• Journal of Korean Home Economics Education Association
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• v.30 no.2
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• pp.39-56
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• 2018

The purpose of this study was to develop Home Economics(HE) teaching and learning process plans applied Problem Based Learning(PBL) focusing on 'food and nutrition' unit for students with intellectual disability and to evaluate the effects of the HE instruction on their food choice·management knowledge and problem-solving skills after implementing the instruction for students with intellectual disability. To develop HE teaching and learning process plans applied PBL focusing on 'food and nutrition' unit for students with intellectual disability, problems that arise in daily life to trigger interest of students were firstly developed. The selected problems and teaching and learning process plans were reviewed for validity by one home economics education professor and three teachers who are experts in special education. This study used the one group pretest and posttest design, sampling 6 students who are in special-education middle school with the intellectual disability. After HE instruction of 6 sessions applied PBL method, this study tested the effects of the instruction. The first three sessions taught how to choose and keep food. The fourth session taught purchasing food ingredients and keeping them for sandwiches. The fifth and sixth sessions let the students make sandwiches and give them to others. The instruments of the study comprised of tools for food choice and management knowledge, tools for problem-solving skills evaluation, self-evaluation sheets, evaluation form of course satisfaction for students, evaluation form of behavior in class for teachers, and daily observation journal and all tools. These instruments were proved to have reliability and validity. The results of this study are as follows. First, all six students who took HE instruction applied PBL method focusing on 'food and nutrition' unit scored 30 points higher out of 100 points after taking the instruction in food choice and management knowledge and scored 5 points higher out of 14 points in problem-solving skills on average. Therefore, it was interpreted that HE instruction applied PBL affected the food choice·management knowledge and the problem solving skills of students with intellectual disability. Secondly, the students with intellectual disability participated actively in HE instruction applied PBL focusing on 'food and nutrition' unit and expressed satisfaction. Three special education experts evaluated HE teaching·learning process plans applied PBL focusing on 'food and nutrition' unit to be well-developed. This study showed that HE instruction applied PBL focusing on 'food and nutrition' unit allowed the students with intellectual disability to acquire comprehensive skills in choosing, keeping, and making safe food and helped them solve problems of their life by themselves. Therefore I suggest that Home Economics should be adopted as a formal subject matter in special school curriculum for students with intellectual disability.

• Journal of the Korean Society of Food Science and Nutrition
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• v.42 no.3
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• pp.464-477
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• 2013

There is a great need to develop a training program proven to change behavior and improve knowledge. The purpose of this study was to evaluate employee hygiene knowledge, hygiene practice, and cleanliness, before and after HACCP system implementation at one small-size restaurant. The efficiency of the system was analyzed using time-temperature control after implementation of u-HACCP$^{(R)}$. The employee hygiene knowledge and practices showed a significant improvement (p<0.05) after HACCP system implementation. In non-heating processes, such as seasoned lettuce, controlling the sanitation of the cooking facility and the chlorination of raw ingredients were identified as the significant CCP. Sanitizing was an important CCP because total bacteria were reduced 2~4 log CFU/g after implementation of HACCP. In bean sprouts, microbial levels decreased from 4.20 logCFU/g to 3.26 logCFU/g. There were significant correlations between hygiene knowledge, practice, and microbiological contamination. First, personnel hygiene had a significant correlation with 'total food hygiene knowledge' scores (p<0.05). Second, total food hygiene practice scores had a significant correlation (p<0.05) with improved microbiological qualities of lettuce salad. Third, concerning the assessment of microbiological quality after 1 month, there were significant (p<0.05) improvements in times of heating, and the washing and division process. On the other hand, after 2 months, microbiological was maintained, although only two categories (division process and kitchen floor) were improved. This study also investigated time-temperature control by using ubiquitous sensor networks (USN) consisting of an ubi reader (CCP thermometer), an ubi manager (tablet PC), and application software (HACCP monitoring system). The result of the temperature control before and after USN showed better thermal management (accuracy, efficiency, consistency of time control). Based on the results, strict time-temperature control could be an effective method to prevent foodborne illness.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.2
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• pp.117-121
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• 2010

Purpose: In nuclear medicine study, there are two methods, preset count method and preset time method, to acquire static images. We usually use preset count method for static image in $^{99m}Tc$-DMSA renal scan, but occasionally use preset time method. In case of using preset count method, we always acquire same counts but it causes a difference of scan time. In case of using preset time method, it takes same scan time to acquire images but it causes different counts. Therefore, the purpose of this study is to investigate any differences of function and formal information in both kidney by acquisition counts Materials and Methods: From January 11, 2010 to March 31, 2010, we analyzed the 30 patients (M: 11, W: 19). who were examined by $^{99m}Tc$-DMSA scan and have one side of functioning kidney relatively between 40~60%. And the patients who have cold and hot region in image were analyzed but we did not accept images of patients when it was hard to divide kidney into cortex. There was no division between subjects and age of subjects is $14.83{\pm}22.07$ old. We used the BrightView gamma camera from PHILIPS. To analyze function and formal of kidney, we used JET stream release 3.0 version from PHILIPS. Using SPSS 12.0 program, we compared descriptive statistics and paired T-test. Images were acquired sequentially in the same parameters, but there are three methods which different from acquisition time and scan time, 100 kcounts, 300 kcounts and 7 minutes method (exceed 300 kcounts). To assess function and formal information of kidney, we measured renal relative function, geometric mean and size of kidney and analyzed each difference. Results: In case of renal relative function in both kidney, 100 kcounts method was $50.52{\pm}3.64%$. 300 kcounts method was $50.38{\pm}3.66%$ and 7 minutes method was $49.91{\pm}3.40%$ and there were no statistical significant differences between each method. In case of geometric mean, 100 kcounts method was $50.08{\pm}3.25%$. 300 kcounts method was $49.89{\pm}3.40%$ and 7 minutes method was $49.91{\pm}3.24%$. And also, there were no statistical significant differences. When comparing size of kidney, 100 kcounts method was $8.23{\pm}1.96$ cm. 300 kcounts method was $8.12{\pm}1.90$ cm and 7 minutes method was $8.35{\pm}1.97$ cm. In case of right kidney, 100 kcounts method was $7.91{\pm}1.88$ cm. 300 kcounts method was $8.12{\pm}1.90$ cm and 7 minutes method was $8.25{\pm}1.96$ cm. From those values, we recognized that there were significant differences each method (p<0.05). Conclusion: From results of this study, there were no statistical differences in renal relative function and geometric mean by acquisition counts. However, in shape of kidney, the more acquisition counts are increasing, the more size of kidney is getting big. And there were statistical significant differences. Therefore, to perform reliable quantitative result, preset count method is more desirable than preset time method. Especially, in case of a follow-up test, if we use preset time method, it will cause differences of formal results in kidney due to acquisition counts each time we examine patients.

• The Korean Journal of Nuclear Medicine Technology
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• v.20 no.2
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• pp.3-8
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• 2016

Purpose SUV is one of the parameters that assist diagnosis in origin, metastasis and staging of cancer. Specially, it is important to compare SUV before and after chemo or radiation therapy to find out effectiveness of treatment. Storing PET data which has no quantitative change is needed for SUV comparison. However, there is a possibility to loss the data in external hard drive or MINIpacs that are managed by department of nuclear medicine. The aim of this study is to evaluate SUV and metabolic tumor volume (MTV) among reconstructed data (R-D) in workstation, R-D and re-sliced data (S-D) in PACS. Materials and Methods Data of 20 patients (aged $60.5{\pm}8.3y$) underwent $^{18}F-FDG$ PET (Biograph truepoint 40, mCT 40, mCT 64, mMR, Siemens) study were analysed. $SUV_{max}$, $SUV_{peak}$ and MTV were measured in liver, aorta and tumor after sending R-D in workstation, R-D and S-D in PACS to syngo.via software. Results R-D of workstation and PACS showed the same value as mean $SUV_{max}$ in liver, aorta and tumor were $2.95{\pm}0.59$, $2.35{\pm}0.61$, $10.36{\pm}6.15$ and $SUV_{peak}$ were $2.70{\pm}0.51$, $2.07{\pm}0.43$, $7.67{\pm}3.73$(p>0.05) respectively. Mean $SUV_{max}$ of S-D in PACS were decreased by 5.18%, 7.22%, 12.11% and $SUV_{peak}$ 2.61%, 3.63%, 10.07%(p<0.05). Correlation between R-D and S-D were $SUV_{max}$ 0.99, 0.96, 0.99 and $SUV_{peak}$ 0.99, 0.99, 0.99. And 2SD in balnd-altman analysis were $SUV_{max}$ 0.125, 0.290, 1.864 and $SUV_{peak}$ 0.053, 0.103, 0.826. MTV of R-D in workstation and PACS show the same value as $14.21{\pm}12.72cm^3$(p>0.05). MTV in PACS was decreased by 0.12% compared to R-D(p>0.05). Correlation and 2SD between R-D and S-D were 0.99 and 2.243. Conclusion $SUV_{max}$, $SUV_{peak}$, MTV showed the same value in both of R-D in workstation and PACS. However, there was statistically difference in $SUV_{max}$, $SUV_{peak}$ of S-D compare to R-D despite of high correlation. It is possible to analyse reliable pre and post SUV if storing R-D in main hospital PACS system.

• The Journal of Korean Society for Radiation Therapy
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• v.26 no.1
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• pp.137-147
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• 2014

Purpose : The purpose of this study is to verify the accuracy of dose delivery according to the patient's breathing cycle in Gated Volumetric Modulated Arc Therapy Materials and Methods : TrueBeam STxTM(Varian Medical System, Palo Alto, CA) was used in this experiment. The Computed tomography(CT) images that were acquired with RANDO Phantom(Alderson Research Laboratories Inc. Stamford. CT, USA), using Computerized treatment planning system(Eclipse 10.0, Varian, USA), were used to create VMAT plans using 10MV FFF with 1500 cGy/fx (case 1, 2, 3) and 220 cGy/fx(case 4, 5, 6) of doserate of 1200 MU/min. The regular respiratory period of 1.5, 2.5, 3.5 and 4.5 sec and the patients respiratory period of 2.2 and 3.5 sec were reproduced with the $QUASAR^{TM}$ Respiratory Motion Phantom(Modus Medical Devices Inc), and it was set up to deliver radiation at the phase mode between the ranges of 30 to 70%. The results were measured at respective respiratory conditions by a 2-Dimensional ion chamber array detector(I'mRT Matrixx, IBA Dosimetry, Germany) and a MultiCube Phantom(IBA Dosimetry, Germany), and the Gamma pass rate(3 mm, 3%) were compared by the IMRT analysis program(OmniPro I'mRT system software Version 1.7b, IBA Dosimetry, Germany) Results : The gamma pass rates of Case 1, 2, 3, 4, 5 and 6 were the results of 100.0, 97.6, 98.1, 96.3, 93.0, 94.8% at a regular respiratory period of 1.5 sec and 98.8, 99.5, 97.5, 99.5, 98.3, 99.6% at 2.5 sec, 99.6, 96.6, 97.5, 99.2, 97.8, 99.1% at 3.5 sec and 99.4, 96.3, 97.2, 99.0, 98.0, 99.3% at 4.5 sec, respectively. When a patient's respiration was reproduced, 97.7, 95.4, 96.2, 98.9, 96.2, 98.4% at average respiratory period of 2.2 sec, and 97.3, 97.5, 96.8, 100.0, 99.3, 99.8% at 3.5 sec, respectively. Conclusion : The experiment showed clinically reliable results of a Gamma pass rate of 95% or more when 2.5 sec or more of a regular breathing period and the patient's breathing were reproduced. While it showed the results of 93.0% and 94.8% at a regular breathing period of 1.5 sec of Case 5 and 6, it could be confirmed that the accurate dose delivery could be possible on the most respiratory conditions because based on the results of 100 patients's respiratory period analysis as no one sustained a respiration of 1.5 sec. But, pretreatment dose verification should be precede because we can't exclude the possibility of error occurrence due to extremely short respiratory period, also a training at the simulation and careful monitoring are necessary for a patient to maintain stable breathing. Consequently, more reliable and accurate treatments can be administered.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.53-77
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• 2012

This study analyses the difference of contents and tones of arguments among three Korean major newspapers, the Kyunghyang Shinmoon, the HanKyoreh, and the Dong-A Ilbo. It is commonly accepted that newspapers in Korea explicitly deliver their own tone of arguments when they talk about some sensitive issues and topics. It could be controversial if readers of newspapers read the news without being aware of the type of tones of arguments because the contents and the tones of arguments can affect readers easily. Thus it is very desirable to have a new tool that can inform the readers of what tone of argument a newspaper has. This study presents the results of clustering and classification techniques as part of text mining analysis. We focus on six main subjects such as Culture, Politics, International, Editorial-opinion, Eco-business and National issues in newspapers, and attempt to identify differences and similarities among the newspapers. The basic unit of text mining analysis is a paragraph of news articles. This study uses a keyword-network analysis tool and visualizes relationships among keywords to make it easier to see the differences. Newspaper articles were gathered from KINDS, the Korean integrated news database system. KINDS preserves news articles of the Kyunghyang Shinmun, the HanKyoreh and the Dong-A Ilbo and these are open to the public. This study used these three Korean major newspapers from KINDS. About 3,030 articles from 2008 to 2012 were used. International, national issues and politics sections were gathered with some specific issues. The International section was collected with the keyword of 'Nuclear weapon of North Korea.' The National issues section was collected with the keyword of '4-major-river.' The Politics section was collected with the keyword of 'Tonghap-Jinbo Dang.' All of the articles from April 2012 to May 2012 of Eco-business, Culture and Editorial-opinion sections were also collected. All of the collected data were handled and edited into paragraphs. We got rid of stop-words using the Lucene Korean Module. We calculated keyword co-occurrence counts from the paired co-occurrence list of keywords in a paragraph. We made a co-occurrence matrix from the list. Once the co-occurrence matrix was built, we used the Cosine coefficient matrix as input for PFNet(Pathfinder Network). In order to analyze these three newspapers and find out the significant keywords in each paper, we analyzed the list of 10 highest frequency keywords and keyword-networks of 20 highest ranking frequency keywords to closely examine the relationships and show the detailed network map among keywords. We used NodeXL software to visualize the PFNet. After drawing all the networks, we compared the results with the classification results. Classification was firstly handled to identify how the tone of argument of a newspaper is different from others. Then, to analyze tones of arguments, all the paragraphs were divided into two types of tones, Positive tone and Negative tone. To identify and classify all of the tones of paragraphs and articles we had collected, supervised learning technique was used. The Na$\ddot{i}$ve Bayesian classifier algorithm provided in the MALLET package was used to classify all the paragraphs in articles. After classification, Precision, Recall and F-value were used to evaluate the results of classification. Based on the results of this study, three subjects such as Culture, Eco-business and Politics showed some differences in contents and tones of arguments among these three newspapers. In addition, for the National issues, tones of arguments on 4-major-rivers project were different from each other. It seems three newspapers have their own specific tone of argument in those sections. And keyword-networks showed different shapes with each other in the same period in the same section. It means that frequently appeared keywords in articles are different and their contents are comprised with different keywords. And the Positive-Negative classification showed the possibility of classifying newspapers' tones of arguments compared to others. These results indicate that the approach in this study is promising to be extended as a new tool to identify the different tones of arguments of newspapers.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.1
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• pp.1-9
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• 2006

Regardless of the recent observed warmer winters in Korea, more freeze injuries and associated economic losses are reported in fruit industry than ever before. Existing freeze-frost forecasting systems employ only daily minimum temperature for judging the potential damage on dormant flowering buds but cannot accommodate potential biological responses such as short-term acclimation of plants to severe weather episodes as well as annual variation in climate. We introduce 'dormancy depth', in addition to daily minimum temperature, as a complementary criterion for judging the potential damage of freezing temperatures on dormant flowering buds of grape vines. Dormancy depth can be estimated by a phonology model driven by daily maximum and minimum temperature and is expected to make a reasonable proxy for physiological tolerance of buds to low temperature. Dormancy depth at a selected site was estimated for a climatological normal year by this model, and we found a close similarity in time course change pattern between the estimated dormancy depth and the known cold tolerance of fruit trees. Inter-annual and spatial variation in dormancy depth were identified by this method, showing the feasibility of using dormancy depth as a proxy indicator for tolerance to low temperature during the winter season. The model was applied to 10 vineyards which were recently damaged by a cold spell, and a temperature-dormancy depth-freeze injury relationship was formulated into an exponential-saturation model which can be used for judging freeze risk under a given set of temperature and dormancy depth. Based on this model and the expected lowest temperature with a 10-year recurrence interval, a freeze risk probability map was produced for Hwaseong County, Korea. The results seemed to explain why the vineyards in the warmer part of Hwaseong County have been hit by more freeBe damage than those in the cooler part of the county. A dormancy depth-minimum temperature dual engine freeze warning system was designed for vineyards in major production counties in Korea by combining the site-specific dormancy depth and minimum temperature forecasts with the freeze risk model. In this system, daily accumulation of thermal time since last fall leads to the dormancy state (depth) for today. The regional minimum temperature forecast for tomorrow by the Korea Meteorological Administration is converted to the site specific forecast at a 30m resolution. These data are input to the freeze risk model and the percent damage probability is calculated for each grid cell and mapped for the entire county. Similar approaches may be used to develop freeze warning systems for other deciduous fruit trees.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.5 no.1
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• pp.8-15
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• 1995

The reliable measurement of metal in biological media in human body is one of critical indicators for the proper evaluation of its toxic effect on human health. Recently in Korea the necessity of quality assurance of measurement in occupational health and occupational hygiene fields brought out regulatory quality control program. Lead is often used as a standard metal for the program in both fields of occupational health and hygiene. During last 20 years lead poisoning was prevalent in Korea and still is one of main heavy metal poisoning and the capability of the measurement of blood lead is one of prerequisites for institute of specialized occupational health in Korea. Furthermore blood lead is most important indicator to evaluate lead burden of human exposure to lead and the reliable and accurate analysis is most needed whenever possible. To evaluate the extent of the interlaboratory differences of blood lead measurement in several well-known institute specialized in occupational health in Korea, authors prepared 68 blood samples from two storage battery industries and all samples were divided into samples with 2 ml. One set of 68 samples were analyzed by authors's laboratory(Soonchunhyang University Institute of Industrial Medicine: SIIM) and 40 samples of other set were analyzed by C University Institute of Industrial Medicine(CIIM) and the rest 28 samples of other set were analyzed by Japanese institute(K Occupational Health Center:KOHC). Authors also prepared test bovine samples which were obtained from Japanese Federation of Occupational Health Organization (JFOHO) for quality control. Authors selected 2 other well-known occupational health laboratories and one laboratory specialized for instrumental analysis. A total of 6 laboratories joined the interlaboratory comparison of blood lead measurement and the results obtained were as follows: 1. There was no significant difference in average blood lead between SIIM and CIIM in different group of blood lead concentration, and the relative standard deviation of two laboratories was less than 3.0%. On the other hand, there was also no significant difference of average blood lead between SIIM and KOHC with relative standard deviation of 6.84% as maximum. 2. Taking less than 15% difference of mean or less than 6 ug/dl difference in below 40 ug/dl in whole blood as a criteria of agreement of measurement between two laboratories, agreement rates were 87.5%(35/40) and 78.6%(22/28) between SIIM and CIIM, SIIM and KOHC respectively. 3. The correlation of blood lead between SIIM and CIIM was 0.975 (p=0.0001) and the regression equation was SIIM = 2.19 + 0.9243 ClIM, whereas the correlation between SUM and KOHC was O.965(p=0.0001) with the equation of SIIM = 1.91 + 0.9794 KOHC. 4. Taking the reference value as a dependent variable and each of 6 laboratories's measurement value as a independent variable, the determination coefficient($R^2$) of simple regression equations of blood lead measurement for bovine test samples were very high($R^2>0.99$), and the regression coefficient(${\beta}$) was between 0.972 and 1.15 which indicated fairly good agreement of measurement results.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.1-20
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• 2013

Nowadays, social network is a huge communication platform for providing people to connect with one another and to bring users together to share common interests, experiences, and their daily activities. Users spend hours per day in maintaining personal information and interacting with other people via posting, commenting, messaging, games, social events, and applications. Due to the growth of user's distributed information in social network, there is a great potential to utilize the social data to enhance the quality of recommender system. There are some researches focusing on social network analysis that investigate how social network can be used in recommendation domain. Among these researches, we are interested in taking advantages of the interaction between a user and others in social network that can be determined and known as social relationship. Furthermore, mostly user's decisions before purchasing some products depend on suggestion of people who have either the same preferences or closer relationship. For this reason, we believe that user's relationship in social network can provide an effective way to increase the quality in prediction user's interests of recommender system. Therefore, social relationship between users encountered from social network is a common factor to improve the way of predicting user's preferences in the conventional approach. Recommender system is dramatically increasing in popularity and currently being used by many e-commerce sites such as Amazon.com, Last.fm, eBay.com, etc. Collaborative filtering (CF) method is one of the essential and powerful techniques in recommender system for suggesting the appropriate items to user by learning user's preferences. CF method focuses on user data and generates automatic prediction about user's interests by gathering information from users who share similar background and preferences. Specifically, the intension of CF method is to find users who have similar preferences and to suggest target user items that were mostly preferred by those nearest neighbor users. There are two basic units that need to be considered by CF method, the user and the item. Each user needs to provide his rating value on items i.e. movies, products, books, etc to indicate their interests on those items. In addition, CF uses the user-rating matrix to find a group of users who have similar rating with target user. Then, it predicts unknown rating value for items that target user has not rated. Currently, CF has been successfully implemented in both information filtering and e-commerce applications. However, it remains some important challenges such as cold start, data sparsity, and scalability reflected on quality and accuracy of prediction. In order to overcome these challenges, many researchers have proposed various kinds of CF method such as hybrid CF, trust-based CF, social network-based CF, etc. In the purpose of improving the recommendation performance and prediction accuracy of standard CF, in this paper we propose a method which integrates traditional CF technique with social relationship between users discovered from user's behavior in social network i.e. Facebook. We identify user's relationship from behavior of user such as posts and comments interacted with friends in Facebook. We believe that social relationship implicitly inferred from user's behavior can be likely applied to compensate the limitation of conventional approach. Therefore, we extract posts and comments of each user by using Facebook Graph API and calculate feature score among each term to obtain feature vector for computing similarity of user. Then, we combine the result with similarity value computed using traditional CF technique. Finally, our system provides a list of recommended items according to neighbor users who have the biggest total similarity value to the target user. In order to verify and evaluate our proposed method we have performed an experiment on data collected from our Movies Rating System. Prediction accuracy evaluation is conducted to demonstrate how much our algorithm gives the correctness of recommendation to user in terms of MAE. Then, the evaluation of performance is made to show the effectiveness of our method in terms of precision, recall, and F1-measure. Evaluation on coverage is also included in our experiment to see the ability of generating recommendation. The experimental results show that our proposed method outperform and more accurate in suggesting items to users with better performance. The effectiveness of user's behavior in social network particularly shows the significant improvement by up to 6% on recommendation accuracy. Moreover, experiment of recommendation performance shows that incorporating social relationship observed from user's behavior into CF is beneficial and useful to generate recommendation with 7% improvement of performance compared with benchmark methods. Finally, we confirm that interaction between users in social network is able to enhance the accuracy and give better recommendation in conventional approach.