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Institution

University of Colorado Colorado Springs

EducationColorado Springs, Colorado, United States
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.


Papers
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Proceedings ArticleDOI
17 Nov 2005
TL;DR: This paper presents an example that demonstrates how using and adapting cryptographic ideas and combining them with intelligent video processing, technological approaches can provide for solutions addressing these critical trade-offs, potentially improving both security and privacy.
Abstract: Signifiicant research progress has been made in intelligent imaging systems, surveillance and biometrics improving robustness, increasing performance and decreasing cost. As a result, deployment of surveillance and intelligent video systems is booming and increasing the impact of these on privacy. For many, networked intelligent video systems, especially video surveillance and biometrics, epitomize the invasion of privacy by an Orwellian "big brother:. While tens of millions in government funding have been spent on research improving video surveillance, virtually none has been invested in technologies to enhance privacy or effectively balance privacy and security. This paper presents an example that demonstrates how using and adapting cryptographic ideas and combining them with intelligent video processing, technological pproaches can provide for solutions addressing these critical trade-offs, potentially improving both security and privacy. After reviewing previous research in privacy improving technology in video systems, the paper then presents cryptographically invertible obscuration. This is an application of encryption techniques to improve the privacy aspects while allowing general surveillance to continue and allowing full access (i.e. violation ofprivacy) only with use of a decryption key, maintained by a court or other thirdparty.

117 citations

Journal ArticleDOI
TL;DR: In this paper, the status of current efforts to assimilate cloud and precipitation-affected satellite data is summarised with special focus on infrared and microwave radiance data obtained from operational Earth observation satellites.
Abstract: The status of current efforts to assimilate cloud- and precipitation-affected satellite data is summarised with special focus on infrared and microwave radiance data obtained from operational Earth observation satellites. All global centres pursue efforts to enhance infrared radiance data usage due to the limited availability of temperature observations in cloudy regions where forecast skill is estimated to strongly depend on the initial conditions. Most systems focus on the sharpening of weighting functions at cloud top providing high vertical resolution temperature increments to the analysis, mainly in areas of persistent high and low cloud cover. Microwave radiance assimilation produces impact on the deeper atmospheric moisture structures as well as cloud microphysics and, through control variable and background-error formulation, also on temperature but to lesser extent than infrared data. Examples of how the impacts of these two observation types are combined are shown for subtropical low-level cloud regimes. The overall impact of assimilating such data on forecast skill is measurably positive despite the fact that the employed assimilation systems have been constructed and optimized for clear-sky data. This leads to the conclusion that a better understanding and modelling of model processes in cloud-affected areas and data assimilation system enhancements through inclusion of moist processes and their error characterization will contribute substantially to future forecast improvement. Copyright © 2011 Royal Meteorological Society, Crown in the right of Canada, and British Crown copyright, the Met Office

117 citations

Journal ArticleDOI
TL;DR: This article examined the knowledge base of 142 elementary-level educators for implementing response-to-intervention (RTI) models in reading and found that participants who had prior code-focused professional development outperformed other participants on all survey subscales.
Abstract: This study examined the knowledge base of 142 elementary-level educators for implementing response-to-intervention (RTI) models in reading. A questionnaire assessed participants’ professional background for teaching reading, as well as their familiarity with specific assessments, research-based instructional models, and interventions potentially useful in RTI approaches. A multiple-choice knowledge survey patterned after a teacher licensure exam, including items situated in classroom contexts, assessed participants’ knowledge about different components of reading, assessment, and RTI practices. Overall, participants obtained the highest scores on a knowledge survey subscale involving fluency/vocabulary/comprehension and the lowest on a subscale involving assessment/RTI practices, with a subscale involving phonemic awareness/phonics in the middle. Mean percentages correct on the subscales ranged from about 58–65% correct. However, participants who said they had prior code-focused professional development outperformed other participants on all survey subscales. General elementary certified teachers performed comparably to special education certified teachers on two out of three subscales, with both groups outperforming unlicensed participants; on the assessment/RTI subscale, only the special educators outperformed unlicensed participants. Most participants were familiar with basic features of RTI such as the three tiered model but were unfamiliar with the research-based instructional approaches and interventions named in the study questionnaire, although participants who had experienced code-focused PD were significantly more likely to be familiar with certain interventions. The study suggests that professional development will be important to enable many educators to implement RTI effectively in reading.

117 citations

Journal ArticleDOI
TL;DR: In cardiology, artificial neural networks have been successfully applied to problems in the diagnosis and treatment of coronary artery disease and myocardial infarction, in electrocardiographic interpretation and detection of arrhythmias and in image analysis in cardiac radiography and sonography.

117 citations

Journal ArticleDOI
TL;DR: The following discussion will describe the pathologic changes that occur in the various units of the exposed alimentary tract and in various components of those units during and especially months or years after radiation therapy.
Abstract: In order to be effective in the treatment of disease, especially neoplastic disease, radiation necessarily needs to be given in large doses. When treating tumors with high radiosensitivity in tissue of relatively low radiosensitivity, few complications of therapy occur. Frequently, however, the differential of sensitivity to radiation between the neoplasm and normal tissues exposed is small and the incidence of radiation injury to normal tissues becomes significant. Nowhere is this more apparent than in treatment of neoplasms during which the alimentary canal is heavily radiated. The following discussion will describe the pathologic changes that occur in the various units of the exposed alimentary tract and in various components of those units during and especially months or years after radiation therapy. The usual rapid and effective regeneration of the rapid-renewal cell system after injury will be noted. The serious delayed manifestations of injury to the fibrovascular tissues with resulting delayed complications of ulcerations, stenoses, fistula formation, and obstructing adhesions will be emphasized. Brief discussions of several other organ systems injured by radiation will be presented.

116 citations


Authors

Showing all 6706 results

NameH-indexPapersCitations
Jeff Greenberg10554243600
James F. Scott9971458515
Martin Wikelski8942025821
Neil W. Kowall8927934943
Ananth Dodabalapur8539427246
Tom Pyszczynski8224630590
Patrick S. Kamath7846631281
Connie M. Weaver7747330985
Alejandro Lucia7568023967
Michael J. McKenna7035616227
Timothy J. Craig6945818340
Sheldon Solomon6715023916
Michael H. Stone6537016355
Christopher J. Gostout6533413593
Edward T. Ryan6030311822
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202325
202246
2021568
2020543
2019479
2018454