16,749 research outputs found

    Processing ERTS and Aircraft MSS data with the General Electric Image 100 system

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    There are no author-identified significant results in this report

    The Penn State ORSER system for processing and analyzing ERTS and other MSS data

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    The author has identified the following significant results. The office for Remote Sensing of Earth Resources (ORSER) of the Space Science and Engineering Laboratory at the Pennsylvania State University has developed an extensive operational system for processing and analyzing ERTS-1 and similar multispectral data. The ORSER system was developed for use by a wide variety of researchers working in remote sensing. Both photointerpretive techniques and automatic computer processing methods have been developed and used, separately and in a combined approach. A remote Job Entry system permits use of an IBM 370/168 computer from any compatible remote terminal, including equipment tied in by long distance telephone connections. An elementary cost analysis has been prepared for the processing of ERTS data

    Preliminary Skylab MSS channel evaluation

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    The author has identified the following significant results. A set of 18 channels which were considered of usable quality were identified. These were channels 1-14, 17, 19-21. Channels 15, 16, 18, and 22 were dropped out because they were of poor quality; channels 7 and 11 were dropped to limit the total channel number to 16. From these 16 channels, a total of 22 signatures were obtained. Eight were developed from uniform blocks of the UMAP, and 14 from use of the DCLUS program. These signatures fell into six basic categories and classified more than 90% of the five scenes mapped: agriculture land (6 signatures); forest aland (4); water (2); open nonagriculture land (2); urban (6); and disturbed land (2)

    A delta Scuti distance to the Large Magellanic Cloud

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    We present results from a well studied delta Scuti star discovered in the LMC. The absolute magnitude of the variable was determined from the PL relation for Galactic delta Scuti stars and from the theoretical modeling of the observed B,V,I light curves. The two methods give distance moduli for the LMC of 18.46+-0.19 and 18.48+-0.15, respectively, for a consistent value of the stellar reddening of E(B-V)=0.08+-0.02. We have also analyzed 24 delta Scuti candidates discovered in the OGLE II survey of the LMC, and 7 variables identified in the open cluster LW 55 and in the galaxy disk by Kaluzny et al. (2003, 2006). We find that the LMC delta Scuti stars define a PL relation whose slope is very similar to that defined by the Galactic delta Scuti variables, and yield a distance modulus for the LMC of 18.50+-0.22 mag. We compare the results obtained from the delta Scuti variables with those derived from the LMC RR Lyrae stars and Cepheids. Within the observational uncertainties, the three groups of pulsating stars yield very similar distance moduli. These moduli are all consistent with the "long" astronomical distance scale for the Large Magellanic Cloud.Comment: Accepted for publication on A

    Self-Supervised Learning for Cardiac MR Image Segmentation by Anatomical Position Prediction

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    In the recent years, convolutional neural networks have transformed the field of medical image analysis due to their capacity to learn discriminative image features for a variety of classification and regression tasks. However, successfully learning these features requires a large amount of manually annotated data, which is expensive to acquire and limited by the available resources of expert image analysts. Therefore, unsupervised, weakly-supervised and self-supervised feature learning techniques receive a lot of attention, which aim to utilise the vast amount of available data, while at the same time avoid or substantially reduce the effort of manual annotation. In this paper, we propose a novel way for training a cardiac MR image segmentation network, in which features are learnt in a self-supervised manner by predicting anatomical positions. The anatomical positions serve as a supervisory signal and do not require extra manual annotation. We demonstrate that this seemingly simple task provides a strong signal for feature learning and with self-supervised learning, we achieve a high segmentation accuracy that is better than or comparable to a U-net trained from scratch, especially at a small data setting. When only five annotated subjects are available, the proposed method improves the mean Dice metric from 0.811 to 0.852 for short-axis image segmentation, compared to the baseline U-net

    Correction of banding in MSS digital data

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    There are no author-identified significant results in this report

    Modifications to the University of Michigan 83‐Inch Cyclotron to Improve Beam Quality

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    Recent studies of the internal and extracted beams at the higher energies (up to 40‐MeV deuterons and 80‐MeV α‐particles) led us to convert the dee system of the 83‐inch cyclotron from two 150° dees to one 180° dee. The primary purpose was to remove from the deflector channel the rf dee voltage, which because of its phase opposes the dc deflector voltage and in addition introduces an energy spread in the extracted beam. The one‐dee system offers further advantages. The equivalent first harmonic due to a gap‐crossing driving force which is a function of the dee geometry and dee voltage balance in the two‐dee system, is essentially eliminated, and control of the central orbits, in particular the selection of phase width, is facilitated. The measured values of the beam quality and energy spread are in good agreement with calculations. These results, together with the diagnostic instrumentation used in obtaining them, are described.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/87291/2/366_1.pd

    Single-machine scheduling with stepwise tardiness costs and release times

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    We study a scheduling problem that belongs to the yard operations component of the railroad planning problems, namely the hump sequencing problem. The scheduling problem is characterized as a single-machine problem with stepwise tardiness cost objectives. This is a new scheduling criterion which is also relevant in the context of traditional machine scheduling problems. We produce complexity results that characterize some cases of the problem as pseudo-polynomially solvable. For the difficult-to-solve cases of the problem, we develop mathematical programming formulations, and propose heuristic algorithms. We test the formulations and heuristic algorithms on randomly generated single-machine scheduling problems and real-life datasets for the hump sequencing problem. Our experiments show promising results for both sets of problems

    BVRIJK light curves and radial velocity curves for selected Magellanic Cloud Cepheids

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    We present high precision and well sampled BVRIJK light curves and radial velocity curves for a sample of five Cepheids in the SMC. In addition we present radial velocity curves for three Cepheids in the LMC. The low metallicity (Fe/H ~ -0.7) SMC stars have been selected for use in a Baade-Wesselink type analysis to constrain the metallicity effect on the Cepheid Period-Luminosity relation. The stars have periods of around 15 days so they are similar to the Cepheids observed by the Extragalactic Distance Scale Key Project on the Hubble Space Telescope. We show that the stars are representative of the SMC Cepheid population at that period and thus will provide a good sample for the proposed analysis. The actual Baade-Wesselink analysis are presented in a companion paper.Comment: Accepted for publication in A&A, 23 pages, 10 figures, data tables will be made available electronically from the CD
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