• Journal of Advanced Marine Engineering and Technology
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• 제36권2호
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• pp.302-308
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• 2012

해상통신의 제약을 극복하는 해상통신망 모델로 자율망 모델이 있다. 육상 데이터통신망의 다양성과 혼재성을 활용하여 해상통신망에 더 강한 연결성과 확장성을 부여하려는 연구의 일환으로 이 논문에서는 해상자율망 모델에서 다양한 해육상의 캐리어를 활용하는 경로배정방식을 새롭게 제안한다. 이것은, 기존의 최소 홉 수가 아니라 목적선박과의 거리에 의거하여 캐리어별 최적경로를 탐색하고 그 가운데 응용과 캐리어의 전송특성과 거리의 정규값을 고려하여 최적 캐리어의 경로를 최종적으로 선택하는(NLTCR) 방식이다. 기존의 최다승방식(MWR)과 단순 전송특성 정규값에 의한 방식(NTCR)과 성능을 비교하였다.

• Journal of the Korean Data and Information Science Society
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• 제17권1호
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• pp.41-52
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• 2006

Because most common assumption is normality in statistical analysis, testing normality is very important. The Q-Q plot is a powerful tool to test normality with full samples in statistical package. But the plot can't test normality in type-II censored samples. This paper proposed the modified the Q-Q plot and the modified normalized sample Lorenz curve(NSLC) for normality test in the type-II censored samples. Using the two Hodgkin's disease data sets and the type-II censored samples, we picture the modified Q-Q plot and the modified normalized sample Lorenz curve.

• Journal of the Korean Data and Information Science Society
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• 제19권4호
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• pp.1441-1448
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• 2008

We propose the modified quantile-quantile (Q-Q) plot using the approximate maximum likelihood estimators and the modified normalized sample Lorenz curve (NSLC) plot for the extreme value distribution based on multiply Type-II censored samples. Using two example data sets, we picture the modified Q-Q plot and the modified NSLC plot.

• Communications for Statistical Applications and Methods
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• 제8권1호
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• pp.185-192
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• 2001

Using the Lorenz curve that is proved to be a powerful tool to measure the income inequality within a population of income receivers, we propose the normalized sample Lorenz curve for the goodness-of-fit test that is very important test in statistical analysis. For two hodgkin's disease data sets, we compare the Q-Q plot and the proposed normalized sample Lorenz curve.

• 한국측량학회지
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• 제22권3호
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• pp.261-268
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• 2004

위성영상자료를 통해 각 파장대별로 기록된 지표면에 대한 반사특성정보로 정규산화율지수(NBR)나 정규식생지수(NDVI)를 구하여 산림에 대한 분석을 할 수 있다. 따라서 본 연구에서는 산불이 발생한 강릉시 사천면 지역을 중심으로 산불 발생이전 산림이 온전하였던 시기의 영상과 산불 발생 직 후, 발생 1년 후 그리고 2년 후의 영상으로 정규산화율지수와 정규식생지수를 각각 구하여 이 지수를 비교 분석함으로써 정규산화율지수의 효용성을 강조하였다. 그 결과 NBR영상간 차이가 NDVI영상간 차이보다 큰 범위의 동적변화를 보이고 있으므로 산불 피해강도나 식생회복상태 분석 시 NBR영상을 사용하는 것이 좋을 것으로 판단되며, 산불피해 지역에서도 NBR 영상이 NDVI영상보다 산림피해강도나 회복상태를 더욱 뚜렷하게 보여주고 있다.

• Journal of the Korean Data and Information Science Society
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• 제14권3호
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• pp.653-660
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• 2003

In this paper, we prove that the transformed sample Lorenz curve, normalized sample Lorenz curve, and the test statistics for testing of normality based on the normalized sample Lorenz curve and the modified Lorenz curve which were introduced by Kang and Cho (2001a, 2002) are location and scale invariant statistics.

• 한국초지조사료학회지
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• 제40권4호
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• pp.196-202
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• 2020

본 연구는 동계사료작물의 무인기기반 생육모니터링을 위하여 호밀, 총체보리, IRG를 대상으로 다중분광영상으로 건물수량을 예측하기 위한 최적식생지수를 테스트하였다. 2019년 2월부터 4월까지 나주의 실경작지에서 무인기 다중분광카메라로 분광영상을 수집하여 4종류의 식생지수(Normalized Difference Vegetation Index; NDVI, Green Normalized Difference Vegetation Index; GNDVI, Normalized Green Red Difference Index; NGRDI and Normalized Difference Red Edge Index; NDREI)를 산출하고 지상에서 건물수량을 조사하여 식생지수와 건물수량의 상관관계를 조사하였다. 호밀, 총체보리, IRG에 대하여 건물수량과 NDVI의 상관관계(R2)는 0.91~0.92, GNDVI는 0.92~0.94, NGRDI는 0.71~0.85, NDREI는 0.84~0.91로 GNDVI가 가장 효과적이었다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2006년도 하계종합학술대회
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• pp.455-456
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• 2006

This paper presents an automatic pose-normalized 3D face data acquisition method using 2D and 3D information. We propose an automatic pose-normalized 3D face acquisition method that accomplishes 3D face modeling and 3D face pose-normalization at once. The proposed method uses 2D information with AAM (Active Appearance Model) and 3D information with 3D normal vector. The 3D face modeling system consists of 2 cameras and 1 projector. In order to verify proposed pose-normalized 3D modeling method, we made an experiment for 2.5D face recognition. The experimental result shows that proposed method is robust against pose variation.

• 한국군사과학기술학회지
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• 제20권4호
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• pp.474-481
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• 2017

This paper presents a multiple target tracking system using Normalized Rayleigh likelihood of amplitude information of target. Although many studies of Radar systems using amplitude information have been studied, they are focused on single target tracking. This paper proposes the multiple target tracking using amplitude information as well as kinematic information from Radar sensor. The amplitude information are applied in generating the association probability of joint probabilistic data association(JPDA) algorithm through the normalized Rayleigh likelihood. It is verified that the proposed system can enhance the track maintenance and tracking accuracy, especially, in the target crossing case.

• Structural Engineering and Mechanics
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• 제70권2호
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• pp.209-219
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• 2019

By normalizing the internal hysteresis variable and eliminating the redundant parameter, the normalized Bouc-Wen model is considered to be an improved and more reasonable form of the Bouc-Wen model. In order to facilitate application and further research of the normalized Bouc-Wen model, some key aspects of the model need to be uncovered. In this paper, hysteresis characterization of the normalized Bouc-Wen model is first studied with respect to the model parameters, which reveals the influence of each model parameter to the shape of the hysteresis loops. The parameter identification scheme is then proposed based on an improved genetic algorithm (IGA), and verified by experimental test data. It is proved that the proposed method can be an efficacious tool for identification of the model parameters by matching the reconstructed hysteresis loops with the target hysteresis loops. Meanwhile, the IGA is shown to outperform the standard GA. Finally, a simplified identification method is proposed based on parameter sensitivity, which indicates that the efficiency of the identification process can be greatly enhanced while maintaining comparable accuracy if the low-sensitivity parameters are reasonably restricted to narrower ranges.