• Survey Research
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• v.12 no.3
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• pp.25-48
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• 2011

In this paper, we overview the sample design, sampling error, non-response rate and prediction errors of the exit poll conducted for 2010 local elections and discusses how to detect a prediction bias in exit poll. To investigate the bias problem in exit poll in regional(Si-Do) level, we analyze exit poll data for 2007 presidential election and 2006 local elections as well as 2010 local elections in Korea. The measure of predictive accuracy A proposed by Martin et al.(2005) is used to assess the exit poll bias. The empirical studies based on three exit polls clearly show that there exits systematic bias in exit poll and the predictive bias of candidates affiliated to conservative party (such as Hannara-Dang) is serious in the specific regions. The result of this study on systematic bias will be very useful to improving the exit poll methodology in Korea.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.601-602
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• 2013

경로손실 예측 모델은 무선 네트워크 설계를 위한 기본 척도이며, 적용 환경과 적용 시스템에 영향을 받는 특징이 있다. 대부분의 기존 연구는 도심, 교외와 같은 육상 환경을 기반으로 한다. 일반적으로 해수면 경로 손실은 전파의 잦은 굴절로 인해 지표면 보다 크며, 주파수에 비례한 경로손실이 있다고 알려져 있다. 하지만 해상 환경의 관련 연구는 자유공간에 적용하기 때문에 예측 모델의 정확성을 낮춘다. 본 논문은 해상 무선통신 서비스를 위한 2.4 GHz 대역의 해수면 경로손실 예측 모델을 제안한다. 이를 위해 육상과 해상에서 각각 수신신호 세기를 측정하고, 다양한 예측 모델과 비교 분석하여 실용성과 정확성을 입증한다.

• The Korean Journal of Applied Statistics
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• v.35 no.5
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• pp.645-655
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• 2022

In this paper, we investigate automatic functions for time series forecasting in R system and compare their performances. For the exponential smoothing models and ARIMA (autoregressive integrated moving average) models, we focus on the representative time series forecasting functions in R: forecast::ets(), forecast::auto.arima(), smooth::es() and smooth::auto.ssarima(). In order to compare their forecast performances, we use M3-Competiti on data consisting of 3,003 time series and adopt 3 accuracy measures. It is confirmed that each of the four automatic forecasting functions has strengths and weaknesses in the flexibility and convenience for time series modeling, forecasting accuracy, and execution time.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.298-301
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• 2009

시간 속성을 갖는 이벤트들의 집합에서 이벤트들 사이의 인과관계를 보다 정확히 파악할 수 있는 방법의 개발은 의료 분야 등의 응용에서 미리 발생할 이벤트에 발생 시점 예측을 위하여 필요하다. 본 논문은 이벤트들의 시퀀스를 독립적인 서브 시퀀스로 나누고 각 서브 시퀀스를 인터벌을 갖는 이벤트로 요약하여 인터벌 이벤트들 사이의 관계를 표현한다. 그리고 인터벌 이벤트 관계에서 원인 인터벌 이벤트가 결과 이벤트에 미친 영향 정도의 측정 방법을 개발하고 실험을 통하여 사용한 척도의 의미와 정확성을 파악한다. 실험 결과는 제안 방법이 지지도 기반의 평가보다 보다 우수함을 입증한다.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.2 no.1
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• pp.77-85
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• 2004

Regulations and guidelines for radioactive waste disposal require detailed information about the characteristics of radioactive waste drums prior to transport to the disposal sites. However, estimation of radionuclide concentrations in the drummed radioactive waste is difficult and unreliable. In order to overcome this difficulty, scaling factor (SF) method has been used to assess the activities of radionuclides, which could not be directly analyzed. A radioactive waste assay system has been operated at Korean nuclear power plant (KORI site) since 1996 and consolidated SF concept has played a dominant role in the determination of radionuclide concentrations. However, SFs are somewhat dispersive and limited in KORI site. Therefore establishment of the assay system using more improved SFs is planned and progressed. In this paper, the scope of research is briefly introduced. For the selection of more reliable activity determination method, the accuracy of predicted SF values for each activity determination method is compared. From the comparison of each activity determination method, it is recommended that SF determination method should be changed from the arithmetic mean to the geometrical mean for more reliable estimation of radionuclide activity. Arithmetic mean method and geometric mean method are compared based on the data set in KORI system. And, this change of SF determination method will prevent an inordinate over-estimation of radionuclide inventory in radwaste drum.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.221-226
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• 2021

Collaborative filtering based recommender systems recommend user-preferrable items based on rating history and are essential function for the current various commercial purposes. In order to determine items to recommend, prediction of preference score for unrated items is estimated based on similar rating history. Previous studies usually employ two methods individually, i.e., similar user based or similar item based ones. These methods have drawbacks of degrading prediction accuracy in case of sparse user ratings data or when having difficulty with finding similar users or items. This study suggests a new rating prediction method by integrating the two previous methods. The proposed method has the advantage of consulting more similar ratings, thus improving the recommendation quality. The experimental results reveal that our method significantly improve the performance of previous methods, in terms of prediction accuracy, relevance level of recommended items, and that of recommended item ranks with a sparse dataset. With a rather dense dataset, it outperforms the previous methods in terms of prediction accuracy and shows comparable results in other metrics.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.3
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• pp.295-303
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• 2012

Clarify wind energy productivity depends on three factors: the wind probability density function(PDF), the turbine's power curve, and the air density. The wind PDF gives the probability that a variable will take on the wind speed value. Wind shear refers to the change in wind speed with height above ground. The wind speed tends to increase with the height above ground. also, Wind PDF refers to the change with height above ground. Wind analysts typically use the Weibull distribution to characterize the breadth of the distribution of wind speeds. The Weibull distribution has the two-parameter: the scale factor c and the shape factor k. We can use a linear least squares algorithm(or Ln-least method) and moment method to fit a Weibull distribution to measured wind speed data which data was located same site and different height. In this study, find that the scale factor is related to the average wind speed than the shape factor. and also different types of terrain are characterized by different the scale factor slop with height above ground. The gross turbine power output (before accounting for losses) was caculated the power curve whose corresponding air density is closest to the air density. and air desity was choose two way. one is the pressure of the International Standard Atmosphere up to an elevation, the other is the measured air pressure and temperature to calculate the air density. and then each power output was compared.

• Management & Information Systems Review
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• v.36 no.3
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• pp.151-165
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• 2017

This study investigates the effect of revenue recognition by percentage of completion method on financial analysts' earnings forecasting information in order industry. Specifically, we examines how the analysts' earnings forecast errors and biases differ according to whether or not to report the unbilled revenue account balance and the level of unbilled revenue account balance. The sample consists of 453 firm-years listed in Korea Stock Exchange during the period from 2010 to 2014 since the information on unbilled revenue accounts can be obtained after the adoption of K-IFRS. The results are as follows. First, we find that the firms with unbilled revenue account balances have lower analysts' earnings forecast accuracy than the firms who do not report unbilled revue account balances. In addition, we find that the accuracy of analysts' earnings forecasts decreases as the amount of unbilled revenue increases. Unbilled revenue account balances occur when the revenue recognition of the contractor is faster than the client. There is a possibility that managerial discretionary judgment and estimation may intervene when the contractor calculates the progress rate. The difference between the actual progress of the construction and the progress recognized by the company lowers the predictive value of financial statements. Our results suggest that the analysts' earnings forecasts may be more difficult for the firms that report unbilled revenue balances as applying the revenue recognition method based on the progress criteria. Second, we find that the firms reporting unbilled revenue account balances tend to have higher the optimistic biases in analysts' earnings forecast than the firms who do not report unbilled revenue account balances. And we find that the analysts' earnings forecast biases are increases as the amount of unbilled revenue increases. This study suggests an effort to reduce the arbitrary adjustment and estimation in the measurement of the progress as well as the introduction of the progress measurement method which can reflect the actual progress. Investors are encouraged to invest and analyze the characteristics of the order-based industry accounting standards. In addition, the results of this study empower the accounting transparency enhancement plan for order industry proposed by the policy authorities.

• Journal of the Korea institute for structural maintenance and inspection
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• v.15 no.5
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• pp.113-123
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• 2011

LCC analysis is a method that coordinates with function evaluation for value improvement, rather than a separate one for cost evaluation. Although its accuracy is rising, materials and structural types developed or applied relatively recently have yet to obtain a sufficient maintenance profile DB, inducing reliability to reduce from difficulties in estimating maintenance records. Based on the above mentioned background, this paper presents the LCC methodology of coordinating functional intensification matters with cost for analysis on alternatives with difficulties in setting maintenance profile. Recently, steel plate bridge deck pavements are faced with problems such as plastic deformation due to the increase in heavy vehicles and traffic, promoting the development of a new compound pavement. This paper execute LCC analysis by mentioning case studies of SMA, Guss and PSMA pavements to include performance scale compared between alternatives as relative evaluation coefficients into the maintenance profile.

• Journal of Korea Water Resources Association
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• v.32 no.6
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• pp.657-664
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• 1999

This paper introduced the basic theory of LRCS(Linear Reservoir and Channel System) rainfall runoff model proposed by Korean researchers(Lee and Lee, 1995), and discussed the change of model output according to objective functions in sensitivity analysis and calibration process of model. It proposed "hat" matrix and affluence measures for affluence analysis of parameters in calibration, and investigated relationship between change of model output according to error propagation in parameter estimation, and sensitivity of model output according to variance of model output and change of parameters. Accuracy of parameter estimates was known by analysis of sensitivity coefficient, diagonal element $h_i$ and $D_i$._i$.