Engineering topics
Publications and source records attributed to Kramer, C..
Design and characterization of a high-performance multi-acuity, multi-window dynamicaly reconfigurable vision (DRV) CMOS imager for real-time staring vision systems is presented.
Upper limits for the molecular gas mass of 11 high redshift (1.
The Amazon rain forest is a region of the earth that is undergoing rapid change. Man-made disturbance, such as clear cutting for agriculture or mining, is altering the rain forest ecosystem. For many parts of the rain forest, seasonal changes from the wet to the dry season are also significant. Changes in the seasonal cycle of flooding and draining can cause significant alterations in the forest ecosystem.Because much of the Amazon basin is regularly covered by thick clouds, optical and infrared coverage from the LANDSAT and SPOT satellites is sporadic. Imaging radar offers a much better potential for regular monitoring of changes in this region. In particular, the J-ERS-1 satellite carries an L-band HH SAR system, which via an on-board tape recorder, can collect data from almost anywhere on the globe at any time of year.In this paper, we show how J-ERS-1 radar images can be used to accurately classify different forest types (i.e., forest, hill forest, flooded forest), disturbed areas such as clear cuts and urban areas, and river courses in the Amazon basin. J-ERS-1 data has also shown significant differences between the dry and wet season, indicating a strong potential for monitoring seasonal change. The algorithm used to classify J-ERS-1 data is a standard maximum-likelihood classifier, using the radar image local mean and standard deviation of texture as input. Rivers and clear cuts are detected using edge detection and region-growing algorithms. Since this classifier is intended to operate successfully on data taken over the entire Amazon, several options are available to enable the user to modify the algorithm to suit a particular image.
Vegetation maps of inaccessible areas in the tropics tend to divide vegetation into broad types.
In recently years, Ga(0.5)In((0.5)P/GaAs cells have drawn increased attention both because of their high efficiencies and because they are well suited for space applications. They can be grown and processed as two-junction devices with roughly twice the voltage and half the current of GaAs cells. They have low temperature coefficients, and have good potential for radiation hardness. We have previously reported the effects of electron irradiation on test cells which were not optimally designed for space. From those results we estimated that an optimally designed cell could achieve 20 percent after irradiation with 10(exp 15) cm(exp -2) 1 MeV electrons. Modeling studies predicted that slightly higher efficiencies may be achievable. Record efficiencies for EOL performance of other types of cells are significantly lower. Even the best Si and InP cells have BOL efficiencies lower than the EOL efficiency we report here. Good GaAs cells have an EOL efficiency of 16 percent. The InP/Ga(0.5)In(0.5)As two-junction, two-terminal device has a BOL efficiency as high as 22.2 percent, but radiation results for these cells were limited. In this study we use the previous modeling and irradiation results to design a set of Ga(0.5)In(0.5)P/GaAs cells that will demonstrate the importance of the design parameters and result in high-efficiency devices. We report record AMO efficiencies: a BOL efficiency of 25.7 percent for a device optimized for BOL performance and two of different designs with EOL efficiencies of 19.6 percent (at 10(exp 15) cm(exp -2) 1MeV electrons). We vary the bottom-cell base doping and the top-cell thickness to show the effects of these two important design parameters. We get an unexpected result indicating that the dopant added to the bottom-cell base also increases the degradation of the top cell.
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We report on the detection of CO(4 [leads into, converted to] 3) and CO(5 [leads into, converted to] 4) emission from the powerful radio galaxy B2 0902+34 at a redshift < z(sub co) > = 3.3995 +/- )0.0002.