• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1997.11a
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• pp.75-78
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• 1997

본 논문에서는 여러 개의 클래스가 정의되어 있을 경우에 피춰(feature)추출을 최적화 하는 방법을 제안한다. 제안된 알고리즘은 피춰를 하나씩 추출하며 그 과정마다 각 클래스의 가중치를 조정하여 최적의 해를 얻는 방법을 사용한다. 처음에는 각 클래스에 동일한 가중치를 주어 criterion function을 구하고 이로부터 첫 번째 피춰를 얻는다. 이 피춰에 의한 오류와 전체 피춰를 사용하였을 경우의 오류의 차이가 가장 큰 클래스에 더 많은 가중치를 주어 새로운 criterion function을 구하여 두 번째 피춰를 얻는다. 이 과정에서 오류는 Bhattacharyya distance에 의해 예측한다.

• Journal of the Korea Society of Computer and Information
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• v.14 no.7
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• pp.9-15
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• 2009

The fuzzy weighted mean classifier is one of the most common classification models and could achieve high performance by adjusting the weights. However, the weights were generally decided based on the experience of experts, which made the resulting classifiers to suffer the lack of consistency and objectivity. To resolve this problem, in this paper, a weight deciding method based on the statistics of the data is introduced, which ensures the learned classifiers to be consistent and objective. To investigate the effectiveness of the proposed methods, Iris data set available from UCI machine learning repository is used and promising results are obtained.

• The Korean Journal of Applied Statistics
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• v.36 no.5
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• pp.381-397
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• 2023

The most representative design used in clinical trials is randomization, which is used to accurately estimate the treatment effect. However, comparison between the treatment group and the control group in an observational study without randomization is biased due to various unadjusted differences, such as characteristics between patients. Propensity score weighting is a widely used method to address these problems and to minimize bias by adjusting those confounding and assess treatment effects. Inverse probability weighting, the most popular method, assigns weights that are proportional to the inverse of the conditional probability of receiving a specific treatment assignment, given observed covariates. However, this method is often suffered by extreme propensity scores, resulting in biased estimates and excessive variance. Several alternative methods including trimming, overlap weights, and matching weights have been proposed to mitigate these issues. In this paper, we conduct a simulation study to compare performance of various propensity score weighting methods under diverse situation, such as limited overlap, misspecified propensity score, and treatment contrary to prediction. From the simulation results overlap weights and matching weights consistently outperform inverse probability weighting and trimming in terms of bias, root mean squared error and coverage probability.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04a
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• pp.679-681
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• 2002

본 논문에서는 화질 향상을 위한 콘트라스트 조정 기법을 제안한다. 제안한 방식은 기존의 알고리즘을 단순화하여서 실시간 처리가 가능하며 콘트라스트의 범위를 조정하는 가중치를 두었다. 연산을 함에 있어 기준이 되는 값을 선언하여 콘트라스트의 효율적인 조정과 오차율을 줄였다. 제안한 방식에 의한 처리 결과와 원 영상의 화질 평가를 위해 시각적 검증과 히스토그램의 표준 편차를 도입 하였다.

• Proceedings of the Korea Contents Association Conference
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• 2005.05a
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• pp.406-409
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• 2005

This paper is related with a standard for verification of program completion when there are complaints for software development. Therefore, in this paper, we propose weight setting method and a method to accommodate relative importance for each function in program.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10b
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• pp.658-660
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• 2003

본 논문에서는 AMBA 기반의 FPD 시스템에 적용 가능한 콘트라스트 컨트롤러를 설계 및 구현하였다. 제안한 콘트라스트 컨트롤러 내부에는 AMBA의 인터페이스 spec을 준수한 AMBA AHB 컨트롤러와 콘트라스트조정 블록, 메모리 컨트롤러. FPD 컨트롤러가 내장되어있다. 구현한 알고리즘은 실시간 처리가 가능하며 콘트라스트의 범위를 조정하는 가중치를 가진 알고리즘으로 기준되는 값을 이용하여 콘트라스트의 효율적인 조정이 가능하다. 콘트라스트 컨트롤러는 VHDL로 설계하였으며 FPGA를 이용한 H/W를 구현하여 TFT-LCD panel에 디스플레이 하여 검증하였다.

• Journal of Navigation and Port Research
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• v.29 no.1 s.97
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• pp.59-64
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• 2005

MDMG(Multiple Decision-Making Group) problems comprise those of UDMG(Unit Decision-Making Group) which contradict each other. For the evaluation problem of port competitiveness, it has the complicated evaluation characteristics of multi-strata-complex and multi-attributes. Especially, it becomes typical MDMG problems in the evaluation which a great number of decision makers such as shipping companies, freight forwarders, logistics companies and researchers participate in This evaluation of complex problems needs the compensated process of weight which rationally unites heterogeneous preferences of each of groups. In this respect, the purpose of this study is to remove the uncertainty of the UDMG using the theory of DS (Dempster-Shafer) and present the integrated weight through the level process.

• Journal of Environmental Impact Assessment
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• v.26 no.3
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• pp.171-180
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• 2017

The vulnerability analysis of climate change driven disaster has been used as institutional framework for the urban policies of disaster prevention since 2012. However, some problems have occurred due to the structure of vulnerability analysis, such as overweighted variables and duplicated application of variables of similar meaning. The goal of this study is to examine the differences of results between the method of current guideline and the method of weight equalization. For this, we examines the current structural framework of the vulnerability analysis, and performs empirical analysis. As a result, the extent and magnitude of vulnerability showed different spatial patterns depending on the weighting methods. Standardized weighting method relatively represented wider vulnerable areas compared to the pre-existing method which follows the current instruction manual. To apply the results of vulnerability analysis to urban planning process for disaster prevention, this study suggests that the reliability of the results should be ensured by improving analytical framework and detailed review of the results.

• Journal of Broadcast Engineering
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• v.18 no.4
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• pp.550-558
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• 2013

The infrared and visible images are represented by different information due to the different wavelength of the light. The infrared image has thermal information and the visible image has texture information. Desirable results are obtained by fusing infrared and visible information. To enhance a visible image, we extract a weight map from a visible image using saturation, brightness. After that, the weight map is adjusted using thermal information in the infrared image. Finally, an enhanced image is resulted from combining an infrared image and a visible image. Our experiment results show that our proposed algorithm is working well to enhance the smoke in the original image.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4D
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• pp.549-551
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• 2006

Vehicle License Plate Recognition System reads information from vehicles license plate using image detection devices. Of many applications provided by Vehicle License Plate Recognition System, some, such as speed enforcing system, can be problematic when the system incorrectly scans letters or numbers from a vehicle's license plate. Using Cautious Classifier avoids such problems by discarding the scanned information when the confidence level is doubted to be low. This study develops the License Plate Recognition System using Cautious Classifier and investigates effectiveness of applying the Weighted Instance Method to improve the performance of Cautious Classifier.