University of Colorado Colorado Springs

About: University of Colorado Colorado Springs is a education organization based out in Colorado Springs, Colorado, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 6664 authors who have published 10872 publications receiving 323416 citations. The organization is also known as: UCCS & University of Colorado at Colorado Springs.

Adverse Health Consequences of Performance-Enhancing Drugs: An Endocrine Society Scientific Statement

Abstract: Despite the high prevalence of performance-enhancing drug (PED) use, media attention has focused almost entirely on PED use by elite athletes to illicitly gain a competitive advantage in sports, and not on the health risks of PEDs. There is a widespread misperception that PED use is safe or that adverse effects are manageable. In reality, the vast majority of PED users are not athletes but rather nonathlete weightlifters, and the adverse health effects of PED use are greatly underappreciated. This scientific statement synthesizes available information on the medical consequences of PED use, identifies gaps in knowledge, and aims to focus the attention of the medical community and policymakers on PED use as an important public health problem. PED users frequently consume highly supraphysiologic doses of PEDs, combine them with other PEDs and/or other classical drugs of abuse, and display additional associated risk factors. PED use has been linked to an increased risk of death and a wide variety of cardiova...

Particle swarm optimization

Abstract: Gerhard Venter (gventer_vrand.conl) *Vanderpla(ds Research and Development, bit.1767 S 8th St'reef. Suite 100, Colorado Springs. CO 80906Jaroslaw Sobieszczanski-Sobieski (j.sobieski:_larc.nasa.gov) *A_4SA Lcmgley Research Ce,_terMS 240, Hampton, I:4 23681-2199The purpose of this paper is to show how the search algorithm, known as par-ticle swarm optimization performs. Here, particle swarm optimization ks appliedto structural design problems, but the method.has a much wider range of possi-ble applications. The paper's new contributions are improvements to the particleswarm optimization algorithm and conclusions and recommendations as to theutility of the algorithm. Results of numerical experiments for both continuousand discrete applications are presented in the paper. The results indicate that theparticle swarm optimization algorithm does locate the constrained minimum de-sign in continuous applications with very good precision, albeit at a much highercomputational cost than that of a typical gradient based optimizer. However, thetrue potential of particle swarm optimization is primarily in applications withdiscrete and/or discontinuous functions and variables. Additionally, particleswarm optimization has the potential of e3_icient computation with very largenumbers of concurrently operating processors.

Approximation methods in multidisciplinary analysis and optimization: a panel discussion

Abstract: This paper summarizes the discussion at the Approximation Methods Panel that was held at the 9 th AIAA/ISSMO Symposium on Multidisciplinary Analysis & Optimization in Atlanta, GA on September 2–4, 2002. The objective of the panel was to discuss the current state-of-the-art of approximation methods and identify future research directions important to the community. The panel consisted of five representatives from industry and government: (1) Andrew J. Booker from The Boeing Company, (2) Dipankar Ghosh from Vanderplaats Research & Development, (3) Anthony A. Giunta from Sandia National Laboratories, (4) Patrick N. Koch from Engineous Software, Inc., and (5) Ren-Jye Yang from Ford Motor Company. Each panelist was asked to (i) give one or two brief examples of typical uses of approximation methods by his company, (ii) describe the current state-of-the-art of these methods used by his company, (iii) describe the current challenges in the use and adoption of approximation methods within his company, and (iv) identify future research directions in approximation methods. Several common themes arose from the discussion, including differentiating between design of experiments and design and analysis of computer experiments, visualizing experimental results and data from approximation models, capturing uncertainty with approximation methods, and handling problems with large numbers of variables. These are discussed in turn along with the future directions identified by the panelists, which emphasized educating engineers in using approximation methods.

Promoting Causal Agency: The Self-Determined Learning Model of Instruction

Abstract: Teachers seeking to promote the self-determination of their students must enable them to become self-regulated problem-solvers. This article introduces a model of teaching, The Self-Determined Learning Model of Instruction, incorporating principles of self-determination, which enables teachers to teach students to become causal agents in their own lives. This model was field-tested with students with disabilities. Students receiving instruction from teachers using the model attained educationally relevant goals, showed enhanced self-determination, and communicated their satisfaction with the process. Teachers implementing the model likewise indicated their satisfaction with the process and suggested that they would continue to use the model after the completion of the field test.