• Journal of The Korean Society of Agricultural Engineers
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• v.46 no.5
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• pp.117-127
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• 2004

A risk analysis on the cutting slope of roads near Cheongju area was carried out with the data from geological map, field investigation, and laboratory test and with the Geographic Information System. A risk analysis method on the cutting slope of road using the Geographic Information System was developed with the data from geological map, field investigation and laboratory tests. In the GIS, road factors which are safety factor, class of road, slake index, slope-protection works, and height of slope in the cutting slopes are classified into some ranks, and their weighting factors were taken into account. This method can be applied effectively to a road management.

• Communications for Statistical Applications and Methods
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• v.7 no.2
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• pp.574-574
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• 2000

Consider the problem of estimating regression function from a set of data which is contaminated by a long-tailed error distribution. The linear smoother is a kind of a local weighted average of response, so it is not robust against outliers. The kernel M-smoother and the lowess attain robustness against outliers by down-weighting outliers. However, the kernel M-smoother and the lowess requires the iteration for computing the robustness weights, and as Wang and Scott(1994) pointed out, the requirement of iteration is not a desirable property. In this article, we propose the robust nonparametic regression method which does not require the iteration. Robustness can be achieved not only by down-weighting outliers but also by transforming outliers. The rank transformation is a simple procedure where the data are replaced by their corresponding ranks. Iman and Conover(1979) showed the fact that the rank transformation is a robust and powerful procedure in the linear regression. In this paper, we show that we can also use the rank transformation to nonparametric regression to achieve the robustness.

• Communications for Statistical Applications and Methods
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• v.7 no.2
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• pp.575-583
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• 2000

Consider the problem of estimating regression function from a set of data which is contaminated by a long-tailed error distribution. The linear smoother is a kind of a local weighted average of response, so it is not robust against outliers. The kernel M-smoother and the lowess attain robustness against outliers by down-weighting outliers. However, the kernel M-smoother and the lowess requires the iteration for computing the robustness weights, and as Wang and Scott(1994) pointed out, the requirement of iteration is not a desirable property. In this article, we propose the robust nonparametic regression method which does not require the iteration. Robustness can be achieved not only by down-weighting outliers but also by transforming outliers. The rank transformation is a simple procedure where the data are replaced by their corresponding ranks. Iman and Conover(1979) showed the fact that the rank transformation is a robust and powerful procedure in the linear regression. In this paper, we show that we can also use the rank transformation to nonparametric regression to achieve the robustness.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1992.04a
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• pp.13-18
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• 1992

구조물의 동적실험을 통하여 얻은 하중과 거동에 대한 시간기록을 분석하여, 구조계의 동 특성계수들을 추정하는 기법에 대하여 연구하였다. 실험과정 및 해석모형과정의 오차를 고려하기 위하여, 하중기록과 구조거동기록간의 관계를 추계론적 자동회기 및 이동평균모형(Stochastic Auto-Regressive and Moving-Average (ARMAX) Model)음 사용하여 모형화하였다. 미지의 ARMAX 계수행렬들은 순차적 예측오차기법을 사용하여 추정하였으며, 계수추정기법의 효율성을 증진시키기 위하여, Exponential Data Weighting, Global Data Weighting 및 Square Root Estimation 기법을 활용하였다. 다중거동측정계의 예제해석을 통하여 이의 효율성을 분석하였다.

• The Journal of the Acoustical Society of Korea
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• v.23 no.2E
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• pp.51-55
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• 2004

In this paper, we propose a style-specific language model adaptation scheme using n-gram based tf*idf similarity for Korean spontaneous speech recognition. Korean spontaneous speech shows especially different style-specific characteristics such as filled pauses, word omission, and contraction, which are related to function words and depend on preceding or following words. To reflect these style-specific characteristics and overcome insufficient data for training language model, we estimate in-domain dependent n-gram model by relevance weighting of out-of-domain text data according to their n-. gram based tf*idf similarity, in which in-domain language model include disfluency model. Recognition results show that n-gram based tf*idf similarity weighting effectively reflects style difference.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.71-76
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• 2003

The purpose of this study is the development, application and assessment of probability and artificial neural network methods for assessing landslide susceptibility in a chosen study area. As the basic analysis tool, a Geographic Information System (GIS) was used for spatial data management. A probability method was used for calculating the rating of the relative importance of each factor class to landslide occurrence, For calculating the weight of the relative importance of each factor to landslide occurrence, an artificial neural network method was developed. Using these methods, the landslide susceptibility index was calculated using the rating and weight, and a landslide susceptibility map was produced using the index. The results of the landslide susceptibility analysis, with and without weights, were confirmed from comparison with the landslide location data. The comparison result with weighting was better than the results without weighting. The calculated weight and rating can be used to landslide susceptibility mapping.

• Journal of Korea Multimedia Society
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• v.17 no.11
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• pp.1286-1295
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• 2014

This paper suggests the way that it could improve the reliability about preference of user's feedback by adding weighting factor on sentiment analysis, and efficiently make a sentiment analysis of users' emotional perspective on the big data massively generated on twitter. To solve errors on earlier studies, this paper has improved recall and precision of sensibility determination by using sensibility dictionary subdivided sentiment polarity based on the level of sensibility and given impotance to sensibility determination by populating slang, new words, emoticons and idiomatic expressions not in the system dictionary. It has considered the context through conjunctive adverbs fixed in korean characteristics which are free to the word order. It also recognize sensibility words such as TF(Term Frequency), RT(Retweet), Follower which are weighting factors of preference and has increased reliability of preference analysis considering weight on 'a very emotional tweet', 'a recognised tweet from users' and 'a tweeter influencer'

• 유체기계공업학회:학술대회논문집
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• 2005.12a
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• pp.185-190
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• 2005

This work presents a numerical procedure to optimize the elliptic-shaped pin fin arrays to enhance turbulent heat transfer. The response surface method is used as an optimization technique with Reynolds-averaged Navier Stokes analysis of flow and heat transfer. Shear stress transport (SST) turbulence model is used as a turbulence closure. Computational results for average heat transfer rate show a reasonable agreement with the experimental data. Four variables including major axis length, minor axis length, pitch and the pin fin length nondimensionalized by duct height are chosen as design variables. The objective function is defined as a linear combination of heat transfer and friction-loss related terms with weighting factor. D-optimal design is used to reduce the data points, and, with only 28 points, reliable response surface is obtained. Optimum shapes of the pin-fin arrays have been obtained in the range from 0.0 to 0.1 of weighting factor.

• Journal of Korea Spatial Information System Society
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• v.10 no.4
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• pp.21-26
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• 2008

A method for processing huge airborne laser scanned data using parallel computing and virtual grid is proposed and the method is tested by generating raster DSM(Digital Surface Model) with IDW(Inverse Distance Weighting). Parallelism is involved for fast interpolation of huge point data and virtual grid is adopted for enhancing searching efficiency of irregularly distributed point data. Processing time was checked for the method using cluster constituted of one master node and six slave nodes, resulting in efficiency near to 1 and load scalability property. Also large data which cannot be processed with a sole system was processed with cluster system.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.17 no.5
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• pp.161-172
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• 2018

This paper proposed the robot vision control method to track a moving rigid body target using the vision system model that can actively control camera parameters even if the relative position between the camera and the robot and the focal length and posture of the camera change. The proposed robotic vision control scheme uses a batch method that uses all the vision data acquired from each moving point of the robot. To process all acquired data, this robot vision control scheme is divided into two cases. One is to give an equal weight for all acquired data, the other is to give weighting for the recent data acquired near the target. Finally, using the two proposed robot vision control schemes, experiments were performed to estimate the positions of a moving rigid body target whose spatial positions are unknown but only the vision data values are known. The efficiency of each control scheme is evaluated by comparing the accuracy through the experimental results of each control scheme.