The federal No Child Left behind Act of 2001 (NCLB) expanded the federal role in American education, and by doing so altered the distribution of power among the federal government, states, and local districts. This latest federal education policy includes an accountability component that requires states to administer tests and emphasizes student achievement by a single, objective, standardized assessment. Consequently, students, teachers, principals, schools and even districts are judged as failing or successful based upon a single measure. Studies indicate urban schools of high poverty are more likely to be identified for improvement due to their failure to meet the benchmarks established under NCLB and its measures of adequate yearly progress. Using a conceptual framework of bureaucratic school culture, this case study examines the influence of federal and state accountability policy on the perceptions of educators and students about effective teaching and learning in one urban high school identified for improvement. Findings reveal an overarching conclusion that an established bureaucratic school culture is perpetuated by accountability policy, serving as a barrier to implementation of perceived effective teaching practices that are believed to produce improved student learning. / Thesis (Ph.D.)--Wichita State University, College of Education, Dept. of Educational Leadership

We have found an exact solution to the nonlinear Yukawa system in four dimensions, and used it to derive the time development of the system. Theorems are stated and proved regarding the essential self-adjointness of the operator solutions. Suggestions are given to complete the task of proving existence of the theory in the Wightman sense. An explicit statement of all new results obtained in this research is the content of Chapter 10. / Thesis (Ph.D.) - Wichita State University, College of Liberal Arts and Sciences, Dept. of Mathematics

The most desirable characteristic of a facility layout is its ability to maintain its efficiency over time while coping with the uncertainty in product demand. A traditional facility layout design method is governed by the flow intensity between departments, which is the product flow quantity between two departments. Hence, an error in the product demand assessment can render the layout inefficient with respect to material handling costs. Most of this research integrates uncertainty in the form of probability of occurrence of different from-to charts. In an environment where the variability of each product demand is independent, the derivation of “probabilistic from-to chart” based scenarios cannot be used to address uncertainty of individual demands. This dissertation presents a facility layout problem approach to deal with the uncertainty of each product demand in the design of facility layout. Two procedures are presented: the first procedure is utilized to assess the risk associated with the layout, while the second procedure is used to develop the layout that minimizes risk. Results from case studies have shown that the procedure results in reduction of risk by as much as 68 percent. / Thesis (Ph.D.) - Wichita State University, College of Engineering, Dept. of Industrial and Mechanical Engineering

This dissertation develops operational methods for minimization of energy consumption of manufacturing equipments. Using the frameworks developed, a significant amount of energy can be saved when non-bottleneck and/or underutilized machines/equipment are turned on during a long idle time. In this dissertation, mathematical models are developed for multi-objective problems (on single or parallel machines) with minimization of a scheduling criteria and minimization) of total energy consumption. Metaheuristics approaches have been developed to solve the resulting mathematical models. Genetic algorithm, greedy randomized adaptive search procedure, and hybrid metaheuristic based approaches are utilized to obtain good approximate sets of non-dominated solutions in reasonable amount of time for different optimization problems. The decision-maker can use the results from these frameworks to plan for energy efficient production. The methods to obtain an approximate pareto front is combined with a selection method such as the Analytic Hierarchy Process to obtain a full schedule that minimizes other secondary objectives. Further research includes studying the reliability of the machine under repeated turned-off and turned-on. Also a maintenance model could be developed to include the energy minimization framework. This additional model would be useful in scheduling maintenance team with the objective of decreasing the costs associated with breakdowns including the energy-related cost. Another area of interest might be on developing a model to minimize energy consumption and scheduling objectives for machines with multi-state sleep modes. / Thesis (Ph.D.) - Wichita State University, College of Engineering, Dept. of Industrial and Manufacturing Engineering

This qualitative study focused on what eight urban high school students from varying backgrounds had to say about their lives and experiences in school. Discussions with the students involved multifarious topics such as racism, stereotypes, and discrimination and influences in and outside of school that encourage or hinder their education. The theoretical perspectives of critical theory, critical pedagogy, and critical multiculturalism and the narrative inquiry approach to research provided the foundation for this study. Individual narratives and narratives of the student group discussions are shared. The students provided insightful assessments of their schooling experiences and reported they desire greater forums for them to discuss cultures, race, and other issues important to their lives for purposes of influencing much needed change. / Thesis (Ph.D.) - Wichita State University, College of Education, Dept. of Educational Leadership

The purpose of this study was to describe how Complete High School Maize (CHSM) students describe their high point learning experiences. The study also described how CHSM students describe their dreams for effective learning. A qualitative case study research design was used to facilitate an AI Learning Team in the first two stages of the 4-D Cycle—Discovery and Dream. Eight CHSM students, four males and four females, were purposively selected as the AI Learning Team (Cooperrider, Whitney, & Stavros, 2003; Ludema, Whitney, Mohr, & Griffin, 2003). Data collection methods included: participant group discussions, semi-structured participant paired interviews, and participant created documents, participant generated video, and a participant created presentation for district administrators. Data were analyzed using several techniques: content analysis, open coding, axial coding, text analysis software, and pattern matching with the use of a content analysis matrix. Careful attention was made to ensure that the quality of the research addressed trustworthiness in terms of credibility, transferability, dependability, and confirmability throughout my study. Four salient findings emerged: (1) CHSM students believe that they need other experiences built into their class work, (2) CHSM students believe students and teachers respect rules, students talk with teachers, and people help each other, (3) CHSM students want to create a better learning environment that mixes fun with academics, and (4) CHSM students believe that the students and teachers are a family and common activities are important. The findings from this study suggest that further research with AI in educational settings may have important implications to inspire educators to think in new ways about learning. AI as an action research methodology can be used to inform teacher practice and impact the effectiveness of the teaching and learning process. As well, the use of AI as a theoretical perspective with its positive approach can contribute to best practices in teaching where changes in a teacher’s own pedagogical practice leads to excellence in education. / Thesis (Ph.D.) - Wichita State University, College of Education, Dept. of Educational Leadership

Increasingly, fiber reinforced polymers are being used in aerospace, naval, and automotive industries due to their high specific strength and high stiffness. Some of the damage problems encountered during machining these materials include: delamination, surface roughness and high rate of tool wear. Major factors that affect damage during machining in these materials are cutting forces, tool geometry, feed rate, and spindle speed. The first part of this study aims to develop an approximate mechanistic model to predict the cutting forces in the orthogonal cutting of unidirectional fiber reinforced polymers (FRP) when the fiber orientation varies from 00 to 1800. This work utilizes the mechanistic modeling approach for predicting cutting forces and simulating the milling process of fiber reinforced polymers with a straight cutting edge. Specific energy functions were developed by multiple regression analysis (MR) and committee neural network approximation (CN) of milling force data and a cutting model was developed based on these energies and the cutting geometry. Cutting force prediction models were constructed for principal and thrust cutting directions. The models are based on the specific cutting energy principle and account for a wide range of fiber orientations and chip thickness. Results from two forms of non-linear modeling methods, non-linear regression and committee neural networks, were compared. It was found that the committee neural networks provide better prediction capability of smoothing and capturing the inherent non-linearity in the data. The model predictions were found to be in good agreement with experimental results over entire range of fiber orientations from 0* to 180*. The second part of this study dealt with an improved mechanistic cutting force model for complex tool geometry by sectioning the helical cutting edge into a stacked series of straight edge cutter segments with angular offsets and calculating the forces for each segment, then adding the forces for all segments of the cutting edge. The scope of this work is to establish a three dimensional cutting force prediction model for complex cutting tool geometry using orthogonal machining database developed in first part. The cutting forces predicted have shown a good agreement with experimental results. The third part of this study dealt with building a generalized model to predict cutting forces for any combination of process parameters such as spindle speed (nt), feed rate (Vf), depth of cut (ae), rake angle (αi) and workpiece fiber layup direction ψ. Committee neural network is constructed using machining parameters – chip thickness (ac), fiber orientation angle (θ), spindle speed (nt) and feed rate (Vf) as input variables and average specific cutting energy values, (Kc and Kt) as output variables. Exhaustive experimentation is conducted to develop the model and to validate it. The training of the networks is performed with experimental machining data. Results showed that the model provides good results for unidirectional composites for all fiber orientation. The experimental results show a reasonably good fit to the predicted values, suggesting that the current approach is successful and well suitable for studying the machining of fiber reinforced polymers. Results also showed that the cutting forces are directly dependent on fiber orientation, chip thickness, rake angle, spindle speed, and feed rate. / Thesis (Ph.D.)--Wichita State University, College of Engineering, Dept. of Industrial and Manufacturing Engineering / Includes bibliographic references (leaves 149-154)

Particle filtering techniques have captured the attention of many researchers in various communities, including those in signal processing, communication and image processing. Particle filtering is particularly useful in dealing with nonlinear state space models and non-Gaussian probability density functions. The underlying principle of the methodology is the approximation of relevant distributions with random measures composed of particles (samples from the space of the unknowns) and their associated weights. This dissertation makes three main contributions in the field of particle filtering. The first problem deals with target tracking in radar signal processing. The second problem deals with object tracking in video. The third problem deals with estimating error bounds for particle filtering based symbol estimation in communication systems. / Thesis (Ph.D.)--Wichita State University, College of Engineering Dept. of Electrical and Computer Engineering / Includes bibliographic references (leaves 69-76)

Research on the maintenance of repairable machines has mostly focused on an open-loop system consisting of an infinite number of identical machines working in a production system, and a repair shop along with a spare parts inventory. The machines used in the production system are subject to failure and are replaced upon failure utilizing a spare part inventory. Meanwhile, the failed parts are repaired in the service center and are sent back to the spare parts inventory. The parts after repair are considered as good as new. In this dissertation it is assumed that the population of machines in the system is finite resulting in a closed-loop system. However, this changes the nature of problem in which the well-known queuing systems and stochastic processes need to be modified accordingly. Moreover, the times in the system are assumed to be generally distributed. For this system, the performance of the overall system is evaluated and the capacities of the repair shop together with the level of spares in inventory which optimize the performance of the system are determined simultaneously. Furthermore, the developed models and algorithms in this scenario, are utilized in order to study and optimize the performance of a healthcare system in which the length of stay of patients are generally distributed in different phases of health care process. / Thesis (Ph.D.)--Wichita State University, College of Engineering, Dept. of Industrial and Manufacturing Engineering / Includes bibliographic references (leaves 138-139)

HIV/AIDS continues to be one of the leading causes of death for African Americans. The African-American rate of HIV/AIDS infection is six times higher than that for Caucasians (CDC, 2006). Not only has an HIV/AIDS impacted African American adult, but African-American youth are also disproportionately affected by HIV/AIDS (CDC, HIV/AIDS among Youth: Fact Sheet, 2006). Compared to other youth, new infection rates for African American adolescent HIV incidence have remained steady; not resulting in a decrease despite over twenty years of prevention education and intervention. As the HIV/AIDS pandemic continues to devastate the African American community increases in sustainable community prevention interventions that address racial, cultural, age, and gender specific differences are sorely needed. This research study of the Risk Reduction Project examined the role that single parenting plays on the HIV/AIDS sexual behaviors of African American youth residing in a Midwest community. Overall, the results from this study indicate that the theory of reasoned action was effective in predicting sexual behavior, however, gender differences existed. Despite reporting greater levels of sexual activity and condom use, male participant sexual intentions and behaviors were found to be more positively impacted by parent subjective norms than female participants. Female sexual intentions, on the other hand, were negatively impacted by parent subjective norms. For participants residing in single mother households, males were found to be significantly impacted by mother referent subjective norm while females were negatively impacted. / Wichita State University, College of Liberal Arts and Sciences, Dept. of Psychology. / Includes bibliographic references (leaves 65-73)