• The Bulletin of The Korean Astronomical Society
• /
• v.46 no.1
• /
• pp.47.4-48
• /
• 2021

Gravitationally lensed Type Ia supernovae may be the next frontier in cosmic probes, able to deliver independent constraints on dark energy, spatial curvature, and the Hubble constant. Measurements of time delays between the multiple images become more incisive due to the standardized candle nature of the source, monitoring for months rather than years, and partial immunity to microlensing. While currently extremely rare, hundreds of such systems should be detected by upcoming time-domain surveys. Others will have the images spatially unresolved, with the observed lightcurve a superposition of time delayed image fluxes. We investigate whether unresolved images can be recognized as lensed sources given only lightcurve information and whether time delays can be extracted robustly. We develop a method that we show can identify these systems for the case of lensed Type Ia supernovae with two images and time delays exceeding ten days. When tested on such an ensemble the method achieves a false positive rate of ≲5%, and measures the time delays with the completeness of ≳93% and with a bias of ≲0.5% for time delay ≳10 days. Since the method does not assume a template of any particular type of SN, the method has the potential to work on other types of lensed SNe systems and possibly on other transients.

• The Bulletin of The Korean Astronomical Society
• /
• v.33 no.1
• /
• pp.31.1-31.1
• /
• 2008

• Journal of Biomedical Engineering Research
• /
• v.14 no.1
• /
• pp.9-16
• /
• 1993

For efficient storage and transmission of medical images, the requirement of image com pression is increasing. Because differences between reconstructed images and original images are related with errors In the diagnosis, lossless compression is generally preferred in mod- ical images. in Run Length Coding which is one of the lossless compression method, we have applied modified scanning direction based on the Hilbert curve, which is a kind of space fill ins curve. We have substituted the traditional raster scanning by Hilbert curve direction scanning. Using this method, we have studied enhancement of compression efficiency for medical images.

• Aerospace Engineering and Technology
• /
• v.12 no.2
• /
• pp.64-73
• /
• 2013

In order to observe the deep space more efficiently, a satellite installed with a telescope on earth is needed. Advanced countries in space such as U.S.A and E.U. etc. have obtained and analyzed informations and images of the space from Hubble telescope, Kepler space observatory and Herschel space observatory. This paper studied specifications and operation status of space observation satellite of the several foreign countries and described technologies and plans for the domestic deep space observation satellite.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.37 no.6
• /
• pp.1077-1085
• /
• 2017

Urban space is a place that shows the behavior, experience and lifestyle of residents. Also by the combination of local attributes and assets, creating a space that reflects the unique image of the city. For the development of the city, it is important to actively reflect the identity of the space created by the difference of each space. In this study, we focused on the disparate of space and found the characteristics of urban space. And psychological factors on disparate images of the spatial analysis. As a result, 14 spatial image characteristics of Busan showed difference. In terms of dimensions, it could be classified as an natural, artificial, dynamic, static images. Also, the preference cluster of individuals showed a positive response in naturalness, openness, gentle slope and static space.

• The Bulletin of The Korean Astronomical Society
• /
• v.44 no.2
• /
• pp.58.2-58.2
• /
• 2019

BITSE is a technology demonstration mission to remotely measure the speed, temperature, and density of the solar wind as it forms as close as 3 Rs. BITSE obtained coronal images during its one day flight above more than 99% of the atmosphere, and calibration data are taken in the laboratory as well as during the flight. As the linearly polarized K-corona is much fainter than other bright sources like diffraction, sky, and F-corona, a careful data reduction is required to obtain reliable scientific results. We will report status of the obtained data, the reduction progress, and future plan.

• Bulletin of the Korean Space Science Society
• /
• 2000.04a
• /
• pp.26-26
• /
• 2000

No Abstract, See Full Text

• Bulletin of the Korean Space Science Society
• /
• 1999.04a
• /
• pp.21-21
• /
• 1999

No Abstract, See Full Text

• Journal of Broadcast Engineering
• /
• v.19 no.5
• /
• pp.677-686
• /
• 2014

This paper analyzes the 3D accuracy of stereo images captured from a mobile phone. For 3D accuracy evaluation, we have compared the accuracy result according to the amount of the convergence angle. In order to calculate the 3D model space coordinate of control points, we perform inner orientation, distortion correction and image geometry estimation. And the quantitative 3D accuracy was evaluated by transforming the 3D model space coordinate into the 3D object space coordinate. The result showed that relatively precise 3D information is generated in more than $17^{\circ}$ convergence angle. Consequently, it is necessary to set up stereo model structure consisting adequate convergence angle as an measurement distance and a baseline distance for accurate 3D information generation. It is expected that the result would be used to stereoscopic 3D contents and 3D reconstruction from images captured by a mobile phone camera.

• The Bulletin of The Korean Astronomical Society
• /
• v.42 no.2
• /
• pp.61.1-61.1
• /
• 2017

As the application of deep-learning methods has been succeeded in various fields, they have a high potential to be applied to space weather forecasting. Convolutional neural network, one of deep learning methods, is specialized in image recognition. In this study, we apply the AlexNet architecture, which is a winner of Imagenet Large Scale Virtual Recognition Challenge (ILSVRC) 2012, to the forecast of daily solar flare occurrence using the MatConvNet software of MATLAB. Our input images are SOHO/MDI, EIT $195{\AA}$, and $304{\AA}$ from January 1996 to December 2010, and output ones are yes or no of flare occurrence. We consider other input images which consist of last two images and their difference image. We select training dataset from Jan 1996 to Dec 2000 and from Jan 2003 to Dec 2008. Testing dataset is chosen from Jan 2001 to Dec 2002 and from Jan 2009 to Dec 2010 in order to consider the solar cycle effect. In training dataset, we randomly select one fifth of training data for validation dataset to avoid the over-fitting problem. Our model successfully forecasts the flare occurrence with about 0.90 probability of detection (POD) for common flares (C-, M-, and X-class). While POD of major flares (M- and X-class) forecasting is 0.96, false alarm rate (FAR) also scores relatively high(0.60). We also present several statistical parameters such as critical success index (CSI) and true skill statistics (TSS). All statistical parameters do not strongly depend on the number of input data sets. Our model can immediately be applied to automatic forecasting service when image data are available.