• The Bulletin of The Korean Astronomical Society
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• v.41 no.2
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• pp.54.2-54.2
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• 2016

We present a machine learning approach to estimating stellar atmospheric parameters, effective temperature (Teff), surface gravity (log g), and metallicity ([Fe/H]) for stars observed during the course of the Sloan Digital Sky Survey (SDSS). For training a neural network, we randomly sampled the SDSS data with stellar parameters available from SEGUE Stellar Parameter Pipeline (SSPP) to cover the parameter space as wide as possible. We selected stars that are not included in the training sample as validation sample to determine the accuracy and precision of each parameter. We also divided the training and validation samples into four groups that cover signal-to-noise ratio (S/N) of 10-20, 20-30, 30-50, and over 50 to assess the effect of S/N on the parameter estimation. We find from the comparison of the network-driven parameters with the SSPP ones the range of the uncertainties of 73~123 K in Teff, 0.18~0.42 dex in log g, and 0.12~0.25 dex in [Fe/H], respectively, depending on the S/N range adopted. We conclude that these precisions are high enough to study the chemical and kinematic properties of the Galactic disk and halo stars, and we will attempt to apply this technique to Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST), which plans to obtain about 8 million stellar spectra, in order to estimate stellar parameters.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.595-600
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• 2007

Greater expansion and more frequent operation of the railroad transportation system anticipated due to its characteristics including low cost, safety and mass transportation. Recently, effects on the railway structures due to expansion of newly constructed road, construction of subway, city gas pipeline, communication network, electric power network and construction of other railway underground crossing in accordance with urban planning and organization has influenced safe operation of trains. Accordingly, standard for selection of construction method that will enable construction of more economical and rational subway underground crossing structures by preventing problems occurring at the time of above construction works and accidents in safe operation of trains due to construction in advance is definitively necessary. Although there are numerous construction methods that can be applied at the time of construction of railway underground crossing, there are much difficulties in selection of appropriate construction method that considers characteristics of each construction method on non-excavation type construction method, train operation plan of number of operational routes and on-site circumstances. Therefore, this research aims to present rational standard for selection of construction method for such, and standard for slowdown speed and interception of train when passing the areas of slowdown in sectors under construction.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.221.1-221.1
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• 2012

The Korea Astronomy and Space Science Institute (KASI) is developing three 1.6m optical telescopes with $18k{\times}18k$ mosaic CCD cameras. These telescopes will be installed and operated at Chile, South Africa, and Australia for Korea Micro-lensing Telescope Network (KMTNet) project. The main scientific goal of the project is to discover earth-like extra-solar planets using the gravitational micro-lensing technique. To achieve the goal, each telescope at three sites will continuously monitor the specific region of Galactic bulge with 2.5 minute cadence for five years. Assuming 12 hour observation in maximum for a night, the amount of 200 GB file storage is required for one night observation at one observatory. If we consider the whole project period and the data processing procedure, a few PB class data storage, high-speed network, and high performance computers are essential. In this presentation, we introduce the KMTNet data management plan that handles gigantic data; raw image collecting, image processing, photometry pipeline, database archiving, and backup.

• Journal of Convergence for Information Technology
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• v.9 no.8
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• pp.1-8
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• 2019

Dialog system is becoming a new dominant interaction way between human and computer. It allows people to be provided with various services through natural language. The dialog system has a common structure of a pipeline consisting of several modules (e.g., speech recognition, natural language understanding, and dialog management). In this paper, we tackle a task of domain classification for the natural language understanding module by employing machine learning models such as convolutional neural network and random forest. For our dataset of seven service domains, we showed that the random forest model achieved the best performance (F1 score 0.97). As a future work, we will keep finding a better approach for domain classification by investigating other machine learning models.

• Journal of Korean Society of Water and Wastewater
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• v.30 no.3
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• pp.253-261
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• 2016

A variety of methods for detecting the location of an underground water pipeline are being used across the world; the current main methods used in South Korea, however, have the problems of low precision and efficiency and the limitations in actual application. On this, this study developed locator capable of detecting the location of a water pipe by the use of an IMU sensor, and technology for using the extended karman filter to correct error in location detection and to plot the location on the coordinate system. This study carried out a tract test and a road test as basic experiments to measure the performance of the developed technology and equipment. As a result of the straight line, circular and ellipse track tests, the 1750 IMU sensor showed the average error of 0.08-0.11%; and thus it was found that the developed locator can detect a location precisely. As a result of the 859.6-m road test, it was found that the error was 0.31 m in case the moving rate of the sensor was 0.3-0.6 m/s; and thus it was judged that the equipment developed by this study can be applied to long-distance water pipes of over 1 km sufficiently. It is planned to evaluate its field applicability in the future through an actual pipe network pilot test, and it is expected that locator capable of detecting the location of a water pipe more precisely will be developed through research for the enhancement of accuracy in the algorithm of location detection.

• Journal of Korea Water Resources Association
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• v.33 no.3
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• pp.289-298
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• 2000

In order to minimize the impact of water hammer In a pipeline, a determination of optimum position of hydraulic structures with best operation of pressure relief valve was explored at the Seobyun pumping station. Method of characteristics is used to simulate a surge impact originating from abrupt stop of pumping operation in a pipeline. Genetic algorithm shows a powerful capability in searching a global solution, especially for a nonlinear problem The application results suggests that the maximum positive pressure can be relaxed by decreasing the opening time of pressure relief valve, meanwhile the maximum negative pressure can be relaxed by increasing the opening time of pressure relief valve. This study shows that the integration of a genetic algorithm with a transient analysis technique such as method of characteristic can improve the design of hydraulic structure in a pipe network.

• The KIPS Transactions:PartC
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• v.16C no.3
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• pp.363-372
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• 2009

For large scale VOD service, cluster servers are spotlighted to their high performance and low cost. A cluster server usually consists of a front-end node and multiple back-end nodes. Though increasing the number of back-end nodes can result in the more QoS streams for clients, the possibility of failures in back-end nodes is proportionally increased. The failure causes not only the stop of all streaming service but also the loss of the current playing positions. In this paper, when a back-end node becomes a failed state, the recovery mechanisms are studied to support the unceasing streaming service. For the actual VOD service environment, we implement a cluster-based VOD servers composed of general PCs and adopt the parallel processing for MPEG movies. From the implemented VOD server, a video block recovery mechanism is designed on parity algorithms. However, without considering the architecture of cluster-based VOD server, the application of the basic technique causes the performance bottleneck of the internal network for recovery and also results in the inefficiency CPU usage of back-end nodes. To address these problems, we propose a new failure recovery mechanism based on the pipeline computing concept.

• Journal of Korean Society of Water and Wastewater
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• v.37 no.6
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• pp.347-361
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• 2023

Water utilities are making various efforts to reduce water losses from water networks, and an essential part of them is to recognize the moment when a pipe burst occurs during operation quickly. Several physics-based methods and data-driven analysis are applied using real-time flow and pressure data measured through a SCADA system or smart meters, and methodologies based on machining learning are currently widely studied. Water utilities should apply various approaches together to increase pipe burst detection. The most intuitive and explainable water balance method and its procedure were presented in this study, and the applicability and detection performance were evaluated by applying this approach to water supply pipelines. Based on these results, water utilities can establish a mass balance-based pipe burst detection system, give a guideline for installing new flow meters, and set the detection parameters with expected performance. The performance of the water balance analysis method is affected by the water network operation conditions, the characteristics of the installed flow meter, and event data, so there is a limit to the general use of the results in all sites. Therefore, water utilities should accumulate experience by applying the water balance method in more fields.

• Journal of The Korean Astronomical Society
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• v.49 no.1
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• pp.37-44
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• 2016

The Korea Microlensing Telescope Network (KMTNet) is a wide-field photometric system installed by the Korea Astronomy and Space Science Institute (KASI). Here, we present the overall technical specifications of the KMTNet observation system, test observation results, data transfer and image processing procedure, and finally, the KMTNet science programs. The system consists of three 1.6 m wide-field optical telescopes equipped with mosaic CCD cameras of 18k by 18k pixels. Each telescope provides a 2.0 by 2.0 square degree field of view. We have finished installing all three telescopes and cameras sequentially at the Cerro-Tololo Inter-American Observatory (CTIO) in Chile, the South African Astronomical Observatory (SAAO) in South Africa, and the Siding Spring Observatory (SSO) in Australia. This network of telescopes, which is spread over three different continents at a similar latitude of about -30 degrees, enables 24-hour continuous monitoring of targets observable in the Southern Hemisphere. The test observations showed good image quality that meets the seeing requirement of less than 1.0 arcsec in I-band. All of the observation data are transferred to the KMTNet data center at KASI via the international network communication and are processed with the KMTNet data pipeline. The primary scientific goal of the KMTNet is to discover numerous extrasolar planets toward the Galactic bulge by using the gravitational microlensing technique, especially earth-mass planets in the habitable zone. During the non-bulge season, the system is used for wide-field photometric survey science on supernovae, asteroids, and external galaxies.

• Journal of Power System Engineering
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• v.9 no.2
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• pp.45-49
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• 2005

Liquefied natural gas takes up six hundredths of the volume of natural gas, which makes storage and transportation much easier. To send out natural gas via a pipeline network across the nation, high-pressure LNG pumps supply highly compressed LNG to high-pressure vaporization facilities. The Number of high-pressure LNG pumps determined the send-out amount in LNG receiving terminal. So it is main equipment at LNG production process and should be maintained on best conditions. In this paper, to find out the cause of high beat vibration at cryogenic pumps, vibration and motor current signal analysis have been performed. High vibration of cryogenic pumps could be reduced due to the modification of motor rotor.