Framework for enterprise systems engineering

This research aimed at developing a research framework for the emerging field of enterprise systems engineering (ESE). The framework consists of an ESE definition, an ESE classification scheme, and an ESE process. This study views an enterprise as a system that creates value for its customers. Thus, developing the framework made use of system theory and IDEF methodologies. This study defined ESE as an engineering discipline that develops and applies systems theory and engineering techniques to specification, analysis, design, and implementation of an enterprise for its life cycle. The proposed ESE classification scheme breaks down an enterprise system into four elements. They are work, resources, decision, and information. Each enterprise element is specified with four system facets: strategy, competency, capacity, and structure. Each element-facet combination is subject to the engineering process of specification, analysis, design, and implementation, to achieve its pre-specified performance with respect to cost, time, quality, and benefit to the enterprise. This framework is intended for identifying research voids in the ESE discipline. It also helps to apply engineering and systems tools to this emerging field. It harnesses the relationships among various enterprise aspects and bridges the gap between engineering and management practices in an enterprise. The proposed ESE process is generic. It consists of a hierarchy of engineering activities presented in an IDEF0 model. Each activity is defined with its input, output, constraints, and mechanisms. The output of an ESE effort can be a partial or whole enterprise system design for its physical, managerial, and/or informational layers. The proposed ESE process is applicable to a new enterprise system design or an engineering change in an existing system. The long-term goal of this study aims at development of a scientific foundation for ESE research and development.

Development of surface flaw thresholds for pre-cured fiber reinforced polymer and groove size tolerance for near surface mounted fiber reinforced polymer retrofit systems

Since the introduction of fiber reinforced polymers (FRP) for the repair and retrofit of concrete structures in the 1980’s, considerable research has been devoted to the feasibility of their application and predictive modeling of their performance. However, the effects of flaws present in the constitutive components and the practices in substrate preparation and treatment have not yet been thoroughly studied. This research aims at investigating the effect of surface preparation and treatment for the pre-cured FRP systems and the groove size tolerance for near surface mounted (NSM) FRP systems; and to set thresholds for guaranteed system performance. This study was conducted as part of the National Cooperative Highway Research Program (NCHRP) Project 10-59B to develop construction specifications and process control manual for repair and retrofit of concrete structures using bonded FRP systems. The research included both analytical and experimental components. The experimental program for the pre-cured FRP systems consisted of a total of twenty-four (24) reinforced concrete (RC) T-beams with various surface preparation parameters and surface flaws, including roughness, flatness, voids and cracks (cuts). For the NSM FRP systems, a total of twelve (12) additional RC T-beams were tested with different grooves sizes for FRP bars and strips. The analytical program included developing an elaborate nonlinear finite element model using the general purpose software ANSYS. The bond interface between FRP and concrete was modeled by a series of nonlinear springs. The model was validated against test data from the present study as well as those available from the literature. The model was subsequently used to extend the experimental range of parameters for surface flatness in pre-cured FRP systems and for groove size study in the NSM FRP systems. Test results, confirmed by further analyses, indicated that contrary to the general belief in the industry, the impact of surface roughness on the global performance of pre-cured FRP systems was negligible. The study also verified that threshold limits set for wet lay-up FRP systems can be extended to pre-cured systems. The study showed that larger surface voids and cracks (cuts) can adversely impact both the strength and ductility of pre-cured FRP systems. On the other hand, frequency (or spacing) of surface cracks (cuts) may only affect system ductility rather than its strength. Finally, within the range studied, groove size tolerance of ±1/8 in. does not appear to have an adverse effect on the performance of NSM FRP systems.

Framework for Enterprise Systems Engineering

This research aimed at developing a research framework for the emerging field of enterprise systems engineering (ESE). The framework consists of an ESE definition, an ESE classification scheme, and an ESE process. This study views an enterprise as a system that creates value for its customers. Thus, developing the framework made use of system theory and IDEF methodologies. This study defined ESE as an engineering discipline that develops and applies systems theory and engineering techniques to specification, analysis, design, and implementation of an enterprise for its life cycle. The proposed ESE classification scheme breaks down an enterprise system into four elements. They are work, resources, decision, and information. Each enterprise element is specified with four system facets: strategy, competency, capacity, and structure. Each element-facet combination is subject to the engineering process of specification, analysis, design, and implementation, to achieve its pre-specified performance with respect to cost, time, quality, and benefit to the enterprise. This framework is intended for identifying research voids in the ESE discipline. It also helps to apply engineering and systems tools to this emerging field. It harnesses the relationships among various enterprise aspects and bridges the gap between engineering and management practices in an enterprise. The proposed ESE process is generic. It consists of a hierarchy of engineering activities presented in an IDEF0 model. Each activity is defined with its input, output, constraints, and mechanisms. The output of an ESE effort can be a partial or whole enterprise system design for its physical, managerial, and/or informational layers. The proposed ESE process is applicable to a new enterprise system design or an engineering change in an existing system. The long-term goal of this study aims at development of a scientific foundation for ESE research and development.

On-screen pre-deblurring of digital images using the wavefront aberration function of the human eye to improve computer access for the visually impaired

Traditional Optics has provided ways to compensate some common visual limitations (up to second order visual impairments) through spectacles or contact lenses. Recent developments in wavefront science make it possible to obtain an accurate model of the Point Spread Function (PSF) of the human eye. Through what is known as the "Wavefront Aberration Function" of the human eye, exact knowledge of the optical aberration of the human eye is possible, allowing a mathematical model of the PSF to be obtained. This model could be used to pre-compensate (inverse-filter) the images displayed on computer screens in order to counter the distortion in the user's eye. This project takes advantage of the fact that the wavefront aberration function, commonly expressed as a Zernike polynomial, can be generated from the ophthalmic prescription used to fit spectacles to a person. This allows the pre-compensation, or onscreen deblurring, to be done for various visual impairments, up to second order (commonly known as myopia, hyperopia, or astigmatism). The technique proposed towards that goal and results obtained using a lens, for which the PSF is known, that is introduced into the visual path of subjects without visual impairment will be presented. In addition to substituting the effect of spectacles or contact lenses in correcting the loworder visual limitations of the viewer, the significance of this approach is that it has the potential to address higher-order abnormalities in the eye, currently not correctable by simple means.

Utilizing Traditional Cognitive Measures of Academic Preparation to Predict First-Year Science, Technology, Engineering, and Mathematics (STEM) Majors' Success in Math and Science Courses

For the past several years, U.S. colleges and universities have faced increased pressure to improve retention and graduation rates. At the same time, educational institutions have placed a greater emphasis on the importance of enrolling more students in STEM (science, technology, engineering and mathematics) programs and producing more STEM graduates. The resulting problem faced by educators involves finding new ways to support the success of STEM majors, regardless of their pre-college academic preparation. The purpose of my research study involved utilizing first-year STEM majors’ math SAT scores, unweighted high school GPA, math placement test scores, and the highest level of math taken in high school to develop models for predicting those who were likely to pass their first math and science courses. In doing so, the study aimed to provide a strategy to address the challenge of improving the passing rates of those first-year students attempting STEM-related courses. The study sample included 1018 first-year STEM majors who had entered the same large, public, urban, Hispanic-serving, research university in the Southeastern U.S. between 2010 and 2012. The research design involved the use of hierarchical logistic regression to determine the significance of utilizing the four independent variables to develop models for predicting success in math and science. The resulting data indicated that the overall model of predictors (which included all four predictor variables) was statistically significant for predicting those students who passed their first math course and for predicting those students who passed their first science course. Individually, all four predictor variables were found to be statistically significant for predicting those who had passed math, with the unweighted high school GPA and the highest math taken in high school accounting for the largest amount of unique variance. Those two variables also improved the regression model’s percentage of correctly predicting that dependent variable. The only variable that was found to be statistically significant for predicting those who had passed science was the students’ unweighted high school GPA. Overall, the results of my study have been offered as my contribution to the literature on predicting first-year student success, especially within the STEM disciplines.