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.

The Prevalence of Depression in Male Sex Addicts Residing in the United States

Abstract: This study evaluated the prevalence of depression among male sex addicts against the general male population. This research utilized the high estimate of 12% for male depression in the general population as reported by the Diagnostic and Statistical Manual of Mental Disorders (American Psychiatric Association, 2000). This research had 418 participants, 220 of whom qualified as male sexual addicts residing in the United States. Participants were recipients of a free sexual recovery e-mail newsletter from www.sexaddict.com. A score of 14 or higher on the Sexual Addiction Screening Test operationally defined sexual addiction. A score of 14 or higher on the Beck Depression Inventory (BDI) operationally defined depression. Male sex addicts had a 28% prevalence rate of depression. The hypothesis of male sex addicts having higher scores on the BDI was upheld. An exploratory hypothesis, that participants having received treatment for sexual addiction would have lower depression scores, was upheld.

Social support mediates the effects of dual-focus mutual aid groups on abstinence from substance use.

Abstract: Background: Specialized 12-step based groups have emerged to address the needs of persons recovering from both substance abuse and psychiatric illness. Objective: This study investigates the role of social support in mediating the association between mutual aid participation and subsequent substance use for dually diagnosed persons. Method: A cohort of Double Trouble in Recovery (DTR) members in New York City were studied prospectively over a two-year period. Findings: Longer DTR participation during the first year of the study was associated with lower substance use in the second year; that effect was partially explained by the maintenance of high level of social support. Conclusion: These findings speak of the enduring influence of 12-step attendance on reducing substance use, and underline the importance of both 12-step attendance and supportive networks for dually diagnosed persons.

Remote usability testing

Abstract: Imagine being able to collect data lie static and full motion screen images, user video, and user comments , through your computer. Think about observing from your office or lab as an evaluation participant worked in their own o&e. What if you could sample from an intercity, interregional, or international user base without having to leave your office or lab? Thanks to recent developments in the areas of information sharing and collabora-tive work tools, each of these objectives is now attainable Usability evaluators can now view computer networks and modem connections as frameworks upon which distributed usability labs can be constructed, and all network or modem accessible machines as potential windows into remote test sites. These remote test sites can range from a machine down the hall to one on the other side of the world. The technological building blocks needed to create remote testing facilities are now available, in varying degrees, on all major computing platforms (i.e., Unix, MS Windows, Macintosh, OS/2). With computer-to-computer video conferencing tools product development teams can now both see and listen to evaluation participants sitting in front of properly equipped computers anywhere in the world. They can observe evaluation participants as they examine and annotate screen shots or g documentation using shared whiteboard tools. Observers can also watch full motion images of f the participant's screen from remote locations H g as participants use their products. By mixing p and matching these technological building i blocks, usability specialists can conduct a myri-ad of usability engineering activities remotely.

Meeting Mr. Farmer Versus Meeting a Farmer: Specific Effects of Aging on Learning Proper Names.

Abstract: Previous research testing age-related learning and memory problems specific to proper names has yielded mixed results. In the present experiments, young and older participants saw faces of previously unknown people identified by name and occupation. On subsequent presentations of each picture, participants attempted to recall the pictured person's name and occupation. Young and older adults made more name errors (the occupation was recalled but not the correct name) than occupation errors (the name was recalled but not the correct occupation), and older adults made relatively more name but not occupation errors than young adults. This specific age-related deficit in proper-name learning is explained within an interactive-activation model of memory and language that has been extensively applied to cognitive aging and proper-name retrieval.

Robust fusion: extreme value theory for recognition score normalization

Abstract: Recognition problems in computer vision often benefit from a fusion of different algorithms and/or sensors, with score level fusion being among the most widely used fusion approaches. Choosing an appropriate score normalization technique before fusion is a fundamentally difficult problem because of the disparate nature of the underlying distributions of scores for different sources of data. Further complications are introduced when one or more fusion inputs outright fail or have adversarial inputs, which we find in the fields of biometrics and forgery detection. Ideally a score normalization should be robust to model assumptions, modeling errors, and parameter estimation errors, as well as robust to algorithm failure. In this paper, we introduce the w-score, a new technique for robust recognition score normalization. We do not assume a match or non-match distribution, but instead suggest that the top scores of a recognition system's non-match scores follow the statistical Extreme Value Theory, and show how to use that to provide consistent robust normalization with a strong statistical basis.