• Korean Journal of Agricultural Science
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• v.9 no.1
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• pp.396-450
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• 1982

To obtain basic information on the Korean local corn lines a total of 57 lines were selected from 1,000 Korean local collection at Chungnam National University, classified by principal component analysis, and genetic nature was investigated. The results are summarized as follows. 1. There were a great variation in mean values of plant characters of the lines. The mean values of plant characters except for density of kernels varied with types of crossing. All characters except. for tasselling dates were reduced in magnitude when selfed, while those characters were increased when topcrossed. 2. The correlation coefficients among characters studied ranged front 0.99 to -0.59. The correlation coefficients among characters were not greatly changed depending upon types of crosses. 3. In order to classify the lines more effectively, selected 12 plant characters were used to classify 57 local lines by principal component analysis. The first four component could explain 86.4%, 83.4% and 81.1% of the total variations in sibbed lines, selfed lines and topcrossed lines, respectively. 4. Contribution of characters to principal component was high at upper principal components and low at lower principal components. 5. Biological meaning of the principal component and plant types corresponding to the each principal component were explained clearly by the correlation coefficient between principal components and characters. The first principal component appeared to correspond to the size of plant and ear. The second principal component appeared to correspond to the degree of differentiation in organs and the duration of vegetative growing period. But biological meaning of the third and fourth principal components was not clear. 6. The lines were classified into 4 lineal groups by the taxonomic distance. Group I included 52 lines which was 91.2% of total lines, group II 3 lines, group III 1 lines and group IV I lines, respectively. Four groups could be characterized as follows : Group I : early maturity, short-culmed, medium height plant, small ears, medium kernels and medium yielding. Group II : late maturity, medium height plant, small ears, small kernels, prolific ears and higher yielding. Group III : medium maturity, tall-culmed, small ears, small kernels and low yielding. Group IV : medium maturity, tall-calmed, large ears, one ear plant and me yielding. 7. The inbreeding depression varied with plant characters and lines. The characters such as yield, kernel weight per ear, ear weight and plant height showed great degree of inbreeding depression. Group I showed high inbreeding depression in such characters as 100 kernel weight, leaf number, plant height and days to tasselling, while group II showed high inbreeding depression in other plant characters. 8. Heterosis of plant characters varied also with lines. The ear weight, kernel weight per ear, yield, 100 kernel weight, and plant height were some of the plant characters showing high heterosis. Group II showed high values of heterosis in such characters as ear length, ear diameter, ear weight, kernel weight per ear, 100 kernel weight, and leaf length, while group I was high in heterosis in other plant characters. 9. The degree of homozgosity was highest in ear weight (79.1%) and lowest in ear number per plant (-21%). Group II showed higher degree of homozygosity than group I. 10. Correlation coefficients between characters of ribbed and topcrossed lines were positive for all characters. Highly significant. correlation coefficients between ribbed and topcrossed lines were obtained especially for characters such as ear number per plant, plant height, leaf length and yield per plot.

• Journal of the Korean Society of Food Science and Nutrition
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• v.41 no.8
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• pp.1118-1133
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• 2012

This research aimed to suggest an efficient improvement plan for school food services by investigating the operating situation and recognition of menu management in school food services for school food service dietitians (and nutrition teachers) in Chungbuk. A total of 328 questionnaires were distributed to school food service dietitians (and nutrition teachers) in Chungbuk by e-mail in September, 2010. A total of 265 questionnaires (80.8%) were used for the analysis. The highest allocation of nutrients and calories per day in school food services was 1:1.5:1.5 (breakfast : lunch : dinner) (38.5%). The reasoning for applying a flexible allocation of nutrients and calories per day was 'considering the ratio of students who do not eat breakfast' (59.2%). And the way to apply the flexible allocation for nutrients and calories per day was 'by agreement from the school operating committee in arbitrary data without situation surveys' (86 respondents, 49.4%), and 'by agreement from the school operating committee in analysis data through situation surveys' (80 respondents, 46.0%). The operational method of standardized recipes was 'cooking management site of national education information systems' (87.5%) and the items included in standardized recipes were menu name, food material name, portion size, cooking method, nutrition analysis, and critical control point in HACCP. The main reason for not utilizing all items of a cooking management site of the national education information system was 'no big trouble in menu management even though it is used partly (29.1%). In addition, the highest use of standardized recipe was for 'maintaining consistency of food production quantity' (74.0%).

• Radiation Oncology Journal
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• v.19 no.2
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• pp.100-106
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• 2001

Purpose : We performed a retrospective analysis to compare short term results of induction chemotherapy-radiotherapy versus concurrent chemo-radiotherapy in patients with locally advanced nasopharyngeal carcinoma. Materials and Methods : From Oct. 1989 to May 1998, 62 patients with locally advanced nasopharyngeal carcinoma were treated with induction chemotherapy followed by radiotherapy (induction group) or concurrent chemo-radiotherapy (concurrent group). Induction chemotherapy was done for 50 patients, and concurrent chemotherapy for 12 patients. Age, sex, performance status, and pathologic types were evenly distributed between two groups. Stage distribution showed $32\%$ with IIB, $32\%$ with III, and $38\%$ with IV in induction group, and $50\%,\;33.3\%,\;and\;16.7\%$ in concurrent group, respectively. Chemotherapy regimen was CF (cisplatin and 5-FU) in both groups, and drug delivery method also same. Cisplatin $100\;mg/m^2$ was intravenously infused on day 1, and 5-FU $1,000\;mg/m^2$ on day $2\~6$. This was repeated at 3 weeks interval. At the end of radiotherapy, total cycles of chemotherapy were $1\~3$ (median 2) in both groups. Conventionally fractionated radiotherapy with daily fraction size $1.8\~2.0\;Gy$ and 5 fractions/week was done. Total dose was $69.4\~86\;Gy$(median 73.4 Gy) for induction group, and $69.4\~75.4\;Gy$ (median 70.8 Gy) for concurrent group. Follow-up time was $9\~116$ months (median 40.5 months) for induction group, $14\~29$ months (median 21 months) for concurrent group, respectively. Results : Overall 2 year survival rate (2YSR) for all patients was $78.7\%$. According to treatment modality, 2YSR were $77\%$ for induction group, $87\%$ for concurrent group (p>0.05). 2 year disease-free survival rate were $56\%$ and $81\%\;(p>0.05)$, respectively. Complete response to treatment were $75.5\%$ for induction group and $91.7\%$ for concurrent group, but there was no statistical difference. The incidence of grade $3\~4$ hematologic toxicity during radiotherapy was not differ between two groups, but grade 2 leukopenia was more frequent in concurrent group $(18\%\;vs\;66.7\%)$Grade $3\~4$ mucositis was more frequent in concurrent group $(4.0\%\;vs\;33.3\%)$. Overall incidence of grade $3\~4$ acute toxicity during radiotherapy was more frequent in concurrent group $(6.0\%\;vs\;41.7\%,\;p=0.005)$. Conclusion : Concurrent chemo-radiotherapy showed a trend of improvement in short-term survival and in treatment response when compared with induction chemotherapy-radiotherapy in locally advanced nasopharyngeal carcinoma. More controlled randomized trial are needed.

• Journal of Korean Society of Forest Science
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• v.77 no.4
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• pp.429-444
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• 1988

Considering the recent trent toward the development of multiple-use of forest trees, investigations for comprehensive information on these young stands of Hinoki cypress are necessary for rational forest management. From this point of view, 83 sample trees were selected and cut down from 23-ear old stands of Hinoki cypress at Changsung-gun, Chonnam-do. Various stem growth factors of felled trees were measured and canonical correlaton analysis, principal component analysis and factor analysis were applied to investigate the stem growth characteristics, relationships among stem growth factors, and to get potential information and comprehensive information. The results are as follows ; Canonical correlation coefficient between stem volume and quality growth factor was 0.9877. Coefficient of canonical variates showed that DBH among diameter growth factors and height among height growth factors had important effects on stem volume. From the analysis of relationship between stem-volume and canonical variates, which were linearly combined DBH with height as one set, DBH had greater influence on volume growth than height. The 1st-2nd principal components here adopted to fit the effective value of 85% from the pincipal component analysis for 12 stem growth factors. The result showed that the 1st-2nd principal component had cumulative contribution rate of 88.10%. The 1st and the 2nd principal components were interpreted as "size factor" and "shape factor", respectively. From summed proportion of the efficient principal component fur each variate, information of variates except crown diameter, clear length and form height explained more than 87%. Two common factors were set by the eigen value obtained from SMC (squared multiple correlation) of diagonal elements of canonical matrix. There were 2 latent factors, $f_1$ and $f_2$. The former way interpreted as nature of diameter growth system. In inherent phenomenon of 12 growth factor, communalities except clear length and crown diameter had great explanatory poorer of 78.62-98.30%. Eighty three sample trees could he classified into 5 stem types as follows ; medium type within a radius of ${\pm}1$ standard deviation of factor scores, uniformity type in diameter and height growth in the 1st quadrant, slim type in the 2nd quadrant, dwarfish type in the 3rd quadrant, and fall-holed type in the 4 th quadrant.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.85-109
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• 2018

Recommender system recommends the items expected to be purchased by a customer in the future according to his or her previous purchase behaviors. It has been served as a tool for realizing one-to-one personalization for an e-commerce service company. Traditional recommender systems, especially the recommender systems based on collaborative filtering (CF), which is the most popular recommendation algorithm in both academy and industry, are designed to generate the items list for recommendation by using 'overall rating' - a single criterion. However, it has critical limitations in understanding the customers' preferences in detail. Recently, to mitigate these limitations, some leading e-commerce companies have begun to get feedback from their customers in a form of 'multicritera ratings'. Multicriteria ratings enable the companies to understand their customers' preferences from the multidimensional viewpoints. Moreover, it is easy to handle and analyze the multidimensional ratings because they are quantitative. But, the recommendation using multicritera ratings also has limitation that it may omit detail information on a user's preference because it only considers three-to-five predetermined criteria in most cases. Under this background, this study proposes a novel hybrid recommendation system, which selectively uses the results from 'traditional CF' and 'CF using multicriteria ratings'. Our proposed system is based on the premise that some people have holistic preference scheme, whereas others have composite preference scheme. Thus, our system is designed to use traditional CF using overall rating for the users with holistic preference, and to use CF using multicriteria ratings for the users with composite preference. To validate the usefulness of the proposed system, we applied it to a real-world dataset regarding the recommendation for POI (point-of-interests). Providing personalized POI recommendation is getting more attentions as the popularity of the location-based services such as Yelp and Foursquare increases. The dataset was collected from university students via a Web-based online survey system. Using the survey system, we collected the overall ratings as well as the ratings for each criterion for 48 POIs that are located near K university in Seoul, South Korea. The criteria include 'food or taste', 'price' and 'service or mood'. As a result, we obtain 2,878 valid ratings from 112 users. Among 48 items, 38 items (80%) are used as training dataset, and the remaining 10 items (20%) are used as validation dataset. To examine the effectiveness of the proposed system (i.e. hybrid selective model), we compared its performance to the performances of two comparison models - the traditional CF and the CF with multicriteria ratings. The performances of recommender systems were evaluated by using two metrics - average MAE(mean absolute error) and precision-in-top-N. Precision-in-top-N represents the percentage of truly high overall ratings among those that the model predicted would be the N most relevant items for each user. The experimental system was developed using Microsoft Visual Basic for Applications (VBA). The experimental results showed that our proposed system (avg. MAE = 0.584) outperformed traditional CF (avg. MAE = 0.591) as well as multicriteria CF (avg. AVE = 0.608). We also found that multicriteria CF showed worse performance compared to traditional CF in our data set, which is contradictory to the results in the most previous studies. This result supports the premise of our study that people have two different types of preference schemes - holistic and composite. Besides MAE, the proposed system outperformed all the comparison models in precision-in-top-3, precision-in-top-5, and precision-in-top-7. The results from the paired samples t-test presented that our proposed system outperformed traditional CF with 10% statistical significance level, and multicriteria CF with 1% statistical significance level from the perspective of average MAE. The proposed system sheds light on how to understand and utilize user's preference schemes in recommender systems domain.

• Progress in Medical Physics
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• v.27 no.2
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• pp.64-71
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• 2016

We develop a manufacture procedure for the production of a patient specific customized bolus (PSCB) using a 3D printer (3DP). The dosimetric accuracy of the 3D-PSCB is evaluated for electron beam therapy. In order to cover the required planning target volume (PTV), we select the proper electron beam energy and the field size through initial dose calculation using a treatment planning system. The PSCB is delineated based on the initial dose distribution. The dose calculation is repeated after applying the PSCB. We iteratively fine-tune the PSCB shape until the plan quality is sufficient to meet the required clinical criteria. Then the contour data of the PSCB is transferred to an in-house conversion software through the DICOMRT protocol. This contour data is converted into the 3DP data format, STereoLithography data format and then printed using a 3DP. Two virtual patients, having concave and convex shapes, were generated with a virtual PTV and an organ at risk (OAR). Then, two corresponding electron treatment plans with and without a PSCB were generated to evaluate the dosimetric effect of the PSCB. The dosimetric characteristics and dose volume histograms for the PTV and OAR are compared in both plans. Film dosimetry is performed to verify the dosimetric accuracy of the 3D-PSCB. The calculated planar dose distribution is compared to that measured using film dosimetry taken from the beam central axis. We compare the percent depth dose curve and gamma analysis (the dose difference is 3%, and the distance to agreement is 3 mm) results. No significant difference in the PTV dose is observed in the plan with the PSCB compared to that without the PSCB. The maximum, minimum, and mean doses of the OAR in the plan with the PSCB were significantly reduced by 9.7%, 36.6%, and 28.3%, respectively, compared to those in the plan without the PSCB. By applying the PSCB, the OAR volumes receiving 90% and 80% of the prescribed dose were reduced from $14.40cm^3$ to $0.1cm^3$ and from $42.6cm^3$ to $3.7cm^3$, respectively, in comparison to that without using the PSCB. The gamma pass rates of the concave and convex plans were 95% and 98%, respectively. A new procedure of the fabrication of a PSCB is developed using a 3DP. We confirm the usefulness and dosimetric accuracy of the 3D-PSCB for the clinical use. Thus, rapidly advancing 3DP technology is able to ease and expand clinical implementation of the PSCB.

• Journal of Food Hygiene and Safety
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• v.26 no.4
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• pp.322-329
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• 2011

This study was done to analyze the contents of minerals and vitamins to compare the measured values of minerals, vitamins with labeled values of them in food labeling and to investigate the ratio of measured values to labeled values in 437 specimen with minerals and vitamins - fortified commercial beverages and liquid teas. Content of calcium and sodium in samples after microwave digestion was analyzed with an ICP-OES (Inductively Coupled Plasma Optical Emission Spectrometer) and vitamins were determined using by HPLC (High Performance Liquid Chromatography). The measured values of calcium were ranged 80.3~142.6% of the labeled values in 21 samples composed calcium - fortified commercial beverages and liquid teas. In case of sodium, measured values were investigated 33.9~48.5% of the labeled values in 21 sports beverages. The measured values of vitamin C, vitamin $B_2$ and niacin were ranged 99.7~2003.6, 81.1~336.7, 90.7~393.2% of the labeled values in vitamins - fortified commercial beverages and liquid teas, 57, 12, 11 samples. To support achievement of the accurate nutrition label, there must be program and initiatives for better understanding and guidances on food labelling and nutrition for food manufacture.

• Journal of the Korean Society of Food Science and Nutrition
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• v.36 no.8
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• pp.995-1009
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• 2007

The purpose of this study was to investigate the dietary habits, behaviors, and food consumption frequency according to gender and obesity level among middle school students in the Jeonju area. Subjects for the questionnaire were 450 middle school students (male 255, female 195) and were classified as either obese students (n=150 or non-obese students (n=299) by the obesity assessment method. The results were analyzed with SAS program (Version 9.1), and were as follows. 1. Dietary behaviors were significantly different in the rate of 'Skipping breakfast (p<0.05)', 'Duration of meal time (min) (p<0.05)' and 'Unbalanced diet (p<0.01)' between males and females. Dietary habits and behaviors also differed significantly for the rate of ‘Taste preferences (p<0.05)’, and 'Unbalanced diet (p<0.01)' between obese students and non-obese students. 2. Food consumption frequency per week was as follows. First, males were significantly higher than females in 'Instant noodle (p<0.05)', 'Milk (p<0.01)', and 'Soda pop (p<0.01)'; on the other hand females were significantly higher than males in 'Chocolate, Candy (p<0.01)'. Second, non-obese students were significantly higher than obese students in 'Instant noodle (p<0.05)', 'Hamburger, Pizza (p<0.05)', and 'Chocolate, Candy (p<001)'. Especially, non-obese male students were higher in 'Instant noodle (p<0.05)' and 'Hamburger, Pizza (p<0.05)'; non-obese female students were higher in 'Chocolate, Candy (p<0.01)'. In conclusion, an action program is needed to encourage healthful dietary behaviors, increased physical activity, and forming good lifelong habits.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.113-125
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• 2013

Every company wants to know customer's requirement and makes an effort to meet them. Cause that, communication between customer and company became core competition of business and that important is increasing continuously. There are several strategies to find customer's needs, but VOC (Voice of customer) is one of most powerful communication tools and VOC gathering by several channels as telephone, post, e-mail, website and so on is so meaningful. So, almost company is gathering VOC and operating VOC system. VOC is important not only to business organization but also public organization such as government, education institute, and medical center that should drive up public service quality and customer satisfaction. Accordingly, they make a VOC gathering and analyzing System and then use for making a new product and service, and upgrade. In recent years, innovations in internet and ICT have made diverse channels such as SNS, mobile, website and call-center to collect VOC data. Although a lot of VOC data is collected through diverse channel, the proper utilization is still difficult. It is because the VOC data is made of very emotional contents by voice or text of informal style and the volume of the VOC data are so big. These unstructured big data make a difficult to store and analyze for use by human. So that, the organization need to automatic collecting, storing, classifying and analyzing system for unstructured big VOC data. This study propose an intelligent VOC analyzing system based on opinion mining to classify the unstructured VOC data automatically and determine the polarity as well as the type of VOC. And then, the basis of the VOC opinion analyzing system, called domain-oriented sentiment dictionary is created and corresponding stages are presented in detail. The experiment is conducted with 4,300 VOC data collected from a medical website to measure the effectiveness of the proposed system and utilized them to develop the sensitive data dictionary by determining the special sentiment vocabulary and their polarity value in a medical domain. Through the experiment, it comes out that positive terms such as "칭찬, 친절함, 감사, 무사히, 잘해, 감동, 미소" have high positive opinion value, and negative terms such as "퉁명, 뭡니까, 말하더군요, 무시하는" have strong negative opinion. These terms are in general use and the experiment result seems to be a high probability of opinion polarity. Furthermore, the accuracy of proposed VOC classification model has been compared and the highest classification accuracy of 77.8% is conformed at threshold with -0.50 of opinion classification of VOC. Through the proposed intelligent VOC analyzing system, the real time opinion classification and response priority of VOC can be predicted. Ultimately the positive effectiveness is expected to catch the customer complains at early stage and deal with it quickly with the lower number of staff to operate the VOC system. It can be made available human resource and time of customer service part. Above all, this study is new try to automatic analyzing the unstructured VOC data using opinion mining, and shows that the system could be used as variable to classify the positive or negative polarity of VOC opinion. It is expected to suggest practical framework of the VOC analysis to diverse use and the model can be used as real VOC analyzing system if it is implemented as system. Despite experiment results and expectation, this study has several limits. First of all, the sample data is only collected from a hospital web-site. It means that the sentimental dictionary made by sample data can be lean too much towards on that hospital and web-site. Therefore, next research has to take several channels such as call-center and SNS, and other domain like government, financial company, and education institute.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.143-156
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• 2012

People easily believe that news and stock index are closely related. They think that securing news before anyone else can help them forecast the stock prices and enjoy great profit, or perhaps capture the investment opportunity. However, it is no easy feat to determine to what extent the two are related, come up with the investment decision based on news, or find out such investment information is valid. If the significance of news and its impact on the stock market are analyzed, it will be possible to extract the information that can assist the investment decisions. The reality however is that the world is inundated with a massive wave of news in real time. And news is not patterned text. This study suggests the stock-index invest model based on "News Big Data" opinion mining that systematically collects, categorizes and analyzes the news and creates investment information. To verify the validity of the model, the relationship between the result of news opinion mining and stock-index was empirically analyzed by using statistics. Steps in the mining that converts news into information for investment decision making, are as follows. First, it is indexing information of news after getting a supply of news from news provider that collects news on real-time basis. Not only contents of news but also various information such as media, time, and news type and so on are collected and classified, and then are reworked as variable from which investment decision making can be inferred. Next step is to derive word that can judge polarity by separating text of news contents into morpheme, and to tag positive/negative polarity of each word by comparing this with sentimental dictionary. Third, positive/negative polarity of news is judged by using indexed classification information and scoring rule, and then final investment decision making information is derived according to daily scoring criteria. For this study, KOSPI index and its fluctuation range has been collected for 63 days that stock market was open during 3 months from July 2011 to September in Korea Exchange, and news data was collected by parsing 766 articles of economic news media M company on web page among article carried on stock information>news>main news of portal site Naver.com. In change of the price index of stocks during 3 months, it rose on 33 days and fell on 30 days, and news contents included 197 news articles before opening of stock market, 385 news articles during the session, 184 news articles after closing of market. Results of mining of collected news contents and of comparison with stock price showed that positive/negative opinion of news contents had significant relation with stock price, and change of the price index of stocks could be better explained in case of applying news opinion by deriving in positive/negative ratio instead of judging between simplified positive and negative opinion. And in order to check whether news had an effect on fluctuation of stock price, or at least went ahead of fluctuation of stock price, in the results that change of stock price was compared only with news happening before opening of stock market, it was verified to be statistically significant as well. In addition, because news contained various type and information such as social, economic, and overseas news, and corporate earnings, the present condition of type of industry, market outlook, the present condition of market and so on, it was expected that influence on stock market or significance of the relation would be different according to the type of news, and therefore each type of news was compared with fluctuation of stock price, and the results showed that market condition, outlook, and overseas news was the most useful to explain fluctuation of news. On the contrary, news about individual company was not statistically significant, but opinion mining value showed tendency opposite to stock price, and the reason can be thought to be the appearance of promotional and planned news for preventing stock price from falling. Finally, multiple regression analysis and logistic regression analysis was carried out in order to derive function of investment decision making on the basis of relation between positive/negative opinion of news and stock price, and the results showed that regression equation using variable of market conditions, outlook, and overseas news before opening of stock market was statistically significant, and classification accuracy of logistic regression accuracy results was shown to be 70.0% in rise of stock price, 78.8% in fall of stock price, and 74.6% on average. This study first analyzed relation between news and stock price through analyzing and quantifying sensitivity of atypical news contents by using opinion mining among big data analysis techniques, and furthermore, proposed and verified smart investment decision making model that could systematically carry out opinion mining and derive and support investment information. This shows that news can be used as variable to predict the price index of stocks for investment, and it is expected the model can be used as real investment support system if it is implemented as system and verified in the future.