• Title/Summary/Keyword: Observation data

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Method Extracting Observation Data by Spatial Factor for Analysis of Selective Attention of Vision (시각의 선택적 주의집중 분석을 위한 공간요소별 주시데이터 추출방법)

  • Kim, Jong-Ha;Kim, Ju-Yeon
    • Science of Emotion and Sensibility
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    • v.18 no.4
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    • pp.3-14
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    • 2015
  • This study has extracted observation data by spatial factor for the analysis of subjects' selective attention with the objects of public space at the entrance of subway stations. The methods extracting observation data can be summarized as the following. First, the frequency analysis by lattice was prevalent for those methods, but there is a limitation to the analysis of the observation data. On the contrary, the method extracting observation data by factor applied in this study can make it clear if any sight is concentrated on any particular factors in a space. Second, the results from the extracted data corresponding to the observation area can be objectified while the method setting up the observation area by applying the radius of fovea. Third, time-sequential trace of observation results of relevant factors was possible through hourly analysis of spatial factors. The consideration of the results of "corresponding spatial scope" which is the object of this study will reveal that the more the observation time, the less the degree of attention it receives. Fourth, the frequency of observation superiority was applied for the analysis of the sections with selective attention by time scope; this revealed that men and women had intensive observation in time scope I (52.4 %) and in time scope IV (24.0 %), respectively.

Nonparametric Inference for the Recurrent Event Data with Incomplete Observation Gaps

  • Kim, Jin-Heum;Nam, Chung-Mo;Kim, Yang-Jin
    • The Korean Journal of Applied Statistics
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    • v.25 no.4
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    • pp.621-632
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    • 2012
  • Recurrent event data can be easily found in longitudinal studies such as clinical trials, reliability fields, and the social sciences; however, there are a few observations that disappear temporarily in sight during the follow-up and then suddenly reappear without notice like the Young Traffic Offenders Program(YTOP) data collected by Farmer et al. (2000). In this article we focused on inference for a cumulative mean function of the recurrent event data with these incomplete observation gaps. Defining a corresponding risk set would be easily accomplished if we know the exact intervals where the observation gaps occur. However, when they are incomplete (if their starting times are known but their terminating times are unknown) we need to estimate a distribution function for the terminating times of the observation gaps. To accomplish this, we treated them as interval-censored and then estimated their distribution using the EM algorithm proposed by Turnbull (1976). We proposed a nonparametric estimator for the cumulative mean function and also a nonparametric test to compare the cumulative mean functions of two groups. Through simulation we investigated the finite-sample performance of the proposed estimator and proposed test. Finally, we applied the proposed methods to YTOP data.

Development of Ground-based GNSS Data Assimilation System for KIM and their Impacts (KIM을 위한 지상 기반 GNSS 자료 동화 체계 개발 및 효과)

  • Han, Hyun-Jun;Kang, Jeon-Ho;Kwon, In-Hyuk
    • Atmosphere
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    • v.32 no.3
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    • pp.191-206
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    • 2022
  • Assimilation trials were performed using the Korea Institute of Atmospheric Prediction Systems (KIAPS) Korea Integrated Model (KIM) semi-operational forecast system to assess the impact of ground-based Global Navigation Satellite System (GNSS) Zenith Total Delay (ZTD) on forecast. To use the optimal observation in data assimilation of KIM forecast system, in this study, the ZTD observation were pre-processed. It involves the bias correction using long term background of KIM, the quality control based on background and the thinning of ZTD data. Also, to give the effect of observation directly to data assimilation, the observation operator which include non-linear model, tangent linear model, adjoint model, and jacobian code was developed and verified. As a result, impact of ZTD observation in both analysis and forecast was neutral or slightly positive on most meteorological variables, but positive on geopotential height. In addition, ZTD observations contributed to the improvement on precipitation of KIM forecast, specially over 5 mm/day precipitation intensity.

International Trend Towards Comparability of Glabal Oceanic Nutrient Data: SCOR Working Group 147 (Towards Comparability of Global Oceanic Nutrient Data, COMPONUT) Activity (전 세계 대양 영양염 자료의 상호 비교성 향상을 위한 국제동향 : SCOR Working Group 147 (Towards Comparability of Global Oceanic Nutrient Data, COMPONUT) 활동에 대하여)

  • Rho, TaeKeun;Kim, Eun-Soo;Kahng, Sung-Hyun;Cho, Sung-Rok
    • Ocean and Polar Research
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    • v.37 no.3
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    • pp.225-233
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    • 2015
  • To understand the fluctuation of global carbon levels caused by the biogeochemical cycle within the ocean interior, it is essential to achieve comparability of global oceanic nutrient data to a fairly high degree. The Scientific Committee on Ocean Research (SCOR) commissioned a working group (WG147) to establish a system for achieving comparability of oceanic nutrient data within 1% among laboratories around the world. The introduction of international activities for improving nutrient comparability will facilitate the use of nutrient reference material of seawater by researchers within Korea, which will help in meeting international standards of nutrient comparability and promote international cooperation.

A Study on the Features of Visual-Information Acquirement Shown at Searching of Spatial Information - With the Experiment of Observing the Space of Hall in Subway Station - (공간정보의 탐색과정에 나타난 시각정보획득특성에 관한 연구 - 지하철 홀 공간의 주시실험을 대상으로 -)

  • Kim, Jong-Ha
    • Korean Institute of Interior Design Journal
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    • v.23 no.2
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    • pp.90-98
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    • 2014
  • This study has analyzed the meaning of observation time in the course of acquiring the information of subjects who observed the space of hall in subway stations to figure out the process of spatial information excluded and the features of intensive searching. The followings are the results from the analysis of searching process with the interpretation of the process for information acquirement through the interpretation of observation area and time. First, based on the general definition of observation time, the reason for analyzing the features of acquiring spatial information according to the subjects' observation time has been established. The feature of decreased analysis data reflected that of observation time in the process of perceiving and recognizing spatial information, which showed that the observation was focused on the enter of the space during the time spent in the process of observing the space and the spent time with considerable exclusion of bottom end (in particular, right bottom end). Second, while the subjects were observing the space of hall in subway stations, they focused on the top of the left center and the signs on the right exit the most, which was followed by the focus on the both side horizontally and the clock on the top. Third, the analysis of consecutive observation frequency enabled the comparison of the changes to the observation concentration by area. The difference of time by area produced the data with which the change to the contents of spatial searching in the process of searching space could be known. Fourth, as the observation frequency in the area of I changed [three times -> six times -> 9 times], the observation time included in the area increased, which showed the process for the change from perception to recognition of information with the concentration of attention through visual information. It makes it possible to understand that more time was spent on the information to be acquired with the exclusion of the unnecessary information around.

Study on the Impact of Various Observations Data Assimilation on the Meteorological Predictions over Eastern Part of the Korean Peninsula (관측자료별 자료동화 성능이 한반도 동부 지역 기상 예보에 미치는 영향 분석 연구)

  • Kim, Ji-Seon;Lee, Soon-Hwan;Sohn, Keon-Tae
    • Journal of Environmental Science International
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    • v.27 no.11
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    • pp.1141-1154
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    • 2018
  • Numerical experiments were carried out to investigate the effect of data assimilation of observational data on weather and PM (particulate matter) prediction. Observational data applied to numerical experiment are aircraft observation, satellite observation, upper level observation, and AWS (automatic weather system) data. In the case of grid nudging, the prediction performance of the meteorological field is largely improved compared with the case without data assimilations because the overall pressure distribution can be changed. So grid nudging effect can be significant when synoptic weather pattern strongly affects Korean Peninsula. Predictability of meteorological factors can be expected to improve through a number of observational data assimilation, but data assimilation by single data often occurred to be less predictive than without data assimilation. Variation of air pressure due to observation nudging with high prediction efficiency can improve prediction accuracy of whole model domain. However, in areas with complex terrain such as the eastern part of the Korean peninsula, the improvement due to grid nudging were only limited. In such cases, it would be more effective to aggregate assimilated data.

Analysis on the Yeongdong Downslope Windstorms Generation Condition Verified by Observation Cases (관측사례로 검증한 영동강풍 발생조건 분석)

  • Park, Yu-Jung;Han, Youn-Deok
    • Atmosphere
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    • v.31 no.4
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    • pp.405-420
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    • 2021
  • Forest fire happens every year at Yeongdong, Gangwon-do, due to the strong local wind during the spring time and it causes a huge damage. This wind is named "Yangganjipung" or "Yanggangjipung" that blows along Yeongdong. However, the occurrence conditions of the wind have been still unclear. To identify the occurrence mechanism of local strong wind through three-dimensional observation data, Gangwon Regional Meteorological Administration performed Joint Gangwon-Yeongdong 3D Observation Project in 2020. The special observation was carried out for 6 times from March to April. The observation data was analyzed by focusing on the structure of synoptic pressure distribution and inversion layer. The result showed that the strength of wind is different depending on the latitude of low pressure, intensity of inversion layer, and changes on height in the south-high and north-low pressure distribution. As the interval of the upper and lower parts of the inversion layer was narrow, the strength of the wind became stronger, which is one of the observational characteristics of the springtime wind pattern at Yeongdong, Gangwon-do. In future, the clear mechanism of the local wind in the Yeongdong during the spring time is expected to be verified based on the accumulative observation data and close analysis.

A Study on the Characteristics of Observation seen in the Process of Perception and Recognition of Space (공간의 지각과 인지과정에 나타난 주시메커니즘 특성 연구)

  • Kim, Jong-Ha
    • Korean Institute of Interior Design Journal
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    • v.22 no.6
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    • pp.108-118
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    • 2013
  • This study has analyzed the process of space information perceived and recognized through the estimation of observation frequency and number according to the time range of observation data acquired from observation experiment with the object of hospital lobby. The followings are the results analyzed at this study. First, the continual observation of 3 and 6 times was attentive and conscious for probing to find an object rather than for acquiring exact information and that of 9 times could be regarded as the time for acquiring visual appreciation. However, the repetitive occurrence of high and low frequencies can be thought of repetitive acts for visual appreciation. Second, the continual observation of 3 and 6 times had the highest observation frequency of II, while that of 9 times had the highest observation frequency of III. In case of 3 and 6 times, the observation frequency had the tendency to become a little higher after being low since V, and in case of 9 times it had the repetition of becoming low and high and from IX it characteristically got higher. This feature can be thought to be the process that the subject repeats the fixation and movement of observation at a visual activity for perception and recognition. In the process of first observation, the observation frequency was the highest after 20 seconds or so, but since then, it gets lower and repeatedly gets higher and lower as time passes. After 90 seconds, the frequency showed the tendency of getting higher continuously. Third, the examination of changing features of frequency may show the characteristics of exploration for and attention to space but if the observation frequency is not associated with observation times for analysis there will a limitation that the features of observation frequency cannot be clarified. Accordingly, the simultaneous analysis of both is very effective for estimating the observation characteristics seen at the processes of perception and recognition. Fourth, the general analysis of the both revealed: with the progress of observation time the discontinuous space exploration decreased, and as the observation time got longer the fixed attention to a specific spot increased. Fifth, in order to estimate the observation characteristics by the change of time range the observation frequency and times by trend line was analyzed, which approach seems to be an appropriate technique that can comprehensively show the overall flow of time series data.

Data Assimilation Effect of Mobile Rawinsonde Observation using Unified Model Observing System Experiment during the Summer Intensive Observation Period in 2013 (2013년 여름철 집중관측동안 통합모델 관측시스템실험을 이용한 이동형 레윈존데 관측의 자료동화 효과)

  • Lim, Yun-Kyu;Song, Sang-Keun;Han, Sang-Ok
    • Journal of the Korean earth science society
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    • v.35 no.4
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    • pp.215-224
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    • 2014
  • Data assimilation effect of mobile rawinsonde observation was evaluated using Unified Model (UM) with a Three-Dimensional Variational (3DVAR) data assimilation system during the intensive observation program of 2013 summer season (rainy season: 20 June-7 July 2013, heavy rain period: 8 July-30 July 2013). The analysis was performed by two sets of simulation experiments: (1) ConTroL experiment (CTL) with observation data provided by Korea Meteorological Administration (KMA) and (2) Observing System Experiment (OSE) including both KMA and mobile rawinsonde observation data. In the model verification during the rainy season, there were no distinctive differences for 500 hPa geopotential height, 850 hPa air temperature, and 300 hPa wind speed between CTL and OSE simulation due to data limitation (0000 and 1200 UTC only) at stationary rawinsonde stations. In contrast, precipitation verification using the hourly accumulated precipitation data of Automatic Synoptic Observation System (ASOS) showed that Equivalent Threat Score (ETS) of the OSE was improved by about 2% compared with that of the CTL. For cases having a positive effect of the OSE simulation, ETS of the OSE showed a significantly higher improvement (up to 41%) than that of the CTL. This estimation thus suggests that the use of mobile rawinsonde observation data using UM 3DVAR could be reasonable enough to assess the improvement of prediction accuracy.

Analysis of Social Welfare Effects of Onion Observation Using Big Data (빅데이터를 활용한 양파 관측의 사회적 후생효과 분석)

  • Joo, Jae-Chang;Moon, Ji-Hye
    • Korean Journal of Organic Agriculture
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    • v.29 no.3
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    • pp.317-332
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    • 2021
  • This study estimated the predictive onion yield through Stepwise regression of big data and weather variables by onion growing season. The economic feasibility of onion observations using big data was analyzed using estimated predictive data. The social welfare effect was estimated through the model of Harberger's triangle using onion yield prediction with big data and it without big data. Predicted yield using big data showed a deviation of -9.0% to 4.2%. As a result of estimating the social welfare effect, the average annual value was 23.3 billion won. The average annual value of social welfare effects if big data was not used was measured at 22.4 billion won. Therefore, it was estimated that the difference between the social welfare effect when the prediction using big data was used and when it was not was about 950 million won. When these results are applied to items other than onion items, the effect will be greater. It is judged that it can be used as basic data to prove the justification of the agricultural observation project. However, since the simple Harberger's triangle theory has the limitation of oversimplifying reality, it is necessary to evaluate the economic value through various methods such as measuring the effect of agricultural observation under a more realistic rational expectation hypothesis in future studies.