• 대한인간공학회지
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• 제29권2호
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• pp.217-224
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• 2010

Research has been conducted to examine the effects of mechanical and sound characteristics of fabrics on affective quality. The present study developed the Affective Quality Evaluation and Estimation System for Textiles (AQEEST) with distinguished features that can be effectively used in the affective research of fabric frictional sound. The AQEEST consists of three subsystems (affective quality evaluation, affective quality estimation, and audible distance estimation subsystems) and each subsystem consists of three to four modules (e.g., evaluation condition setup, evaluation experimentation, and textile database management modules) depending on its functional requirements. The affective quality evaluation subsystem was designed to help administer an experiment in a systematic manner and present acoustic and visual stimuli simultaneously in various gait conditions (walking, jogging, and running) to mimic a more realistic situation of textile frictional sound production. Next, the affective quality estimation subsystem was designed to estimate the sound characteristics, affective qualities, overall psychological satisfaction, and reference cluster of a textile using its mechanical and/or sound characteristic information. Lastly, the audible distance estimation subsystem was designed to estimate the just noticeable sound pressure levels and audible distances of a textile for various gait conditions using its mechanical characteristic information. The AQEEST can be upgraded by accommodating more affective quality study results for various textiles.

• 한국ITS학회 논문지
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• 제10권1호
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• pp.67-75
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• 2011

본 논문은 기존의 단일값(점추정)으로 제시하던 검지기 성능평가 결과를 통계적 신뢰구간(구간추정)으로 제시하기 위한 검지기 성능평가 방안을 제시했다. 일반적으로 구간추정은 점추정에 비해 표본 통계의 더 많은 정보를 제공하기 때문에 기존 단일값으로 제시해 오던 검지기 성능평가 결과의 신뢰성을 향상시킬 수 있다. 방법론은 크게 표본 추출, 평가척도 분석, 평가결과 제시의 세 부분으로 나누어진다. 표본추출 방법에는 다양한 통계적 표본 추출 방법이 있지만 교통, 조도, 기상조건에 따라 변화하는 차량검지기 성능의 특성상 층화추출법이 통계적 신뢰구간 제시를 위한 가장 적합한 방법론으로 간주되었다. 또한 기존에 널리 사용된 검지기 성능평가 척도들의 특징을 면밀히 분석하여 평가자로 하여금 해당 검지자료에 적합한 평가척도를 선택할 수 있는 프로세스를 정립하였다. 마지막으로 평가기간 전체(예. 30분)와 개별분석 단위(예. 1분) 평가결과의 통계적 신뢰구간을 반영하기 위한 방법론을 제시했다. 본 연구는 기존 검지기 성능평가 결과의 단일값 제시로 인해 불가능 했던 신뢰구간 제시를 가능하게 함에 따라 검지기 성능평가 결과의 신뢰성을 향상시킬 수 있을 것으로 판단된다.

• 한국정보과학회논문지:소프트웨어및응용
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• 제37권2호
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• pp.95-103
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• 2010

소프트웨어 제품의 시장 경쟁력을 향상시키기 위해서는 이해관계자의 요구사항에 부합하는 품질을 제공하는 동시에 개발 예산 내에 개발 가능한 아키텍처를 획득할 수 있는 방안이 요구된다. 하지만 아키텍처의 품질 검토 및 선정을 위해 사용되는 기존 아키텍처 평가 기법은 아키텍처 설계를 통해 획득 가능한 품질속성에만 초점을 맞추고 있어 아키텍처가 개발 비용에 미치는 영향을 체계적으로 고려하지 않는다. 본 논문에서는 소프트웨어 비용 추정 모델인 COCOMO II를 적용한 아키텍처 비용 추정 기법을 제안하여 기존 아키텍처 평가와 병행 가능한 비용 분석을 통해 기존 아키텍처 평가 기법을 보완하며 품질과 비용이 함께 고려된 아키텍처 선정을 지원한다. 제안 기법의 정확성 검증을 위해 본 논문의 기법을 RPS (Robot Patrol System)의 아키텍처 후보 목록에 적용한 뒤 비용 추정 결과를 각 아키텍처 후보의 실측 공수와 비교하였다.

• 한국경영과학회지
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• 제32권2호
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• pp.163-175
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• 2007

[ $ulcorner$ ]Cost-Effectiveness Analysis$\lrcorner$ has been wifely used to evaluate economic efficiency of R&D projects, but most of cost-effectiveness evaluation systems have some problems such as systematic method for setting and evaluating cost factors, estimation of single effect on each R&D project, and estimation of cross effects among R&D projects. To solve these problems, we have designed a new evaluation indicator called a $ulcorner$Cost-Cross Effect Integration Indicator$lrcorner$ including cross effects developed in this research. The major research findings are summarized as follows : (1) $ulcorner$Coist Estimation Model$lrcorner$, which estimates the cost factors divided into two classes of assembly product and system product and then integrates the total cost values, has been designed. (2) A new method for estimating parameters of cross effects among R&D projects has been developed. (3) $ulcorner$Cross Effects Estimation Model$lrcorner$ to estimate multi-effects and cross effects by completion time among several projects has been designed. (4) $ulcorner$Integration Estimation Indicator$lrcorner$ for setting priority on a project group has been extracted by combination of total cost value and total effect value.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2000년도 춘계학술대회논문집
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• pp.1710-1715
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• 2000

Estimation of damping ratio for vibration signals measured on the passenger car's seat is useful for the objective evaluation of impact harshness in car. The vibration signal is a transient signal represented by many coupled modes of suspension system. Wavelet transform automatically decouples these modes in the time-frequency domain. Damping ratios for decoupled modes are obtained by logarithmic treatment for the Wavelet transformed signal. The objective evaluation using Wavelet transform has been well corresponded with subjective evaluation done by skilled engineers.

• 한국산학기술학회논문지
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• 제11권7호
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• pp.2420-2435
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• 2010

본 논문은 웹사이트 평가 개선을 위하여 웹사이트 유형 및 사용자 이용 목적을 고려한 평가 프레임워크를 제시하였다. 또한 이를 이용하여 기존 웹사이트를 분석 평가하였다. 평가 프레임워크내의 각 평가요소간 상대적인 중요도를 일반사용자 및 업체사용자로 구분하여 분석하였으며, AHP 방법을 적용하여 웹사이트 평가모형으로서의 신뢰성을 확보하고 웹사이트 구축, 운영, 관리시 중요 고려요인을 제시하였다. 본 연구를 통하여 웹사이트 평가 분야 연구자들에게는 사이트 유형별 평가 영역간 가중치 산정의 필요성을 제시하고, 웹사이트 기획 및 운영자들에게는 사용자 유형(개인, 업체 등)에 따른 차별화된 컨텐츠 제공이 필수적임을 제시하여 좀 더 효율적이고 전략적인 서비스 제공을 할 수 있는 가이드라인을 제시하였다.

• 한국공작기계학회논문집
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• 제14권3호
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• pp.38-46
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• 2005

The destructive method is reliable and widely used for the estimation of material degradation but it have time-consuming and a great difficulty in preparing specimens from in-service industrial facilities. Therefore, the estimation of degraded structural materials used at high temperature by nondestructive evaluation such as electric resistance method, replica method, Barkhausen noise method, electro-chemical method and ultrasonic method are strongly desired. In this study, various nondestructive evaluation(NDE) parameters of the Barkhausen noise method, such as MPA(Maximum Peak Amplitude), RMS, IABNS(Internal Area of Barkhausen Noise on Signal) and average amplitude of frequency spectrum are investigated and correlated with thermal damage level of 2.25cr-1.0Mo steel using wavelet analysis. Those parameters tend to increase while thermal degradation proceeds. It also turns out that the wavelet technique can help to reduce experimental false call in data analysis.

• 대한안전경영과학회지
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• 제5권1호
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• pp.13-31
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• 2003

This provided a basic frame to analyze the investment effect on the road, railroad, airport and port as a national dimension but it still has a limitation to analyze the specific economic and financial validities to consider the characteristics of the traffic facilities within the area. Conclusively, the aims of this study provide the reasonable evaluation guidelines effectively to the local automatic groups, especially Chungju in the frame of the present evaluation guidelines. We provide the adaptive alternatives on the present systems which are difficult to adapt to the present investment evaluation guidelines; the estimation method of the social economic index and the estimation method of the traffic demand. Additionally, we discuss the research method of the passage actual state for a reasonable estimation of the traffic demand. The result of this study will be activated for the validity check and construction plan of the reasonable traffic investment plan of Chungju city.

• 한국통신학회논문지
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• 제22권5호
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• pp.881-888
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• 1997

The existing method s for curvature estimation have a common problem in determining a unique smoothong factor. we previously proposed two approaches to overcome that problem: a constrained regularization approach and a mean field annealing approach. We consistently detected corners from the perprocessed smooth boundary obtained by either the constrained eglarization approach or the mean field annealing approach. Moreover, we defined corner sharpness to increase the robustness of both approaches. We evaluate the performance of those methods proposed in this paper. In addition, we show some matching results using a two-dimensional Hopfield neural network in the presence of occlusion as a demonstration of the power of our proposed methods.

• 전력전자학회논문지
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• 제27권4호
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• pp.332-338
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• 2022

This study proposes a battery state-of-health estimation method by applying a feature extraction technique. The technique that can improve estimation performance is the process of identifying and extracting meaningful data. To apply a data-driven-based aging state estimation method to batteries, health indicators are used as training data. However, limitations occur in extracting health indicators from charge/discharge cycles. This study proposes a deep-learning-based battery state-of-health estimation method that applies feature extraction techniques to compensate for this problem. According to the performance evaluation result of the proposed method, it has a low estimation error of 0.3887% based on an absolute error evaluation method.