1,113 research outputs found

    Solar optical telescope dome control system Patent

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    Light sensitive control system for automatically opening and closing dome of solar optical telescop

    Surveying Persons with Disabilities: A Source Guide (Version 1)

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    As a collaborator with the Cornell Rehabilitation Research and Training Center on Disability Demographics and Statistics, Mathematica Policy Research, Inc. has been working on a project that identifies the strengths and limitations in existing disability data collection in both content and data collection methodology. The intended outcomes of this project include expanding and synthesizing knowledge of best practices and the extent existing data use those practices, informing the development of data enhancement options, and contributing to a more informed use of existing data. In an effort to provide the public with an up-to-date and easily accessible source of research on the methodological issues associated with surveying persons with disabilities, MPR has prepared a Source Guide of material related to this topic. The Source Guide contains 150 abstracts, summaries, and references, followed by a Subject Index, which cross references the sources from the Reference List under various subjects. The Source Guide is viewed as a “living document,” and will be periodically updated

    Readout system for radiation detector

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    Improved electrical circuit determines the amount of light detected by a photomultiplier tube when its output signal is in the dark-current range of the tube. The low-intensity light to which the tube responds arises from a thermo-luminescent ionized dosimeter

    The Icon Formation of Ruby Bridges Within Hegemonic Memory of the Civil Rights Movement

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    In 1960, when Ruby Bridges was six-years-old, she desegregated the formerly all white William Frantz Elementary School in New Orleans, Louisiana. This thesis traces her formation as a Civil Rights icon and how her icon narratives are influenced by, perpetuate, or challenge hegemonic memory of the Civil Rights Movement. The hegemonic narrative situates the Civil Rights Movement as a triumphant moment of the past, and is based upon the belief that it abolished institutionalized racism, leaving us in a world where lingering prejudice is the result of the failings of individuals. Analysis of narratives about Ruby Bridges by Norman Rockwell, Robert Coles, and Bridges herself show that there is a consistent shift over time in which the icon narratives conform to and reinforce the hegemonic narrative. These icon narratives situate Bridges’ story as a historical account of the past that teaches lessons of how to combat instances of interpersonal racism through kindness and tolerance, and obscures Bridges’ lived experience. These reductive stories demonstrate just how powerful the hegemonic narrative is and create a comforting morality tale that pervades dominant culture and prevents us from understanding and finding ways to combat the institutionalized racism and inequality that still exists within the United States

    Three R\u27s and the Hickory Stick on the Texas Frontier

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    From the Reviews Editor

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    Contributors

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    The Atomic Bomb: A Violent Means of Peacemaking

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    Undergraduate Textual or Investigativ

    Intelligent Selection Techniques For Virtual Environments

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    Selection in 3D games and simulations is a well-studied problem. Many techniques have been created to address many of the typical scenarios a user could experience. For any single scenario with consistent conditions, there is likely a technique which is well suited. If there isn\u27t, then there is an opportunity for one to be created to best suit the expected conditions of that new scenario. It is critical that the user be given an appropriate technique to interact with their environment. Without it, the entire experience is at risk of becoming burdensome and not enjoyable. With all of the different possible scenarios, it can become problematic when two or more are part of the same program. If they are put closely together, or even intertwined, then the developer is often forced to pick a single technique that works so-so in both, but is likely not optimal for either, or maybe optimal in just one of them. In this case, the user is left to perform selections with a technique that is lacking in one way or another, which can increase errors and frustration. In our research, we have outlined different selection scenarios, all of which were classified by their level of object density (number of objects in scene) and object velocity. We then performed an initial study on how it impacts performance of various selection techniques, including a new selection technique that we developed just for this test, called Expand. Our results showed, among other things, that a standard Raycast technique works well in slow moving and sparse environments, while revealing that our new Expand technique works well in denser environments. With the results from our first study, we sought to develop something that would bridge the gap in performance between those selection techniques tested. Our idea was a framework that could harvest several different selection techniques and determine which was the most optimal at any time. Each selection technique would report how effective it was, given the provided scenario conditions. The framework was responsible for activating the appropriate selection technique when the user made a selection attempt. With this framework in hand, we performed two additional user studies to determine how effective it could be in actual use, and to identify its strengths and weaknesses. Each study compared several selection techniques individually against the framework which utilized them collectively, picking the most suitable. Again, the same scenarios from our first study were reused. From these studies, we gained a deeper understanding of the many challenges associated with automatic selection technique determination. The results from these two studies showed that transitioning between techniques was potentially viable, but rife with design challenges that made its optimization quite difficult. In an effort to sidestep some of the issues surrounding the switching of discrete techniques, we sought to attack the problem from the other direction, and make a single technique act similarly to two techniques, adjusting dynamically to conditions. We performed a user study to analyze the performance of such a technique, with promising results. While the qualitative differences were small, the user feedback did indicate that users preferred this technique over the others, which were static in nature. Finally, we sought to gain a deeper understanding of existing selection techniques that were dynamic in nature, and study how they were designed, and how they could be improved. We scrutinized the attributes of each technique that were already being adjusted dynamically or that could be adjusted and innovated new ways in which the technique could be improved upon. Within this analysis, we also gave thought to how each technique could be best integrated into the Auto-Select framework we proposed earlier. This overall analysis of the latest selection techniques left us with an array of new variants that warrant being created and tested against their existing versions. Our overall research goal was to perform an analysis of selection techniques that intelligently adapt to their environment. We believe that we achieved this by performing several iterative development cycles, including user studies and ultimately leading to innovation in the field of selection. We conclude our research with yet more questions left to be answered. We intend to pursue further research regarding some of these questions, as time permits
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