• Title/Summary/Keyword: Mitchell's algorithm

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An analysis on the security of the 3GPP MAC algorithm (3GPP MAC 알고리즘 안전성 분석)

  • 홍도원;신상욱;강주성;이옥연
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.11 no.2
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    • pp.59-65
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    • 2001
  • 3GPP proposed a variant CBC-MAC based on the block cipher KASUMI to provide the data integrity over a radio access link. We have studied deeply the Knudsen and Mitchell\`s attack. In this paper we proposed a definite performing algorithm of the Knudsen and Mitchell\`s alack and compute the success probability and complexity of that algorithm. Moreover We also analyze a security of 3GPP-MAC comparing with the original CBC-MAC.

A low-cost compensated approximate multiplier for Bfloat16 data processing on convolutional neural network inference

  • Kim, HyunJin
    • ETRI Journal
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    • v.43 no.4
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    • pp.684-693
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    • 2021
  • This paper presents a low-cost two-stage approximate multiplier for bfloat16 (brain floating-point) data processing. For cost-efficient approximate multiplication, the first stage implements Mitchell's algorithm that performs the approximate multiplication using only two adders. The second stage adopts the exact multiplication to compensate for the error from the first stage by multiplying error terms and adding its truncated result to the final output. In our design, the low-cost multiplications in both stages can reduce hardware costs significantly and provide low relative errors by compensating for the error from the first stage. We apply our approximate multiplier to the convolutional neural network (CNN) inferences, which shows small accuracy drops with well-known pre-trained models for the ImageNet database. Therefore, our design allows low-cost CNN inference systems with high test accuracy.

Calibration and Validation of Ocean Color Satellite Imagery (해양수색 위성자료의 검.보정)

  • ;B. G. Mitchell
    • Journal of Environmental Science International
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    • v.10 no.6
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    • pp.431-436
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    • 2001
  • Variations in phytoplankton concentrations result from changes of the ocean color caused by phytoplankton pigments. Thus, ocean spectral reflectance for low chlorophyll waters are blue and high chlorophyll waters tend to have green reflectance. In the Korea region, clear waters and the open sea in the Kuroshio regions of the East China Sea have low chlorophyll. As one moves even closer In the northwestern part of the East China Sea, the situation becomes much more optically complicated, with contributions not only from higher concentration of phytoplankton, but also from sediments and dissolved materials from terrestrial and sea bottom sources. The color often approaches yellow-brown in the turbidity waters (Case Ⅱ waters). To verify satellite ocean color retrievals, or to develop new algorithms for complex case Ⅱ regions requires ship-based studies. In this study, we compared the chlorophyll retrievals from NASA's SeaWiFS sensor with chlorophyll values determined with standard fluorometric methods during two cruises on Korean NFRDI ships. For the SeaWiFS data, we used the standard NASA SeaWiFS algorithm to estimate the chlorophyll_a distribution around the Korean waters using Orbview/ SeaWiFS satellite data acquired by our HPRT station at NFRDl. We studied In find out the relationship between the measured chlorophyll_a from the ship and the estimated chlorophyll_a from the SeaWiFs satellite data around the northern part of the East China Sea, in February, and May, 2000. The relationship between the measured chlorophyll_a and the SeaWiFS chlorophyll_a shows following the equations (1) In the northern part of the East China Sea. Chlorophyll_a =0.121Ln(X) + 0.504, R²= 0.73 (1) We also determined total suspended sediment mass (55) and compared it with SeaWiFS spectral band ratio. A suspended solid algorithm was composed of in-.situ data and the ratio (L/sub WN/(490 ㎚)L/sub WN/(555 ㎚) of the SeaWiFS wavelength bands. The relationship between the measured suspended solid and the SeaWiFS band ratio shows following the equation (2) in the northern part of the East China Sea. SS = -0.703 Ln(X) + 2.237, R²= 0.62 (2) In the near future, NFRDI will develop algorithms for quantifying the ocean color properties around the Korean waters, with the data from regular ocean observations using its own research vessels and from three satellites, KOMPSAT/OSMl, Terra/MODIS and Orbview/SeaWiFS.

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