to the field of computer usage later in life, as novices compared to other users. As a group they exhibit a resentment, mistrust and ignorance towards cyber related technology that is born out of their educational and social experiences prior to widespread information technology. The shift from analogue to digital proficiency has been understated for a generation of citizens who were educated before computer usage and internet ubiquity. This paper examines the language difficulties encountered by senior citizens in attempting to engage in banking and communications …

Development Of An Instrument To Measure The Adoption Of Mobile Services, Shang Gao, John Krogstie, Keng Siau

Research Collection School Of Computing and Information Systems

Currently, there is no standard instrument for measuring user adoption of mobile services. Based on the mobile service acceptance model, this paper reports on the development of a survey instrument designed to measure user perception on mobile services acceptance. A survey instrument was developed by using some existing scales from prior instruments and by creating additional items which might appear to fit the construct definitions. In addition, a pilot study was conducted by distributing the survey to 25 users of a mobile service called Mobile Student Information Systems. As a result, a survey instrument containing 22 items were retained. Furthermore, …

Specification Of Data Properties To Identify Anomalies In Scientific Sensor Data, Irbis Gallegos

Open Access Theses & Dissertations

Environmental scientists use advanced sensor technology such as meteorological towers, wireless sensor networks and robotic trams equipped with sensors to perform data collection at remote research sites. Because the amount of environmental sensor data acquired by such instruments is increasing, the ability to evaluate the accuracy of the data at collection time and to check that the instrumentation is operating correctly become critical in order to not lose valuable time and information. The goal of the research is to define a solution, based on software-engineering techniques, to support the scientist's ability to specify data properties that can identify anomalies in …

Modularizing Crosscutting Concerns In Software, Nalin Saigal

USF Tampa Graduate Theses and Dissertations

Code modularization provides benefits throughout the software life cycle; however, the presence of crosscutting concerns (CCCs) in software hinders its complete modularization. Traditional modularization techniques work well under the assumption that code being modularized is functionally orthogonal to the rest of the code; as a result, software engineers try to separate code segments that are orthogonal in their functionality into distinct modules. However, in practice, software does not decompose neatly into modules with distinct, orthogonal functionality. In this thesis, we investigate the modularization of CCCs in software using two different techniques.

Firstly, we discuss IVCon, a GUI-based tool that provides …

A Review Of Situation Identification Techniques In Pervasive Computing, Juan Ye, Simon Dobson, Susan Mckeever

Conference papers

No abstract provided.

Examining The Use Of Collocations In Natural Language Processing, Patrick Anthony Burke

Dissertations and Theses @ UNI

Studies in Natural Language Processing are often dedicated to defining the lexicon and grammar rules of individual languages. It is a common understanding that virtually all statements that a language user encounters are unique constructions that have never been seen before. Because of this, there has been very little modem research regarding the use of repeated language when attempting to provide computers with language processing functionality. It seems reasonable that most statements we use on a daily basis are completely new when they are evaluated in their entirely. However, it is possible that smaller portions of these statements are reused. …

An Analysis And Comparison Of Predominant Word Sense Disambiguation Algorithms, David J. Craggs

Theses : Honours

This thesis investigates research performed in the area of natural language processing. It is the aim of this research to compare a selection of predominant word sense disambiguation algorithms, and also determine if they can be optimised by small changes to the parameters used by the algorithms. To perform this research, several word sense disambiguation algorithms will be implemented in Java, and run on a range of test corpora. The algorithms will be judged on metrics such as speed and accuracy, and any other results obtained; while an algorithm may be fast and accurate, there may be other factors making …

Enhancing Automated Red Teaming With Monte Carlo Tree Search, Daniel Beard

Theses : Honours

This study has investigated novel Automated Red Teaming methods that support replanning. Traditional Automated Red Teaming (ART) approaches usually use evolutionary computing methods for evolving plans using simulations. A drawback of this method is the inability to change a team’s strategy part way through a simulation. This study focussed on a Monte-Carlo Tree Search (MCTS) method in an ART environment that supports re-planning to lead to better strategy decisions and a higher average score

User Experiments Of A Social, Faceted Multimedia Classification System, Liuliu Fu, Kurt Maly, Elizabeth Rasnick, Harris Wu, Mohammad Zubair

Computer Science Faculty Publications

Internet document sharing systems such as Flickr store billions of user-contributed images. Many collections on the Web contain large numbers of multimedia objects such as images. While such systems are designed to encourage user contributions and sharing, they are not well-organized collections on any given subject and are not easy to browse for specific subject matters. We have built a system that systematically organizes a large multimedia collection into an evolving faceted classification. This paper discusses the evaluation of such a system through a number of usage studies in a university setting.

Concept-Driven Multi-Modality Fusion For Video Search, Xiao-Yong Wei, Yu-Gang Jiang, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

As it is true for human perception that we gather information from different sources in natural and multi-modality forms, learning from multi-modalities has become an effective scheme for various information retrieval problems. In this paper, we propose a novel multi-modality fusion approach for video search, where the search modalities are derived from a diverse set of knowledge sources, such as text transcript from speech recognition, low-level visual features from video frames, and high-level semantic visual concepts from supervised learning. Since the effectiveness of each search modality greatly depends on specific user queries, prompt determination of the importance of a modality …

The Role Of Contextual Associations In The Selection Of Objects, Noah Patrick Sulman

USF Tampa Graduate Theses and Dissertations

This paper describes a sequence of experiments addressing basic questions about the control of visual attention and the relationship between attention and object recognition. This work reviews compelling findings addressing attentional control on the basis of high-level perceptual properties. In five experiments observers were presented with a rapid sequence of object photographs and instructed to either detect or selectively encode a verbally cued object category. When these object categories (e.g. "baseball") were preceded by contextual images associated with a given object category (e.g. "baseball diamond"), observers were less likely to accurately report information about the target item. This effect obtained …

Combining Natural Language Processing And Statistical Text Mining: A Study Of Specialized Versus Common Languages, Jay Jarman

USF Tampa Graduate Theses and Dissertations

This dissertation focuses on developing and evaluating hybrid approaches for analyzing free-form text in the medical domain. This research draws on natural language processing (NLP) techniques that are used to parse and extract concepts based on a controlled vocabulary. Once important concepts are extracted, additional machine learning algorithms, such as association rule mining and decision tree induction, are used to discover classification rules for specific targets. This multi-stage pipeline approach is contrasted with traditional statistical text mining (STM) methods based on term counts and term-by-document frequencies. The aim is to create effective text analytic processes by adapting and combining individual …

Design Of Multi Agent Based Crowd Injury Model, Emin Kugu

Electrical & Computer Engineering Theses & Dissertations

A major concern of many government agencies is to predict and control the behavior of crowds in different situations. Many times such gatherings are legal, legitimate, and peaceful. But there are times when they can turn violent, run out of control, result in material damages and even casualties. It then becomes the duty of governments to bring them under control using a variety of techniques, including non-lethal and lethal weapons, if necessary.

In order to aid decision makers on the course of action in crowd control, there are modeling and simulation tools that can provide guidelines by giving programmed rules …

Semantic Enrichment Of Text Representation With Wikipedia For Text Classification, Hiroki Yamakawa, Jing Peng, Anna Feldman

Department of Computer Science Faculty Scholarship and Creative Works

Text classification is a widely studied topic in the area of machine learning. A number of techniques have been developed to represent and classify text documents. Most of the techniques try to achieve good classification performance while taking a document only by its words (e.g. statistical analysis on word frequency and distribution patterns). One of the recent trends in text classification research is to incorporate more semantic interpretation in text classification, especially by using Wikipedia. This paper introduces a technique for incorporating the vast amount of human knowledge accumulated in Wikipedia into text representation and classification. The aim is to …

Pattern Extraction From The World Wide Web, Praveena Mettu

UNLV Theses, Dissertations, Professional Papers, and Capstones

The World Wide Web is a source of huge amount of unlabeled information spread across different sources in varied formats. This presents us with both opportunities and challenges in leveraging such large amount of unstructured data to build knowledge bases and to extract relevant information.

As part of this thesis, a semi-supervised logistic regression model called “Dual Iterative Pattern Relation Extraction” proposed by Sergey Brin is selected for further investigation. DIPRE presents a technique which exploits the duality between sets of patterns and relations to grow the target relation starting from a small sample.

This project built in JAVA using …

Automobile Exhaust Gas Detection Based On Fuzzy Temperature Compensation System, Zhiyong Wang, Hao Ding, Fufei Hao, Zhaoxia Wang, Zhen Sun, Shujin Li

Research Collection School Of Computing and Information Systems

A temperature compensation scheme of detecting automobile exhaust gas based on fuzzy logic inference is presented in this paper. The principles of the infrared automobile exhaust gas analyzer and the influence of the environmental temperature on analyzer are discussed. A fuzzy inference system is designed to improve the measurement accuracy of the measurement equipment by reducing the measurement errors caused by environmental temperature. The case studies demonstrate the effectiveness of the proposed method. The fuzzy compensation scheme is promising as demonstrated by the simulation results in this paper.

Barriers To Computer Use And Internet Competency Among Homeless Women And Low-Income Women At Risk Of Becoming Homeless, Sondra L. Wildman

Communication & Leadership Dissertations and Theses

As our society relies more and more on digital communication methods, the consequences of not having access to computers and the internet will further erode the ability of homeless women to effectively navigate mainstream venues for social and economic interaction. This study strives to explore the barriers that prevent homeless women, and low-income women at risk of becoming homeless, from optimizing their access to computer and internet resources. A group of fifty homeless women was observed using a computer lab at a daytime shelter, and of this group, five women were interviewed. The theoretical framework of the study utilizes Pierre …