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Since the 1954 Brown v. Board of Education ruling against school segregation, Black women teachers (BWTs) have had perpetually high rates of attrition, despite their legacy of providing high quality, emancipatory education. Thus, the purpose of this study was to contextualize the attrition of critical BWTs to better understand the factors that would support their sustainability in urban schools. Specifically, I investigated (a) the relationship between Black women’s intersectional identities and their experiences as critical educators in urban schools, (b) the compounding factors that led to their ultimate departure, and (c) the complexities of their decision to leave the profession.
Using Black feminist thought and cognitive dissonance theory as my framework, I employed sista circle methodology to study fifteen post-service critical Black women teachers. Each participant engaged in an individual interview, one of three sista circles, and a written reflection. Data analysis revealed three major themes that offer rich context and a complex narrative of why critical BWTs love and leave the classroom: instinct vs. opposition, commitments vs. personal needs, and dissonance-reduction strategies. As they are examined, these themes suggest several actions that can be taken by key stakeholders to support their professional sustainability.
As the number of minority students in public schools increases in the U.S., the teacher workforce and administration remain majority White. Increased access to service-learning will help mitigate opportunity gaps that exist in marginalized communities. Service-learning combines academic coursework with volunteer community service experiences, which can be beneficial to in-service and pre-service teachers. Changing the structure of service-learning opportunities to include the voices of African American women is critical to expanding the structure of volunteer efforts, specifically within urban school environments. Using Seidman’s In-Depth Interview Protocol, this research explores the experiences of African American women educators with service-learning and volunteering in local communities and schools. The study examines how Black women educators saw service-learning and volunteering as part of their identities. The findings indicate that service is central to their definitions of social justice work in education and beyond through the concepts of: (a) giving back, (b) serving, (c) family, (d) Black womanhood, (e) leadership and (f) spirituality. The results of this study illustrate how educators’ lived experiences expand conceptions of service. The participants viewed service-learning as being crucial to student and teacher success in urban environments.
Keywords: service-learning, critical service-learning pedagogy, social justice, volunteerism
The task of visually tracking multiple objects remains an active field of algorithm development even after several decades of research in the computer vision community. It remains an active research area because identifying and maintaining the location of multiple targets in a video recording can be approached from several perspectives. Another reason is simply that the general problem of automated tracking can be very challenging. Challenges within visual tracking collectively manifest into three broader design decisions often faced by multiple object tracking (MOT) algorithms. First is how to handle what one could think of as "easy" and "hard" regions of a trajectory. The second is how to handle the sheer number of possible explanations of the data. The third is how do you model certainty. This dissertation aims to better model the uncertainty among possible answers to the tracking data in offline tracking scenarios. Furthermore, the method does so in a way that utilizes the information within the "hard to track" regions — information that is typically not used. The way we do this results in accurate tracking that is better suited for video analysis pipelines that may need to filter or correct any tracking errors.
Subjective perceptions of social mobility are critical for defending societal system and maintain political stability (Day and Fiske 2017; Houle 2019). This dissertation enhances our understanding of factors that shape beliefs in opportunity for upward mobility by focusing on the living environments in American neighborhoods. Inspired by the research from psychology and development economics, I developed and tested the Opportunity Beliefs Theory to explain how the built environment in neighborhoods affects individuals’ opportunity beliefs. The theory aims to elucidate how environmental factors psychologically affect people’s beliefs and behavior. The Opportunity Beliefs theory argues that the living environment can rouse positive or negative emotions. These emotional incentives shape residents’ self-efficacy. These emotions and self-efficacy largely affect people’s expectations for the future. According to the Opportunity Beliefs Theory, for people with low/middle income, those who live in a neighborhood with a better-maintained built environment are more likely to possess positive emotions and hold a high-level of self-efficacy. Furthermore, these residents will perceive more opportunities for themselves and their children for getting ahead in life, and they are more likely to agree that the opportunities are distributed equally in the society.
I have designed three studies which can support each other to explore the valid causal inferences between the built environment in neighborhoods and opportunity beliefs. First, In order to understand how the built environment in neighborhoods affects Americans’ opportunity beliefs, I designed a conventional survey which can obtain samples nation-wide and has high external validity. Next, I conducted two-round survey experiments to explore the causal inference. The results support my hypotheses.
This dissertation explores the interaction between the living environment and human psychological states and enriches the knowledge of emotions, self-efficacy, and opportunity beliefs. This research has important implications for poverty reduction and redistributive policy.
It is so rewarding to help someone to achieve their desires for their health care. The feeling of helping to empower others to know the choices that they have available to them while they can make those choices is profound. It is also gratifying to advocate for others to have a proactive role in the decisions related to their health care.
Registered nurses working in North Carolina each day have ample opportunities to engage with patients, caregivers, and community members on the topic of advance care planning and advance directives. The importance of ensuring that nurses receive education and awareness on these topics cannot be overstated. Improving a nurse’s education and awareness can impact a nurse’s ability and comfort level to discuss these topics with others. In addition to providing education and awareness, it is also important to allow for time of reflection on a nurse’s unique experiences and perceptions on barriers related to advance care planning and advance directive completion.
Through participants completing an initial survey, educational training including open-ended questions and post-survey, this DNP Scholarly Project seeks to look at nurses’ knowledge, attitudes, experiences, perceptions, and self-efficacy related to advance care planning and advance directives while also gaining awareness to nurses’ thoughts on perceived barriers to advance care planning and advance directives and if nurses feel the educational training offered as part of this project would benefit other nurses.
The antibiotic resistance genes (ARGs) have been increasing over time in the environment due to human activities and antibiotic use. According to CDC, antibiotic resistance (AR) causes casual infections untreatable and result in high socioeconomic costs and health care burdens. This study focuses on targeting ARGs origination, distribution, and expression in the water system under anthropogenic effects. Investigation of ARGs takes following goals: 1) Optimization of conventional and new technologies for ARG detection using quantitative polymerase chain reaction (qPCR) and droplet digital PCR (qPCR), 2) Comparison of performance between qPCR and ddPCR on ARGs, 3) Measurement of ARG abundance throughout different types of water bodies such as a lake, river, wetland, underground aquifer across the U.S. water system under anthropogenic effects, and 4) metagenomic bacterial and ARG expression analysis under a stressed environment with metal-laden industrial flue gas desulfurization (FGD) wastewater. This study helps improve surveillance and develop mitigation plans for AR and ARGs in the water system globally. And add knowledge to have better control in tracking, treatment, and containment protecting the health of humans and the ecosystem.
Expectations regarding leadership practices are changing and evolving as the expectations for school leaders and, thus, central office leaders, to lead and support the creation of equitable outcomes for all students. School systems are recognizing methods to acquire and strengthen a critical lens for identifying the inequities within their school systems so that they can tackle barriers to advancement and root causes more directly (Cheatham et al., 2020). Central office leaders should exemplify specific critical roles for school reform (Rorrer et al., 2008). For this phenomenological study, six equity officers from five urban districts were interviewed about their perceptions of how they define equity-driven central office leadership and their perception of the skills needed for central office leaders to actualize their definition of equity-driven central office leadership and to also reflect upon their roles as equity officers. Districts may benefit from learning more about the practical core skills, behaviors, and comprehensive leadership development practices to develop equity-driven central office leaders who impact equitable outcomes for students. The findings indicate that when equity officers have support from the district, including time, financial resources, and access to school leaders, they believe they can have a more significant impact on schools and leaders.
Several urban areas are building new facilities to encourage users of alternative modes of transportation (e.g., public transportation, walking, and bicycling). The existing infrastructure is changed to accommodate/ encourage these alternative mode users. However, there is not enough evidence to justify whether such plans are instrumental in improving mobility and enhancing safety of the transportation system from a multimodal perspective Therefore, the goal of this research is to model the operational performance and safety of urban roads with heterogeneous traffic conditions to improve the safety, reliability, and mobility of people and goods. A two-step approach is used to assess the operational performance of the urban roads with heterogeneous conditions. Firstly, a travel time reliability-based modeling and analysis was conducted to analyze the transportation system performance comprehensively accounting for all the modes of transportation. Secondly, a simulation-based modeling and analysis was conducted to assess the effect of light rail transit (LRT), pedestrian activity, bicyclist activity, and traffic, individually or combined, on the operational performance of the transportation system. Further, surrogate safety assessment was conducted to check the effect of LRT, pedestrian activity, bicyclist activity, and traffic, individually or combined, on the overall safety performance of the transportation system. Notable effects on operational and safety performance were observed between the modeled and evaluated hypothetical scenarios, emphasizing the need to plan and build infrastructure by evaluating complex mobility patterns and interactions between all the mode users. The proposed methodological framework is cross-disciplinary, transferable, and can be applied to other regions.
In recent years the grid modernization and rapid growth in distributed energy resources due to environmental consciousness have resulted in distribution grids becoming more active which has led to significant interaction between transmission and distribution grids. In this dissertation, novel approaches in modeling and management tools are proposed considering integrated power transmission and distribution systems with Distributed Energy Resources (DERs). First, new power methods for power distribution system considering DERs is proposed in a single-phase, three-phase, and three sequence domain. Second, an integrated transmission and distribution (T\&D) grid model where transmission and distribution systems are considered as a single unit is proposed. A coalescing Ybus approach is used to obtain the bus admittance matrix of the combined T\&D system. Further, to successfully capture the effect of unbalances in the system at the same time reducing computational burden owing to the larger size, a three-sequence modeling framework is used for a unified system. A three-sequence-based multi-period power flow method is used to accurately capture the time-varying aspects of the system. Next, a three-sequence fault analysis method capable of conducting short circuit analysis on a DER integrated unbalanced distribution system is developed. All these sequence-based methods are then used for steady-state analysis of the integrated T\&D system. Finally, a sensitivity-based coordinated voltage control scheme using reactive power support from DERs is proposed which can lead to reduced voltage regulator operations and tighter voltage profiles. The proposed methods have been validated using large-scale IEEE T\&D feeders to prove the real-life implementation capabilities of the models and tools
The overwhelming number of recent data breaches reported hundreds of terabytes of highly sensitive information, including national, financial, and personal, have been stolen from different organizations, indicating clear asymmetric disadvantage defender faces against cyber attackers. Modern attackers are well organized, highly stealthy, and stay persistent in the network for years; therefore, known as an advanced persistent threat (APT). Existing detection and prevention based cyber defense techniques usually approach the target for specific, known attack signatures, descriptions, and behaviors. However, APT attackers can easily avoid such detection techniques employing reconnaissance, fingerprinting, and social engineering. It is often very challenging and sometimes infeasible for defenders to prevent the information gathering of the adversary and patch all the vulnerabilities in the system. Therefore, a proactive defense approach is needed to break such asymmetry.
Active Cyber Defense (ACD) is a promising paradigm to achieve this goal. ACD can proactively mislead adversaries and enables a unique opportunity to engage with them to learn new attack tactics and techniques. ACD enhances real-time detection, analysis, and mitigation of APT attacks. ACD can be achieved through cyber agility and cyber deception. Cyber Agility, such as moving target defense (MTD), enables cyber systems to defend proactively against sophisticated attacks by dynamically changing the system configuration parameters (called mutable parameters) in order to deter adversaries from reaching their goals. On the other hand, Cyber Deception is an intentional misrepresentation of the system's ground truth to manipulate adversaries' actions.
Although cyber deception and MTD have been around for more than decades, static configurations and the lack of automation made many of the existing techniques easily discoverable by attackers and too expensive to manage, which diminishes the value of these technologies. Sophisticated APTs are very dynamic and thereby require a highly adaptive and embedded defense that can dynamically create honey resources and orchestrate the ACD environment appropriately according to the adversary behavior in real-time.
To overcome these challenges, this dissertation introduced an autonomous resilient ACD framework, having the following aspects: (1) developing multistrategy ACD policies that leverage an optimal dynamic composition of various MTD and deception techniques to maximize the defense utility, (2) a policy specification language and an extensible rich API integrated with a synthesis engine for developing different MTD techniques without consulting about the low-level network and system configuration management, (3) a theoretical framework and implementation for an autonomous goal-oriented cyber deception planner that optimizes deception decision-making.
