• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 2000년도 THE THIRD INTERNATIONAL CONFERENCE ON AGRICULTURAL MACHINERY ENGINEERING. V.III
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• pp.569-577
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• 2000

The position of tobacco leaves is affluence to the quality. To evaluate its quality, sample leaves was collected according to the position of attachment. In Korea, the position was divided into four classes such as high, middle, low and inside positioned leaves. Until now, the grade of standard sample was determined by human expert from korea ginseng and tobacco company. Many research were done by the chemical and spectrum analysis using NIR and computer vision. The grade of tobacco leaves mainly classified into 5 grades according to the attached position and its chemical composition. In high and low positioned leaves shows a low level grade under grade 3. Generally, inside and medium positioned leaf has a high level grade. This is the basic research to develop a real time tobacco leaves grading system combined with portable NIR spectrum analysis system. However, this research just deals with position recognition and grading using the color machine vision. The RGB color information was converted to HSI image format and the sample was all investigated using the bundle of tobacco leaves. Quality grade and position recognition was performed through well known general error back propagation neural network. Finally, the relationship about attached leaf position and its grade was analyzed.

• 정보보호학회논문지
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• 제19권3호
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• pp.11-25
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• 2009

지문샘플의 품질은 지문인식 시스템에서 매칭 성능에 영향을 주는 중요한 요소이다. 지문인식 시스템에서 낮은 품질의 지문영상을 제거하면 인식 에러율이 현저하게 줄어드는 것을 알 수 있다. 본 논문에서는 minutiae 기반의 지문인식 알고리즘을 이용하여 단일 샘플 품질 측정방법에 대한 유효성을 평가하였다. 우선, minutiae 기반의 지문인식 알고리즘의 매칭성능에 영향을 주는 여러 가지 요소에 대하여 검증하고, 다음, 현재 흔히 사용하는 측정방법에 대해 연구하고, 그 중 효과적인 품질측정방법들을 선택하여 NIST, QualityCheck와 Verifinger 5.0을 이용하여 비교 분석 하였다. FVC 데이터베이스로 실험한 결과 단일 측정방법도 매칭성능을 효과적으로 향상함을 알 수 있었다.

• 한국콘텐츠학회논문지
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• 제11권2호
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• pp.79-87
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• 2011

현재 지문인식시스템 제품은 양적으로 빠른 성장세를 보이고 있으나 그 동안 질적인 품질을 고려하는 노력이 미흡한 것이 사실이었다. 따라서, 본 논문에서는 지식정보보안 제품의 질적인 면을 평가하여 품질 수준을 파악하여 개선방향을 도출함으로써 품질향상을 지원할 수 있는 평가모델을 개발하기 위해 지문인식시스템 제품의 국내외 시장현황과 기술적인 요소들을 분석하였다. 제품의 특성을 고려하여 보안성, 성능, 신뢰성 요구사항을 분석하여 기존 보안기능 중심의 평가에서는 다루지 못했던 비 기능 요소를 포괄적으로 적용할 수 있는 신뢰성 품질평가 모델을 구축하였다. 본 논문을 통해 지문인식 제품 특성과 동향을 반영하고 제품별 평가를 수행할 수 있는 신뢰성 평가모델을 구축함으로써 지식정보보안 제품의 전반적인 품질향상에 기여할 수 있을 것이다.

• 융합신호처리학회논문지
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• 제13권2호
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• pp.91-98
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• 2012

전압강하(sag), 전압상승(swell), 고조파(harmonics)와 충격과도(impulsive transients)와 같은 전력품질(PQ: Power Quality) 신호는 전력전자 장비와 마이크로프로세서 기반 전자장치 운전에 매우 중요한 문제점을 야기시킨다. 웨이블릿 기반 잡음제거 기법과 역전파 신경회로망을 사용하여 잡음 전력품질을 분석하고 인식하는 잡음 전력품질 인식 시스템의 유효성을 본 논문에서 조사하였다. 잡음 전력 인식 시스템에 적용된 알고리즘은 웨이블릿기반 디노이징과 역전파 신경회로망이고, 잡음 전력품질 인식 시스템의 실시간 성능을 검증하기 위하여 Simulink를 사용한 SIL(Software In the Loop)과 TMS320C6713DSK를 사용한 PIL(Processor In the Loop)을 통하여 우수한 인식률을 확인 할 수 있었다.

• 대한후두음성언어의학회지
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• 제15권2호
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• pp.92-97
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• 2004

Background and Objectives : The purpose of this study was to examine objectively pre and post operative voice quality evaluation and intelligibility of alaryngeal voice using speech recognition program, HUVOIS. Materials and Methods : 2 laryngologists and 1 speech pathologist were evaluated 'G', 'R', 'B' in the GRBAS sclae and speech intelligibility using NTID rating scale from standard paragraph. And also acoustic estimates such as jitter, shimmer, HNR were obtained from Lx Speech Studio. Results : Speech recognition rate was not significantly different between pre and post operation for pathological vocie samples though voice quality(G, B) and acoustic values(Jitter, HNR) were significantly improved after post operation. In Alaryngeal voices, reed type electrolarynx 'Moksori' was the highest both speech intelligibility and speech recognition rate, whereas esophageal speech was the lowest. Coefficient correlation of speech intelligibility and speech recognition rate was found in alaryngeal voices, but not in pathological voices. Conclusion : Current study was not proved speech recognition program, HUVOIS during telephone program was not objective and efficient method for assisting subjective GRBAS scale.

• 대한영양사협회학술지
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• 제5권1호
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• pp.29-47
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• 1999

The purpose of this study is to provide the basic data and their analysis to improve hospital foodservice by identifying patient satisfaction with different attributes of hospital foodservice and its influencing factors using self written survey on nine hundred fifteen hospitalized patients in 28 general hospitals in Seoul and Kungki area. The statistical analysis of data was done by SAS/WIN package(Version 6.11) to determine Descriptive Analysis, T-test, Analysis of Variance, Pearson's Correlation, and Factor Analysis. The summary of the study results is as follows : 1. Among sixteen food-service quality attributes, the most unsatisfying one was the meal itself, the provision of nutrition informations, the possibility of menu choices, immediate response on meal problems, and the taste of the meal. 2. There was a positive correlation between the general quality satisfaction and freshness, nutritional considerations, and the temperature of the dishes and trays, and variety of menu in food-service quality were also correlated positively. 3. Based on the result of statistical analysis on the expectation and recognition in hospital food-service quality attributes vs quality satisfaction, expectation was negatively correlated with quality satisfaction : however, recognition was positively correlated.

• 보건교육건강증진학회지
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• 제21권1호
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• pp.217-242
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• 2004

This study was carried out to measure job satisfaction and quality of life and to clarify the factors in job satisfaction which influence on quality of life of dental technicians, using developed tools for job satisfaction and WHOQOL-BREF for quality of life. The subjects for this study were 238 people who worked the in the Daegu-Kyungbuk area. The results of this study were as follows； the general characteristics that influenced job satisfaction, were especially education, hobbies, salary level, job career and work hours. The factors that influenced the quality of life, were especially Married status, hobbies, job position, and office hours. All subfactors in job satisfaction were related to each other. Growth-development factor was intensely related with recognition factor. Also, all subfactors in quality of life were in positive relation to each other, especially psychological domain was highly related with social domain. Factors of safety, recognition and accomplishment in job satisfaction intensely affected quality of life. Therefore, It is suggested that social recognition for dental technician should be promoted and it might be needed to adjust office hours and support hobby life.

• 품질경영학회지
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• 제8권1호
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• pp.8-15
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• 1980

There are many methods of pattern recognition. In this paper we assume that the responses of independent m groups are described by p-variate normal random variables with distinct mean vectors and a common covariance matrix. Under the assumption we give pattern recognition of m groups by means of canonical discrininant analysis and it's computer program. An example is presented.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2007년도 하계종합학술대회 논문집
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• pp.423-424
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• 2007

In this paper, we propose a scalable high-quality speech reconstruction method for distributed speech recognition (DSR). It is difficult to reconstruct speech of high quality with MFCCs at the DSR server. Depending on the bit-rate available by the DSR system, we can send additional information associated with speech coding to the DSR sorrel, where the bit-rate is variable from 4.8 kbit/s to 11.4 kbit/s. The experimental results show that the speech quality reproduced by the proposed method when the bit-rate is 11.4 kbit/s is comparable with that of ITU-T G.729 under both ideal channel and frame error channel conditions while the performance of DSR is maintained to that of wireline speech recognition.

• International Journal of Quality Innovation
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• 제7권3호
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• pp.58-69
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• 2006

This paper presents neural network-based recognition system for automatic light emitting diode (LED) inspection. The back-propagation neural network (BPNN) is proposed and tested. The current-voltage (I-V) characteristic data of LED from the inspection process is used for the network training and testing. This study selects 300 random samples as network training and employs 100 samples as network testing. The experimental results show that if the classification work is done well, the accuracy of recognition is 100%, and the testing speed of the proposed recognition system is almost one half faster than the traditional inspection system does. The proposed neural-network approach is successfully demonstrated by real data sets and can be effectively developed as a recognition system for a practical application purpose.