• 한국지능시스템학회논문지
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• 제16권4호
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• pp.466-471
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• 2006

패턴 인식 문제에서 중요한 전처리 과정 중 하나는 특정을 선택하거나 추출하는 부분이다. 특정을 추출하는 방법으로는 PCA가 보통 사용되고 특정을 선택하는 방법으로는 SFS 나 SBS 등의 방법들이 자주 사용되고 있다. 본 논문은 진화 연산 방법으로써 비선형 최적화 문제에서 유용하게 사용되어 지고 있는 유전자 알고리즘을 특정 선택에 적용하는 유전자 알고리즘 특정 선택 (Genetic Algorithm Feature Selection: GAFS)방법을 개발하여 다른 특징 선택 알고리즘과의 비교를 통해 본 알고리즘의 성능을 관찰한다.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2004년도 학술발표논문집
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• pp.195-198
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• 2004

One Important problem in a cancer microarray study is to identify a set of genes from which a molecular prognostic indicator can be developed. In parallel with this problem is to validate the chosen set of genes. We develop in this note a K-fold cross validation procedure by combining a 'pre-validation' technique and a bootstrap resampling procedure in the Cox regression . The pre-validation technique predicts the microarray predictor of a case without having seen the true class level of the case. It was suggested by Tibshirani and Efron (2002) to avoid the possible over-fitting in the regression in which a microarray based predictor is employed. The bootstrap resampling procedure for the Cox regression was proposed by Sauerbrei and Schumacher (1992) as a means of overcoming the instability of a stepwise selection procedure. We apply this K-fold cross validation to the microarray data of 92 gastric cancers of which the experiment was conducted at Cancer Metastasis Research Center, Yonsei University. We also share some of our experience on the 'false positive' result due to the information leak.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권4호
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• pp.1611-1629
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• 2016

Recently, deploying WiFi access points (APs) for facilitating indoor localization has attracted increasing attention. However, most existing mechanisms in this aspect are typically simulation based and further they did not consider how to jointly utilize pre-existing APs in target environment and newly deployed APs for achieving high localization performance. In this paper, we propose a measurement-based AP deployment mechanism (MAPD) for placing APs in target indoor environment for assisting fingerprint based indoor localization. In the mechanism design, MAPD takes full consideration of pre-existing APs to assist the selection of good candidate positions for deploying new APs. For this purpose, we first choose a number of candidate positions with low location accuracy on a radio map calibrated using the pre-existing APs and then use over-deployment and on-site measurement to determine the actual positions for AP deployment. MAPD uses minimal mean location error and progressive greedy search for actual AP position selection. Experimental results demonstrate that MAPD can largely reduce the localization error as compared with existing work.

• Journal of the Korean Statistical Society
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• 제21권2호
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• pp.93-110
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• 1992

A model selection approach is used to find out whether the mean and the variance of a unique sample are different from the pre-specified values. Normal distribution is selected as an approximating model. Kullback-Leibler discrepancy comes out as a natural measure of discrepancy between the operating model and the approximating model. Several estimates of selection criterion are computed including AIC, TIC, and a coupleof bootstrap estimator of the selection criterion are considered according to the way of resampling. It is shown that a closed form expression is available for the parametric bootstrap estimated cirterion. A Monte Carlo study is provided to give a formal comparison when the operating family itself is normally distributed.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1999년도 추계학술대회 논문집 - 한국공작기계학회
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• pp.345-350
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• 1999

The effectiveness of software error compensation for thermally induced machine tool errors relies on the prediction accuracy of the pre-established thermal error models. The selection of optimal sensor locations is the most important in establishing these empirical models. In this paper, a methodology for the selection of optimal sensor locations is proposed to establish a robust linear model which is not subjected to collinearity. Correlation coefficient and time delay are used as thermal parameters for optimal sensor location. Firstly, thermal deformation and temperatures are measured with machine tools being excited by sinusoidal heat input. And then, after correlation coefficient and time delays are calculated from the measured data, the optimal sensor location is selected through hard c-means clustering and sequential selection method. The validity of the proposed methodology is verified through the estimation of thermal expansion along Z-axis by spindle rotation.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 A
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• pp.22-24
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• 2001

This paper presents a fault phase selection algorithm for transmission line protection by means of the symmetrical components. Accurate fault phase selection is necessary for collect functioning of transmission line relaying, particularly in Extra High Voltage (EHV) networks. The conventional phase selection algorithm used the phase difference between positive and negative sequence current excluding load current. But, it is difficult to abstract only fault current since we can not know the time which a fault occurs. The proposed algorithm can select the accurately fault phase using fault current contained pre-fault current.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2021년도 춘계학술발표대회
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• pp.323-325
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• 2021

In this article, we have improved the prediction of hypertension detection using the feature selection method for the Korean national health data named by the KNHANES database. The study identified a variety of risk factors associated with chronic hypertension. The paper is divided into two modules. The first of these is a data pre-processing step that uses a factor analysis (FA) based feature selection method from the dataset. The next module applies a predictive analysis step to detect and predict hypertension risk prediction. In this study, we compare the mean standard error (MSE), F1-score, and area under the ROC curve (AUC) for each classification model. The test results show that the proposed FIFA-OE-NB algorithm has an MSE, F1-score, and AUC outcomes 0.259, 0.460, and 64.70%, respectively. These results demonstrate that the proposed FIFA-OE method outperforms other models for hypertension risk predictions.

• 상하수도학회지
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• 제22권4호
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• pp.445-448
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• 2008

The application of the membrane filtration process has been increased for the drinking water treatment system because of excellent quality of treated water compared with the sand filtration process. The selection of suitable pre-treatment processes and optimum flux according to the characteristics of raw water are important factors for the design of membrane processes. In this study, the most efficient pre-treatment processes for drinking water was selected by investigating the effects of pre-treatment processes on the operational stability of the membrane filtration process. Both lab-scale and pilot-scale experiments were conducted. In the lab-scale test, the effect of pre-treatment processes on the stability of the membrane filtration process was investigated indirectly by comparing the performance of membrane flux for raw water, pre-treated water, and membrane permeated water. In the pilot-scale test, the usefulness of prefiltration processes was assessed by comparing the performance of single membrane process and hybrid coagulation-membrane process. The results indicated that the coagulation process contributed to the stabilization of trans-membrane pressure (TMP) by removing contaminants on membranes, though the pre-filtration process had little effect on the TMP.

• Asian-Australasian Journal of Animal Sciences
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• 제14권7호
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• pp.905-909
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• 2001

Three groups of wethers viz. Jamunapari ♂$\times$Black Bengal ♀ (JBB), Selected Black Bengal ♂$\times$Selected Black Bengal ♀ (SBB) and Random Black Bengal ♂$\times$Random Black Bengal ♀ (RBB) of 1 year old were evaluated for pre-slaughter traits and carcass characteristics. The correlations between pre-slaughter traits and carcass traits were computed. It was found that the preslaughter weights of JBB and SBB were almost similar in yielding hot and chilled carcass as well as dressing percentage (DP). RBB wethers were lighter (p<0.05) than JBB and SBB in pre- and post-slaughter weights and also inferior (p<0.05) in DP. SBB wethers were found to produce more visceral fat compared to JBB and RBB. Other variety meats appeared erratic in yield.l. Correlations were compared by Z statistic among three genetic groups and the value of Z did not differ (p>0.05) between groups.

• 센서학회지
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• 제23권4호
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• pp.251-258
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• 2014

While the feasibility of vertical velocity as a threshold parameter for pre-impact fall detection has been verified, effects of sensor attachment locations and methods calculating vertical acceleration and velocity on the detection performance have not been studied yet. Regarding the vertical velocity-based pre-impact fall detection, this paper investigates detection accuracies of eight different cases depending on sensor locations (waist vs. sternum), vertical accelerations (accurate acceleration based on both accelerometer and gyroscope vs. approximated acceleration based on only accelerometer), and vertical velocities (velocity with attenuation vs. velocity difference). Test results show that the selection of waist-attached sensor, accurate acceleration, and velocity with attenuation based on accelerometer and gyroscope signals is the best in overall in terms of sensitivity and specificity of the detection as well as lead time.