• Near Infrared Analysis
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• 제1권2호
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• pp.41-44
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• 2000

The objectives of this study are to discriminate the geographical origin and cultivation years of ginseng based on the near-infrared(NIR) reflectance spectroscopic analysis. Korea and China ginseng samples were prepared for discrimination of geographical origin. 4, 5 and 6 years-old ginseng samples from Korea were prepared for discrimination of cultivation years. Used spectrometer were InfraAlyzer 500, InfraAlyzer 400 and Fiber optic. Sample type of ginseng was 3, whole ginseng radix, slide section and powder type. The accuracy was affected by sample types and instruments. The accuracy for discrimination geographical origin was 97% in calibration model using IA 500 and ginseng powder. For discrimination of cultivation years, the model with slide selection using IA500 were relative accurate. The accuracy was 96.7% for 4-year, 91.3% for 5-year and 89.3% for 6-year old ginseng. The study shows that NIR spectroscopic analysis can be used to discriminate the geographical origin and cultivation years of ginseng with acceptable accuracy.

• Journal of Computing Science and Engineering
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• 제10권4호
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• pp.128-136
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• 2016

It is impossible for any human being to analyze the more than 500 million tweets that are generated per day. Lexical ambiguities on Twitter make it difficult to retrieve the desired data and relevant topics. Most of the solutions for the word sense disambiguation problem rely on knowledge base systems. Unfortunately, it is expensive and time-consuming to manually create a knowledge base system, resulting in a knowledge acquisition bottleneck. To solve the knowledge-acquisition bottleneck, a topic signature is used to disambiguate words. In this paper, we evaluate the effectiveness of various features of newspapers on the topic signature extraction for word sense discrimination in tweets. Based on our results, topic signatures obtained from a snippet feature exhibit higher accuracy in discriminating company names than those from the article body. We conclude that topic signatures extracted from news articles improve the accuracy of word sense discrimination in the automated analysis of tweets.

• Advances in Traditional Medicine
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• 제9권1호
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• pp.14-19
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• 2009

The aim of this study is to evaluate appraiser's consistency and accuracy about pulse diagnosis (PD) in discrimination of eight-constitutions using Gage R&R study. Cumulative numbers of PD for discrimination of eight constitutions of three appraisers' experience were 75,000 cases, 50,000 cases, 1,100 cases, respectively. Three Appraisers diagnosed subject's eight-constitutions by PD with blinded method. Gage R&R study was used to verify the results. In the measurements of consistency, appraiser B (agreement = 80%, Value of k = 0.8276) was very good, appraiser A (agreement = 70%, Value of k = 0.7465) was good, and appraiser C (agreement = 50%, Value of k = 0.5365) was moderate. In the measurements of accuracy, appraiser B (agreement = 70%, Value of k = 0.6812) was good, appraiser A (agreement = 60%, Value of k = 0.6414) was good, and appraiser C (agreement = 0%, Value of k = -0.1000) was poor. The results suggest that accuracy of discrimination of constitutions relatively depend on experience and number of cases of PD. Further large controlled study is needed to evaluate the accuracy of PD.

• Journal of Biosystems Engineering
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• 제42권4호
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• pp.293-300
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• 2017

Purpose: This study aims to propose a method for fast geographical origin discrimination between domestic and imported rice using a visible/near-infrared (VNIR) hyperspectral imaging technique. Methods: Hyperspectral reflectance images of South Korean and Chinese rice samples were obtained in the range of 400 nm to 1000 nm. Partial least square discriminant analysis (PLS-DA) models were developed and applied to the acquired images to determine the geographical origin of the rice samples. Results: The optimal pixel dimensions and spectral pretreatment conditions for the hyperspectral images were identified to improve the discrimination accuracy. The results revealed that the highest accuracy was achieved when the hyperspectral image's pixel dimension was $3.0mm{\times}3.0mm$. Furthermore, the geographical origin discrimination models achieved a discrimination accuracy of over 99.99% upon application of a first-order derivative, second-order derivative, maximum normalization, or baseline pretreatment. Conclusions: The results demonstrated that the VNIR hyperspectral imaging technique can be used to discriminate geographical origins of rice.

• Journal of Biosystems Engineering
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• 제37권6호
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• pp.411-419
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• 2012

Purpose: Nondestructive evaluation of seed viability is a highly demanded technique in the seed industry. In this study, hyperspectral imaging system was used for discrimination of viable and non-viable radish seeds. Method: The spectral data with the range from 400 to 1000 nm measured by hyperspectral reflectance imaging system were used. A calibration and a test models were developed by partial least square discrimination analysis (PLS-DA) for classification of viable and non-viable radish seeds. Either each data set of visible (400~750 nm) and NIR (750~1000 nm) spectra and the spectra of the combined spectral ranges were used for developing models. Results: The discrimination accuracy of calibration was 84% for visible range and 76.3% for NIR range. The discrimination accuracy of test was 84.2% for visible range and 75.8% for NIR range. The discrimination accuracies of calibration and test with full range were 92.2% and 92.5%, respectively. The resultant images based on the optimal PLS-DA model showed high performance for the discrimination of the nonviable seeds from the viable seeds with the accuracy of 95%. Conclusions: The results showed that hyperspectral reflectance imaging has good potential for discriminating nonviable radish seeds from massive amounts of viable seeds.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 2017년도 춘계공동학술대회
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• pp.23-23
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• 2017

Recent favor on high quality food and concern on food safety have demonstrated the superiority of Hanwoo (Korean native cattle). In general, the price of cow is higher than those of steer and bull, causing cheating issues in the market. Hence, this study is to discriminate genders of Hanwoo with identification of factors which highly influence gender discrimination based on the big-size deboning data. Totally, there were 31 variables in the deboning data, and we divided into them two categories: data obtained before and after deboning. Discriminant function analysis was then applied into the data to determined the accuracy of gender discrimination in Hanwoo. The result showed that Hanwoo could be classified by gender with 99.2% of accuracy when using all 31 variables. In detail, it was possible to identify 93 of 94 bulls (98.9%), 96 of 96 cows (100%) and 74 of 75 steers (98.7%). The most significant variables was chuck, sirloin, armbone shin, plates, retail and cuts percentage, sequentially. With variables obtainable before deboning, accuracies of classification were 91.5% for bulls, 92.7% for cows, and 89.3% for steers. The most significant variables was water, cold carcass weight and back-fat thickness. The discrimination accuracy was higher with data obtainable after deboning: bulls (98.9%), cows (99.0%) and steers (98.7%). In this case, chuck, sirloin and armbone shin were the factors determined the classification ability. This study showed that Hanwoo can be classified based on deboning data with appropriate statistics, further suggesting weight of cut of beef might be the standard for gender classification.

• 한국인터넷방송통신학회논문지
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• 제21권6호
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• pp.77-82
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• 2021

요검사는 물리적 성상 검사, 화학적 검사, 현미경 검사 세 가지가 있다. 이 중에서 화학적 요검사는 일반인이 쉽게 접근하는 방법으로 요검사지의 화학반응을 눈으로 표준비색표와 비교하거나 휴대용 요검사기를 별도로 구매하여 검사를 진행한다. 현재는 스마트폰의 보급이 대중화되어 스마트폰을 활용한 요검사 서비스 연구가 높아지고 있다. 요검사 스크리닝 애플리케이션은 스마트폰을 활용한 요검사 서비스 중 하나이다. 그러나 요검사 스크리닝 애플리케이션으로 촬영한 요검사 패드 RGB 값은 조명영향으로 인해 큰 편차가 발생한다. 요검사 패드 RGB 값의 편차는 요검사 판별의 정확도를 떨어뜨린다. 따라서 본 논문에서는 스마트폰 기반 요검사 스크리닝 애플리케이션으로 촬영한 요검사지를 검사 항목별 요검사 패드로 분류한 후 CNN을 통해 요검사 패드 이미지 판별의 정확도를 높인다. 요검사지는 다양한 배경에서 촬영하여 CNN 이미지를 생성하였으며 ResNet-50 CNN 모델을 사용하여 요검사 판별을 분석하였다.

• 대한음성학회지:말소리
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• 제61호
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• pp.63-74
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• 2007

Discrimination of music and speech from the multimedia signal is an important task in audio coding and broadcast monitoring systems. This paper deals with the problem of feature parameter extraction for discrimination of music and speech. The wavelet transform is a multi-resolution analysis method that is useful for analysis of temporal and spectral properties of non-stationary signals such as speech and audio signals. We propose new feature parameters extracted from the wavelet transformed signal for discrimination of music and speech. First, wavelet coefficients are obtained on the frame-by-frame basis. The analysis frame size is set to 20 ms. A parameter $E_{sum}$ is then defined by adding the difference of magnitude between adjacent wavelet coefficients in each scale. The maximum and minimum values of $E_{sum}$ for period of 2 seconds, which corresponds to the discrimination duration, are used as feature parameters for discrimination of music and speech. To evaluate the performance of the proposed feature parameters for music and speech discrimination, the accuracy of music and speech discrimination is measured for various types of music and speech signals. In the experiment every 2-second data is discriminated as music or speech, and about 93% of music and speech segments have been successfully detected.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.1087-1089
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• 2003

The aim of this study is to evaluate the Pi-SAR data for land cover discrimination using a standard method. For this purpose, the original polarization and Pauli components of the Pi-SAR X-band and L-band data are used and the results are compared. As a method for the land cover discrimination, the traditional method of statistical maximum likelihood decision rule is selected. To increase the accuracy of the classification result, different spatial thresholds based on local knowledge are determined and used for the actual classification process. Moreover, to reduce the speckle noise and increase the spatial homogeneity of different classes of objects, a speckle suppression filter is applied to the original Pi-SAR data before applying the classification decision rule. Overall, the research indicated that the original Pi-SAR polarization components can be successfully used for separation of different land cover types without taking taking special polarization transformations.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.760-762
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• 2003

This study confirmed the usefulness of short-wavelength infrared (SWIR) in the discrimination and classification of evergreen forest types. A forested area near Hisayama and Sasaguri in Fukuoka Prefecture, Japan, served as the study area. Warm-temperate forest vegetation dominates the study site vegetation. Coniferous plantation forest, natural broad-leaved forest, and bamboo forest were analyzed using LANDSAT5/TM and SPOT4/HRVIR remote sensing data. Samples were extracted for the three forest types, and reflectance factors were compared for each band. Kappa coefficients of various band combinations were also compared by classification accuracy. For the LANDSAT5/TM data observed in April, October, and November, Bands 5 and 7 showed significant differences between bamboo, broad-leaved, and coniferous forests. The same significant difference was not recognized in the visible or near-infrared regions. Classification accuracy, determined by supervised classification, indicated distinct improvements in band combinations with SWIR, as compared to those without SWIR. Similar results were found for both LANDSAT5/TM and SPOT4/HRVIR data. This study identified obvious advantages in using SWIR data in forest-type discrimination and classification.