• KSCE Journal of Civil and Environmental Engineering Research
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• v.12 no.4
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• pp.157-165
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• 1992

IMS, a precision coordinate measuring system using theodolites, is being used to survey and align precision mechanical structures. Compared to conventional mechanical devices for precision measurement, such as CMM (Coordinate Measuring Machine), the target objects of IMS have little limitations in their sizes and shapes, and can be measured in place. Also since IMS displays the coordinate values in real-time, it is possible to perform measurement and alignment of the objects simultaneously. In this paper, the elements and functions of IMS are introduced and a mathematical model of the new software, which utilizes an altered version of the 'Bundle' adjustment algorithm of analytical photogrammetry for the specific use of IMS, is demonstrated. Differences of the mathematical model of IMS from that of analytical photogrammetry are discussed by following the steps of the 'Measurement' option in the 'Main Menu' of the software. A new IMS calibration method is proposed to calculate better first approximations for the 4 unknown theodolite parameters and the coordinates of target objects. The software provides the 'Bundle' procedure for the first approximations of the unknowns before the real-time measurement. It also provides an opportunity of 'bundling' to re-adjust the collected positional data at the end of the measurement.

• Journal of Preventive Medicine and Public Health
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• v.39 no.5
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• pp.433-437
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• 2006

Objectives: The aim of this study is to develop a methodology for estimating a nationwide statistic for hernia operations with using the claim database of the Korea Health Insurance Cooperation (KHIC). Methods: According to the insurance claim procedures, the claim database was divided into the electronic data interchange database (EDI_DB) and the sheet database (Paper_DB). Although the EDI_DB has operation and management codes showing the facts and kinds of operations, the Paper_DB doesn't. Using the hernia matched management code in the EDI_DB, the cases of hernia surgery were extracted. For drawing the potential cases from the Paper_DB, which doesn't have the code, the predictive model was developed using the data mining technique called SEMMA. The claim sheets of the cases that showed a predictive probability of an operation over the threshold, as was decided by the ROC curve, were identified in order to get the positive predictive value as an index of usefulness for the predictive model. Results: Of the claim databases in 2004, 14,386 cases had hernia related management codes with using the EDI system. For fitting the models with applying the data mining technique, logistic regression was chosen rather than the neural network method or the decision tree method. From the Paper_DB, 1,019 cases were extracted as potential cases. Direct review of the sheets of the extracted cases showed that the positive predictive value was 95.3%. Conclusions: The results suggested that applying the data mining technique to the claim database in the KHIC for estimating the nationwide surgical statistics would be useful from the aspect of execution and cost-effectiveness.

• Journal of Korean Society of Steel Construction
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• v.12 no.3 s.46
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• pp.303-315
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• 2000

The main object of this study is to analyze mechanical behaviors as anisotropic three-dimensional body under various static loads. This paper presents the applicability of the finite difference method to three dimensional problem of anisotropic body. The finite difference method as applied here is generalized to anisotropic three-dimensional problem of elastic body where the governing differential equations of equilibrium of such bodies are expressed in terms of the displacement u, v, and w in the coordinates axes x, y and z, care being taken to modify the finite difference expressions to satisfy the appropriate boundary conditions. By adopting a new three dimensional finite difference modelling including elimination of pivotal difference points in the case of free boundary condition, the three dimensional problem of anisotropic body was successfully completed. Several numerical results show quick convergence and numerical validity of finite difference technique in three dimensional problem.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.7 no.1
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• pp.9-16
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• 2009

Transport package for radioactive material should be structurally safe under puncture drop condition and its safety should be verified by test and numerical analysis. Most finite element analyses for puncture drop have been performed without modeling the impact limiter since failure is occurred in the materials of the impact limiter. This paper presents a new modeling methodology, where an element is eroded in case that the material's failure criteria are reached at the element's integration point, to investigate the effect of the impact limiter in the puncture process. The effectiveness of the proposed scheme is shown through the puncture drop analysis of hotcell transport cask, which is under design in KAERI. The results show that about 80 percent of the total impact energy is absorbed due to the deformation of impact limiter. Using the present method the puncture drop can be analyzed more accurately, but it would give conservative results compared to the actual test condition.

• Journal of KIISE:Software and Applications
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• v.30 no.3_4
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• pp.251-258
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• 2003

A support vector machine (SVM) is supposed to provide a good generalization performance, but the actual performance of a actually implemented SVM is often far from the theoretically expected level. This is largely because the implementation is based on an approximated algorithm, due to the high complexity of time and space. To improve this limitation, we propose ensemble of SVMs by using Bagging (bootstrap aggregating) and Boosting. By a Bagging stage each individual SVM is trained independently using randomly chosen training samples via a bootstrap technique. By a Boosting stage an individual SVM is trained by choosing training samples according to their probability distribution. The probability distribution is updated by the error of independent classifiers, and the process is iterated. After the training stage, they are aggregated to make a collective decision in several ways, such ai majority voting, the LSE(least squares estimation) -based weighting, and double layer hierarchical combining. The simulation results for IRIS data classification, the hand-written digit recognition and Face detection show that the proposed SVM ensembles greatly outperforms a single SVM in terms of classification accuracy.

• Journal of KIISE:Software and Applications
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• v.29 no.11
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• pp.785-794
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• 2002

Automatic stock trading systems should be able to solve various kinds of optimization problems such as market trend prediction, stock selection, and trading strategies, in a unified framework. But most of the previous trading systems based on supervised learning have a limit in the ultimate performance, because they are not mainly concerned in the integration of those subproblems. This paper proposes a stock trading system, called R-Trader, based on reinforcement teaming, regarding the process of stock price changes as Markov decision process (MDP). Reinforcement learning is suitable for Joint optimization of predictions and trading strategies. R-Trader adopts two popular reinforcement learning algorithms, temporal-difference (TD) and Q, for selecting stocks and optimizing other trading parameters respectively. Technical analysis is also adopted to devise the input features of the system and value functions are approximated by feedforward neural networks. Experimental results on the Korea stock market show that the proposed system outperforms the market average and also a simple trading system trained by supervised learning both in profit and risk management.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.4
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• pp.707-714
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• 2016

Active driving safety systems for vehicle, such as the front collision avoidance, lane departure warning, and lane change assistance, have been popular to be adopted to the compact car. For improving performance and competitive cost, FMCW radar has been researched to adopt a phased array or a multi-beam antenna, and to integrate the front and the side radar. In this paper we propose several efficient methods to implement the signal processing module of FMCW radar system using low cost DSP. The pulse width modulation (PWM) based analog conversion, the approximation of time-eating functions, and the adoption of vector-based computation, etc, are proposed and implemented. The implemented signal processing board shows the real-time performance of 1.4ms pulse repetition interval (PRI) with 1024pt-FFT. In real road we verify the radar performance under real-time constraints of 10Hz update time.

• 한국지구물리탐사학회:학술대회논문집
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• 2005.05a
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• pp.227-232
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• 2005

Least squares (${\ell}^2-norm$) solutions of seismic inversion tend to be very sensitive to data points with large errors. The ${\ell}^p-norm$ minimization for $1{\le}p<2$ gives more robust solutions, but usually with higher computational cost. Iteratively reweighted least squares (IRLS) gives efficient approximate solutions of these ${\ell}^p-norm$ problems. I propose a simple way to implement the IRLS method for a hybrid ${\ell}^1/{\ell}^2$ minimization problem that behaves as ${\ell}^2$ fit for small residual and ${\ell}^1$ fit for large residuals. Synthetic and a field-data examples demonstrates the improvement of the hybrid method over least squares when there are outliers in the data.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.11
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• pp.927-936
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• 2014

This paper presents development and verification of the progressive failure analysis upon the composite laminates. Strength and stiffness of the fiber-reinforced composite are analyzed by property degradation approach with emphasis on the material nonlinearity and continuum damage mechanics (CDM). Longitudinal and transverse tensile modes derived from Hashin's failure criterion are used to predict the thresholds for damage initiation and growth. The modified Newton-Raphson iterative procedure is implemented for determining nonlinear elastic and viscoelastic constitutive relations. Laminar properties of the composite are obtained by experiments. Prediction on the un-notched tensile (UNT) specimen is performed under the laminate level. Stress-strain curves and strength results are compared with the experimental measurement. It is concluded that the present nonlinear CDM approach is capable of predicting the strength and stiffness more accurately than the corresponding linear CDM one does.

• Spatial Information Research
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• v.8 no.1
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• pp.155-170
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• 2000

When we use R-Tree,a spatial index, to find objects matches some predicate, it often leads to an incorrect result of perform filtering step only with MBR. And , each candidates need to be inspected to conform if it really satisfies with given query, so called, 'refinement step'. In refinement step. we should perform disk I/O and expansive spatial operations which is the cause of increasing retrieval costs. Therefore, to minimize the number of candidate after filtering step, two-phase filtering methods were studied, but there was many problems such as inefficiency of filtering,maintenance of additional informations and reconstruction of data resulted from the loss of original information. So , in this paper, I propose an Extended R-Tree which provides ability to retrieve spatial objects only with some simple logical operations using Grid Table, truth table strong the information about the existence of spatial objects, in second filtering step. Consequently , this Extended R-Tree using Grid Filter has low cost of operation for filtering because of efficient second filtering step, and better filtering efficiency caused by high quality of approximation.