Computer Sciences Commons^™

A Hybrid Approach To Aerial Video Image Registration, Karol T. Salva

Browse all Theses and Dissertations

Many video processing applications, such as motion detection and tracking, rely on accurate and robust alignment between consecutive video frames. Traditional approaches to video image registration, such as pyramidal Kanade-Lucas-Tomasi (KLT) feature detection and tracking are fast and subpixel accurate, but are not robust to large inter-frame displacements due to rotation, scale, or translation. This thesis presents an alternative hybrid approach using normalized gradient correlation (NGC) in the frequency domain and normalized cross-correlation (NCC) in the spatial domain that is fast, accurate, and robust to large displacements. A scale space search is incorporated into NGC to enable more consistent recovery …

An Empirical Assessment Of Employee Cyberslacking In The Public Sector: The Social Engineering Threat, Wilnelia Hernández, Yair Levy, Michelle M. Ramim

CCE Faculty Articles

Employees spend time during work hours on non – work related activities including visiting e - commerce Websites, managing personal email accounts, and engaging in e - banking. These types of actions in the workplace are known as cyber slacking. Cyber slacking affects employees’ productivity, presents legal concerns, and undermines the security of the employer’s network. This research study addressed the problem of cyber slacking in the public sector, by assessing the ethical severity of cyber slacking activities, as well as how employees perceived that the frequency of such activities occurred by their co - workers. Participants from public sector …

An Empirical Study Of Authentication Methods To Secure E-Learning System Activities Against Impersonation Fraud, Shauna Beaudin, Yair Levy, James Parrish, Theon Danet

CCE Faculty Articles

The demand for e – learning systems in both academic and non – academic organizations has increased the need to improve security against impersonation fraud. Although there are a number of studies focused on securing Web - based systems from Information Systems (IS) misuse, research has recognized the importance of identifying suitable levels of authenticating strength for various activities. In e - learning systems, it is evident that due to the variation in authentication strength among controls, a ‘one size fits all’ solution is not suitable for securing diverse e - learning activities against impersonation fraud. The focus of this …

Empirical Results Of An Experimental Study On The Role Of Password Strength And Cognitive Load On Employee Productivity, Stephen Mujeye, Yair Levy, Herbert Mattord, Wei Li

CCE Faculty Articles

The demand or information system authentication has significantly increased over the last decade. Research has shown that the majority of user authentications remain to be password - based,however,itiswelldocumentedthatpasswordshavesignificantlimitations.Toaddress this issue,companieshavebeenplacingincreasedrequirementsontheusertoensuretheir passwords are more complex and consequently stronger with little consideration on the impact on employee productivity .Thus, this study was set to determine the effects of changing the password strength (cognitive load) overtime and its impact on employee productivity .A n experimentwithtwoexperimentalgroupsandonecontrolgroupwasconducted.Datawas collected on the number of failed operating system logon attempts, users’ logon times, task completion times, and number of reset requests.Thedatacollectedfrom72participantswas analyzed for group differences and when controlling …

A Study On The Success Of Group Formation And Cohesiveness In Virtual Teams Using Computer-Mediated Communications, Eliel Melon, Yair Levy, Laurie P. Dringus

CCE Faculty Articles

While the Internet is a major business tool nowadays, individuals are still challenged to form team s and collaboration virtually. To evaluate the success of team formation in a virtual setting, this research study assessed the role of different computer – mediated communications (CMC) employed on the success of team formation measured by task performance (TP), team cohesiveness (TC), computer skills (CS) and social bond (SB), while assessing the differences on such relationships when controlled for gender, age, education level, academic major, as well as academic year. This research used analysis of variance (ANOVA) and analysis of covariance (ANCOVA) to …

Using Data Analytics To Further Understand The Role That Boredom, Loneliness, Social Anxiety, Social Gratification, And Social Relationships (Brag) Play In A Driver’S Decision To Text, Nathan White, Yair Levy, Steven R. Terrell, Steve Bronsburg

CCE Faculty Articles

Texting while driving is a growing problem that current efforts have failed to curtail. This behavior has serious, and sometimes fatal, consequences, and the factors that cause a driver to text are not well understood. This study investigates the influence that boredom, social relationships, social anxiety, and social gratification (BRAG) have upon the texting driver. A survey instrument was used to collect data from 297 respondents at a mid – sized regional university in the Pacific North west of the United States. The data was evaluated with PLS - SEM, which indicated that social gratification plays a very significant role …

Watertight And 2-Manifold Surface Meshes Using Dual Contouring With Tetrahedral Decomposition Of Grid Cubes, Tanweer Rashid, Sharmin Sultana, Michel A. Audette

Computational Modeling & Simulation Engineering Faculty Publications

The Dual Contouring algorithm (DC) is a grid-based process used to generate surface meshes from volumetric data. The advantage of DC is that it can reproduce sharp features by inserting vertices anywhere inside the grid cube, as opposed to the Marching Cubes (MC) algorithm that can insert vertices only on the grid edges. However, DC is unable to guarantee 2-manifold and watertight meshes due to the fact that it produces only one vertex for each grid cube. We present a modified Dual Contouring algorithm that is capable of overcoming this limitation. Our method decomposes an ambiguous grid cube into a …

Tempo-Fit Heart Rate App: Using Heart Rate Sonification As Exercise Performance Feedback, Steven Landry, Yuanjing Sun, Darnishia L. Slade, Myounghoon Jeon

Department of Psychology and Human Factors Publications

Physical inactivity is a worldwide issue causing a variety of health problems. Exploring novel ways to encourage people to engage in physical activity is a topic at the forefront of research for countless stakeholders. Based upon a review of the literature, a pilot study, and exit interviews, we propose an app prototype that utilizes music tempo manipulation to guide users into a target heart rate zone during an exercise session. A study was conducted with 26 participants in a fifteen-minute cycling session using different sonification mappings and combinations of audiovisual feedback based on the user's current heart rate. Results suggest …

Privacy And Accountability In Black-Box Medicine, Roger Allan Ford, W. Nicholson Price Ii

Law Faculty Scholarship

Black-box medicine—the use of big data and sophisticated machine learning techniques for health-care applications—could be the future of personalized medicine. Black-box medicine promises to make it easier to diagnose rare diseases and conditions, identify the most promising treatments, and allocate scarce resources among different patients. But to succeed, it must overcome two separate, but related, problems: patient privacy and algorithmic accountability. Privacy is a problem because researchers need access to huge amounts of patient health information to generate useful medical predictions. And accountability is a problem because black-box algorithms must be verified by outsiders to ensure they are accurate and …

An Attribtue-Based Statistic Model For Privacy Impact Assessment, Yong Wang, Jun Liu

Research & Publications

Personally Identifiable Information (PII) includes any information that can be used to distinguish or trace an individual's identity such as name, social security number, date and place of birth, mother's maiden name, or biometric records. It also includes other information that is linked or linkable to an individual, such as medical, educational, financial, and employment information. PII is often the target of attacks, and loss of PII could result in identity theft. According to the U.S. Department of Justice, the average number of U.S. identity fraud victims annually is 11,571,900 [1]. The total financial loss attributed to identity theft in …

Adjoint Fuzzy Partition And Generalized Sampling Theorem, Irina Perfilieva, Michal Holčapek, Vladik Kreinovich

Departmental Technical Reports (CS)

A new notion of adjoint fuzzy partition is introduced and the reconstruction of a function from its F-transform components is analyzed. An analogy with the Nyquist-Shannon-Kotelnikov sampling theorem is discussed.

A Privacy Gap Around The Internet Of Things For Open-Source Projects, Brian Cusack, Reza Khaleghparast

Australian Information Security Management Conference

The Internet of Things (IoT) is having a more important role in the everyday lives of people. The distribution of connectivity across social and personal interaction discloses personalised information and gives access to a sphere of sensitivities that were previously masked. Privacy measures and security to protect personal sensitivities are weak and in their infancy. In this paper we review the issue of privacy in the context of IoT open-source projects, and the IoT security concerns. A proposal is made to create a privacy bubble around the interoperability of devices and systems and a filter layer to mitigate the exploitation …

17 Human-Car Confluence: “Socially-Inspired Driving Mechanisms”, Andreas Riener, Myounghoon Jeon, Alois Ferscha

Department of Psychology and Human Factors Publications

With self-driving vehicles announced for the 2020s, today’s challenges in Intelligent Transportation Systems (ITS) lie in problems related to negotiation and decision making in (spontaneously formed) car collectives. Due to the close coupling and interconnectedness of the involved driver-vehicle entities, effects on the local level induced by cognitive capacities, behavioral patterns, and the social context of drivers, would directly cause changes on the macro scale. To illustrate, a driver’s fatigue or emotion can influence a local driver-vehicle feedback loop, which is directly translated into his or her driving style, and, in turn, can affect driving styles of all nearby drivers. …

Listen To Your Drive: Sonification Architecture And Strategies For Driver State And Performance, Steven Landry, David Tascarella, Myounghoon Jeon, Maryam Fakhrhosseini

Department of Psychology and Human Factors Publications

Driving is mainly a visual task, leaving other sensory channels open for additional information communication. As the level of automation increases in vehicles, monitoring the state and performance of the driver and vehicle shifts from the secondary to primary task. Auditory channels provide the flexibility to display a wide variety of information to the driver without increasing the workload of driving task. It is important to identify types of auditory displays and sonification strategies that provide integral information necessary for the driving task, and not overload the driver with unnecessary or intrusive data. To this end, we have developed an …

Predicting Intake Of Applications For First Registration In The Property Registration Authority, Orlaith Mernagh

Dissertations

The motivation for this dissertation is rooted in a real business need. The Property Registration Authority is the state organisation tasked with maintaining a register of land ownership on the island of Ireland. The PRA currently faces a series of challenges; a high level of staff retiring and the inherent loss of knowledge associated with this trend, a lack of recruitment in recent years and a large increase in lodgement of applications for first registration as a result of legislation. The organisation therefore requires a reliable system for predicting future intake. Prior to this project, there has also been a …

Choosing A Repository Platform: Open Source Vs. Hosted Solutions, Hillary Corbett, Jimmy Ghaphery, Lauren Work, Sam Byrd

VCU Libraries Faculty and Staff Publications

Discusses selection of a locally hosted, open-source system (DSpace/Fedora) versus a cloud-hosted, proprietary system (Digital Commons), it is important to note that these examples are merely illustrative. Libraries have a range of choices for repository software that includes open source and proprietary in any number of support environments, and exemplary repositories are flourishing on a variety of systems, both open source and proprietary. This chapter focuses on the differences between proprietary and open-source solutions, but also demonstrates how and why libraries choose a repository system. In writing about this process, we realized that it was important to acknowledge that there …

Comparison Of Formulations Of Applied Tasks With Interval, Fuzzy Set And Probability Approaches, Boris Kovalerchuk, Vladik Kreinovich

Departmental Technical Reports (CS)

The focus of this paper is to clarify the concepts of solutions in linear equations in interval, probabilistic and fuzzy sets setting for real word tasks. There is a fundamental difference between formal definitions of the solutions and physically meaningful concept of solution in applied tasks when equations have uncertain components. For instance, a formal definition of the solution in terms of Moore interval analysis can be completely irrelevant for solving a real world task. We show that formal definitions must follow meaningful concept of the solution in the real world. The paper proposed several formalized definitions of the concept …

Robustness As A Criterion For Selecting A Probability Distribution Under Uncertainty, Songsak Sriboonchitta, Hung T. Nguyen, Vladik Kreinovich, Olga Kosheleva

Departmental Technical Reports (CS)

Often, we only have partial knowledge about a probability distribution, and we would like to select a single probability distribution $\rho(x)$ out of all probability distributions which are consistent with the available knowledge. One way to make this selection is to take into account that usually, the values $x$ of the corresponding quantity are also known only with some accuracy. It is therefore desirable to select a distribution which is the most robust -- in the sense the x-inaccuracy leads to the smallest possible inaccuracy in the resulting probabilities. In this paper, we describe the corresponding most robust probability distributions, …

Why Dependence Of Productivity On Group Size Is Log-Normal, Francisco Zapata, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Empirical analysis shows that, on average, the productivity of a group log-normally depends on its size. The current explanations for this empirical fact are based on reasonably complex assumptions about the human behavior. In this paper, we show that the same conclusion can be made in effect, from first principles, without making these complex assumptions.

Implementing Agile Development At Scale: An Industry Case Study, Nikita Kataria

Electronic Theses and Dissertations

Agile software development methodologies are extremely popular. Their dynamic restructuring of the development process has been seen as the silver bullet for increasing the productivity of software development. A significant number of studies have analyzed the impact of implementing agile techniques. However these are mostly evaluated only in smaller team settings. There is very little reporting done on how agile development methods can be implemented at the team level and scaled up at the program/portfolio level in large software organizations.

We present the results of an empirical study conducted at Pearson Education. The study focuses on the penetration of agile …

Optimizing Vehicle Usage Using Csp, Sat And Max-Sat, Raheem T. Al Rammahi

Electronic Theses and Dissertations

Most of the companies in Iraq spend significant amounts of time and money when transferring employees between home and work. In this thesis, we model the problem of the Dhi Qar Oil company (DQOC) transportations using three modeling languages from AI: Constraint Programing (CP), Boolean Satisfiability (SAT), and Maximum Satisfiability (MAX-SAT). We then use solvers to find optimal solutions to this problem.

We show which of these solvers is more efficient when finding optimal solutions. For this purpose, we create a test suite of 360 problems to test these solvers. All solvers are applied to these problems and the final …

Leveraging Client Processing For Location Privacy In Mobile Local Search, Wisam Mohamed Eltarjaman

Electronic Theses and Dissertations

Usage of mobile services is growing rapidly. Most Internet-based services targeted for PC based browsers now have mobile counterparts. These mobile counterparts often are enhanced when they use user's location as one of the inputs. Even some PC-based services such as point of interest Search, Mapping, Airline tickets, and software download mirrors now use user's location in order to enhance their services. Location-based services are exactly these, that take the user's location as an input and enhance the experience based on that. With increased use of these services comes the increased risk to location privacy. The location is considered an …

A Near-To-Far Learning Framework For Terrain Characterization Using An Aerial/Ground-Vehicle Team, Ashkan Hajjam

Electronic Theses and Dissertations

In this thesis, a novel framework for adaptive terrain characterization of untraversed far terrain in a natural outdoor setting is presented. The system learns the association between visual appearance of different terrain and the proprioceptive characteristics of that terrain in a self-supervised framework. The proprioceptive characteristics of the terrain are acquired by inertial sensors recording measurements of one second traversals that are mapped into the frequency domain and later through a clustering technique classified into discrete proprioceptive classes. Later, these labels are used as training inputs to the adaptive visual classifier. The visual classifier uses images captured by an aerial …

Best Cities: Software User Guide, Stephanie Ohshita, C Fino-Chen, L Hong, N Khanna

Environmental Science

The Benchmarking and Energy-Saving Tool for Low Carbon Cities (BEST Cities) is a dynamic decision-making tool, designed to assist local policy makers and urban planners in prioritizing strategies for energy and carbon saving at the city level in China.

China’s 12^th Five-Year Plan (2011-2015) targets a reduction in carbon intensity of the economy (CO₂ emissions per unit of GDP) by 17%. In the "Low Carbon Development 2014-2015 energy saving action plan," the State Council calls for interim targets of more than 4% in 2014 and more than 3.5% in 2015. The …

Best Practices To Increase Efficacy Of Graduate School Admissions Communications At Clark University, Diana Curran, Nikki Feinberg, Mitchell Kelley, Ruiqi Li, Anning Zhou

School of Professional Studies

Within the period of time that a graduate student deposits and subsequently arrives at their academic institution, receiving timely information is important for their preparation. This process has been deemed by the Deans of the Enterprise Schools at Clark University as one that needs further investigation. As such, this Capstone looks at the array of communication that goes out to each graduate student during this four-month period. The purpose of examining this communication is to analyze its effectiveness in engaging students. To analyze the effectiveness of this communication, surveys were distributed to current students in these schools to gather data …

Development Of Cloud-Based Uav Monitoring And Management System, Mason Itkin, Mihui Kim, Younghee Park

Faculty Publications

Unmanned aerial vehicles (UAVs) are an emerging technology with the potential to revolutionize commercial industries and the public domain outside of the military. UAVs would be able to speed up rescue and recovery operations from natural disasters and can be used for autonomous delivery systems (e.g., Amazon Prime Air). An increase in the number of active UAV systems in dense urban areas is attributed to an influx of UAV hobbyists and commercial multi-UAV systems. As airspace for UAV flight becomes more limited, it is important to monitor and manage many UAV systems using modern collision avoidance techniques. In this paper, …

Musical Robots For Children With Asd Using A Client-Server Architecture, Ruimin Zhang, Jaclyn Barnes, Joseph Ryan, Myounghoon Jeon, Chung Hyuk Park, Ayanna Howard

Department of Psychology and Human Factors Publications

People with Autistic Spectrum Disorders (ASD) are known to have difficulty recognizing and expressing emotions, which affects their social integration. Leveraging the recent advances in interactive robot and music therapy approaches, and integrating both, we have designed musical robots that can facilitate social and emotional interactions of children with ASD. Robots communicate with children with ASD while detecting their emotional states and physical activities and then, make real-time sonification based on the interaction data. Given that we envision the use of multiple robots with children, we have adopted a client-server architecture. Each robot and sensing device plays a role as …

Learn Piano With Bach: An Adaptive Learning Interface That Adjusts Task Difficulty Based On Brain State, Beste F. Yuksel, Kurt B. Oleson, Lane Harrison, Evan M. Peck, Daniel Afergan, Remco Chang, Robert Jk Jacob

Faculty Conference Papers and Presentations

We present Brain Automated Chorales (BACh), an adaptive brain-computer system that dynamically increases the levels of difficulty in a musical learning task based on pianists' cognitive workload measured by functional near-infrared spectroscopy. As users' cognitive workload fell below a certain threshold, suggesting that they had mastered the material and could handle more cognitive information, BACh automatically increased the difficulty of the learning task. We found that learners played with significantly increased accuracy and speed in the brain-based adaptive task compared to our control condition. Participant feedback indicated that they felt they learned better with BACh and they liked the timings …

Super-Resolution Reconstruction Of Mri, Sara Gharabaghi, Thomas Wischgoll, Nasser H. Kashou

Computer Science and Engineering Faculty Publications

Magnetic Resonance Imaging (MRI) is a non-invasive technique that is used in clinical applications such as diseases diagnosis and monitoring and treatment progress. Although, MRI scans typically have high in-plane resolution but they have very poor resolution in slice direction. Furthermore, in some applications with limited acquisition time or where the subject is moving, increased slice thickness or inter-slice space (slice gaps) may be used which results in poor resolution MRI.

In this research, we propose a novel Super Resolution (SR) technique for reconstructing High-Resolution (HR) MRI using a sequence of orthogonal Low-Resolution (LR) MRI scans.

The resolution of this …

Uncertainty-Awareness In Open Source Visualization Solutions, Christina Gillmann, Thomas Wischgoll, Hans Hagen

Computer Science and Engineering Faculty Publications

The popularity of open source tools is constantly increasing, as they offer the possibility to quickly create and use visualizations of arbitrary data sources. As the positive effects of uncertainty communication to all kinds of visualizations were discussed over the past years in the academic world, this work examines the uncertaintyawareness of open source solutions. Through a categorization and classification of available tools, this paper identifies the problems in uncertainty-awareness of available open source solutions. To solve this problem, a new paradigm of data handling that extends raw datasets by its uncertainty is suggested