• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2008.04a
• /
• pp.33-36
• /
• 2008

We introduce some properties for fuzzy binomial distributions with fuzzy valued probability. First we define fuzzy type I error and type II error for fuzzy relative frequency and agreement index. And we show that an fuzzy power function and fuzzy binomial frequency function for binomial proportion test.

• Proceedings of the Safety Management and Science Conference
• /
• 2011.11a
• /
• pp.551-556
• /
• 2011

This research presents an implementation strategy of Process Capability Index (PCI) according to the types of process characteristics. The types of process feature are classified as four perspectives of variation range, time period, error position, and process stage. The paper examines short-term or long-term PCI, within or between variation, position of precision or accuracy, and inclusion of measurement or calibration stage. Moreover, the study proposes normality test of unilateral PCI.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.58 no.10
• /
• pp.2047-2051
• /
• 2009

In this paper, we propose the localization method on WSN(Wireless Sensor Network) using fuzzy model and Kalman filter. The proposed method is as follows: First, we estimate the distance of RSSI(Receive Signal Strength Index) by using fuzzy model in order to minimize the distance error. Second, we use a triangulation measurement for estimating the localization. And then, we minimize the localization error using a Kalman filter. Finally, we show the effectiveness and feasibility of the proposed method through some experiments.

• Geomechanics and Engineering
• /
• v.30 no.5
• /
• pp.437-448
• /
• 2022

Alluvial soil is challenging to work with due to its high compressibility. Thus, consolidation settlement of this type of soil should be accurately estimated. Accurate estimation of the consolidation settlement of alluvial soil requires accurate prediction of compressibility parameters. Geotechnical engineers usually use empirical correlations to estimate these compressibility parameters. However, no attempts have been made to develop correlations to estimate compressibility parameters of alluvial soil. Thus, this paper aims to develop new models to predict the compression and recompression indices (Cc and Cr) of alluvial soils. As part of the study, geotechnical laboratory tests have been conducted on large number of undisturbed samples of local alluvial soil. The obtained results from these tests in addition to available results from the literature from different parts in the world have been compiled to form the database of this study. This database is then employed to examine the accuracy of the available empirical correlations of the compressibility parameters and to develop the new models to estimate the compressibility parameters using the nonlinear regression analysis. The accuracy of the new models has been accessed using mean absolute error, root mean square error, mean, percentage of predictions with error range of ±20%, percentage of predictions with error range of ±30%, and coefficient of determination. It was found that the new models outperform the available correlations. Thus, these models can be used by geotechnical engineers with more confidence to predict Cc and Cr.

• Journal of information and communication convergence engineering
• /
• v.9 no.2
• /
• pp.183-186
• /
• 2011

In this work, we consider imperfectness of feedback channels in the adaptive transmission scheme which was previously studied with an assumption of error-free feedback channels. New method of mapping the modulation index into the feedback channel symbols and quantifying feedback error over fading channels are proposed. The presented method and results are expected to offer valuable tools for the system designer to efficiently implement adaptive diversity schemes to compensate for the performance degradation due to feedback error.

• The Journal of Korean Society for Radiation Therapy
• /
• v.26 no.2
• /
• pp.217-224
• /
• 2014

Purpose : Conventional, IMRT, at CSI treatment with VMAT, this study compare the treatment plan with dose changes measured at Junction field according to the error of Setup. Materials and Methods : This study established Conventional, the IMRT, VMAT treatment planning for CSI therapy using the Eclipse 10.0 (Eclipse10.0, Varian, USA) and chose person in Seoul National University Hospital. Verification plan was also created to apply IMRT QA phantom for each treatment plan to the film measurements. At this time, the error of Setup was applied to the 2, 4, 6mm respectively with the head and foot direction. ("+" direction of the head, "-" means that the foot direction.) Using IMRT QA Phantom and EBT2 film, was investigated by placing the error of Setup for each Junction. We check the consistency of the measured Film and plan dose distribution by gamma index (Gamma index, ${\gamma}$). In addition, we compared the error of Setup by the dose distribution, and analyzing the uniformity of the dose distribution within the target by calculating the Homogeneity Index (HI). Results : It was figured out that 90.49%-gamma index we obtained with film is agreement with film scan score and dose distribution of treatment plan. Also, depend on the dose distribution on distance, if we make the error of Setup 2, 4, 6mm in the head direction, it showed that 3.1, 4.5, 8.1 at $^*Diff$(%) of Conventional, 1.1, 3.5, 6.3 at IMRT, and 1.6, 2.5, 5.7 at VMAT. In the same way, if we make the error of Setup 2, 4, 6mm in the foot direction, it showed that -1.6, -2.8, -4.4 at $^*Diff$(%) of Conventional, -0.9, -1.6, -2.9 at IMRT, and -0.5, -2.2, -2.5 at VMAT. Homogeneity Index(HI)s are 1.216 at Conventional, 1.095 at IMRT and 1.069 at VMAT. Discussion and Conclusion : The dose-change depend on the error of Setup at the CSI RT(radiation therapy) using IMRT and VMAT which have advantages, Dose homogeneity and the gradual dose gradients on the Junction part is lower than that of Conventional CSI RT. This a little change of dose means that there is less danger on patients despite of the error of Setup generated at the CSI RT.

• Journal of Distribution Science
• /
• v.15 no.12
• /
• pp.41-51
• /
• 2017

Purpose - This study proposes the impact of the US and Korean economic policy uncertainty on macroeconomy, and its effect on Korea. The economic policy uncertainty index of the US and Korea is used to represent the economic policy uncertainty on Korean economy. Research design, data, and methodology - In this paper, we collect the eight variables to find out the interrelationship among the US and Korean economic policy uncertainty index of the US and macroeconomic indicators during 1990 to 2016, and use Vector Error Correction Model. Result - The distribution industry stock index in Korea is influenced by the economic policy uncertainty index of the US rather than of Korea. All variables are related negatively to the economic policy uncertainty index of the US and Korea from Vector Error Correction Model. This study shows that the economic policy uncertainty index of the US and Korea has the dynamic relationships on the Korean economy. Conclusions - A higher economic policy uncertainty shows a greater economy recession of a country. Finally, the economic policy uncertainty of the Korea has an intensive impact on Korea economy. Particularly, the economic policy uncertainty of the US has a strong impact on distribution industry stock market in Korea.

• Journal of the Korean Data and Information Science Society
• /
• v.23 no.3
• /
• pp.535-542
• /
• 2012

The consumer price index (CPI) data is one of the important economic measurement of the country. In this article, the Autoregressive Error (ARE) model has been considered for analyzing the monthly CPI data at Seoul, Pusan, Daegu, and Gwangju Cities in Korea, In the ARE model, nine economic variables are used as the explanatory variables for the CPI data set. The nine explanatory variables are CCI (coincident composite index), won-dollar rate, producer price index, oil import price, oil import volume, international current account, import price index, unemployment rate, and amount of currency. The result showed that the monthly ARE models explained about 46-52% for describing the CPI.

• The Korean Journal of Applied Statistics
• /
• v.33 no.4
• /
• pp.395-407
• /
• 2020

Most classification accuracy measures for optimal threshold are divided into two types: one is expressed with cumulative distribution functions and probability density functions, the other is based on ROC curve and AUC. Unal (2017) proposed the index of union (IU) as an accuracy measure that considers two types to get them. In this study, ten kinds of accuracy measures (including IU) are divided into six categories, and the advantages of the IU are studied by comparing the measures belonging to each category. The optimal thresholds of these measures are obtained by setting various normal mixture distributions; subsequently, the first and second type of errors as well as the error sums corresponding to each threshold are calculated. The properties and characteristics of the IU statistic are explored by comparing the discriminative power of other accuracy measures based on error values.The values of the first type error and error sum of IU statistic converge to those of the best accuracy measures of the second category as the mean difference between the two distributions increases. Therefore, IU could be an accuracy measure to evaluate the discriminant power of a model.

• The Korean Journal of Applied Statistics
• /
• v.35 no.1
• /
• pp.93-104
• /
• 2022

In forecasting realized volatility of the major US stock price indexes (S&P 500, Russell 2000, DJIA, Nasdaq 100), internet search volume reflecting investor's interests and implied volatility are used to improve forecast via a deep learning method of the LSTM. The LSTM method combined with search volume index produces better forecasts than existing standard methods of the vector autoregressive (VAR) and the vector error correction (VEC) models. It also beats the recently proposed vector error correction heterogeneous autoregressive (VECHAR) model which takes advantage of the cointegration relation between realized volatility and implied volatility.