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Phnom Penh, Cambodia

Norton University is a private university in Cambodia registered with the Ministry of Education, Youth and Sport. It was established in 1996. The University was one of the first private Cambodian educational institutions.In 2006, Tom Chandler, a 3-D modeling specialist from Monash University in Melbourne was invited to Norton as a senior visiting fellow. The aim of the fellowship was to introduce architecture and science students to specialised animation and modeling techniques and allow them to learn to digitally render their own heritage using 3-D techniques.Norton university is considered to be the Best IT Education Center in Cambodia years after its establishment, and was chosen by National ICT Development Authority , Ministry of Post-Telecommunications , International Data Group to receive the award, and that official honor in 2010. The university has two campus both based in Phnom Penh. The current Rector, and Vice Rector of Norton University are Professor Chan Sok Khieng and Professor Un Van Thouen, respectively. Wikipedia.


Ghosh D.D.,Norton University | Olewnik A.,State University of New York at Buffalo
Journal of Mechanical Design, Transactions of the ASME | Year: 2013

Modeling uncertainty through probabilistic representation in engineering design is common and important to decision making that considers risk. However, representations of uncertainty often ignore elements of "imprecision" that may limit the robustness of decisions. Furthermore, current approaches that incorporate imprecision suffer from computational expense and relatively high solution error. This work presents a method that allows imprecision to be incorporated into design scenarios while providing computational efficiency and low solution error for uncertainty propagation. The work draws on an existing method for representing imprecision and integrates methods for sparse grid numerical integration, resulting in the computationally efficient imprecise uncertainty propagation (CEIUP) method. This paper presents details of the method and demonstrates the effectiveness on both numerical case studies, and a thermocouple performance problem found in the literature. Results for the numerical case studies, in most cases, demonstrate improvements in both computational efficiency and solution accuracy for varying problem dimension and variable interaction when compared to optimized parameter sampling (OPS). For the thermocouple problem, similar behavior is observed when compared to OPS. The paper concludes with an overview of design problem scenarios in which CEIUP is the preferred method and offers opportunities for extending the method. © 2013 by ASME.


Lewis K.,Norton University
Journal of Mechanical Design, Transactions of the ASME | Year: 2012

The complexity of many large-scale systems is outpacing our ability to effectively design, analyze, and manage such systems. Projects such as the F-35 Joint Strike Fighter, the Boeing Dreamliner, the Mars Science Lab, Boston's Big Dig, and the U.S. Navy's Independence warship have all been well over budget and behind schedule. While there may be a number of contributing factors, the enormous complexity of the designed systems is certainly a culprit. Large enterprises appear to be embarking on the design of such systems without a fundamental understanding of some critical principles of complex systems. These principles are emerging in the design research community and clearly illustrate that there are some elegant and simple principles that can be used to better understand, predict, and design large-scale complex systems. In this article, a number of these principles are presented in an effort to highlight the emerging research in the science of designing complex systems. An assertion is made that simplicity and complexity can and should co-exist and if simple and elegant principles are ignored, disastrous consequence may await. © 2012 American Society of Mechanical Engineers.


Ghosh D.D.,Norton University | Olewnik A.,State University of New York at Buffalo
Proceedings of the ASME Design Engineering Technical Conference | Year: 2012

Modeling uncertainty through probabilistic representation in engineering design is common and important to decision making that considers risk. However, representations of uncertainty often ignore elements of "imprecision" that may limit the robustness of decisions. Further, current approaches that incorporate imprecision suffer from computational expense and relatively high solution error. This work presents the Computationally Efficient Imprecise Uncertainty Propagation (CEIUP) method which draws on existing approaches for propagation of imprecision and integrates sparse grid numerical integration to provide computational efficiency and low solution error for uncertainty propagation. The first part of the paper details the methodology and demonstrates improvements in both computational efficiency and solution accuracy as compared to the Optimized Parameter Sampling (OPS) approach for a set of numerical case studies. The second half of the paper is focused on estimation of non-dominated design parameter spaces using decision policies of Interval Dominance and Maximality Criterion in the context of set-based sequential design-decision making. A gear box design problem is presented and compared with OPS, demonstrating that CEIUP provides improved estimates of the non-dominated parameter range for satisfactory performance with faster solution times. Parameter estimates obtained for different risk attitudes are presented and analyzed from the perspective of Choice Theory leading to questions for future research. The paper concludes with an overview of design problem scenarios in which CEIUP is the preferred method and offers opportunities for extending the method. © 2012 by ASME.


Ferguson S.M.,North Carolina State University | Olewnik A.T.,Norton University | Cormier P.,State University of New York at Buffalo
Research in Engineering Design | Year: 2014

Introduced nearly 25 years ago, the paradigm of mass customization (MC) has largely not lived up to its promise. Despite great strides in information technology, engineering design practice and manufacturing production, the necessary process innovations that can produce products and systems with sufficient customization and economic efficiency have yet to be found in wide application. In this paper, the state-of-the-art in MC is explored in the context of an envisioned MC development process for both the firm and the customer. Specifically, 130 references are reviewed within the process frameworks (Sect. 3) and/or to highlight opportunities for future development in MC (Sect. 4) based on the review. This review yields opportunities in four primary areas that challenge MC development: (1) customer needs and preference assessment tools, (2) approaches for requirement specification and conceptual design, (3) insights from methodologies focused on the development of durable MC goods and (4) enhancements in information mapping and handling. © 2013 Springer-Verlag London.


Wolff J.E.,University of Texas M. D. Anderson Cancer Center | Wolff J.E.,Tufts Medical Center | Rytting M.E.,University of Texas M. D. Anderson Cancer Center | Vats T.S.,University of Texas M. D. Anderson Cancer Center | And 6 more authors.
Journal of Neuro-Oncology | Year: 2012

Recurrent diffuse intrinsic pontine gliomas (DIPG) are traditionally treated with palliative care since no effective treatments have been described for these tumors. Recently, clinical studies have been emerging, and individualized treatment is attempted more frequently. However, an informative way to compare the treatment outcomes has not been established, and historical control data are missing for recurrent disease. We conducted a retrospective chart review of patients with recurrent DIPG treated between 1998 and 2010. Response progression-free survival and possible influencing factors were evaluated. Thirty-one patients were identified who were treated in 61 treatment attempts using 26 treatment elements in 31 different regimens. The most frequently used drugs were etoposide (14), bevacizumab (13), irinotecan (13), nimotuzumab (13), and valproic acid (13). Seven patients had repeat radiation therapy to the primary tumor. Response was recorded after 58 treatment attempts and was comprised of 0 treatment attempts with complete responses, 7 with partial responses, 20 with stable diseases, and 31 with progressive diseases The median progression-free survival after treatment start was 0.16 years (2 months) and was found to be correlated to the prior time to progression but not to the number of previous treatment attempts. Repeat radiation resulted in the highest response rates (4/7), and the longest progression-free survival. These data provide a basis to plan future clinical trials for recurrent DIPG. Repeat radiation therapy should be tested in a prospective clinical study. © 2011 Springer Science+Business Media, LLC.

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