Park, Sung-Kun;Choi, Jung-Seok;Yu, Soh-Young;Lee, Bo Reom;Kang, Seung-Suk;Roh, Kyu Sik;Ha, Tae-Hyun;Kwon, Jun Soo
Korean Journal of Biological Psychiatry
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v.10
no.2
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pp.168-176
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2003
Objectives:We investigated the characteristics of P300 generators in obsessive-compulsive disorder(OCD) patients by using voxel-based statistical parametric mapping of current density images. Methods:P300 generators, produced by a rare target tone of 1500Hz under a frequent non-target tone of 1,000Hz, were measured in 15 right-handed OCD patients and 15 controls. Low Resolution Electromagnetic Tomography(LORETA), using a realistic head model of the boundary element method based on individual MRI, was applied to the 128-channel EEG. Statistical parametric mapping(SPM) was applied for the statistical analysis. Results:We found that both groups had the mean current density of P300 in the parietal, temporal and prefrontal lobe. There was a trend for decreased current density in the prefrontal area in OCD patients. The statistical comparison showed current density increase in the supraparietal area, a statistically significant longer P300 latency and a trend for reduced P300 amplitude in OCD patients. Conclusion:It suggests that P300 source of both groups exists in multiple brain regions at the same time. And both groups had no statistically significant differences in the current density of P300 except for increased current density in the supraparietal area in OCD patients. But, considering the statistically significant longer P300 latency, a trend for reduced P300 amplitude and relative mean current density reduction in the prefrontal area in OCD patients, this study suggests that the frontal lobe may have a reduced normal inhibitory process in OCD patients.
Proceedings of the Korea Society for Industrial Systems Conference
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1999.12a
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pp.121-129
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1999
When continuous media are transmitted over the communication networks, asynchrony which can not maintain temporal relationships among packets may occur due to a random transit delay. There exist two types of synchronization schemes ; for guaranteed or non-guaranteed resource networks. The former which applies a resource reservation technique maintains delay characteristics, however, the latter supply a best-effort service. In this paper, I propose a intra-media synchronization scheme to transmit continuous media on general networks not guaranteeing a bounded delay tome. The scheme controls transmission times of the packets by estimating next delay time with the delay distribution. So, the arriving packets may be maintained within a limited delay boundary, and playout will be performed after buffering to smoothen small delay variations. The continually increasing delay due to network overload causes buffer underflow at the receiver. To solve it, the transmitter is required to speed up instantaneously. Too much increase of transmission-rate may cause network congestion. At that time, the transmitter drops the current packet when informed excessive delay from the receiver.
The interaction between land surface and atmosphere is essentially affected by hydrometeorological variables including soil moisture. Accurate estimation of soil moisture at spatial and temporal scales is crucial to better understand its roles to the weather systems. The KLDAS(Korea Land Data Assimilation System) is a regional, specifically Korea peninsula land surface information systems. As other prior land data assimilation systems, this can provide initial soil field information which can be used in atmospheric simulations. For this study, as an enabling high-resolution tool, weather research and forecasting(WRF-ARW) model is applied to produce precipitation data using GFS(Global Forecast System) with GFS embedded and KLDAS soil moisture information as initialization data. WRF-ARW generates precipitation data for a specific region using different parameters in physics options. The produced precipitation data will be employed for simulations of Hydrological Models such as HEC(Hydrologic Engineering Center) - HMS(Hydrologic Modeling System) as predefined input data for selected regional water responses. The purpose of this study is to show the impact of a hydrometeorological variable such as soil moisture in KLDAS on hydrological consequences in Korea peninsula. The study region, Chongmi River Basin, is located in the center of Korea Peninsular. This has 60.8Km river length and 17.01% slope. This region mostly consists of farming field however the chosen study area placed in mountainous area. The length of river basin perimeter is 185Km and the average width of river is 9.53 meter with 676 meter highest elevation in this region. We have four different observation locations : Sulsung, Taepyung, Samjook, and Sangkeug observatoriesn, This watershed is selected as a tentative research location and continuously studied for getting hydrological effects from land surface information. Simulations for a real regional storm case(June 17~ June 25, 2006) are executed. WRF-ARW for this case study used WSM6 as a micro physics, Kain-Fritcsch Scheme for cumulus scheme, and YSU scheme for planetary boundary layer. The results of WRF simulations generate excellent precipitation data in terms of peak precipitation and date, and the pattern of daily precipitation for four locations. For Sankeug observatory, WRF overestimated precipitation approximately 100 mm/day on July 17, 2006. Taepyung and Samjook display that WRF produced either with KLDAS or with GFS embedded initial soil moisture data higher precipitation amounts compared to observation. Results and discussions in detail on accuracy of prediction using formerly mentioned manners are going to be presented in 2011 Annual Conference of the Korean Society of Hazard Mitigation.
Kim, Jooil;Park, Sunyoung;Park, Mi-Kyung;Li, Shanlan;Kim, Jae-Yeon;Jo, Chun Ok;Kim, Ji-Yoon;Kim, Kyung-Ryul
Atmosphere
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v.23
no.1
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pp.93-102
/
2013
Atmospheric transport pathway of an air mass is an important constraint controlling the chemical properties of the air mass observed at a designated location. Such information could be utilized for understanding observed temporal variabilities in atmospheric concentrations of long-lived chemical compounds, of which sinks and/or sources are related particularly with natural and/or anthropogenic processes in the surface, and as well as for performing inversions to constrain the fluxes of such compounds. The Lagrangian particle dispersion model FLEXPART provides a useful tool for estimating detailed particle dispersion during atmospheric transport, a significant improvement over traditional "single-line" trajectory models that have been widely used. However, those without a modeling background seeking to create simple back-trajectory maps may find it challenging to optimize FLEXPART for their needs. In this study, we explain how to set up, operate, and optimize FLEXPART for back-trajectory analysis, and also provide automatization programs based on the open-source R language. Discussions include setting up an "AVAILABLE" file (directory of input meteorological fields stored on the computer), creating C-shell scripts for initiating FLEXPART runs and storing the output in directories designated by date, as wells as processing the FLEXPART output to create figures for a back-trajectory "footprint" (potential emission sensitivity within the boundary layer). Step by step instructions are explained for an example case of calculating back trajectories derived for Anmyeon-do, Korea for January 2011. One application is also demonstrated in interpreting observed variabilities in atmospheric $CO_2$ concentration at Anmyeon-do during this period. Back-trajectory modeling information introduced in this study should facilitate the creation and automation of most common back-trajectory calculation needs in atmospheric research.
Journal of the Korean Association of Geographic Information Studies
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v.20
no.1
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pp.1-14
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2017
A land cover map provides basic information to help understand the current state of a region, but its utilization in the ecological research field has deteriorated due to limited temporal and spatial resolutions. The purpose of this study was to investigate the possibility of using a land cover map with data based on high resolution images acquired by UAV. Using the UAV, 10.5 cm orthoimages were obtained from the $2.5km^2$ study area, and land cover maps were obtained from object-based and pixel-based classification for comparison and analysis. From accuracy verification, classification accuracy was shown to be high, with a Kappa of 0.77 for the pixel-based classification and a Kappa of 0.82 for the object-based classification. The overall area ratios were similar, and good classification results were found in grasslands and wetlands. The optimal image segmentation weights for object-based classification were Scale=150, Shape=0.5, Compactness=0.5, and Color=1. Scale was the most influential factor in the weight selection process. Compared with the pixel-based classification, the object-based classification provides results that are easy to read because there is a clear boundary between objects. Compared with the land cover map from the Ministry of Environment (subdivision), it was effective for natural areas (forests, grasslands, wetlands, etc.) but not developed areas (roads, buildings, etc.). The application of an object-based classification method for land cover using UAV images can contribute to the field of ecological research with its advantages of rapidly updated data, good accuracy, and economical efficiency.
Lee, Junhyeok;Ha, Wan Soo;Kim, Yong-Hyuk;Lee, Kang Hoon
Journal of the Korea Computer Graphics Society
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v.24
no.2
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pp.21-28
/
2018
We present interactive methods for visualizing the cloud height data and the backscatter data collected from ceilometers in the three-dimensional virtual space. Because ceilometer data is high-dimensional, large-size data associated with both spatial and temporal information, it is highly improbable to exhibit the whole aspects of ceilometer data simply with static, two-dimensional images. Based on the three-dimensional rendering technology, our visualization methods allow the user to observe both the global variations and the local features of the three-dimensional representations of ceilometer data from various angles by interactively manipulating the timing and the view as desired. The cloud height data, coupled with the terrain data, is visualized as a realistic cloud animation in which many clouds are formed and dissipated over the terrain. The backscatter data is visualized as a three-dimensional terrain which effectively represents how the amount of backscatter changes according to the time and the altitude. Our system facilitates the multivariate analysis of ceilometer data by enabling the user to select the date to be examined, the level-of-detail of the terrain, and the additional data such as the planetary boundary layer height. We demonstrate the usefulness of our methods through various experiments with real ceilometer data collected from 93 sites scattered over the country.
KSCE Journal of Civil and Environmental Engineering Research
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v.38
no.2
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pp.269-281
/
2018
Unlike its archetype predecessor such as the Highway Capacity Manual of the United States, the Korean Highway Capacity Manual of 2013 provides the analytical models for estimating the saturation flow rates for the lane-occupying work-zones in the proximity of the signalized intersections. Direct application of the revised saturation flow rates into the classic control delay models, however, appears to produce unreasonable delay amount as traffic demand approaches lane-group capacities and surpasses them, which is common phenomena in the work-zones. Complex interaction among vehicles, lane-dropping work-zone geometry and signal operations were never accounted in the traditional control delay models, and considerable differences between the delay model outcomes and field observations are repeatedly experienced. This paper proposes the modified approaches to the delay models in the manual, exerted on all three elements of control delay, and particularly focuses on the temporal and spatial boundary expansion in comparing the simulated results to the estimated ones. Extensive microscopic simulation work and calibration effort supports the modified approaches well enough to use them in the work-zone planning and evaluation.
Kim, Young-Hyun;Kim, Eung-Sup;Choi, Myeong-Ju;Shim, Kyo-Moon;Ahn, Joong-Bae
Atmosphere
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v.29
no.5
/
pp.671-687
/
2019
This study evaluates the long-term seasonal predictability of summer (June, July and August) heatwaves over South Korea using 30-year (1989~2018) Hindcast data of the Pusan National University Coupled General Circulation Model (PNU CGCM)-Weather Research and Forecasting (WRF) chain. Heatwave indices such as Number of Heatwave days (HWD), Heatwave Intensity (HWI) and Heatwave Warning (HWW) are used to explore the long-term seasonal predictability of heatwaves. The prediction skills for HWD, HWI, and HWW are evaluated in terms of the Temporal Correlation Coefficient (TCC), Root Mean Square Error (RMSE) and Skill Scores such as Heidke Skill Score (HSS) and Hit Rate (HR). The spatial distributions of daily maximum temperature simulated by WRF are similar overall to those simulated by NCEP-R2 and PNU CGCM. The WRF tends to underestimate the daily maximum temperature than observation because the lateral boundary condition of WRF is PNU CGCM. According to TCC, RMSE and Skill Score, the predictability of daily maximum temperature is higher in the predictions that start from the February and April initial condition. However, the PNU CGCM-WRF chain tends to overestimate HWD, HWI and HWW compared to observations. The TCCs for heatwave indices range from 0.02 to 0.31. The RMSE, HR and HSS values are in the range of 7.73 to 8.73, 0.01 to 0.09 and 0.34 to 0.39, respectively. In general, the prediction skill of the PNU CGCM-WRF chain for heatwave indices is highest in the predictions that start from the February and April initial condition and is lower in the predictions that start from January and March. According to TCC, RMSE and Skill Score, the predictability is more influenced by lead time than by the effects of topography and/or terrain feature because both HSS and HR varies in different leads over the whole region of South Korea.
Sea ice motion is an important factor for assessing change of sea ice because the motion affects to not only regional distribution of sea ice but also new ice growth and thickness of ice. This study presents an application of multi-temporal high-resolution optical satellites images obtained from Korea Multi-Purpose Satellite-2 (KOMPSAT-2) and Korea Multi-Purpose Satellite-3 (KOMPSAT-3) to measure sea ice motion using SIFT (Scale-Invariant Feature Transform), SURF (Speeded Up Robust Features) and ORB (Oriented FAST and Rotated BRIEF) feature tracking techniques. In order to use satellite images from two different sensors, spatial and radiometric resolution were adjusted during pre-processing steps, and then the feature tracking techniques were applied to the pre-processed images. The matched features extracted from the SIFT showed even distribution across whole image, however the matched features extracted from the SURF showed condensed distribution of features around boundary between ice and ocean, and this regionally biased distribution became more prominent in the matched features extracted from the ORB. The processing time of the feature tracking was decreased in order of SIFT, SURF and ORB techniques. Although number of the matched features from the ORB was decreased as 59.8% compared with the result from the SIFT, the processing time was decreased as 8.7% compared with the result from the SIFT, therefore the ORB technique is more suitable for fast measurement of sea ice motion.
Kim, Je-Won;Ryu, Jung-Hee;Na, Seong-Jun;Seong, Seong-Cheol
Journal of the Korean Society for Aeronautical & Space Sciences
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v.50
no.12
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pp.899-907
/
2022
According to the Unmanned aircraft system Traffic Management (UTM), drones are permitted to fly up to 150m above ground, which is located in the atmospheric boundary layer where there is considerable wind fluctuation due to turbulence. Although it is difficult to predict when turbulence will occur drone aviation safety could be enhanced by having a better understanding of the characteristics of vertical profile of wind in the flight area. We used wind lidar (WIndMast 350M) to observe vertical profiles of wind at the test site for aviation meteorological observation equipment located near Incheon International Airport in July and September, 2022. In this study, we utilized the observed wind profile data to propose a technique for obtaining information that could help improve the drone aviation safety. The Fourier transform analysis is used to evaluate the temporal characteristics of the horizontal wind speed at various vertical levels up to 350m. We also examined the relative contribution of the variance of wind having scales of less than an hour, a crucial scale for drone flight, to the variance of wind having all scales at each vertical altitude for days with and without precipitation.
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