• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1338-1340
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• 1987

This paper describes the design of ECG data preprocess module for the ECG signals. This module process the data obtained from two channels. It is composed of the AID converter, QRS detector, one chip micro-computer and memory. This module performs the following functions;digital filtering, R wave detection and determination of reference point for the ST segment. The measured points are transfered to the next data module by the interrupt process. This preprocessor data module is available to the basis for the parallel data processing for the real time automatic diagnosis.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11c
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• pp.560-568
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• 2000

The aims of this research were to investigate the preprocessing effect of spectrum data on prediction performance and to develop a robust model to predict SSC in intact apple. Spectrum data of 320 Fuji apples were measured with the on-line transmittance measurement system at the wavelength range of 550∼1100nm. Preprocess methods adopted for the tests were Savitzky Golay, MSC, SNV, first derivative and OSC. Several combinations of those methods were applied to the raw spectrum data set to investigate the relative effect of each method on the performance of the calibration model. PLS method was used to regress the preprocessed data set and the SSCs of samples, and the cross-validation was to select the optimal number of PLS factors. Smoothing and scattering corection were essential in increasing the prediction performance of PLS regression model and the OSC contributed to reduction of the number of PLS factors. The first derivative resulted in unfavorable effect on the prediction performance. MSC and SNV showed similar effect. A robust calibration model could be developed by the preprocessing combination of Savitzky Golay smoothing, MSC and OSC, which resulted in SEP= 0.507, bias=0.032 and R$^2$=0.8823.

• International Journal of Precision Engineering and Manufacturing
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• v.5 no.3
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• pp.11-18
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• 2004

In this paper, the classification of artificial defects in semiconductor packages is studied by using pattern recognition technology. For this purpose, the pattern recognition algorithm includes the user made MATLAB code. And preprocess is made of the image process and self-organizing map, which is the input of the back-propagation neural network and the dimensionality reduction method, The image process steps are data acquisition, equalization, binary and edge detection. Image process and self-organizing map are compared to the preprocess method. Also the pattern recognition technology is applied to classify two kinds of defects in semiconductor packages: cracks and delaminations.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1995.10a
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• pp.215-222
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• 1995

The objective of this paper is to develop a finite element structural analysis program using VB(Visual Basic) which has been recently getting popular as development tools of application program for Windows. VB provides several functions to develop an application program easily by supporting event-driven programming method and graphic object as control data type. This system is an integrated processor including preprocessor, solver and postprocessor. Automatic mesh generation is available at preprocess stage, and graphic presentation of deformation and stress is also represented at postprocess one.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.336-339
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• 2008

우리가 사용하는 데이터베이스 내에는 많은 양의 데이터 들이 들어 있으며, 계속적으로 그 양은 늘어나고 있다. 이러한 데이터들로부터 질의를 통해 얻을 수 있는 기본적이고 단순한 정보들과 달리 고급 정보를 얻게 해주는 방법이 데이터 마이닝이다. 데이터 마이닝의 기법 중에서 본 논문에서는 k-means 알고리즘을 사용하여 트랜잭션을 클러스터링 함으로써 데이터베이스의 트랜잭션 수를 줄여 연관규칙의 대표적인 알고리즘인 Apriori 알고리즘의 단점인 트랜잭션 스캔으로 인한 성능 저하를 개선하고자 한다.

• Journal of the Korean Data and Information Science Society
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• v.18 no.4
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• pp.1005-1021
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• 2007

Traditional procedures for DNA microarray data analysis are to preprocess and normalize the gene expression data, and then to analyze the normalized data using statistical tests. Drawbacks of the traditional methods are: genuine biological signal may be unwillingly eliminated together with artifacts, the limited number of arrays per gene make statistical tests difficult to use the normality assumption or nonparametric method, and genes are tested independently without consideration of interrelationships among genes. A novel method using average rank in each array is proposed to eliminate such drawbacks. This average rank method monitors differentially regulated genes among genetically different groups and the selected genes are somewhat different from those selected by traditional P-value method. Addition of genes selected by the average rank method to the traditional method will provide better understanding of genetic differences of groups.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.426-429
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• 2001

Many various products are manufactured which have sculptured surfaces recently. Constructing surface of these models is required technique called reverse engineering. In reverse engineering, a product which has sculptured surfaces is measured and we create surface model to acquire complete model data of object. Measured point data needs preprocess and sampling. Next a set of point data in a plane fit section curve. At last, surface is generated by fitting to section curves. Here we uses sweep surface. Sweep surface is compatible fitting CAD model to drawing. This paper discusses converting approximation of NURBS surface as a standard surface.

• Journal of Information Technology Applications and Management
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• v.24 no.4
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• pp.187-196
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• 2017

It is urgent to prepare countermeasures for traffic congestion problems of Korea's metropolitan area where central functions such as economic, social, cultural, and education are excessively concentrated. Most users of public transportation in metropolitan areas including Seoul use the traffic cards. If various information is extracted from traffic big data produced by the traffic cards, they can provide basic data for transport policies, land usages, or facility plans. Therefore, in this study, we extract valuable information such as the subway passengers' frequent travel patterns from the big traffic data provided by the Seoul Metropolitan Government Big Data Campus. For this, we use a Hadoop (High-Availability Distributed Object-Oriented Platform) to preprocess the big data and store it into a Mongo database in order to analyze it by a sequential pattern data mining technique. Since we analysis the actual big data, that is, the traffic cards' data provided by the Seoul Metropolitan Government Big Data Campus, the analyzed results can be used as an important referenced data when the Seoul government makes a plan about the metropolitan traffic policies.

• Proceedings of the KSPS conference
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• 2006.05a
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• pp.41-44
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• 2006

The purpose of state tying is to reduce the number of models and to use relatively reliable output probability distributions. There are two approaches: one is top down clustering and the other is bottom up clustering. For seen data, the performance of bottom up approach is better than that of top down approach. In this paper, we propose a new clustering technique that can enhance the undertrained triphone clustering performance. The basic idea is to tie unreliable triphones before clustering. An unreliable triphone is the one that appears in the training data too infrequently to train the model accurately. We propose to use monophone distance to preprocess these unreliable triphones. It has been shown in a pilot experiment that the proposed method reduces the error rate significantly.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.317-319
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• 2008

Traditionally, it is measured by using basin or empirical formula with meteorology data, while it does not represent the evaportransporation over a regional area. With the advent of improved remote sensing technology, it becomes feasible to assess the ET over a regional scale. Firstly, the IMAGINE ATCOR atmospheric module is used to preprocess for the MODIS imagery. Then MODIS satellite images which have been corrected by radiation and geometry in conjunction with the in-situ surface meteorological measurement are used to estimate the surface heat fluxes such as soil heat flux, sensible heat flux, and latent heat flux. In addition, the correlation coefficient between the derived latent heat and the in-situ measurement is found to be over 0.76. In the future, we will continue to monitor the surface heat fluxes of paddy rice field in Chiayi area.