Computer Sciences Commons^™

Challenges In Developing Applications For Aging Populations, Drew Marie Williams, Md O. Gani, Ivor D. Addo, Akm Jahangir Alam Majumder, Chandana Tamma, Mong-Te Wang, Chih-Hung Chang, Sheikh Iqbal Ahamed, Cheng-Chung Chu

Mathematics, Statistics and Computer Science Faculty Research and Publications

Elderly individuals can greatly benefit from the use of computer applications, which can assist in monitoring health conditions, staying in contact with friends and family, and even learning new things. However, developing accessible applications for an elderly user can be a daunting task for developers. Since the advent of the personal computer, the benefits and challenges of developing applications for older adults have been a hot topic of discussion. In this chapter, the authors discuss the various challenges developers who wish to create applications for the elderly computer user face, including age-related impairments, generational differences in computer use, and the …

Cameron-Liebler Line Classes And Partial Difference Sets, Uthaipon Tantipongipat

Honors Theses

The work consists of three parts. The first is a study of Cameron-Liebler line classes which receive much attention recently. We studied a new construction of infinite family of Cameron-Liebler line classes presented in the paper by Tao Feng, Koji Momihara, and Qing Xiang (rst introduced in 2014), and summarized our attempts to generalize this construction to discover any new Cameron-Liebler line classes or partial difference sets (PDSs) resulting from the Cameron-Liebler line classes. The second is our approach to finding PDS in non-elementary abelian groups. Our attempt eventually led to the same general construction of PDS presented in John …

Nonexistence Of Nonquadratic Kerdock Sets In Six Variables, John Clikeman

Honors Theses

Kerdock sets are maximally sized sets of boolean functions such that the sum of any two functions in the set is bent. This paper modifies the methodology of a paper by Phelps (2015) to the problem of finding Kerdock sets in six variables containing non-quadratic elements. Using a computer search, we demonstrate that no Kerdock sets exist containing non-quadratic six- variable bent functions, and that the largest bent set containing such functions has size 8.

Care-Chair: Opportunistic Health Assessment With Smart Sensing On Chair Backrest, Rakesh Kumar

Masters Theses

"A vast majority of the population spend most of their time in a sedentary position, which potentially makes a chair a huge source of information about a person's daily activity. This information, which often gets ignored, can reveal important health data but the overhead and the time consumption needed to track the daily activity of a person is a major hurdle. Considering this, a simple and cost-efficient sensory system, named Care-Chair, with four square force sensitive resistors on the backrest of a chair has been designed to collect the activity details and breathing rate of the users. The Care-Chair system …

Automated Design Of Boolean Satisfiability Solvers Employing Evolutionary Computation, Alex Raymond Bertels

Masters Theses

"Modern society gives rise to complex problems which sometimes lend themselves to being transformed into Boolean satisfiability (SAT) decision problems; this thesis presents an example from the program understanding domain. Current conflict-driven clause learning (CDCL) SAT solvers employ all-purpose heuristics for making decisions when finding truth assignments for arbitrary logical expressions called SAT instances. The instances derived from a particular problem class exhibit a unique underlying structure which impacts a solver's effectiveness. Thus, tailoring the solver heuristics to a particular problem class can significantly enhance the solver's performance; however, manual specialization is very labor intensive. Automated development may apply hyper-heuristics …

Composite Model Representation For Computer Aided Design Of Functionally Gradient Materials, Fangquan Wang

Masters Theses

"Functionally Gradient Materials (FGMs) feature smooth transition from one material to another within a single object. FGMs modeling is considered to be one of the new challenges in Computer Aided Design (CAD) area. To overcome this challenge, this thesis presents a composite approach to model FGMs. The input in STL format can be meshed and voxelized in FGMs modeling system. The material composition in each voxel can be generated from multiple different types of control features. And LTI filters including Gaussian Filter and Average Filter are applied to blur default material features in order to generate FGMs inside models. The …

In God We Trust. All Others Must Bring Data. - W. Edwards Deming Using Word Embeddings To Recognize Idioms, Jing Peng, Anna Feldman

Department of Computer Science Faculty Scholarship and Creative Works

Expressions, such as add fuel to the fire, can be interpreted literally or idiomatically depending on the context they occur in. Many Natural Language Processing applications could improve their performance if idiom recognition were improved. Our approach is based on the idea that idioms violate cohesive ties in local contexts, while literal expressions do not. We propose two approaches: 1) Compute inner product of context word vectors with the vector representing a target expression. Since literal vectors predict well local contexts, their inner product with contexts should be larger than idiomatic ones, thereby telling apart literals from idioms; and (2) …

Towards A Science Of Security Games, Thanh Hong Nguyen, Debarun Kar, Matthew Brown, Arunesh Sinha, Albert Xin Jiang, Milind Tambe

Research Collection School Of Computing and Information Systems

Security is a critical concern around the world. In many domains from counter-terrorism to sustainability, limited security resources prevent full security coverage at all times; instead, these limited resources must be scheduled, while simultaneously taking into account different target priorities, the responses of the adversaries to the security posture and potential uncertainty over adversary types.Computational game theory can help design such security schedules. Indeed, casting the problem as a Bayesian Stackelberg game, we have developed new algorithms that are now deployed over multiple years in multiple applications for security scheduling. These applications are leading to real-world use-inspired research in the …

Frankenfolk: Distinctiveness And Attractiveness Of Voice And Motion, Jan Ondřej, Cathy Ennis, Niamh Merriman, Carol O'Sullivan

Articles

It is common practice in movies and games to use different actors for the voice and body/face motion of a virtual character. What effect does the combination of these different modalities have on the perception of the viewer? In this article, we conduct a series of experiments to evaluate the distinctiveness and attractiveness of human motions (face and body) and voices. We also create combination characters called FrankenFolks, where we mix and match the voice, body motion, face motion, and avatar of different actors and ask which modality is most dominant when determining distinctiveness and attractiveness or whether the effects …

From Fantasy To Virtual Reality: An Exploration Of Modeling, Rigging And Animating Characters For Video Games, Sarah K. Williams

Senior Independent Study Theses

In the last few decades video games have quickly become one of the most popular forms of entertainment around the world. This can be linked to the improvement of computer systems and graphics which now allow for authentic and highly detailed computer generated characters. This project examines how these characters are modeled and developed. The examination of game characters entails a brief history of video games and their aesthetics. The foundations of character design are discussed and 3D modeling of a character is explored in detail. Finally, rigging or skeleton placement is investigated in order to animate the characters designed …

Using Topic Modelling Algorithms For Hierarchical Activity Discovery, Eoin Rogers, John D. Kelleher, Robert J. Ross

Conference papers

Activity discovery is the unsupervised process of discovering patterns in data produced from sensor networks that are monitoring the behaviour of human subjects. Improvements in activity discovery may simplify the training of activity recognition models by enabling the automated annotation of datasets and also the construction of systems that can detect and highlight deviations from normal behaviour. With this in mind, we propose an approach to activity discovery based on topic modelling techniques, and evaluate it on a dataset that mimics complex, interleaved sensor data in the real world. We also propose a means for discovering hierarchies of aggregated activities …

Mental Workload In Medicine: Foundations, Applications, Open Problems, Challenges And Future Perspectives, Luca Longo

Conference papers

Mental workload is a design concept borrowed from Ergonomics with a significant adoption in the aviation and automobile industries. Nowadays, the consideration of this construct is also taking place in many modern clinical working environments for designing interacting and complex systems that impose ever greater cognitive demand on operators and less physical load. Measuring mental workload is essential for improving the interaction human-system, enhancing performance, reducing the operator’s error and increasing safety. However, defining, measuring, assessing mental workload and understanding how this impinges on performance are still open problems. This secondary research is firstly aimed at introducing the construct of …

Idiom Token Classification Using Sentential Distributed Semantics, Giancarlo Salton, Robert J. Ross, John D. Kelleher

Conference papers

Idiom token classification is the task of deciding for a set of potentially idiomatic phrases whether each occurrence of a phrase is a literal or idiomatic usage of the phrase. In this work we explore the use of Skip-Thought Vectors to create distributed representations that encode features that are predictive with respect to idiom token classification. We show that classifiers using these representations have competitive performance compared with the state of the art in idiom token classification. Importantly, however, our models use only the sentence containing the tar- get phrase as input and are thus less dependent on a potentially …

A Corpus Of Annotated Irish Traditional Dance Music Recordings: Design And Benchmark Evaluations, Pierre Beauguitte, Bryan Duggan, John D. Kelleher

Conference papers

An emerging trend in music information retrieval (MIR) is the use of supervised machine learning to train automatic music transcription models. A prerequisite of adopting a machine learning methodology is the availability of annotated corpora. However, different genres of music have different characteristics and modelling these characteristics is an important part of creating state of the art MIR systems. Consequently, although some music corpora are available the use of these corpora is tied to the specific music genre, instrument type and recording context the corpus covers. This paper introduces the first corpus of annotations of audio recordings of Irish traditional …

Harnessing The Power Of Text Mining For The Detection Of Abusive Content In Social Media, Hao Chen, Susan Mckeever, Sarah Jane Delany

Conference papers

Abstract The issues of cyberbullying and online harassment have gained considerable coverage in the last number of years. Social media providers need to be able to detect abusive content both accurately and efficiently in order to protect their users. Our aim is to investigate the application of core text mining techniques for the automatic detection of abusive content across a range of social media sources include blogs, forums, media-sharing, Q&A and chat - using datasets from Twitter, YouTube, MySpace, Kongregate, Formspring and Slashdot. Using supervised machine learning, we compare alternative text representations and dimension reduction approaches, including feature selection and …

Using Icicle Trees To Encode The Hierarchical Structure Of Source Code, Ivan Bacher, Brian Mac Namee, John D. Kelleher

Conference papers

This paper presents a study which evaluates the use of a tree visualisation (icicle tree) to encode the hierarchical structure of source code. The tree visualisation was combined with a source code editor in order to function as a compact overview to facilitate the process of comprehending the global structure of a source code document. Results from our study show that pro- viding an overview visualisation led to an increase in accuracy and a decrease in completion time when participants performed counting tasks. However, in locating tasks, the presence of the visualisation led to a decrease in participants’ performance.

Personas: A Strategy For More Inclusive And Usable Reproductive Health Tracking Technologies, Anna R. Paul

Dissertations, Master's Theses and Master's Reports

In this report, I argue for the inclusion of personas in the development process of technologies that are designed to allow users to collect and track their health information. Personas provide a profile of a user and their needs, goals, and contexts. This tool can help designers to better understand their users, in order to create better, more usable end products. I examine one particular self-tracking technology, smartphone applications that allow users to record information about their menstrual cycles. Many of the most popular period tracking applications available today only meet the needs of a narrow user group, resulting in …

Representation And Analysis Of Multi-Modal, Nonuniform Time Series Data: An Application To Survival Prognosis Of Oncology Patients In An Outpatient Setting, Jennifer Winikus

Dissertations, Master's Theses and Master's Reports

The representation of nonuniform, multi-modal, time-limited time series data is complex and explored through the use of discrete representation, dimensionality reduction with segmentation based techniques, and with behavioral representation approaches. These explorations are done with a focus on an outpatient oncology setting with the classification and regression analysis being used for length of survival prognosis. Each decision of representation and analysis is not independent, with implications of each decision in method for how the data is represented and then which analysis technique is used. One unique aspect of the work is the use of outpatient clinical data for patients, which …

Two Influential Primate Classifications Logically Aligned, Nico M. Franz, Naomi M. Pier, Deeann M. Reeder, Mingmin Chen, Shizhuo Yu, Parisa Kianmajd, Shaun Bowers, Bertram Ludäscher

Computer Science Faculty Scholarship

Classifications and phylogenies of perceived natural entities change in the light of new evidence. Taxonomic changes, translated into Code-compliant names, frequently lead to name:meaning dissociations across succeeding treatments. Classification standards such as the Mammal Species of the World (MSW) may experience significant levels of taxonomic change from one edition to the next, with potential costs to long-term, large-scale information integration. This circumstance challenges the biodiversity and phylogenetic data communities to express taxonomic congruence and incongruence inways that both humans and machines can process, that is, to logically represent taxonomic alignments across multiple classifications.We demonstrate that such alignments are feasible for …

Reducing Cache Contention On Gpus, Kyoshin Choo

Electronic Theses and Dissertations

The usage of Graphics Processing Units (GPUs) as an application accelerator has become increasingly popular because, compared to traditional CPUs, they are more cost-effective, their highly parallel nature complements a CPU, and they are more energy efficient. With the popularity of GPUs, many GPU-based compute-intensive applications (a.k.a., GPGPUs) present significant performance improvement over traditional CPU-based implementations. Caches, which significantly improve CPU performance, are introduced to GPUs to further enhance application performance. However, the effect of caches is not significant for many cases in GPUs and even detrimental for some cases. The massive parallelism of the GPU execution model and the …

Names Are Not Good Enough: Reasoning Over Taxonomic Change In The Andropogon Complex, Nico M. Franz, Mingmin Chen, Parisa Kianmajd, Shizhuo Yu, Shaun Bowers, Alan S. Weakley, Bertram Ludäscher

Computer Science Faculty Scholarship

We present a novel, logic-based solution to the challenge of reconciling the meanings of taxonomic names across multiple biological taxonomies. The challenge arises due to limitations inherent in using type-anchored taxonomic names as identifiers of granular semantic similarities and differences being expressed in original and revised taxonomic classifications. We address this challenge through: (1) the use of taxonomic concept labels – thereby individuating name usages according to particular sources and allowing each taxonomy to be recognized separately; (2) sets of user-provided Region Connection Calculus articulations among concepts (RCC-5: congruence, proper inclusion, inverse proper inclusion, overlap, exclusion); and (3) the use …

Forecasting Customer Electricity Load Demand In The Power Trading Agent Competition Using Machine Learning, Saiful Abu

Open Access Theses & Dissertations

Accurate electricity load demand forecasting is an important problem in managing the power grid for both economic and environmental reasons. The Power TAC simulation provides a platform to do research on smart grid energy generation and distribution systems. Brokers are the focus of the design task posed to developers by the system. The brokers work as self-interested entities that try to maximize profits by trading electricity across multiple markets. To be successful, a broker has to forecast the electricity demand for customers as accurately as possible so it can use this information to operate efficiently. My proposed forecasting method uses …

An Evaluation Framework For Scientific Programming Productivity, W.K. Umayanganie Munipala Munipala

Open Access Theses & Dissertations

Substantial time is spent on building, optimizing and maintaining large-scale software that is run on supercomputers. However, little has been done to utilize overall resources efficiently when it comes to including expensive human resources. The community is beginning to acknowledge that optimizing the hardware performance such as speed and memory bottlenecks contributes less to the overall productivity than does the development lifecycle of high-performance scientific applications. Researchers are beginning to look at overall scientific workflows for high performance computing. Scientific programming productivity is measured by time and effort required to develop, configure, and maintain a simulation experiment and its constituent …

Combining Interval And Probabilistic Uncertainty In Engineering Applications, Andrew Martin Pownuk

Open Access Theses & Dissertations

In many practical application, we process measurement results and expert estimates. Measurements and expert estimates are never absolutely accurate, their result are slightly different from the actual (unknown) values of the corresponding quantities. It is therefore desirable to analyze how this measurement and estimation inaccuracy affects the results of data processing. There exist numerous methods for estimating the accuracy of the results of data processing under different models of measurement and estimation inaccuracies: probabilistic, interval, and fuzzy. To be useful in engineering applications, these methods should provide accurate estimate for the resulting uncertainty, should not take too much computation time, …

Implementation Of An Enhanced System Of Motion Tracking For Virtual Reality Using 'Common Off-The-Shelf' Items, Sean M. O'Hara

Honors Theses

My project was tasked and guided by Dr. Adam Jones of the University of Mississippi's Computer Science Department to design and implement an improved system of infrared motion tracking for virtual reality. The enhancements allow Dr. Jones to use motion tracking for VR in ways that he previously could not, and these improvements include the ability to track multiple objects along with a foundation for expanding my project's use to work with a multiple camera setup for motion tracking. The hardware used in my project made use of Dr. Jones' supply of technology for development and research within the area …

The Corporate Security Stratum Of Work: Identifying Levels Of Work In The Domain, Codee Roy Ludbey

Theses : Honours

Corporate security is a practicing domain and developing academic discipline that provides for the protection of people, information and assets, as well as the self-protection of organisations. Fayol (1949) articulated such an activity within organisations to be a core business function of significant importance; embedding security operations within all aspects of organisational work. This embedded nature of security within organisations has led to difficulty in the literature delineating roles and responsibilities of security practitioners; consequently leading to a nebulous understanding of security as a whole. Therefore, an investigation of the corporate security stratum of work has been undertaken to address …

Cyberbullying Detection With A Pronunciation Based Convolutional Neural Network, Xiang Zhang, Jonathan Tong, Nishant Vishwamitra, Elizabeth Whittaker, Joseph P. Mazer, Robin Kowalski, Hongxin Hu, Feng Luo, Jamie C. Macbeth, Edward Dillon

Computer Science: Faculty Publications

Cyberbullying can have a deep and long lasting impact on its victims, who are often adolescents. Accurately detecting cyberbullying helps prevent it. However, the noise and errors in social media posts and messages make detecting cyberbullying very challenging. In this paper, we propose a novel pronunciation based convolutional neural network (PCNN) to address this challenge. Upon observing that the pronunciation of misspelled words in informal online conversations is often unchanged, we used the phoneme codes of the text as the features for a convolutional neural network. This procedure corrects spelling errors that did not alter the pronunciation, thereby alleviating the …

Information-Theoretic Secure Outsourced Computation In Distributed Systems, Zhaohong Wang

Theses and Dissertations--Electrical and Computer Engineering

Secure multi-party computation (secure MPC) has been established as the de facto paradigm for protecting privacy in distributed computation. One of the earliest secure MPC primitives is the Shamir's secret sharing (SSS) scheme. SSS has many advantages over other popular secure MPC primitives like garbled circuits (GC) -- it provides information-theoretic security guarantee, requires no complex long-integer operations, and often leads to more efficient protocols. Nonetheless, SSS receives less attention in the signal processing community because SSS requires a larger number of honest participants, making it prone to collusion attacks. In this dissertation, I propose an agent-based computing framework using …

U.S. Energy Sector Cybersecurity: Hands-Off Approach Or Effective Partnership?, T. M. Ballou, Joseph A. Allen, Kyle Francis

Psychology Faculty Publications

Recent reporting has identified significant threats to the U.S. energy’s critical infrastructure from nation states and other groups through cyberspace. Efforts to improve the security and resilience of U.S. energy infrastructure relies upon voluntary partnerships between the U.S. Government and public and private energy infrastructure owners. This paper examines ideal Public-Private Partnership (PPP) characteristics and compares them to an actual PPP in the U.S. The results identify strengths of and challenges to efforts to secure U.S. energy infrastructure. The research was conducted through a combination of literature reviews and interviews with a sample of U.S-government and private-energy infrastructure representatives.

Cloud Practical Exam Invigilation Control Systems With The Objective Of Enhancing Quality Control For Online Exams, Gordon O'Reilly

Theses

Online cloud computing courses are becoming more common place facilitating a student to study from home from anywhere in the world. Coupled with this trend is a need for educational institutions to facilitate students to take tests or exams online from home. It reduces the remote student’s time and cost of travel to an exam invigilation centre as well as reducing the educational institution’s test administration overhead. It does however introduce potential quality control concerns. A new industry called online proctoring has emerged that attempts to provide quality control in these online test scenarios.

This research provides an insight into …