• The Korean Journal of Applied Statistics
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• v.25 no.6
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• pp.925-932
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• 2012

The article introduces a method to estimate a cointegrated vector autoregressive model, using mixed-frequency data, in terms of a state-space representation of the vector error correction(VECM) of the model. The method directly estimates the parameters of the model, in a state-space form of its VECM representation, using the available data in its mixed-frequency form. Then it allows one to compute in-sample smoothed estimates and out-of-sample forecasts at their high-frequency intervals using the estimated model. The method is applied to a mixed-frequency data set that consists of the quarterly real gross domestic product and three monthly coincident indicators. The result shows that the method produces accurate smoothed and forecasted estimates in comparison to a method based on single-frequency data.

• Publications of The Korean Astronomical Society
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• v.32 no.1
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• pp.5-9
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• 2017

This paper provides an overview of the AKARI mission, which was the first Japanese satellite dedicated to infrared astronomy. The AKARI satellite was launched in 2006, and performed both an all-sky survey and pointed observations during its 550 days in the He-cooled mission phases (Phases 1 and 2). After the He ran out, we continued near-infrared observations with mechanical cryocoolers (Phase 3). Due to a failure of its power supply, AKARI was turned off in 2011. The AKARI data are unique in terms of the observed wavelengths as well as the sky coverage, and provide a unique legacy resource for many astronomical studies. Since April 2013, a dedicated new team has been working to refine the AKARI data processing. The goal of this activity is to provide processed datasets for most of the AKARI observations in a Science Ready form, so that more users can utilize the AKARI data in their astronomical research. The data to be released will include revised All-Sky Point Source Catalogues, All-Sky Image Maps, as well as high-sensitivity images and spectra obtained by pointed observations. We expect that the data will be made public by in the Spring of 2016.

• Journal of Astronomy and Space Sciences
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• v.33 no.1
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• pp.45-54
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• 2016

This study developed an approach for improving Carrier-phase Differential Global Positioning System (CDGPS) based realtime satellite relative navigation by applying laser baseline measurement data. The robustness against the space operational environment was considered, and a Synthetic Wavelength Interferometer (SWI) algorithm based on a femtosecond laser measurement model was developed. The phase differences between two laser wavelengths were combined to measure precise distance. Generated laser data were used to improve estimation accuracy for the float ambiguity of CDGPS data. Relative navigation simulations in real-time were performed using the extended Kalman filter algorithm. The GPS and laser-combined relative navigation accuracy was compared with GPS-only relative navigation solutions to determine the impact of laser data on relative navigation. In numerical simulations, the success rate of integer ambiguity resolution increased when laser data was added to GPS data. The relative navigational errors also improved five-fold and two-fold, relative to the GPS-only error, for 250 m and 5 km initial relative distances, respectively. The methodology developed in this study is suitable for application to future satellite formation-flying missions.

• Publications of The Korean Astronomical Society
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• v.21 no.1
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• pp.1-9
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• 2006

An archiving system designed to enable documenting database of astronomical images, with functions of search and download, is being developed by Korean Astronomical Data Center(KADC) of Korea Astronomy and Space Science Institute(KASI). The system consists of three PCs for web server, database server, and system management server. The search program for the web environment is operated in the web server. In the management server, several utility program we developed are installed: input program for the database, program for transfer from fits to jpg files, program for data recovery and management, and programs for statistics and connect management. The collected data would be sorted out by the system manager to input into the database. The online input is possible in an observatory where the data is produced. We applied the content management system(CMS) module for the database management. On the basic of CMS module, we set up a management system for the whole life cycle of metadata from creation and collection to storage and deletion of the data. For the search function, we employed a technique to extract indices from the metadata. In addition, MySQL is adopted for DBMS. We currently display about 2,700 and 25,000 photographs for astronomical phenomena and astronomical objects on the data, respectively.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.337-340
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• 2007

Many researches conducted to investigate the relationship between surface emissivity and surface temperature in the past two decades and pointed out that the emissivity play a key role in applying remote sensing data to retrieve surface temperature. The task of surface temperature estimation is so important in many research fields, such as earth energy budgets, evapotranspiration, drought, global change and heat island effect. Therefore, it is indispensable to develop an effective and accurate technique to estimate the emissivity for accurate surface temperature estimations. This study developed an improved emissivity estimation technique for the use of surface temperature retrievals with MODIS data. The result of applying this improved technique using Band 31 of MODIS shows that the accuracy of estimated surface temperatures will be improved. This study also uses MODIS data observed in 2005 to establish the relationship between the surface emissivity correction factor and NDVI. Through the use of these correction factors, the land surface temperature can be retrieved more accurate with MODIS data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.843-847
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• 2005

The development of distributed application in the standardized CORBA(Common Object Request Broker Architecture) environments reduces the developing time and maintaining cost of the systems. Because of these advantages, the development of application is being progressed in the several fields using the CORBA environments. The programmers in the CORBA environments usually develop the application programs using the CORBA IDL(Interface Definition Language). The IDL files are compiled by IDL compiler and translated into the stubs and skeleton codes which are mapped onto particular target language. The stubs produced by IDL compilers processes the marshaling a data into message buffer. Before a stub can marshal a data into its message buffer, the stub must ensure that the buffer has at least enough free space to contain the encoded representation of the data. But, the stubs produced by typical IDL compilers check the amount of free buffer space before every atomic data is marshaled, and if necessary, expand the message buffer. These repeated tests are wasteful and incidence of overheads, especially if the marshal buffer space must be continually expanded. Thus, the performance of the application program may be poor. In this paper, we suggest the way that the stub code is maintain the enough free space before marshaling the data into message buffer. This methods were analyzes the overall storage requirements of every message that will be exchanged between client and server. For these analysis, in the Front End of compiler has maintain the information that the storage requirements and alignment constraints for data types. Thus, stub code is optimized and the performance of application program is increased.

• Journal of KIISE:Databases
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• v.32 no.1
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• pp.1-11
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• 2005

An aggregation query computes aggregate information over a data cube in the query range specified by a user Existing methods based on the prefix-sum approach use an additional cube called the prefix-sum cube(PC), to store the cumulative sums of data, causing a high space overhead. This space overhead not only leads to extra costs for storage devices, but also causes additional propagations of updates and longer access time on physical devices. In this paper, we propose a new prefix-sum cube called 'SPEC' which drastically reduces the space of the PC in a large data warehouse. The SPEC decreases the update propagation caused by the dependency between values in cells of the PC. We develop an effective algorithm which finds dense sub-cubes from a large data cube. We perform an extensive experiment with respect to various dimensions of the data cube and query sizes, and examine the effectiveness and performance ot our proposed method. Experimental results show that the SPEC significantly reduces the space of the PC while maintaining a reasonable query performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.3238-3257
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• 2019

Closed-circuit television (CCTV) technology continuously captures and stores video streams. Users are typically required by policy to store all the captured video for a certain period. Accordingly, increasing the number of CCTV operation cycles and photographing positions expands the amount of data to be stored. However, expanding the available storage space for video data incurs increased costs. In recent years, this problem has been addressed with cloud storage solutions, which enable multiple users and devices to access and store data simultaneously. However, because of the large amount of data to be stored, a vast storage space is required. Consequently, cloud storage administrators need a way to store data more efficiently. To save storage space, deduplication technology has been proposed to prevent duplicate storage of the same data. However, because cloud storage is hosted on remote servers, data encryption technology must be applied to address data exposure issues. Although deduplication techniques for encrypted data have been studied, there have been various security vulnerabilities. We attempted to solve this problem by addressing various issues such as poison attacks, property forgery, and ownership management while removing the redundant data and handling the data more securely.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.1
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• pp.71.3-71.3
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• 2015

Deep UBVI and $H{\alpha}$ photometry of the ${\eta}$ Carina nebula, one of the brightest nebulae on the sky, was obtained with the CTIO 4m telescope and MOSAIC II CCD Camera to determine the initial mass function down to low-mass (~1 M¤) stars. We modified the spatial variation coefficients in transformation relations of the MOSAIC II CCD. From the cross-identification of optical sources with previous surveys in X-ray, near-infrared, and mid-infrared, a clear PMS sequence is revealed in the optical color-magnitude diagrams down to V=23 mag. Our previous SSO 1m UBVI data for Trumpler 14 (Tr 14) and Trumpler 16 (Tr 16) region, and additional SSO 1m UBVI data for Trumpler 15 (Tr 15) region were combined with the CTIO 4m data to re-examine the reddening law and distance of the young open clusters in the ${\eta}$ Carina nebula. From the new photometric data for Tr 15 region, we report that RV[=AV/E(B-V)], the total-to-selective extinction ratio, decreases from southern part of the nebula (Tr 14 and Tr 16) to northern part (Tr 15) in our field of view.

• Journal of The Korean Astronomical Society
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• v.47 no.6
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• pp.209-214
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• 2014

In this study we develop a set of solar proton event (SPE) forecast models with NOAA scales by Multi Layer Perceptron (MLP), one of neural network methods, using GOES solar X-ray flare data from 1976 to 2011. Our MLP models are the first attempt to forecast the SPE scales by the neural network method. The combinations of X-ray flare class, impulsive time, and location are used for input data. For this study we make a number of trials by changing the number of layers and nodes as well as combinations of the input data. To find the best model, we use the summation of F-scores weighted by SPE scales, where F-score is the harmonic mean of PODy (recall) and precision (positive predictive value), in order to minimize both misses and false alarms. We find that the MLP models are much better than the multiple linear regression model and one layer MLP model gives the best result.