Computer Sciences Commons^™

Strategies Federal Government It Project Managers Use To Migrate It Systems To The Cloud, Latonya Denise Griffith

Walden Dissertations and Doctoral Studies

Several processes, security, and confidentiality challenges cause the slow adoption of cloud computing within the federal government. Information Technology (IT) senior leadership in the federal government is concerned about the slow adoption of cloud computing because it impedes federal IT systems management. Grounded in the technology acceptance model, the purpose of this exploratory multiple case study was to explore strategies federal government IT project managers used to select systems to migrate to the cloud. Participants consisted of 10 IT project managers from 3 federal organizations in Virginia and Washington, D.C., responsible for migrating federal government systems to the cloud. Data …

The Impact Of Technological Advances On Older Workers, Toni Mcintosh

Walden Dissertations and Doctoral Studies

The general problem addressed in this study was the treatment of older workers in the information technology industry that contributes to age discrimination in the workplace. Age discrimination is against the law irrespective of whether it is aimed at older workers in the workforce or becoming job candidates at an advanced age. Although previous research has shown that age discrimination is prevalent in work environments, little has been suggested to eradicate the issue in the workplace. The purpose of this qualitative case study was to investigate the issue of age discrimination as it relates to workers over the age of …

It Security Managers' Strategies For Mitigating Data Breaches In Texas School Districts, Mercy Ikhuoria Nwankwo

Walden Dissertations and Doctoral Studies

School districts are increasingly becoming a prime target for cybercriminals. As a result, information technology (IT) security managers in Texas school districts are concerned about hackers gaining access to network resources that could lead to data breaches on their network. Grounded in the technology threat avoidance theory, the purpose of this qualitative multiple case study was to explore strategies IT security managers use to mitigate data breaches in school district networks in Texas. The participants comprised 6 IT security managers in 3 Texas school districts whose roles involved managing and implementing data security strategies. Data collection involved conducting semistructured interviews …

Evaluation Of Telehealth Applications For Patients Seeking Hospice Care, Victoria Emma Surujlall

Walden Dissertations and Doctoral Studies

Telehealth (TH) is one of the newest avenues for improving accessibility and healthcare accommodations for patients with chronic health issues and terminal illness. The purpose of a quality improvement (QI) initiative at the project site was to align current evidence-based practice to address the disparities in the admissions process experienced by patients seeking hospice care from remote locations. The health belief model and Roger's diffusion of innovation theory were used to inform this doctor of nursing QI evaluation project to determine whether using a standardized evidence-based intake assessment process delivered by TH would increase accessibility for patients seeking hospice services. …

Youth Leadership Development Program Evaluation, Loreley Lyn Smith

Walden Dissertations and Doctoral Studies

In competitive youth sports organizations, few organizational leaders focus on leadership development to prepare youth for life situations. Sports organizational leaders are concerned about youth leadership development, as development allows youth to build skills necessary to understand their strengths and weaknesses and recognize ways to overcome fears. Grounded in social learning theory, the purpose of this summative program evaluation was to determine the extent to which a competitive youth sports leadership development program aligned with the organization’s primary objective to provide skilled athletic training while providing lessons to prepare youth for adulthood. The participants comprised 40 key stakeholders, including participants …

Analysis Of Driving Forces That Ensures The Sustainability Of Voter Accreditation Technology, Lawrence Oluwagbenga Bayode

Walden Dissertations and Doctoral Studies

Nigeria’s electoral body, the independent national electoral commission (INEC), deployed a novel information technology (IT) based voter accreditation technology in 2015. Benefits realized included transparency and curtailed electoral malpractices. The purpose of this quantitative correlational study was to examine the relationship(s) between some variables categorized into technological, organizational, and economic factors, and Sustainability of voter accreditation technology (SVAT). The theoretical framework for the study was the e-voting system adoption model in combination with constructs from three other theories. A total of 138 IT experts participated and were asked (via SurveyMonkey) of the relationships between the following factors and SVAT: ease …

Information Technology Infrastructure Library: Postimplementation Experiences Of Small Business It Support Employees., Imoovberame Darren Obazu

Walden Dissertations and Doctoral Studies

Information technology (IT) employees of small business organizations have been the driving force for the implementation of innovative standardized IT service management and process improvement initiatives. Competitiveness amongst small business IT organizations in the market for quality IT service delivery led small business IT leaders toward the implementation of an information technology infrastructure library (ITIL) as an IT service management framework. The problem addressed in this research encompassed the needs of small business IT leaders and ITIL designers to understand the perceptions of IT operation employees following ITIL implementation. The purpose of this qualitative multiple case study was to explore …

Exploring Strategies For Enforcing Cybersecurity Policies, Bayo Olushola Omoyiola

Walden Dissertations and Doctoral Studies

Some cybersecurity leaders have not enforced cybersecurity policies in their organizations. The lack of employee cybersecurity policy compliance is a significant threat in organizations because it leads to security risks and breaches. Grounded in the theory of planned behavior, the purpose of this qualitative case study was to explore the strategies cybersecurity leaders utilize to enforce cybersecurity policies. The participants were cybersecurity leaders from 3 large organizations in southwest and northcentral Nigeria responsible for enforcing cybersecurity policies. The data collection included semi-structured interviews of participating cybersecurity leaders (n = 12) and analysis of cybersecurity policy documents (n = 20). Thematic …

Ethics Of Collection And Use Of Consumer Information On The Internet, Thanh M. Pham

Walden Dissertations and Doctoral Studies

Consumer online activities can generate massive volumes of data that private companies may collect and use for business purposes. Consumer personal data need to be protected from unauthorized access and misuse. The specific problem is that consumers have little control regarding their data being collected and used by private companies. The purpose of this qualitative archival research was to explore business practices involving collection and use of consumer data without an individual’s consent. This study used the big data ethical conceptual framework to focus on various privacy issues, including those related to ownership, transparency, ethics, and consumer privacy laws. Archival …

Strategies Used By It Project Managers To Integrate Icts In The Eastern Caribbean, Carl St. Aubin Roberts

Walden Dissertations and Doctoral Studies

Current practices used to guide information and communication technology (ICT) projects in the Caribbean and developing countries lead to high project failure rates. Project managers must adopt new innovative approaches for transformation towards a 21st-century information society and sustainable digital economies. Grounded in the technology acceptance model (TAM), the purpose of this qualitative multiple-case study was to explore strategies information technology (IT) project managers use to implement IT frameworks designed to guide Caribbean ICT integration. Data were collected from face to face interviews and company documents and analyzed using coding, thematic analysis, and methodological triangulation. The participants were 12 IT …

Knowledge Management, Innovations Systems, And Firm Performance, Henry Dion Young

Walden Dissertations and Doctoral Studies

Small and medium sized-enterprise managers are unable to effectively manage employees’ knowledgeability and innovation systems successfully, which results in negative firm performance. Managers who do not consider employee knowledge management and the benefits related to innovation systems experience financial hardships within the organization. Grounded in the unified model of dynamic organizational knowledge creation theory, the purpose of this quantitative correlational study was to examine the relationship between knowledge management, innovation systems, and firm performance. Data were collected using SurveyMonkey to gather online survey responses from 80 small and medium-sized enterprise managers in California. The results of the standard multiple linear …

Technology Business Leaders' Strategies To Increase Employees' Engagement, Desmond J. L. Browne

Walden Dissertations and Doctoral Studies

AbstractEmployee disengagement is costly and reduces an organization's ability to meet its full potential to produce business results. Technology business leaders who have engaged employees can positively alter the company's rapid transformation to be more competitive. Grounded by the social exchange theory, the purpose of this qualitative single case study was to explore strategies 6 technology leaders in the Atlanta metropolitan area use to engage employees. Data were collected through semistructured interviews and company documents. Data were analyzed using Yin's 5-step data analysis process. Three themes emerged: communicate with transparency, provide offerings for training and rewards, and identify and implement …

Automated Recognition Of Facial Affect Using Deep Neural Networks, Behzad Hasani

Electronic Theses and Dissertations

Automated Facial Expression Recognition (FER) has been a topic of study in the field of computer vision and machine learning for decades. In spite of efforts made to improve the accuracy of FER systems, existing methods still are not generalizable and accurate enough for use in real-world applications. Many of the traditional methods use hand-crafted (a.k.a. engineered) features for representation of facial images. However, these methods often require rigorous hyper-parameter tuning to achieve favorable results.

Recently, Deep Neural Networks (DNNs) have shown to outperform traditional methods in visual object recognition. DNNs require huge data as well as powerful computing units …

Towards A General Solution For Layout Of Visual Goal Models With Actors: Supplemental Material, Yilin Lucy Wang, Alicia M. Grubb

Computer Science: Faculty Publications

Supplemental material for the paper:

"Towards a General Solution for Layout of Visual Goal Models with Actors"

This paper presents early results and lays a foundation for discussion within our GORE community.

The Role Of Latency And Task Complexity In Predicting Visual Search Behavior, Leilani Battle, R. Jordan Crouser, Audace Nakeshimana, Ananda Montoly, Remco Chang, Michael Stonebraker

Computer Science: Faculty Publications

Latency in a visualization system is widely believed to affect user behavior in measurable ways, such as requiring the user to wait for the visualization system to respond, leading to interruption of the analytic flow. While this effect is frequently observed and widely accepted, precisely how latency affects different analysis scenarios is less well understood. In this paper, we examine the role of latency in the context of visual search, an essential task in data foraging and exploration using visualization. We conduct a series of studies on Amazon Mechanical Turk and find that under certain conditions, latency is a statistically …

Reconstructing The Past: The Case Of The Spadina Expressway, Alicia M. Grubb, Marsha Chechik

Computer Science: Faculty Publications

In order to build resilient systems that can be operational for a long time, it is important that analysts are able to model the evolution of the requirements of that system. The Evolving Intentions framework models how stakeholders’ goals change over time. In this work, our aim is to validate applicability and effectiveness of this technique on a substantial case. In the absence of ground truth about future evolutions, we used historical data and rational reconstruction to understand how a project evolved in the past. Seeking a well-documented project with varying stakeholder intentions over a substantial period of time, we …

Enhancing Learning With Primitive-Decomposed Cognitive Representations, Jamie C. Macbeth

Computer Science: Faculty Publications

This paper proposes work that applies insights from meaning representation systems for in-depth natural language understanding to representations for self-supervised learning systems, which show promise in developing complex, deeply-nested symbolic structures through self-motivated exploration of their environments. The core of the representation system transforms language inputs into language-free structures that are complex combinations of conceptual primitives, forming a substrate for human-like understanding and common-sense reasoning. We focus on decomposing representations of expectation, intention, planning, and decision-making which are essential to a self-motivated learner. These meaning representations may enhance learning by enabling a rich array of mappings between new experiences and …

Towards An Evaluation Visualization With Color, Megan H. Varnum, Kate M.B. Spencer, Alicia M. Grubb

Computer Science: Faculty Publications

Goal models help stakeholders understand project scenarios and make decisions. In prior work, we used Tropos evaluation semantics to allow for automated analysis over time; however, formal evaluation labels (e.g., (F, ⊥)) are difficult for users to interpret across a large model. In this paper, we present our work towards understanding the extent to which using colors in goal modeling affects users’ ability to make decisions. Specifically, we are interested in studying if coloring intentions with evaluation information allows for better comparisons of initial states and simulations of future paths. To address this question, we developed a color visualization extension …

A Preliminary Investigation Of The Utility Of Goal Model Construction, Naomi Cebula, Lily Diao, Alicia M. Grubb

Computer Science: Faculty Publications

Goal models have long been used in the literature to model and reason about stakeholders’ intentions. Prior work proposed several studies aimed at investigating what utility stakeholders derive from constructing and analyzing goal models. We designed and conducted an initial empirical study that explores the construction stage of goal modeling, asking whether stakeholders benefit from manually drawing their own model. We recruited eight qualified participants and asked each to create a goal model for a decision they were considering while talking out loud. Half of the participants in this study used BloomingLeaf, while the remaining participants drew goal models by …

A Machine Learning Approach To Estimate The Annihilation Photon Interactions Inside The Scintillator Of A Pet Scanner, Sai Akhil Bharthavarapu

Graduate Theses, Dissertations, and Problem Reports (ETD)

Biochemical processes are chemical processes that occur in living organisms. They can be studied with nuclear medicine through the help of radioactive tracers. Based on the radioisotope used, the photons that are emitted from the body tissue are either detected by single-photon emission computed tomography (SPECT) or by positron emission tomography (PET) scanners. SPECT uses gamma rays as tracer but gives a weaker contrast and spatial resolution compared to a PET scanner which uses positrons as tracer. PET scans show the metabolic changes occurring at the cellular level in an organ or a tissue. This detection is important because diseases …

Process Based Analysis Of Fluvial Stratigraphic Record: Middle Pennsylvanian Allegheny Formation, North-Central Wv, Oluwasegun O. Abatan

Graduate Theses, Dissertations, and Problem Reports (ETD)

Fluvial deposits represent some of the best hydrocarbon reservoirs, but the quality of fluvial reservoirs varies depending on the reservoir architecture, which is controlled by allogenic and autogenic processes. Allogenic controls, including paleoclimate, tectonics, and glacio-eustasy, have long been debated as dominant controls in the deposition of fluvial strata. However, recent research has questioned the validity of this cyclicity and may indicate major influence from autogenic controls. To further investigate allogenic controls on stratal order, I analyzed the facies architecture, geomorphology, paleohydrology, and the stratigraphic framework of the Middle Pennsylvanian Allegheny Formation (MPAF), a fluvial depositional system in the Appalachian …

Estimating Refactoring Efforts For Architecture Technical Debt, Samir Deeb

Graduate Theses, Dissertations, and Problem Reports (ETD)

Paying-off the Architectural Technical Debt by refactoring the flawed code is important to control the debt and to keep it as low as possible. Project Managers tend to delay paying off this debt because they face difficulties in comparing the cost of the refactoring against the benefits they gain. For these managers to decide whether to refactor or to postpone, they need to estimate the cost and the efforts required to conduct these refactoring activities as well as to decide which flaws have higher priority to be refactored among others.

Our research is based on a dataset used by other …

Representation Learning With Adversarial Latent Autoencoders, Stanislav Pidhorskyi M.S.

Graduate Theses, Dissertations, and Problem Reports (ETD)

A large number of deep learning methods applied to computer vision problems require encoder-decoder maps. These methods include, but are not limited to, self-representation learning, generalization, few-shot learning, and novelty detection. Encoder-decoder maps are also useful for photo manipulation, photo editing, superresolution, etc. Encoder-decoder maps are typically learned using autoencoder networks.
Traditionally, autoencoder reciprocity is achieved in the image-space using pixel-wise
similarity loss, which has a widely known flaw of producing non-realistic reconstructions. This flaw is typical for the Variational Autoencoder (VAE) family and is not only limited to pixel-wise similarity losses, but is common to all methods relying upon …

Image And Video-Based Autism Spectrum Disorder Detection Via Deep Learning, Mindi Ruan

Graduate Theses, Dissertations, and Problem Reports (ETD)

People with Autism Spectrum Disorder (ASD) show atypical attention to social stimuli and aberrant gaze when viewing images of the physical world. However, it is unknown how they perceive the world from a first-person perspective. In this study, we used machine learning to classify photos taken in three different categories (people, indoors, and outdoors) as either having been taken by individuals with ASD or by peers without ASD. Our classifier effectively discriminated photos from all three categories but was particularly successful at classifying photos of people with >80% accuracy. Importantly, the visualization of our model revealed critical features that led …

Searches For Fast Radio Bursts Using Machine Learning, Devansh Agarwal

Graduate Theses, Dissertations, and Problem Reports (ETD)

Fast Radio bursts (FRBs) are enigmatic astrophysical events with millisecond durations and flux densities in the range 0.1-100 Jy, with the prototype source discovered by Lorimer et al. (2007). Like pulsars, FRBs show the characteristic inverse square sweep in observing frequency due to propagation through an ionized medium. This effect is quantified by the dispersion measure (DM). Unlike pulsars, FRBs have anomalously high DMs, which are consistent with an extragalactic origin. Over 100 FRBs have been published at the time of writing, and 13 have been conclusively identified with host galaxies with spectroscopically determined redshifts in the range 0.003 ≤ …

V-Slam And Sensor Fusion For Ground Robots, Ejup Hoxha

Dissertations and Theses

In underground, underwater and indoor environments, a robot has to rely solely on its on-board sensors to sense and understand its surroundings. This is the main reason why SLAM gained the popularity it has today. In recent years, we have seen excellent improvement on accuracy of localization using cameras and combinations of different sensors, especially camera-IMU (VIO) fusion. Incorporating more sensors leads to improvement of accuracy,but also robustness of SLAM. However, while testing SLAM in our ground robots, we have seen a decrease in performance quality when using the same algorithms on flying vehicles.We have an additional sensor for ground …

Fast Decision-Making Under Time And Resource Constraints, Kyle Gabriel Lassak

Graduate Theses, Dissertations, and Problem Reports (ETD)

Practical decision makers are inherently limited by computational and memory resources as well as the time available in which to make decisions. To cope with these limitations, humans actively seek methods which limit their resource demands by exploiting structure within the environment and exploiting a coupling between their sensing and actuation to form heuristics for fast decision-making. To date, such behavior has not been replicated in artificial agents. This research explores how heuristics may be incorporated into the decision-making process to quickly make high-quality decisions through the analysis of a prominent case study: the outfielder problem. In the outfielder problem, …

Quantifying Seagrass Distribution In Coastal Water With Deep Learning Models, Daniel Perez, Kazi Islam, Victoria Hill, Richard Zimmerman, Blake Schaeffer, Yuzhong Shen, Jiang Li

OES Faculty Publications

Coastal ecosystems are critically affected by seagrass, both economically and ecologically. However, reliable seagrass distribution information is lacking in nearly all parts of the world because of the excessive costs associated with its assessment. In this paper, we develop two deep learning models for automatic seagrass distribution quantification based on 8-band satellite imagery. Specifically, we implemented a deep capsule network (DCN) and a deep convolutional neural network (CNN) to assess seagrass distribution through regression. The DCN model first determines whether seagrass is presented in the image through classification. Second, if seagrass is presented in the image, it quantifies the seagrass …

Interactions Between Humans, Virtual Agent Characters And Virtual Avatars, Tamara Griffith

Electronic Theses and Dissertations, 2020-2023

Simulations allow people to experience events as if they were happening in the real world in a way that is safer and less expensive than live training. Despite improvements in realism in simulated environments, one area that still presents a challenge is interpersonal interactions. The subtleties of what makes an interaction rich are difficult to define. We may never fully understand the complexity of human interchanges, however there is value in building on existing research into how individuals react to virtual characters to inform future investments. Virtual characters can either be automated through computational processes, referred to as agents, or …

The Susceptibility Of Deep Neural Networks To Natural Perturbations, Mesut Ozdag

Electronic Theses and Dissertations, 2020-2023

Deep learning systems have achieved great success in various types of applications in recent years. They are increasingly being adopted for safety-critical tasks such as face recognition, surveillance systems, speech recognition, and autonomous driving. On the other hand, it has been found that deep neural networks (DNNs) can easily be fooled by adversarial input samples. These imperceptible perturbations on images can lead any machine learning system to misclassify the objects with high confidence. Furthermore, they can be almost indistinguishable to a human observer. These systems can also be exposed to adverse weather conditions such as fog, rain, and snow. This …