• Journal of KIISE:Software and Applications
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• v.37 no.6
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• pp.455-463
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• 2010

In this paper, we present an approach to sentence boundary detection for web documents that builds on statistical-based methods and uses rule-based correction. The proposed system uses the classification model learned offline using a training set of human-labeled web documents. The web documents have many word-spacing errors and frequently no punctuation mark that indicates the end of sentence boundary. As sentence boundary candidates, the proposed method considers every Ending Eomis as well as punctuation marks. We optimize engine performance by selecting the best feature, the best training data, and the best classification algorithm. For evaluation, we made two test sets; Set1 consisting of articles and blog documents and Set2 of web community documents. We use F-measure to compare results on a large variety of tasks, Detecting only periods as sentence boundary, our basis engine showed 96.5% in Set1 and 56.7% in Set2. We improved our basis engine by adapting features and the boundary search algorithm. For the final evaluation, we compared our adaptation engine with our basis engine in Set2. As a result, the adaptation engine obtained improvements over the basis engine by 39.6%. We proved the effectiveness of the proposed method in sentence boundary detection.

• Korean Journal of Construction Engineering and Management
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• v.17 no.2
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• pp.39-48
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• 2016

According to the order receipt report over the past 10 years the overseas construction business total trades were 54.05% and 68.09% done by the Middle East and other industrial facilities respectively. In the Middle East based on data collected in 2014 the country with most overseas construction business is Saudi Arabia with 34.10%, and the industrial facility occupies the larger share with 56%. Overseas construction business is suffering from a reduction in work orders in the Middle East because of the recent oil price reduction. At this point of view, it is necessary to consider economy fluctuation for the diversification of construction type and work orders. This study analyzed, focusing in Saudi Arabia how the economical fluctuations of nations of progress can affect overseas construction business' trade orders. The analysis results demonstrated that most construction types depends on GDP, investment fund. Also industrial facility can be substituted with Architecture and civil engineering. This work is expected to be used as a basis for trade order amount maintenance and construction type diversification.

• International Commerce and Information Review
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• v.13 no.3
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• pp.77-95
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• 2011

This paper investigates the relationship between export and economic variables such as trade insurance, world economy activity, relative price, unemployment rate, exchange rate volatility, using monthly data. I employ Johansen cointegration methodology since the model must be stationary to avoid the spurious results. The results indicate that there is a long-run relationship between export and variables. Also, the empirical analysis of cointegrating vector using the CCR, DOLS, FMOLS reveals that the increases of trade insurance has positive relations and the increases of exchange rate volatility have negative relations with export. Especially, DOLS based on Monte Carlo simulations, of this estimator being superior in small samples compared to a number of alternative estimators, as well as being able not only to accommodate higher orders of integration but also to account for possible simultaneity within regressors of a potential system. This paper also applies impulse-response functions to get the additional information regarding the responses of the export to the shocks of the variables. The result indicates that export positively to trade insurance and then decay fast compare with exchange rate volatility. Consequently, trade insurance plays the role of trade policy for export promotion in Korea. Whereas, increase of exchange risk result in reduction of export. Therefore, the support of trade insurance should be expanded and the stabilization of the foreign exchange market must be done for the export promotion.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.227-230
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• 2007

If we use the microwave of SAR, we can observe on the ocean in spite of bad weather, day and night time. Sea surface images on the ocean of SAR have a lot of information on the atmospheric phenomena related to surface wind vector. Information of wind speed which is extracted from SAR images is used variously. Wind direction data and sigma nought value are put in the CMOD which can extract wind information in order to estimate sea surface wind from SAR images. Wind spectrum which is extracted from SAR always presents opposed two points of $180^{\circ}$ because of applying to 2D-FFT. These ambiguities should be decided by position of land, wind direction or numerical model. Previously, we converted into sigma nought after extracting Digital Number from RadarSat-1 SAR using ENVI4.0, thus, it took a long time because every process was manual. Therefore, we converted sigma nought by matlab code after making matlab code. After that, we are extracting wind direction from sigma nought. Now, to decide wind direction needs further study because wind direction has $180^{\circ}$ ambiguity.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.5
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• pp.345-352
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• 2014

In this paper, the CAD data for the optimal shape design obtained by isogeometric shape optimization is directly used to fabricate the specimen by using 3D printer for the experimental validation. In a conventional finite element method, the geometric approximation inherent in the mesh leads to the accuracy issue in response analysis and design sensitivity analysis. Furthermore, in the finite element based shape optimization, subsequent communication with CAD description is required in the design optimization process, which results in the loss of optimal design information during the communication. Isogeometric analysis method employs the same NURBS basis functions and control points used in CAD systems, which enables to use exact geometrical properties like normal vector and curvature information in the response analysis and design sensitivity analysis procedure. Also, it vastly simplify the design modification of complex geometries without communicating with the CAD description of geometry during design optimization process. Therefore, the information of optimal design and material volume is exactly reflected to fabricate the specimen for experimental validation. Through the design optimization examples of elasticity problem, it is experimentally shown that the optimal design has higher stiffness than the initial design. Also, the experimental results match very well with the numerical results. Using a non-contact optical 3D deformation measuring system for strain distribution, it is shown that the stress concentration is significantly alleviated in the optimal design compared with the initial design.

• Journal of the Economic Geographical Society of Korea
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• v.15 no.4
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• pp.585-600
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• 2012

The purpose of this study related to the liquidity impact of the housing market variables using vector auto-regressive model(VAR) and empirical analysis is to derive some policy implications. October 2003 until May 2012 using monthly data for liquidity variables mortgage rates, mortgage, financial liquidity, as the composite index and nation, Seoul, Gangnam, Gangbuk, the Apartment sales prices were analyzed. Granger Causality Test Results, mortgage rates and mortgage at a bargain price two regions had a strong causal relationship. Since the impulse response analysis, Geothermal difference there, but housing price housing price itself, the most significant ongoing positive (+) reactions were liquidity-related variables are mortgage loans is large and persistent positive (+), financial liquidity weakly positive (+), mortgage interest rates are negative (-), KOSPI, the negative (-) reacted. Liquidity and housing prices that the rise can be and Gangnam in Gangbuk is greater than the factor that housing investment was confirmed empirically. Government to consider the current economic situation, while maintaining low interest rates and liquidity of the market rather than the real estate industry must ensure that activities can be embedded and local enforcement policies should be differentiated according to the policy will be able to reap significant effect.

• Korean Journal of Construction Engineering and Management
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• v.15 no.6
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• pp.105-112
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• 2014

The objective of this study is to examine the relationship between the degree of business diversification of a construction company and two of the indicators that represent financial stability, namely, a current ratio and a debt ratio, in order to draw policy implications. The current ratio and the debt ratio were used as variables that represent financial stability of a construction company. Berry-Herfindahl Index was used to measure the degree of business portfolio diversification of a construction company. For the analysis, quarterly time series data were retrieved from the financial information disclosure system of Korea's Financial Supervisory Service for the period between the first quarter of 2001 and the third quarter of 2013. The analysis results showed that a higher current ratio and a debt ratio led to a greater extent of business diversification. A higher level of business diversification led to a higher current ratio and a lower debt ratio. It was also shown that the impact of business diversification on the current ratio and the debt ratio outweighed the impact of changes in the current ratio and the debt ratio on business diversification. Meanwhile, an increase in the level of business diversification showed a quite positive effect as it raised the current ratio and lowered the debt ratio of a construction company. These findings suggest that diversification of business portfolio is essential for construction companies to strengthen their financial stability.

• Journal of Korea Multimedia Society
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• v.13 no.5
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• pp.722-729
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• 2010

Prediction problems are widely used in medical domains. For example, computer aided diagnosis or prognosis is a key component in a CDSS (Clinical Decision Support System). SVMs with nonlinear kernels like RBF kernels, have shown superior accuracy in prediction problems. However, they are not preferred by physicians for medical prediction problems because nonlinear SVMs are difficult to visualize, thus it is hard to provide intuitive interpretation of prediction results to physicians. Nomogram was proposed to visualize SVM classification models. However, it cannot visualize nonlinear SVM models. Localized Radial Basis Function (LRBF) was proposed which shows comparable accuracy as the RBF kernel while the LRBF kernel is easier to interpret since it can be linearly decomposed. This paper presents a new tool named VRIFA, which integrates the nomogram and LRBF kernel to provide users with an interactive visualization of nonlinear SVM models, VRIFA visualizes the internal structure of nonlinear SVM models showing the effect of each feature, the magnitude of the effect, and the change at the prediction output. VRIFA also performs nomogram-based feature selection while training a model in order to remove noise or redundant features and improve the prediction accuracy. The area under the ROC curve (AUC) can be used to evaluate the prediction result when the data set is highly imbalanced. The tool can be used by biomedical researchers for computer-aided diagnosis and risk factor analysis for diseases.

• Journal of Cadastre & Land InformatiX
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• v.47 no.2
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• pp.159-174
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• 2017

The long-term imbalances between supply and demand in office market can weaken urban growth since excessive supply of offices led to office market instability and excessive demand of offices weakens growth of urban industry. Recently, there have been a lot of new large-scale supplies, which increased volatility in Seoul office market. Nevertheless, new supply of Seoul office has not been fully examined. Given this, the focus of this article was on confirming the influences of profitability, replacement cost, and demand on new office supplies in Seoul. In examining those influences, another focus was on their relative influences over time. For these purposes, we analyzed quarterly data of Seoul office market between 2003 and 2015 using a vector error correction model (VECM). As a result, in terms of the influences on the current new supply, the impact of supply before the first quarter was negative, while that of office employment before the first quarter was positive. Also, that of interest rate before the second quarter was positive, while those of cap rate before the first quarter and cap rate before the second quarter were negative. Based on the findings, it is suggested that prediction models on Seoul offices need to be developed considering the influences of profitability, replacement cost, and demand on new office supplies in Seoul.

• Journal of KIISE
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• v.43 no.10
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• pp.1085-1093
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• 2016

Community-based Question Answering system is a system which provides answers for each question from the documents uploaded on web communities. In order to enhance the capacity of question analysis, former methods have developed specific rules suitable for a target region or have applied machine learning to partial processes. However, these methods incur an excessive cost for expanding fields or lead to cases in which system is overfitted for a specific field. This paper proposes a multiple machine learning method which automates the overall process by adapting appropriate machine learning in each procedure for efficient processing of community-based Question Answering system. This system can be divided into question analysis part and answer selection part. The question analysis part consists of the question focus extractor, which analyzes the focused phrases in questions and uses conditional random fields, and the question type classifier, which classifies topics of questions and uses support vector machine. In the answer selection part, the we trains weights that are used by the similarity estimation models through an artificial neural network. Also these are a number of cases in which the results of morphological analysis are not reliable for the data uploaded on web communities. Therefore, we suggest a method that minimizes the impact of morphological analysis by using character features in the stage of question analysis. The proposed system outperforms the former system by showing a Mean Average Precision criteria of 0.765 and R-Precision criteria of 0.872.