430 research outputs found

    Alternative packet switch architectures for a 30/20 GHz FDMA/TDMA geostationary communication satellite network

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    This study has investigated alternatives for realizing a packet-based network switch for deployment on a communication satellite. The emphasis was on the avoidance of contention problems that can occur due to the simultaneous arrival of an excessive number of packets destined for the same downlink dwell. The study was to look ahead, beyond the current Advanced Communications Technology Satellite (ACTS) capability, to the next generation of satellites. The study has not been limited by currently available technology, but has used university and commercial research efforts as a basis for designs that can be readily constructed and launched within the next five years. Tradeoffs in memory requirement, power requirement, and architecture have been considered as a part of our study

    Technical support for digital systems technology development. Task order 1: ISP contention analysis and control

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    Alternatives for realizing a packet-based network switch for use on a frequency division multiple access/time division multiplexed (FDMA/TDM) geostationary communication satellite were investigated. Each of the eight downlink beams supports eight directed dwells. The design needed to accommodate multicast packets with very low probability of loss due to contention. Three switch architectures were designed and analyzed. An output-queued, shared bus system yielded a functionally simple system, utilizing a first-in, first-out (FIFO) memory per downlink dwell, but at the expense of a large total memory requirement. A shared memory architecture offered the most efficiency in memory requirements, requiring about half the memory of the shared bus design. The processing requirement for the shared-memory system adds system complexity that may offset the benefits of the smaller memory. An alternative design using a shared memory buffer per downlink beam decreases circuit complexity through a distributed design, and requires at most 1000 packets of memory more than the completely shared memory design. Modifications to the basic packet switch designs were proposed to accommodate circuit-switched traffic, which must be served on a periodic basis with minimal delay. Methods for dynamically controlling the downlink dwell lengths were developed and analyzed. These methods adapt quickly to changing traffic demands, and do not add significant complexity or cost to the satellite and ground station designs. Methods for reducing the memory requirement by not requiring the satellite to store full packets were also proposed and analyzed. In addition, optimal packet and dwell lengths were computed as functions of memory size for the three switch architectures

    Deep learning-based fully automatic segmentation of wrist cartilage in MR images

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    The study objective was to investigate the performance of a dedicated convolutional neural network (CNN) optimized for wrist cartilage segmentation from 2D MR images. CNN utilized a planar architecture and patch-based (PB) training approach that ensured optimal performance in the presence of a limited amount of training data. The CNN was trained and validated in twenty multi-slice MRI datasets acquired with two different coils in eleven subjects (healthy volunteers and patients). The validation included a comparison with the alternative state-of-the-art CNN methods for the segmentation of joints from MR images and the ground-truth manual segmentation. When trained on the limited training data, the CNN outperformed significantly image-based and patch-based U-Net networks. Our PB-CNN also demonstrated a good agreement with manual segmentation (Sorensen-Dice similarity coefficient (DSC) = 0.81) in the representative (central coronal) slices with large amount of cartilage tissue. Reduced performance of the network for slices with a very limited amount of cartilage tissue suggests the need for fully 3D convolutional networks to provide uniform performance across the joint. The study also assessed inter- and intra-observer variability of the manual wrist cartilage segmentation (DSC=0.78-0.88 and 0.9, respectively). The proposed deep-learning-based segmentation of the wrist cartilage from MRI could facilitate research of novel imaging markers of wrist osteoarthritis to characterize its progression and response to therapy

    Fertilizer Statistics for Texas, 1926-1938.

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    23 p

    Commercial Fertilizers in 1944-45.

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    31 p

    Commercial Fertilizers in 1943-44.

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    pg 2

    Integrated data requirements for natural resource management

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    We do not have sufficient data to adequately describe the integrated socio-ecologicalsystems that support us. It is prohibitively expensive to collect enough data to describe all,so it is important to think strategically about how to (i) use the information we do have and (ii) prioritise the collection of new data. We aim to help by finding efficient ways of improving the information that is available for policy-makers to generate better human–nature outcomes
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