• 대한음성학회지:말소리
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• 제56호
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• pp.1-13
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• 2005

This study examined the speech intelligibility of one-syllable words with phonetic contrasts and analyzed segmental factors that can predict the overall speech intelligibility in hearing-impaired adults. To identify the speech error characteristics, a Korean word list was audio-recorded by 7 hearing-impaired adults, and 35 listeners selected the heard word out of 5 choices. Based in part on previous studies of speech of the hearing impaired, the word list consisted of monosyllabic consonant-vowel-consonant (CVC) real word pairs. Stimulus words included 77 phonetic contrast pairs. The results showed that the percentage of errors in final position (coda) contrast was higher than in any other position in syllable. And the intelligibility deficit factors of phonetic contrast in the hearing-impaired were analyzed through stepwise regression analysis. The overall intelligibility was predicted by the error rate of manner contrast at coda, voicing contrast (homorganic triplets) at onset and high-low contrast at nucleus.

• 대한임상검사과학회지
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• 제39권1호
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• pp.25-30
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• 2007

In this study, the two sampling methods for blood glucose measurement were evaluated in order to reduce pre-analytical error. For this purpose, glucose levels of Li-heparinized plasma (LHP) and Na-fluorinated plasma (NFP) in blood collected from healthy volunteers were determined by using routine hexokinase procedures. The percentage range of pre-analytical error was quantitated by comparing LHP glucose values with NFP glucose values according to delaying analytical time (0, 60, and 120 min). LHP glucose values were decreased by 6.6% in 60 min., 17.7% in 120 min, whereas NFP glucose values decreased by 1.1% in 60 min, 2.0% in 120 min. Therefore it may be recommended that the NFP sampling method should be used for routine blood glucose determination in diabetes mellitus diagnosis.

• Nuclear Engineering and Technology
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• 제50권1호
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• pp.159-164
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• 2018

An evaluation of various radiometric methods to analyze $^{226}Ra$ in water has been employed on a set of 10 standard solutions of different concentrations in the range of $1-10Bq/L^{-1}$. The analysis was carried out using well-established procedures by means of gamma-ray, alpha-particle and liquid scintillation spectrometry. The feasibility of the various methods has been quantified in terms of relative standard error and percentage error. Correlations between the various methods have been presented and discussed. In general, good agreement was found in the results of various methodologies, which assures the accuracy of the methods and allows for the validation of instrumentation and procedures. Of the different methods adopted here, a combined procedure for the determination of $^{226}Ra$ along with $^{228}Ra$ using Quantulus 1220 ultra-low level background liquid scintillation counting gave the most accurate results.

• 한국연초학회지
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• 제31권2호
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• pp.95-106
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• 2009

Semiquantitative analysis by ICP-MS has proven to be a powerful tool for fast screening, in addition, it does not require the element of interest to be present in the calibration standard, making it especially useful for the analysis of unknown samples. In this study, seven cigarette samples were analyzed by the rapid semi-quantitative analysis method based on the ICP-MS. For each cigarette sample, cut tobacco, cigarette paper, filter (before and after smoking), and smoke condensate were analyzed. The accuracy of the analysis technique was evaluated by comparing results obtained from Calibration Check Standard(CCS) and calibration method. Relative Percentage Error(RPE) value of all elements measured for three CCS showed a stable result of less than ${\pm}20%$. Compared to full quantitative analysis by calibration method, the results for cigarette samples showed average error within ${\pm}15%$.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2006년도 하계종합학술대회
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• pp.49-50
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• 2006

Digital satellite systems are usually integrated with terrestrial systems to provide various services, and in these cases they should satisfy the performance objectives defined by the terrestrial systems. Recommendation ITU-R S.1062 specifies the performance of digital satellite systems. The performance objectives were given in terms of bit error probability divided by the average number of errors per burst versus percentage of time. This paper presents theoretical method to estimate performance measure of digital satellite systems defined in Recommendation ITU-R S.1062. We show performance estimation results of duo-binary Turbo codes, and verify them by comparing to the simulation results.

• 대한전기학회논문지:전력기술부문A
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• 제51권3호
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• pp.109-117
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• 2002

High accuracy of the load forecasting for power systems improves the security of the power system and generation cost. However, the forecasting problem is difficult to handle due to the nonlinear and the random-like behavior of system loads as well as weather conditions and variation of economical environments. So far. many studies on the problem have been made to improve the prediction accuracy using deterministic, stochastic, knowledge based and artificial neural net(ANN) method. In the conventional load forecasting method, the load forecasting maximum error occurred for the holidays on Saturday and Monday. In order to reduce the load forecasting error of the daily peak load for the holidays on Saturday and Monday, fuzzy concept and linear regression theory have been adopted into the load forecasting problem. The proposed algorithm shows its good accuracy that the average percentage errors are 2.11% in 1996 and 2.84% in 1997.

• 대한전기학회논문지:전력기술부문A
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• 제52권8호
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• pp.450-456
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• 2003

This paper proposes a multiple time-series model with dummy variables for one-hour ahead load forecasting. We used 11 dummy variables that were classified by day characteristics such as day of the week, holiday, and special holiday. Also, model specification and selection of input variables including dummy variables were made by test statistics such as AIC(Akaike Information Criterion) and t-test statistics of each coefficient. OLS (Ordinary Least Squares) method was used for estimation and forecasting. We found out that model specifications for each hour are not identical usually at 30％ of optimal significance level, and dummy variables reduce the forecasting error if they are classified properly. The proposed model has much more accurate estimates in forecasting with less MAPE (Mean Absolute Percentage Error).

• Journal of Information Processing Systems
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• 제14권4호
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• pp.904-915
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• 2018

We demonstrate how social media content can be used to predict the unemployment rate, a real-world indicator. We present a novel method for predicting the unemployment rate using social media analysis based on natural language processing and statistical modeling. The system collects social media contents including news articles, blogs, and tweets written in Korean, and then extracts data for modeling using part-of-speech tagging and sentiment analysis techniques. The autoregressive integrated moving average with exogenous variables (ARIMAX) and autoregressive with exogenous variables (ARX) models for unemployment rate prediction are fit using the analyzed data. The proposed method quantifies the social moods expressed in social media contents, whereas the existing methods simply present social tendencies. Our model derived a 27.9% improvement in error reduction compared to a Google Index-based model in the mean absolute percentage error metric.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.68-68
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• 2022

코로나바이러스는(COVID-19)는 2019년 12일 중국 후베이성 우한시에서 시작된 코로나바이러스감염증으로 2020년 1월부터 전 세계로 퍼져, 일부 국가 및 지역을 제외한 대부분의 나라와 모든 대륙으로 확산되었다. 이에 WHO는 범 유행전염병(Pandemic)을 선언하였다. 2022년 3월 18일 현재 국내 누적 확진환자 8,657,609명과 11,782명의 사망자를 일으켰고 전 세계적으로도 많은 사상자를 내고 있는 실정이고 사회 및 경제적인 피해로도 계속 확대되고 있다. 많은 감염자와 사망자의수에 대한 예측은 코로나바이러스의 전염병을 예방하고 즉각적 조치를 취할 수 있는데 도움이 될 수 있다. 본 연구에서는 문화적 인자를 제외한 국내에서 연구 사례가 많지 않은 기상 요인을 인자로 포함하여 머신러닝 모델을 통해 확진자를 예측하였다. 그리고 여러 가지 모델을 성능 평가 기법인 Root Mean Square Error(RMSE) 및 Mean Absolute Percentage Error(MAPE)를 통해 성능을 평가하고 비교하여 정확도 높은 모델을 제시하였다.

• 한국ITS학회 논문지
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• 제11권2호
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• pp.10-20
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• 2012

본 연구에서는 일반국도 수시조사 지점의 AADT 추정값의 정확도를 높이기 위하여 새로운 그룹핑방법을 제시하였다. 일반적으로 수시조사 자료의 AADT 추정을 위해 월보정계수, 요일보정계수, 조사된 24시간 교통량을 이용하여 AADT를 추정 하므로 상시조사 지점을 그룹핑할 때 상기 세 가지 요인(43개 변수)을 모두 적용하여 그룹핑하였다. 이 방법은 기존의 월보정계수와 요일보정계수만을 이용하여 그룹핑한것과 비교하여 시간대별 교통량을 적용한 것에 있어서 차이가 있다. 그룹핑 결과 5개의 군집이 가장 적당한 것으로 분석되었다. 5개의 군집 중 2개의 군집은 해당되는 지점이 몇 지점 없어 설명하기 어려웠고, 나머지 3개의 군집에서 각각 출퇴근로, 관광부도로, 지방부도로의 특성을 가지는 것으로 나타났다. 각 그룹의 월보정계수 평균과 요일보정계수 평균, 시간대별 교통량 비율의 평균으로 각 그룹의 대표 보정계수를 산출하고, 분석대상지점의 평일 교통량을 해당 그룹의 대표 보정계수를 적용하여 AADT를 추정한 결과 평균적으로 오차가 8.7%인 것으로 나타났다. 이는 기존 연구에서 우수하다고 분석된 동일 대구간 내의 상시조사 보정계수를 적용한 것보다 1.5%오차가 더 적은 것으로 나타났다. 이러한 AADT 산출방법은 전체 수시조사 지점에 적용 가능하므로 실무에서의 활용도가 매우 크다고 판단된다.