• Title/Summary/Keyword: National processing statistic

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Developing the Quality Assessment Indicators for the National Processing Statistics of Korea

  • Kim, Soo-Taek;Jeong, Ki-Ho;Kim, Seol-Hee
    • Communications for Statistical Applications and Methods
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    • v.14 no.3
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    • pp.649-665
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    • 2007
  • The improvement of quality is a continuous process and one of the main objectives of the Statistical Strategy launched by the Korea National Statistical Office (KNSO) is the enhancement of the quality of Korea national statistics. In this paper, we define the processing statistic, classify the Korea national processing statistics, and develop the quality indicators and check list for assessing the national processing statistics of Korea. During its development, the indicators has been discussed with the processing statistic managers of the KNSO and the checklist tested in a pilot study covering a variety of processing statistic areas.

Korean Word Spacing System Using Syllable N-Gram and Word Statistic Information (음절 N-Gram과 어절 통계 정보를 이용한 한국어 띄어쓰기 시스템)

  • Choi, Sung-Ja;Kang, Mi-Young;Heo, Hee-Keun;Kwon, Hyuk-Chul
    • Annual Conference on Human and Language Technology
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    • 2003.10d
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    • pp.47-53
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    • 2003
  • 본 논문은 정제된 대용량 말뭉치로부터 얻은 음절 n-gram과 어절 통계를 이용한 한국어 자동 띄어쓰기 시스템을 제안한다. 한 문장 내에서 최적의 띄어쓰기 위치는 Viterbi 알고리즘에 의해 결정된다. 통계 기반 연구에 고유한 문제인 데이터 부족 문제, 학습 말뭉치 의존 문제를 개선하기 위하여 말뭉치를 확장하고 실험을 통해 얻은 매개변수를 사용하고 최장 일치 Viable Prefix를 찾아 어절 목록에 추가한다. 본 연구에 사용된 학습 말뭉치는 33,641,511어절로 구성되어 있으며 구어와 문어를 두루 포함한다.

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Use of Unmanned Aerial Vehicle for Multi-temporal Monitoring of Soybean Vegetation Fraction

  • Yun, Hee Sup;Park, Soo Hyun;Kim, Hak-Jin;Lee, Wonsuk Daniel;Lee, Kyung Do;Hong, Suk Young;Jung, Gun Ho
    • Journal of Biosystems Engineering
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    • v.41 no.2
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    • pp.126-137
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    • 2016
  • Purpose: The overall objective of this study was to evaluate the vegetation fraction of soybeans, grown under different cropping conditions using an unmanned aerial vehicle (UAV) equipped with a red, green, and blue (RGB) camera. Methods: Test plots were prepared based on different cropping treatments, i.e., soybean single-cropping, with and without herbicide application and soybean and barley-cover cropping, with and without herbicide application. The UAV flights were manually controlled using a remote flight controller on the ground, with 2.4 GHz radio frequency communication. For image pre-processing, the acquired images were pre-treated and georeferenced using a fisheye distortion removal function, and ground control points were collected using Google Maps. Tarpaulin panels of different colors were used to calibrate the multi-temporal images by converting the RGB digital number values into the RGB reflectance spectrum, utilizing a linear regression method. Excess Green (ExG) vegetation indices for each of the test plots were compared with the M-statistic method in order to quantitatively evaluate the greenness of soybean fields under different cropping systems. Results: The reflectance calibration methods used in the study showed high coefficients of determination, ranging from 0.8 to 0.9, indicating the feasibility of a linear regression fitting method for monitoring multi-temporal RGB images of soybean fields. As expected, the ExG vegetation indices changed according to different soybean growth stages, showing clear differences among the test plots with different cropping treatments in the early season of < 60 days after sowing (DAS). With the M-statistic method, the test plots under different treatments could be discriminated in the early seasons of <41 DAS, showing a value of M > 1. Conclusion: Therefore, multi-temporal images obtained with an UAV and a RGB camera could be applied for quantifying overall vegetation fractions and crop growth status, and this information could contribute to determine proper treatments for the vegetation fraction.

Optimization of Wet Reduction Processing for Nanosized Cobalt Powder (나노코발트 분말합성을 위한 액상환원공정의 최적화)

  • Hong, Hyun-Seon;Jung, Hang-Chul;Kim, Geon-Hong;Kang, Lee-Seung;Suk, Han-Gil
    • Journal of Powder Materials
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    • v.20 no.3
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    • pp.191-196
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    • 2013
  • Nano-sized cobalt powder was fabricated by wet chemical reduction method at room temperature. The effects of various experimental variables on the overall properties of fabricated nano-sized cobalt powders have been investigated in detail, and amount of NaOH and reducing agent and dropping speed of reducing agent have been properly selected as experimental variables in the present research. Minitab program which could find optimized conditions was adopted as a statistic analysis. 3D Scatter-Plot and DOE (Design of Experiments) conditions for synthesis of nano-sized cobalt powder were well developed using Box-Behnken DOE method. Based on the results of the DOE process, reproducibility test were performed for nano-sized cobalt powder. Spherical nano-sized cobalt powders with an average size of 70-100 nm were successfully developed and crystalline peaks for the HCP and FCC structure were observed without second phase such as $Co(OH)_2$.

A Combination and Calibration of Multi-Model Ensemble of PyeongChang Area Using Ensemble Model Output Statistics (Ensemble Model Output Statistics를 이용한 평창지역 다중 모델 앙상블 결합 및 보정)

  • Hwang, Yuseon;Kim, Chansoo
    • Atmosphere
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    • v.28 no.3
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    • pp.247-261
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    • 2018
  • The objective of this paper is to compare probabilistic temperature forecasts from different regional and global ensemble prediction systems over PyeongChang area. A statistical post-processing method is used to take into account combination and calibration of forecasts from different numerical prediction systems, laying greater weight on ensemble model that exhibits the best performance. Observations for temperature were obtained from the 30 stations in PyeongChang and three different ensemble forecasts derived from the European Centre for Medium-Range Weather Forecasts, Ensemble Prediction System for Global and Limited Area Ensemble Prediction System that were obtained between 1 May 2014 and 18 March 2017. Prior to applying to the post-processing methods, reliability analysis was conducted to identify the statistical consistency of ensemble forecasts and corresponding observations. Then, ensemble model output statistics and bias-corrected methods were applied to each raw ensemble model and then proposed weighted combination of ensembles. The results showed that the proposed methods provide improved performances than raw ensemble mean. In particular, multi-model forecast based on ensemble model output statistics was superior to the bias-corrected forecast in terms of deterministic prediction.

The evaluation of statistic processing on korean compound nouns (복합명사의 통계적 처리에 대한 평가)

  • Nam, Se-Jin;Lee, Ji-Yun;Shin, Dong-Wook;Chae, Mi-Ok
    • Annual Conference on Human and Language Technology
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    • 1996.10a
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    • pp.36-41
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    • 1996
  • 한글을 대상으로 하는 검색 시스템의 강우 문서의 대부분을 차지하는 복합명사는 원칙적으로 단어와 단어 사이를 띄어 써야 하지만 붙여쓰기 또한 허용하므로 정보 검색 시스템에서는 이를 고려하여야 한다. 본 논문에서는 MIDAS/IR 정보검색 시스템에서 통계적인 정보를 이용하여 복합명사를 처리하는 방법을 구현하고 이를 실험을 통하여 평가하고자 한다. MIDAS/IR은 크게 복합명사의 통계적인 정보를 이용하는 색인 부분과 확장 불리한 모델 및 벡터 공간 모델을 제공하는 검색 부분으로 이루어져 있다. 색인기에서는 복합명사를 처리할 뿐 아니라 고유명사와 같이 사전에 등록되지 않은 명사를 처리하는 작업을 하게 되며 검색 부분은 클래스 라이브러리로 구현되어 있어 임의의 검색 모델도 쉽게 추가 될 수 있도록 설계하였다. 본 연구에서는 KTSET을 이용하여 불리한 모델 및 벡타 공간 모델에서의 성능을 실험을 통하여 평가하였으며, n-그램을 사용한 시스템과 비교 분석하였다.

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A Statistic Correlation Analysis Algorithm Between Land Surface Temperature and Vegetation Index

  • Kim, Hyung-Moo;Kim, Beob-Kyun;You, Kang-Soo
    • Journal of Information Processing Systems
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    • v.1 no.1 s.1
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    • pp.102-106
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    • 2005
  • As long as the effective contributions of satellite images in the continuous monitoring of the wide area and long range of time period, Landsat TM and Landsat ETM+ satellite images are surveyed. After quantization and classification of the deviations between TM and ETM+ images based on approved thresholds such as gains and biases or offsets, a correlation analysis method for the compared calibration is suggested in this paper. Four time points of raster data for 15 years of the highest group of land surface temperature and the lowest group of vegetation of the Kunsan city Chollabuk_do Korea located beneath the Yellow sea coast, are observed and analyzed their correlations for the change detection of urban land cover. This experiment based on proposed algorithm detected strong and proportional correlation relationship between the highest group of land surface temperature and the lowest group of vegetation index which exceeded R=(+)0.9478, so the proposed Correlation Analysis Model between the highest group of land surface temperature and the lowest group of vegetation index will be able to give proof an effective suitability to the land cover change detection and monitoring.

Big Data Processing and Performance Improvement for Ship Trajectory using MapReduce Technique

  • Kim, Kwang-Il;Kim, Joo-Sung
    • Journal of the Korea Society of Computer and Information
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    • v.24 no.10
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    • pp.65-70
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    • 2019
  • In recently, ship trajectory data consisting of ship position, speed, course, and so on can be obtained from the Automatic Identification System device with which all ships should be equipped. These data are gathered more than 2GB every day at a crowed sea port and used for analysis of ship traffic statistic and patterns. In this study, we propose a method to process ship trajectory data efficiently with distributed computing resources using MapReduce algorithm. In data preprocessing phase, ship dynamic and static data are integrated into target dataset and filtered out ship trajectory that is not of interest. In mapping phase, we convert ship's position to Geohash code, and assign Geohash and ship MMSI to key and value. In reducing phase, key-value pairs are sorted according to the same key value and counted the ship traffic number in a grid cell. To evaluate the proposed method, we implemented it and compared it with IALA waterway risk assessment program(IWRAP) in their performance. The data processing performance improve 1 to 4 times that of the existing ship trajectory analysis program.

Estimation of a Nationwide Statistics of Hernia Operation Applying Data Mining Technique to the National Health Insurance Database (데이터마이닝 기법을 이용한 건강보험공단의 수술 통계량 근사치 추정 -허니아 수술을 중심으로-)

  • Kang, Sung-Hong;Seo, Seok-Kyung;Yang, Yeong-Ja;Lee, Ae-Kyung;Bae, Jong-Myon
    • Journal of Preventive Medicine and Public Health
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    • v.39 no.5
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    • pp.433-437
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    • 2006
  • Objectives: The aim of this study is to develop a methodology for estimating a nationwide statistic for hernia operations with using the claim database of the Korea Health Insurance Cooperation (KHIC). Methods: According to the insurance claim procedures, the claim database was divided into the electronic data interchange database (EDI_DB) and the sheet database (Paper_DB). Although the EDI_DB has operation and management codes showing the facts and kinds of operations, the Paper_DB doesn't. Using the hernia matched management code in the EDI_DB, the cases of hernia surgery were extracted. For drawing the potential cases from the Paper_DB, which doesn't have the code, the predictive model was developed using the data mining technique called SEMMA. The claim sheets of the cases that showed a predictive probability of an operation over the threshold, as was decided by the ROC curve, were identified in order to get the positive predictive value as an index of usefulness for the predictive model. Results: Of the claim databases in 2004, 14,386 cases had hernia related management codes with using the EDI system. For fitting the models with applying the data mining technique, logistic regression was chosen rather than the neural network method or the decision tree method. From the Paper_DB, 1,019 cases were extracted as potential cases. Direct review of the sheets of the extracted cases showed that the positive predictive value was 95.3%. Conclusions: The results suggested that applying the data mining technique to the claim database in the KHIC for estimating the nationwide surgical statistics would be useful from the aspect of execution and cost-effectiveness.

Brain Neuroadaptative Changes in Adolescents with Internet Addiction : An FDG-PET Study with Statistical Parametric Mapping Analysis

  • Koo, Young-Jin;Paeng, Jin-Chul;Joo, Eun-Jeong;Kang, Hye-Jin;Im, Youn-Seok;Seok, Ju-Won;Kang, Ung-Gu
    • Journal of the Korean Academy of Child and Adolescent Psychiatry
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    • v.19 no.1
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    • pp.13-18
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    • 2008
  • Objectives : Internet addiction or pathologic internet use is one of the major mental health problems in children and adolescents in Korea. Internet addiction is defined as uncontrollable, markedly time-consuming internet use, which lasts for a period of at least six months. Internet addiction results in poor academic performance and negative parent-child relationships. By using $^{18}F$-fluorodeoxyglucose-positron emission tomography (FDG-PET), we investigated the effects of internet addiction on functional changes occurring in the adolescent brain. Methods : Adolescent patients with an internet addiction (4 boys and 2 girls; $15.6{\pm}1.2$ years) participated in this study. Eight healthy young adults (5 males and 3 females; 18-30 years old) with no previous history of psychiatric illness also participated as normal controls. Brain FDG-PET data was obtained with the participants in the resting condition and with no addictive stimuli. Results : Statistic parametric mapping analysis of the brain FDG-PET data revealed hypometabolic changes in the visual information processing circuits and hypermetabolic changes in the prefrontal areas in the adolescents with internet addiction, as compared with normal controls (p<.001). Conclusion : These results suggest a neuronal adaptation to excessive visual stimulation and synaptic plasticity due to internet addiction.

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