• 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.

• Korean Journal of Soil Science and Fertilizer
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• v.21 no.3
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• pp.316-338
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• 1988

To identify the physiological phenomena on the sudden wilting of japonica/indica crossed varieties, Pot experiment was carried out under the heavy N application with various levels of potassium in Japan. The results obtained are as follows. 1. Sudden wilting was occurred in both varieties used, Yushin and Milyang 23. The former showed a higher degree than the latter. 2. Sudden wilting was occurred into two types, one at early ripening stage and the other at late ripening stage. The former type was found in the field with low potassium supply and the latter was seemed to be related to varietal wilting tolerence. 3. By the investigation of concerning the effective tillering rate and the change of dry weight of each organ at the heading stage, it was inferred that the growth status from young panicle formation stage to heading stage were related to sudden wilting tolerence. 4. Manganese content at heading stage, ratio of Fe/Mn and Fe. Fe/Mn in stern at late ripening stage and $K_2$ O/N ratio of stem at harvesting stage were recognized as the specific factors in connection with sudden wilting. Mn content in the sudden wilting rice plant was already in creased remarkably at heading stage. In relation to root age and absoption characteristics of Mn, the senility of root before heading stage was inferred as the cause of increase the value of Fe/Mn or Fe. Fe/Mn. 5. The $K_2$ O/N ratio of culm at harvesting stage was lower in upper node than lower node in relation to sudden wilting. And it was well accordance with the fact that the symptoms of sudden wilting proceeded from upper leaf to lower leaf. These phenomenon was different from the usual one that the effect of potassium deficiency was more remarkable in lower node than upper node. 6. All varieties which have a condition of potassium deficiency have a high degree of nitrogen content of leaves at heading stage and the $K_2$ O/N ratio of each organ was low, Especialy, $K_2$ O/N ratio is much lower in sheath and culm than leaves.

• Korean Journal of Heritage: History & Science
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• v.42 no.1
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• pp.88-99
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• 2009

This study was conducted to formulate management guidelines for Natural monumental old trees in Korea through survey of tree vigor and analysis of growing environments. A total of 20 old trees designated as natural monuments in Seoul, Incheon, and Gyeonggi Province were surveyed. The biological characteristics were surveyed with 4 items of species, ages and height of trees. The surrounding environments were surveyed with 2 items of location types and surroundings. The root conditions were surveyed with 2 items of denudation and molding depth. The health conditions were surveyed with 5 items of withering rate, cavity size, bark breakaway rate, damages by blight and insects, and growing tips. The soil conditions were surveyed with 6 items of PH, organic contents, valid phosphoric acid, transposal cations(K, Ca) and soil compaction. On the basis of outcomes of these research items, mutual relations among locations, growings and soil conditions of old trees were analyzed by carring out cross tabulation, correlation, and simple and multiple regression. Management guidelines were presented searching the factors effecting on the health of the monumental old trees. On the biological characteristics, the old trees designated as natural monuments were Pinus bungeana(4 trees), Juniperus chinensis(3 trees), Ginkgo biloba(3 trees), Poncirus trifoliata(2 trees). Actinidia arguta, Wisteria floribunda, Thuja orientalis, Quercus mongolica, Sophora japonica, Fraxinus rhynchophylla, Zelkova serrata, and Pinus densiflora. The tree height ranged from 4.2 to 39.2m, and root collar rounds ranged from 1.01 to 15.2m. On the surrounding environments, The location types ; Gardens(4), historical sites(5), residental sections(3) open agricultural fields(3), mountain hills(3), and near ocean beaches(1) and stream site(1). The surroundings ; 75% denudation of roots, molded more than 10cm except 4 trees(25%). On the health conditions, 1)Withering rate ; Ginkgo biloba(20%) in Yongmoon temple, (5%) in Saki-ri, kanwha-gun, and others had no withering rate. 2) Cavity size ; all subject had $5{\sim}100cm^3$ of cavity. 3) Bark breakaway rate ; Pinus bungeana in Soosong-dong, in the shrine of Confucius, in Samchung-dong, especially high rate of cavity(5~50%) in Seoul area and in Saki-ri, Kangwha-gun were high 45% brakeaway rate. 4) Damages by blight and insects was slight due to managements. 5Growing tips ; In cases of Juniperus chinensis in Changdeok palace and SunnogDang, seoul, growing tips were 1/2, presumably cause by air pollution, and in cases of Fraxinus rhynchophylla in Paju city and Pinus densiflora in BacksaDorip-ri, Icheon city, growing tips were fine, presumably because there were no moldings. On the Soil conditions, Soil pH ranged from 5.2 to 8.3, organic matter contents from 12% to 56%, phosphorus contents from 104 to 618ppm, soil compaction ranged from 7 to 28mm( among them, Denudation was severe with 21~28mm soil compactions in cases of Pinus bungeana in Soosong -dong, Thuja orientalis in Samchung -dong, Ginkgo biloba in the shrine of Confucius and in Yongmoon temple.) Results of cross tabulation, correlation, and regression analysis showed that molding depth was the most serious factor to deteriorate the tree vigor and cambium conductivity. In addition, soil acidity, organic matter contents, disease and insect damages and cambial detachment were also related to the tree vigor. Additional research of these relationships will be needed to conduct more detailed studies. Based on the relationships between the tree vigor and growing environments, it is considered that old trees should be managed to give them more growing spaces and less abuses. Also, molded soils should be removed and further soil-molding around the tree collar should be prohibited. For the construction of systematic management and removal of harmful factors, appropriative management according to spices, persistent monitering of damaged cases and construction of management system through the accumulation of data on the relationships of soil conditions are required.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.4
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• pp.207-222
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• 2023

In order to improve employment rates, most universities operate programs to strengthen students' employment and entrepreneurship, regardless of whether they are selected as the Leading Industry-Innovative University (LINC) or not. In particular, in the case of non-metropolitan universities are risking their lives to improve employment rates. In order to overcome the limitations of university establishment type and university location, which absolutely affect the employment rate, we are operating a startup education & startup support program in order to strengthen employment and entrepreneurship, and capstone design & field training as industry-academia-linked education programs are always available. Although there are studies on effectiveness verification centered on LINC (Leaders in Industry-University Cooperation) in previous studies, but a longitudinal study was conducted on all factors of university factors, startup education & startup support, and capstone design & field training as industry-university-linked education programs as factors affecting the employment rate based on public disclosure indicators. No cases of longitudinal studies were reported. This study targets 116 universities that satisfy the conditions based on university disclosure indicators from 2018 to 2020 that were recently released on university factors, startup education & startup support, and capstone design & field training as industry-academia-linked education programs as factors affecting the employment rate. We analyzed the differences between the LINC (Leaders in Industry-University Cooperation) 51 participating universities and 64 non-participating universities. In addition, considering that there is no historical information on the overlapping participation of participating students due to the limitations of public indicators, the Exposure Effect theory states that long-term exposure to employment and entrepreneurship competency enhancement programs will affect the employment rate through competency enhancement. Based on this, the effectiveness of the 2nd LINC+ (socially customized Leaders in Industry-University Cooperation) was verified from 2017 to 2021 through a longitudinal causal relationship analysis. As a result of the study, it was found that the startup education & startup support and capstone design & field training as industry-academia-linked education programs of the 2nd LINC+ (socially customized Leaders in Industry-University Cooperation) did not affect the employment rate. As a result of the longitudinal causal relationship analysis, it was reconfirmed that universities in metropolitan areas still have higher employment rates than universities in non-metropolitan areas due to existing university factors, and that private universities have higher employment rates than national universities. Among employment and entrepreneurship competency strengthening programs, the number of people who complete entrepreneurship courses, the number of people who complete capstone design, the amount of capstone design payment, and the number of dedicated faculty members partially affect the employment rate by year, while field training has no effect at all by year. It was confirmed that long-term exposure to the entrepreneurship capacity building program did not affect the employment rate. Therefore, it was reconfirmed that in order to improve the employment rate of universities, the limitations of non-metropolitan areas and national and public universities must be overcome. To overcome this, as a program to strengthen employment and entrepreneurship capabilities, it is important to strengthen entrepreneurship through participation in entrepreneurship lectures and actively introduce and be confident in the capstone design program that strengthens the concept of PBL (Problem Based Learning), and the field training program improves the employment rate. In order for actually field training affect of the employment rate, it is necessary to proceed with a substantial program through reorganization of the overall academic system and organization.

• Radiation Oncology Journal
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• v.15 no.1
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• pp.27-36
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• 1997

Purpose : This study was tried to evaluate the Potential benefits of concurrent chemoradiation therapy (low dose daily cisplatin combined with split course radiation therapy) compared with conventional radiation therapy alone in stage III non-small cell lung cancer. The end points of analyses were response rate. overall survival, survival without locoregional failure, survival without distant metastasis, prognostic factors affecting survival and treatment related toxicities. Materials and Methods : Between April 1992 and March 1994, 32 patients who had stage III non-small cell lung cancer were treated with concurrent chemoradiation therapy. Radiation therapy for 2 weeks (300 cGy given 10 times up to 3000 cGy) followed by a 3 weeks rest period and then radiation therapy for 2 more weeks (250 cGy given 10 times up to 2500 cGy) was combined with $6mg/m^2$ of cisplatin. Follow-up period ranged from 13 months to 48 months with median of 24 months. Historical control group consisted of 32 patients who had stage III non-small cell lung cancer were received conventionally fractionated (daily 170-200 cGy) radiation therapy alone. Total radiation dose ranged from 5580 cGy to 7000 cGy with median of 5940 cGy. Follow-up Period ranged from 36 months to 105 months with median of 62 months. Result : Complete reponse rate was higher in chemoradiation therapy (CRT) group than radiation therapy (RT) group (18.8% vs. 6.3%, CRT group showed lower in-field failure rate compared with RT group(25% vs. 47%. The overall survival rate had no significant differences in between CRT group and RT group (17.5% vs. 9.4% at 2 years). The survival without locoregional failure (16.5% vs. 5.3% at 2 years) and survival without distant metastasis (17% vs. 4.6% at 2 years) also had no significant differences. In subgroup analyses for Patients with good performance status (Karnofsky performance scale 80), CRT group showed significantly higher overall survival rate compared with RT group (62.5% vs. 15.6% at 2 years). The prognostic factors affecting survival rate were performance status and pathologic subtype (squamous cell cancer vs. nonsquamous cell cancer) in CRT group. In RT alone group, performance status and stage (IIIa vs IIIb) were identified as a Prognostic factors. RTOG/EORTC grade 2-3 nausea and vomiting(22% vs 6% and bone marrow toxicities (25% vs. 15.6% were significantly higher in CRT group compared with RT alone group. The incidence of RTOG/EORTC grade 3-4 pulmonary toxicity had no significant differences in between CRT group and RT group (16% vs. 6%. The incidence of WHO grade 3-4 pulmonary fibrosis also had no significant differences in both group (38% vs. 25%. In analyses for relationship of field size and Pulmonary toxicity, the Patients who treated with field size beyond 200cm2 had significantly higher rates of pulmonary toxicities. Conclusion : The CRT group showed significantly higher local control rate than RT group. There were no significant differences of survival rate in between two groups. The subgroup of patients who had good performance status showed higher overall survival rate in CRT group than RT group. In spite of higher incidence of acute toxicities with concurrent chemoradiation therapy, the survival gain in subgroup of patients with good performance status were encouraging. CRT group showed higher rate of early death within 1 year, higher 2 year survival rate compared with RT group Therefore, to evaluate the accurate effect on survival of concurrent chemoradiation therapy, systematic follow-up for long term survivors are needed.