21,092 research outputs found

    Faculty Excellence

    Get PDF
    Each year, the University of New Hampshire selects a small number of its outstanding faculty for special recognition of their achievements in teaching, scholarship and service. Awards for Excellence in Teaching are given in each college and school, and university-wide awards recognize public service, research, teaching and engagement. This booklet details the year\u27s award winners\u27 accomplishments in short profiles with photographs and text

    Shifting perspectives: holography and the emergence of technical communities

    Get PDF
    Holography, the technology of three-dimensional imaging, has repeatedly been reconceptualised by new communities. Conceived in 1947 as a means of improving electron microscopy, holography was revitalized in the early 1960s by engineer-scientists at classified laboratories. The invention promoted the transformation of a would-be discipline (optical engineering) and spawned limited artist-scientist collaborations. However, a separate artisanal community promoted a distinct countercultural form of holography via a revolutionary technology: the sandbox optical table. Their tools, sponsorship, products, literature and engagement with wider culture differentiated the communities, which instituted a limited ‘technological trade’. The subject strikingly illustrates the co-evolution of new technology along with highly dissimilar user groups, neither of which fostered the secure establishment of a profession or discipline. The case generalises the concept of 'research-technologists' and 'peripheral science', and extends the ideas of Langdon Winner by demonstrating how the political dimensions of a technology can be important but evanescent in the growth of technical communities

    Spartan Daily, April 9, 1957

    Get PDF
    Volume 44, Issue 108https://scholarworks.sjsu.edu/spartandaily/12464/thumbnail.jp

    Advanced space system concepts and their orbital support needs (1980 - 2000). Volume 1: Executive summary

    Get PDF
    The likely system concepts which might be representative of NASA and DoD space programs in the 1980-2000 time period were studied along with the programs' likely needs for major space transportation vehicles, orbital support vehicles, and technology developments which could be shared by the military and civilian space establishments in that time period. Such needs could then be used by NASA as an input in determining the nature of its long-range development plan. The approach used was to develop a list of possible space system concepts (initiatives) in parallel with a list of needs based on consideration of the likely environments and goals of the future. The two lists thus obtained represented what could be done, regardless of need; and what should be done, regardless of capability, respectively. A set of development program plans for space application concepts was then assembled, matching needs against capabilities, and the requirements of the space concepts for support vehicles, transportation, and technology were extracted. The process was pursued in parallel for likely military and civilian programs, and the common support needs thus identified

    The application of remote sensing to resource management and environmental quality programs in Kansas

    Get PDF
    The activities of the Kansas Applied Remote Sensing (KARS) Program during the period April 1, 1982 through Marsh 31, 1983 are described. The most important work revolved around the Kansas Interagency Task Force on Applied Remote Sensing and its efforts to establish an operational service oriented remote sensing program in Kansas state government. Concomitant with this work was the upgrading of KARS capabilities to process data for state agencies through the vehicle of a low cost digital data processing system. The KARS Program continued to take an active role in irrigation mapping. KARS is now integrating data acquired through analysis of LANDSAT into geographic information systems designed for evaluating groundwater resources. KARS also continues to work at the national level on the national inventory of state natural resources information systems

    Spartan Daily, March 26, 1965

    Get PDF
    Volume 52, Issue 95https://scholarworks.sjsu.edu/spartandaily/4710/thumbnail.jp

    VANET Applications: Hot Use Cases

    Get PDF
    Current challenges of car manufacturers are to make roads safe, to achieve free flowing traffic with few congestions, and to reduce pollution by an effective fuel use. To reach these goals, many improvements are performed in-car, but more and more approaches rely on connected cars with communication capabilities between cars, with an infrastructure, or with IoT devices. Monitoring and coordinating vehicles allow then to compute intelligent ways of transportation. Connected cars have introduced a new way of thinking cars - not only as a mean for a driver to go from A to B, but as smart cars - a user extension like the smartphone today. In this report, we introduce concepts and specific vocabulary in order to classify current innovations or ideas on the emerging topic of smart car. We present a graphical categorization showing this evolution in function of the societal evolution. Different perspectives are adopted: a vehicle-centric view, a vehicle-network view, and a user-centric view; described by simple and complex use-cases and illustrated by a list of emerging and current projects from the academic and industrial worlds. We identified an empty space in innovation between the user and his car: paradoxically even if they are both in interaction, they are separated through different application uses. Future challenge is to interlace social concerns of the user within an intelligent and efficient driving

    Deep Thermal Imaging: Proximate Material Type Recognition in the Wild through Deep Learning of Spatial Surface Temperature Patterns

    Get PDF
    We introduce Deep Thermal Imaging, a new approach for close-range automatic recognition of materials to enhance the understanding of people and ubiquitous technologies of their proximal environment. Our approach uses a low-cost mobile thermal camera integrated into a smartphone to capture thermal textures. A deep neural network classifies these textures into material types. This approach works effectively without the need for ambient light sources or direct contact with materials. Furthermore, the use of a deep learning network removes the need to handcraft the set of features for different materials. We evaluated the performance of the system by training it to recognise 32 material types in both indoor and outdoor environments. Our approach produced recognition accuracies above 98% in 14,860 images of 15 indoor materials and above 89% in 26,584 images of 17 outdoor materials. We conclude by discussing its potentials for real-time use in HCI applications and future directions.Comment: Proceedings of the 2018 CHI Conference on Human Factors in Computing System
    • …
    corecore