• Title/Summary/Keyword: spectral

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MODEL INFRARED SPECTRA FOR PROTO STARS

  • 서경원;송인옥
    • Journal of Astronomy and Space Sciences
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    • v.14 no.2
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    • pp.202-206
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    • 1997
  • We have modeled the infrared spectral energy distributions of proto stars with close attention to the dust envelopes around the stars. The observed spectral energy distributions are closely compared with our models. The model results and observations are compared on IRAS color-color diagrams. Typical model results can explain the observations fairly well.

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SPECTRAL SENSITIZATION AND PHOTOGRAPHIC CHARACTERISTICS OF NAPHTHOTHIAZOLO CARBOCYANINE DYE

  • Kim, Yeoung-Chan
    • Journal of Photoscience
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    • v.3 no.2
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    • pp.65-69
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    • 1996
  • In this paper, it was studied about the red-sensitive layer. UV-Vis data of the dye at monomeric and J-state were considered with respect to their performance(contrast, density and fog) in photographic emulsion. The sensitizing effect of the dye is found to be strongly structuredependent. Naphthothiazolo carbocyanine dye can be used as red-sensitizing dye for the spectral sensitization of photographic emulsion.

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On a Generalized Volterra Equation by means of Spectral Measures

  • Kim, Jee Gon
    • The Mathematical Education
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    • v.21 no.3
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    • pp.25-28
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    • 1983
  • In this paper we examine some properties of spectral measures and try to establish a fundamental theorem on the existence of the solution of a generalized Volterra equation in a Hilbert space as the results.

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DEPTH OF TOR

  • Choi, Sang-Ki
    • Bulletin of the Korean Mathematical Society
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    • v.37 no.1
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    • pp.103-108
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    • 2000
  • Using spectral sequences we calculate the highest nonvanishing index of Tor for modules of finite projective dimension. The result is applied to compute the depth of the highest nonvanishing Tor. This is one of the cases when a problem of Auslander is positive.

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Prediction of the Following BCI Performance by Means of Spectral EEG Characteristics in the Prior Resting State (뇌신호 주파수 특성을 이용한 CNN 기반 BCI 성능 예측)

  • Kang, Jae-Hwan;Kim, Sung-Hee;Youn, Joosang;Kim, Junsuk
    • KIPS Transactions on Computer and Communication Systems
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    • v.9 no.11
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    • pp.265-272
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    • 2020
  • In the research of brain computer interface (BCI) technology, one of the big problems encountered is how to deal with some people as called the BCI-illiteracy group who could not control the BCI system. To approach this problem efficiently, we investigated a kind of spectral EEG characteristics in the prior resting state in association with BCI performance in the following BCI tasks. First, spectral powers of EEG signals in the resting state with both eyes-open and eyes-closed conditions were respectively extracted. Second, a convolution neural network (CNN) based binary classifier discriminated the binary motor imagery intention in the BCI task. Both the linear correlation and binary prediction methods confirmed that the spectral EEG characteristics in the prior resting state were highly related to the BCI performance in the following BCI task. Linear regression analysis demonstrated that the relative ratio of the 13 Hz below and above the spectral power in the resting state with only eyes-open, not eyes-closed condition, were significantly correlated with the quantified metrics of the BCI performance (r=0.544). A binary classifier based on the linear regression with L1 regularization method was able to discriminate the high-performance group and low-performance group in the following BCI task by using the spectral-based EEG features in the precedent resting state (AUC=0.817). These results strongly support that the spectral EEG characteristics in the frontal regions during the resting state with eyes-open condition should be used as a good predictor of the following BCI task performance.