The U.S. federal government spends millions of taxpayer dollars to implement the federal enterprise architecture framework (FEAF). This qualitative multiple case study extracted successful FEAF implementation strategies used by agencies in the Washington, DC, metropolitan area. The population for this study included 10 information technology (IT) planners in 3 federal agencies. Data were collected from semistructured interviews and triangulated in comparison to 33 public documents. General system theory was used as a conceptual framework for the study, and data analysis included reviews of the academic literature, thematic analysis, and member checking to identify themes and codes related to successful aspects of the strategies collected. Key themes emerging from data analysis included critical leadership support for implementation, organizational culture, practices for maintaining an accurate organizational history, and means to maintain this knowledge. Based on the findings, the implications of this study for positive social change include efficient, effective, and reliable government services for U.S. citizens and a significant reduction in IT spending in federal agencies. In turn, the results may result in effective federal services and effective use of taxpayer money.

A single cyberattack event involving 1 major corporation can cause severe business and social devastation. In this single case study, a major U.S. airline company was selected for exploration of the strategies information technology administrators and airline managers implemented to reduce the financial devastation that may be caused by a cyberattack. Seven participants, of whom 4 were airline managers and 3 were IT administrators, whose primary responsibility included implementation of strategies to plan for and respond to cyberattacks participated in the data collection process. This study was grounded on the general systems theory. Data collection entailed semistructured face-to-face and telephone interviews and collection and review of public documents. The data analysis process of this study involved the use of Yin's 5-step process of compiling, disassembling, reassembling, interpreting, and concluding, which provided a detailed analysis of the emerging themes. The findings produced results that identified strategies organizational managers and administrators of a U.S. airline implemented to reduce the fiscal influence of cyberattacks, such as proactive plans for education and training, active management, and an incident response plan. The findings of this study might affect social change by offering all individuals a perspective on creating effective cyberculture. An understanding of cyberculture could include the focus of a heightened understanding, whereby, to ensure the security of sensitive or privileged data and information and of key assets, thus, reducing the fiscal devastation that may be caused by cyberattacks.

Data mining involves the use of data analysis tools to discover previously unknown, valid patterns and relationships from large amounts of data stored in databases, data warehouses, or other information repositories. Feature selection is an important preprocessing step of data mining that helps increase the predictive performance of a model. The main aim of feature selection is to choose a subset of features with high predictive information and eliminate irrelevant features with little or no predictive information. Using a single feature selection technique may generate local optima. In this thesis we propose an ensemble approach for feature selection, where multiple feature selection techniques are combined to yield more robust and stable results. Ensemble of multiple feature ranking techniques is performed in two steps. The first step involves creating a set of different feature selectors, each providing its sorted order of features, while the second step aggregates the results of all feature ranking techniques. The ensemble method used in our study is frequency count which is accompanied by mean to resolve any frequency count collision. Experiments conducted in this work are performed on the datasets collected from Kent Ridge bio-medical data repository. Lung Cancer dataset and Lymphoma dataset are selected from the repository to perform experiments. Lung Cancer dataset consists of 57 attributes and 32 instances and Lymphoma dataset consists of 4027 attributes and 96 ix instances. Experiments are performed on the reduced datasets obtained from feature ranking. These datasets are used to build the classification models. Model performance is evaluated in terms of AUC (Area under Receiver Operating Characteristic Curve) performance metric. ANOVA tests are also performed on the AUC performance metric. Experimental results suggest that ensemble of multiple feature selection techniques is more effective than an individual feature selection technique.

The bring your own device (BYOD) phenomenon has proliferated, making its way into different business and educational sectors and enabling multiple vectors of attack and vulnerability to protected data. The purpose of this multiple-case study was to explore the strategies information technology (IT) security professionals working in a university setting use to secure an environment to support BYOD in a university system. The study population was comprised of IT security professionals from the University of California campuses currently managing a network environment for at least 2 years where BYOD has been implemented. Protection motivation theory was the study's conceptual framework. The data collection process included interviews with 10 IT security professionals and the gathering of publicly-accessible documents retrieved from the Internet (n = 59). Data collected from the interviews and member checking were triangulated with the publicly-accessible documents to identify major themes. Thematic analysis with the aid of NVivo 12 Plus was used to identify 4 themes: the ubiquity of BYOD in higher education, accessibility strategies for mobile devices, the effectiveness of BYOD strategies that minimize risk, and IT security professionals' tasks include identifying and implementing network security strategies. The study's implications for positive social change include increasing the number of users informed about cybersecurity and comfortable with defending their networks against foreign and domestic threats to information security and privacy. These changes may mitigate and reduce the spread of malware and viruses and improve overall cybersecurity in BYOD-enabled organizations.

There is a significant technology deficiency within the U.S. manufacturing industry compared to other countries. To adequately compete in the global market, lean manufacturing organizations in the United States need to look beyond their traditional methods of evaluating their processes to optimize their assembly cells for efficiency. Utilizing the task-technology fit theory this quantitative correlational study examined the relationships among software using probabilistic algorithms, lean methodology techniques, and manufacturer cell optimization results. Participants consisted of individuals performing the role of the systems analyst within a manufacturing organization using lean methodologies in the Southwestern United States. Data were collected from 118 responses from systems analysts through a survey instrument, which was an integration of two instruments with proven reliability. Multiple regression analysis revealed significant positive relationships among software using probabilistic algorithms, lean methodology, and cell optimization results. These findings may provide management with information regarding the skillsets required for systems analysts to implement software using probabilistic algorithms and lean manufacturing techniques to improve cell optimization results. The findings of this study may contribute to society through the potential to bring sustainable economic improvement to impoverished communities through the implementation of efficient manufacturing solutions with lower capital expenditures.

Successful attacks on critical infrastructure have increased in occurrence and sophistication. Many cybersecurity strategies incorporate conventional best practices but often do not consider organizational circumstances and nonstandard critical infrastructure protection needs. The purpose of this qualitative multiple case study was to explore cybersecurity strategies used by information technology (IT) managers and compliance officers to mitigate cyber threats to critical infrastructure. The population for this study comprised IT managers and compliance officers of 4 case organizations in the Pacific Northwest United States. The routine activity theory developed by criminologist Cohen and Felson in 1979 was used as the conceptual framework. Data collection consisted of interviews with 2 IT managers, 3 compliance officers, and 25 documents related to cybersecurity and associated policy governance. A software tool was used in a thematic analysis approach against the data collected from the interviews and documentation. Data triangulation revealed 4 major themes: a robust workforce training program is crucial, make infrastructure resiliency a priority, importance of security awareness, and importance of organizational leadership support and investment. This study revealed key strategies that may help improve cybersecurity strategies used by IT and compliance professionals, which can mitigate successful attacks against critical infrastructure. The study findings will contribute to positive social change through an exploration and contextual analysis of cybersecurity strategy with situational awareness of IT practices to enhance cyber threat mitigation and inform business processes.

The Structured Query Language (SQL) is widely used and challenging to master. Within the context of lab exercises in an introductory database course, this thesis analyzes the student learning process and seeks to answer the question: ``Which SQL concepts, or concept combinations, trouble students the most?'' We provide comprehensive taxonomies of SQL concepts and errors, identify common areas of student misunderstanding, and investigate the student problem-solving process. We present an interactive web application used by students to complete SQL lab exercises. In addition, we analyze data collected by this application and we offer suggestions for improvement to database lab activities.

Humans are the weakest link in any information security (IS) environment. Research has shown that humans account for more than half of all security incidents in organizations. The purpose of this qualitative case study was to explore the strategies IS managers use to provide training and awareness programs that improve compliance with organizational security policies and reduce the number of security incidents. The population for this study was IS security managers from 2 organizations in Western New York. Information theory and institutional isomorphism were the conceptual frameworks for this study. Data collection was performed using face-to-face interviews with IS managers (n = 3) as well as secondary data analysis of documented IS policies and procedures (n = 28). Analysis and coding of the interview data was performed using a qualitative analysis tool called NVivo, that helped identify the primary themes. Developing IS policy, building a strong security culture, and establishing and maintaining a consistent, relevant, and role-based security awareness and training program were a few of the main themes that emerged from analysis. The findings from this study may drive social change by providing IS managers additional information on developing IS policy, building an IS culture and developing role-specific training and awareness programs. Improved IS practices may contribute to social change by reducing IS risk within organizations as well as reducing personal IS risk with improved IS habits.

This project uses exploratory 3D geospatial analyses to assess the taphonomy of the Gray Fossil Site (GFS). During the Pliocene, the GFS was a forested, inundated sinkhole that accumulated biological materials between 4.9-4.5 mya. This deposit contains fossils exhibiting different preservation modes: from low energy lacustrine settings to high energy colluvial deposits. All macro-paleontological materials have been mapped in situ using survey-grade instrumentation. Vertebrate skeletal material from the site is well-preserved, but the degree of skeletal articulation varies spatially within the deposit. This analysis uses geographic information systems (GIS) to analyze the distribution of mapped specimens at different spatial scales. Factors underpinning spatial association, skeletal completeness, and positioning of specimens were examined. At the scale of the individual skeleton, analyses of the Mastodon Pit explore how element completeness and orientation/inclination of the mastodon reflect post-depositional processes.

Many leaders of nonprofit organizations (NPOs) in the United States do not have plans to adopt cloud computing. However, the factors accounting for their decisions is not known. This correlational study used the extended unified theory of acceptance and use of technology (UTAUT2) to examine whether performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, price value, and habit can predict behavioral intention (BI) and use behavior (UB) of NPO information technology (IT) managers towards adopting cloud computing within the Phoenix metropolitan area of Arizona of the U.S. An existing UTAUT2 survey instrument was used with a sample of IT managers (N = 106) from NPOs. A multiple regression analysis confirmed a positive statistically significant relationship between predictors and the dependent variables of BI and UB. The first model significantly predicted BI, F (7,99) =54.239, p -?¤ .001, R^2=.795. Performance expectancy (β = .295, p = .004), social influence (β = .148, p = .033), facilitating conditions (β = .246, p = .007), and habit (β = .245, p = .002) were statistically significant predictors of BI at the .05 level. The second model significantly predicted UB, F (3,103) = 37.845, p -?¤ .001, R^2 = .527. Habit (β = .430, p = .001) was a statistically significant predictor for UB at a .05 level. Using the study results, NPO IT managers may be able to develop strategies to improve the adoption of cloud computing within their organization. The implication for positive social change is that, by using the study results, NPO leaders may be able to improve their IT infrastructure and services for those in need, while also reducing their organization's carbon footprint through use of shared data centers for processing.