Prospectus, November 5, 1986

https://spark.parkland.edu/prospectus_1986/1028/thumbnail.jp

The Pacifican, Feburary 12,1998

https://scholarlycommons.pacific.edu/pacifican/1639/thumbnail.jp

The Pacifican, Feburary 12,1998

https://scholarlycommons.pacific.edu/pacifican/1639/thumbnail.jp

Product grammar : construction and exploring solution spaces

Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2004.Page 79 blank.Includes bibliographical references (p. 77-78).Developing a design methodology that accounts for system- and component-level parameters in the design of products is a challenge for design and manufacturing organizations. Designed products like automobiles, personal electronics, mass-customized homes, and apparel follow design processes that have evolved over time into compartmentalized approaches toward design synthesis. Many products are designed "by committee" because the nature of the problem is sufficiently sophisticated that isolating the different disciplines of engineering, design, manufacturing, and marketing has become the only way to produce a product. This thesis rethinks design methods by critically analyzing design rules and their role in product development. Systematic and unbiased mapping of possible configurations is a method employed in generative design systems. A mapping of a solution space is achieved by parameterizing the constraints of the problem in order to develop a feasible envelope of possibilities at the component and system level. Once parametric modeling begins, then a flexible hierarchical and associative assembly must be put in place to integrate components into the product structure. What results is a complex tree structure of the possible solutions that can be optimized to ergonomic, structural, aerodynamic, manufacturing and material perspectives. The tree structure is organized so that any changes in the component structure can be accommodated at any level. Subsystems can then be easily substituted in order to fit to mass-customization preferences.by Ryan C.C. Chin.S.M

Shaping the future through Artificial Intelligent technologies to reduce vehicle accidents in Abu Dhabi

Traffic accidents (TAs) constitute one of the top killers in the United Arab Emirates (UAE). Without practical approaches to address the TAs in Abu Dhabi, the region is likely to experience continued economic losses and health burden to the affected families and country. This study identified interventions and solutions for mitigating TAs in Abu Dhabi. The study was guided by research questions that focused on the causes of accidents and how to mitigate TA. The study was based on descriptive observational methodology where quantitative data was collected using a detailed survey questionnaire (n= 300) that assessed various aspects relating to the driver’s behaviour. The 2007 to 2017 MVC injuries baseline data were also analyzed. Data on TAs control strategies from existing studies were used to assess the artificial intelligent approaches in road safety management. The quantitative data analysis was carried out using SPSS software and Microsoft Excel software. The study findings showed that the most common traffic problems on Abu Dhabi's roads include driver-related factors, vehicular factors, and road condition-related factors. Risky overtaking, violation of the need to keep a safe distance and violation of speed limits were noted as the significant violations associated with the traffic problems on Abu Dhabi’s roads. The baseline data analysis findings indicated that the three regions in Abu Dhabi registered a general reduction in TAs over the 10 years (2007 to 2017). However, the reduction in Al Ain was minimal over the study period. The study’s findings relating to the forecasting of the accident trends showed that the Western region and Abu Dhabi would continue to experience a reduction in TAs in the future while the frequency of accidents in Al Ain will increase between 2017 and 2024. Most of the accidents in Abu Dhabi are associated with driver behaviour. The identified risky driver behaviours include the failure to keep adequate distance, maintain recommended speeds, and reckless driving. The study also noted the need to adopt artificial intelligent based interventions to limit the occurrence of accidents and enhance road safety. Based on the reported findings, management of the traffic problems need to focus on controlling risky driver behaviours. Road safety authorities in Abu Dhabi should adopt artificial intelligent approaches in the management of road safety

1997 NASA-ODU American Society for Engineering Education (ASEE) Summer Faculty Fellowship Program

Since 1964, the National Aeronautics and Space Administration (NASA) has supported a program of summer faculty fellowships for engineering and science educators. In a series of collaborations between NASA research and development centers and nearby universities, engineering faculty members spend 10 weeks working with professional peers on research. The Summer Faculty Program Committee of the American Society for Engineering Education supervises the programs. Objectives of the program are as follows: (1) To further the professional knowledge of qualified engineering and science faculty members, (2) To stimulate and exchange ideas between participants and NASA; (3) To enrich and refresh the research and teaching activities of participants' institutions; and (4) To contribute to the research objectives of the NASA center. Program description is as follows: College or university faculty members will be appointed as Research Fellows to spend 10 weeks in cooperative research and study at the NASA Langley Research Center. The Fellow will devote approximately 90 percent of the time to a research problem and the remaining time to a study program. The study program will consist of lectures and seminars on topics of interest or that are directly relevant to the Fellows' research topics. The lectures and seminar leaders will be distinguished scientists and engineers from NASA, education, and industry