• Asia pacific journal of information systems
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• v.24 no.2
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• pp.211-232
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• 2014

Recently, there is a growing interest toward social commerce using SNS(Social Networking Service), and the size of its market is also expanding due to popularization of smart phones, tablet PCs and other smart devices. Accordingly, various studies have been attempted but it is shown that most of the previous studies have been conducted from perspectives of the users. The purpose of this study is to derive user-centered CSF(Critical Success Factor) of social commerce from the previous studies and analyze the CSF perception gap between social commerce service providers and users. The CSF perception gap between two groups shows that there is a difference between ideal images the service providers hope for and the actual image the service users have on social commerce companies. This study provides effective improvement directions for social commerce companies by presenting current business problems and its solution plans. For this, This study selected Korea's representative social commerce business Ticket Monster, which is dominant in sales and staff size together with its excellent funding power through M&A by stock exchange with the US social commerce business Living Social with Amazon.com as a shareholder in August, 2011, as a target group of social commerce service provider. we have gathered questionnaires from both service providers and the users from October 22, 2012 until October 31, 2012 to conduct an empirical analysis. We surveyed 160 service providers of Ticket Monster We also surveyed 160 social commerce users who have experienced in using Ticket Monster service. Out of 320 surveys, 20 questionaries which were unfit or undependable were discarded. Consequently the remaining 300(service provider 150, user 150)were used for this empirical study. The statistics were analyzed using SPSS 12.0. Implications of the empirical analysis result of this study are as follows: First of all, There are order differences in the importance of social commerce CSF between two groups. While service providers regard Price Economic as the most important CSF influencing purchasing intention, the users regard 'Trust' as the most important CSF influencing purchasing intention. This means that the service providers have to utilize the unique strong point of social commerce which make the customers be trusted rathe than just focusing on selling product at a discounted price. It means that service Providers need to enhance effective communication skills by using SNS and play a vital role as a trusted adviser who provides curation services and explains the value of products through information filtering. Also, they need to pay attention to preventing consumer damages from deceptive and false advertising. service providers have to create the detailed reward system in case of a consumer damages caused by above problems. It can make strong ties with customers. Second, both service providers and users tend to consider that social commerce CSF influencing purchasing intention are Price Economic, Utility, Trust, and Word of Mouth Effect. Accordingly, it can be learned that users are expecting the benefit from the aspect of prices and economy when using social commerce, and service providers should be able to suggest the individualized discount benefit through diverse methods using social network service. Looking into it from the aspect of usefulness, service providers are required to get users to be cognizant of time-saving, efficiency, and convenience when they are using social commerce. Therefore, it is necessary to increase the usefulness of social commerce through the introduction of a new management strategy, such as intensification of search engine of the Website, facilitation in payment through shopping basket, and package distribution. Trust, as mentioned before, is the most important variable in consumers' mind, so it should definitely be managed for sustainable management. If the trust in social commerce should fall due to consumers' damage case due to false and puffery advertising forgeries, it could have a negative influence on the image of the social commerce industry in general. Instead of advertising with famous celebrities and using a bombastic amount of money on marketing expenses, the social commerce industry should be able to use the word of mouth effect between users by making use of the social network service, the major marketing method of initial social commerce. The word of mouth effect occurring from consumers' spontaneous self-marketer's duty performance can bring not only reduction effect in advertising cost to a service provider but it can also prepare the basis of discounted price suggestion to consumers; in this context, the word of mouth effect should be managed as the CSF of social commerce. Third, Trade safety was not derived as one of the CSF. Recently, with e-commerce like social commerce and Internet shopping increasing in a variety of methods, the importance of trade safety on the Internet also increases, but in this study result, trade safety wasn't evaluated as CSF of social commerce by both groups. This study judges that it's because both service provider groups and user group are perceiving that there is a reliable PG(Payment Gateway) which acts for e-payment of Internet transaction. Accordingly, it is understood that both two groups feel that social commerce can have a corporate identity by website and differentiation in products and services in sales, but don't feel a big difference by business in case of e-payment system. In other words, trade safety should be perceived as natural, basic universal service. Fourth, it's necessary that service providers should intensify the communication with users by making use of social network service which is the major marketing method of social commerce and should be able to use the word of mouth effect between users. The word of mouth effect occurring from consumers' spontaneous self- marketer's duty performance can bring not only reduction effect in advertising cost to a service provider but it can also prepare the basis of discounted price suggestion to consumers. in this context, it is judged that the word of mouth effect should be managed as CSF of social commerce. In this paper, the characteristics of social commerce are limited as five independent variables, however, if an additional study is proceeded with more various independent variables, more in-depth study results will be derived. In addition, this research targets social commerce service providers and the users, however, in the consideration of the fact that social commerce is a two-sided market, drawing CSF through an analysis of perception gap between social commerce service providers and its advertisement clients would be worth to be dealt with in a follow-up study.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.71-88
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• 2017

Language models were originally developed for speech recognition and language processing. Using a set of example sentences, a language model predicts the next word or character based on sequential input data. N-gram models have been widely used but this model cannot model the correlation between the input units efficiently since it is a probabilistic model which are based on the frequency of each unit in the training set. Recently, as the deep learning algorithm has been developed, a recurrent neural network (RNN) model and a long short-term memory (LSTM) model have been widely used for the neural language model (Ahn, 2016; Kim et al., 2016; Lee et al., 2016). These models can reflect dependency between the objects that are entered sequentially into the model (Gers and Schmidhuber, 2001; Mikolov et al., 2010; Sundermeyer et al., 2012). In order to learning the neural language model, texts need to be decomposed into words or morphemes. Since, however, a training set of sentences includes a huge number of words or morphemes in general, the size of dictionary is very large and so it increases model complexity. In addition, word-level or morpheme-level models are able to generate vocabularies only which are contained in the training set. Furthermore, with highly morphological languages such as Turkish, Hungarian, Russian, Finnish or Korean, morpheme analyzers have more chance to cause errors in decomposition process (Lankinen et al., 2016). Therefore, this paper proposes a phoneme-level language model for Korean language based on LSTM models. A phoneme such as a vowel or a consonant is the smallest unit that comprises Korean texts. We construct the language model using three or four LSTM layers. Each model was trained using Stochastic Gradient Algorithm and more advanced optimization algorithms such as Adagrad, RMSprop, Adadelta, Adam, Adamax, and Nadam. Simulation study was done with Old Testament texts using a deep learning package Keras based the Theano. After pre-processing the texts, the dataset included 74 of unique characters including vowels, consonants, and punctuation marks. Then we constructed an input vector with 20 consecutive characters and an output with a following 21st character. Finally, total 1,023,411 sets of input-output vectors were included in the dataset and we divided them into training, validation, testsets with proportion 70:15:15. All the simulation were conducted on a system equipped with an Intel Xeon CPU (16 cores) and a NVIDIA GeForce GTX 1080 GPU. We compared the loss function evaluated for the validation set, the perplexity evaluated for the test set, and the time to be taken for training each model. As a result, all the optimization algorithms but the stochastic gradient algorithm showed similar validation loss and perplexity, which are clearly superior to those of the stochastic gradient algorithm. The stochastic gradient algorithm took the longest time to be trained for both 3- and 4-LSTM models. On average, the 4-LSTM layer model took 69% longer training time than the 3-LSTM layer model. However, the validation loss and perplexity were not improved significantly or became even worse for specific conditions. On the other hand, when comparing the automatically generated sentences, the 4-LSTM layer model tended to generate the sentences which are closer to the natural language than the 3-LSTM model. Although there were slight differences in the completeness of the generated sentences between the models, the sentence generation performance was quite satisfactory in any simulation conditions: they generated only legitimate Korean letters and the use of postposition and the conjugation of verbs were almost perfect in the sense of grammar. The results of this study are expected to be widely used for the processing of Korean language in the field of language processing and speech recognition, which are the basis of artificial intelligence systems.

• Journal of Global Scholars of Marketing Science
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• v.18 no.2
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• pp.65-88
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• 2008

Since the implementation of economic reforms in 1978, the Chinese economy grows rapidly at an average annul growth rate of 9% over the post two decades. Franchising has been widely recognized as an important source of entrepreneurial activity. Trust is important in that it facilitates relational exchanges by permits partners to transcend short-run inequities or risks to concentrate on long-term profits or gains. In the relationship between the franchisors and franchisees, trust has been described as an important source of competitive advantage. However, little research has been done on the factors affecting trust in Chinese franchisor-franchisee relationships. The purpose of this study is to investigate what factors affect the trust in the franchise system in China, and to provide guidelines and insights to franchisors which enter Chinese market. In this study, according to Morgan and Hunt (1994), trust is defined as the extending when one party has confidence in an exchange partner's reliability and integrity. We offered a conceptual model of the empirical study. The model shows that the factors affecting the trust include franchisor's supports, communication, satisfaction with previous outcome and conflict. We also suggested the franchisor's supports and communication like to enhance the franchisee's satisfaction with previous outcome, and the franchisor's supports, communication and he franchisee's satisfaction with previous outcome tend to decrease conflict. Before the formal study, a pretest involving exploratory interviews with owners from three franchisees was conducted to make sure the questionnaire was relevant and clear to the respondents. The data were collected using trained interviewers to carry out personal interviews with the aid of an unidentified, muti-page, structured questionnaire. The respondents comprised of owners, managers, and owner managers of franchisee-owned food service franchises located in Beijing, China. Even though a total of 256 potential franchises were initially contacted, the finally usable sample consisted of 125 respondents. As expected, the sampling method was successful in soliciting respondents with waried personal and firm characteristics. Self-administrated questionnaires were used for all measures. And established scales were used to measure the latent constructs in this study. The measures tapped the franchisees' perceptions of the relationship with the referent franchisor. Five-point Likert-type scales ranging from "strongly disagree" (=1) to "strongly agree" (=7) were used throughout the constructs (trust, eight items; support, five items; communication, four items; satisfaction, six items; conflict, three items). The reliability measurements traditionally employed, such as the Cronbach's alpha, were used. All the reliabilities were greater than.80. The proposed measurement model was estimated using SPSS 12.0 and AMOS 5.0 analysis package. We conducted A series of exploratory factor analyses and confirmatory factor analyses to assess the convergent validity, discriminant validity, and reliability. The results indicate reasonable overall fits between the model and the observed data. The overall fit of measurement model were $X^2$= 159.699, p=0.004, d.f. = 116, GFI =.879, NFI =.898, CFI =.969, IFI =.970, TLI =.959, RMR =.058. The results demonstrated that the data reasonably fitted the model. We also examined construct reliability and reliability and average variance extracted (AVE). The construct reliability of each construct was greater than.80 and the AVE of each construct was greater than.50. According to the analysis of Structure Equation Modeling (SEM), the results of path model indicated an adequate fit of the model: $X^2$= 142.126, p = 0.044, d.f. = 115, GFI =.892, NFI =.909, CFI =.981, IFI =.981, TLI =.974, RMR =.057. As hypothesized, the results showed that it is strategically important to establish trust in a franchise system, and the franchisor's supports, communication and satisfaction with previous outcome tend to reinforce franchisee's trust. The results also showed trust seems to decrease as the experience of conflict episodes increases. And we also noticed that franchisor's supports and communication tend to enhance the franchisee's satisfaction with previous outcome, and communication tend to decrease conflict. If the trust between the franchisor and franchisee can be established in a franchise system, franchising offers many benefits and reduces many costs. To manage a mutual trust of relationship with their franchisees, franchisor's should provide support effectively to their franchisees. Effective assistant services have direct effect on franchisees' satisfaction with previous outcome and trust in franchisor. Especially, franchise sales process, orientation, and training in the start-up period are key elements for success of the franchise system. Franchisor's support is an accumulated separate satisfaction evaluation with different kind of service provided by the franchisor. And providing support definitely can improve the trustworthy image of the franchisor. In the franchise system, conflicts of interests and exertions of different power sources are very common. The experience of conflict episodes seems to negatively relate to trust. Therefore, it is important to reduce the negative side of the relationship conflicts. Communication actually plays a broader role in reducing conflict and establish mutual trust in franchisor-franchisee relationship. And effective communication between franchisors and franchisees can improve franchisees' satisfaction toward the franchise system. As the diversification of Chinese markets, both franchisors and franchisees must keep the relevant, timely, and reliable communication. And it is very important to improve the quality of communication. Satisfaction with precious outcomes seems to positively relate to trust. Franchisors and franchisees that are highly satisfied with the previous outcomes that flow from their relationship will perceive their partner as advancing their goal achievement. Therefore, it is necessary for both franchisor and their franchisees to make the welfare of partner with effort. Little literature has focused on what factors affect the trust between franchisors and their franchisees in China. This study developed the hypotheses regarding the factors affecting trust in the transaction relationship. The results of data analysis supported the hypotheses strongly. There are certain limitations in this study. First, we may point out that some other factors missed in this study could be significantly important. Second, the context of this study, food service industry, limits its potential generalizability for all franchise systems. More studies in different categories of franchise system are needed to broaden its generalizability. Third, the model was tested empirically in a sample in Beijing, more empirical tests of the proposed model in other Chinese areas are needed. Finally, the analysis in this study was solely based on the perception of franchisees and the opinions of franchisors were not included.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.111-136
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• 2018

In this paper, we propose a methodology to extract answer information about queries from various types of unstructured documents collected from multi-sources existing on web in order to expand knowledge base. The proposed methodology is divided into the following steps. 1) Collect relevant documents from Wikipedia, Naver encyclopedia, and Naver news sources for "subject-predicate" separated queries and classify the proper documents. 2) Determine whether the sentence is suitable for extracting information and derive the confidence. 3) Based on the predicate feature, extract the information in the proper sentence and derive the overall confidence of the information extraction result. In order to evaluate the performance of the information extraction system, we selected 400 queries from the artificial intelligence speaker of SK-Telecom. Compared with the baseline model, it is confirmed that it shows higher performance index than the existing model. The contribution of this study is that we develop a sequence tagging model based on bi-directional LSTM-CRF using the predicate feature of the query, with this we developed a robust model that can maintain high recall performance even in various types of unstructured documents collected from multiple sources. The problem of information extraction for knowledge base extension should take into account heterogeneous characteristics of source-specific document types. The proposed methodology proved to extract information effectively from various types of unstructured documents compared to the baseline model. There is a limitation in previous research that the performance is poor when extracting information about the document type that is different from the training data. In addition, this study can prevent unnecessary information extraction attempts from the documents that do not include the answer information through the process for predicting the suitability of information extraction of documents and sentences before the information extraction step. It is meaningful that we provided a method that precision performance can be maintained even in actual web environment. The information extraction problem for the knowledge base expansion has the characteristic that it can not guarantee whether the document includes the correct answer because it is aimed at the unstructured document existing in the real web. When the question answering is performed on a real web, previous machine reading comprehension studies has a limitation that it shows a low level of precision because it frequently attempts to extract an answer even in a document in which there is no correct answer. The policy that predicts the suitability of document and sentence information extraction is meaningful in that it contributes to maintaining the performance of information extraction even in real web environment. The limitations of this study and future research directions are as follows. First, it is a problem related to data preprocessing. In this study, the unit of knowledge extraction is classified through the morphological analysis based on the open source Konlpy python package, and the information extraction result can be improperly performed because morphological analysis is not performed properly. To enhance the performance of information extraction results, it is necessary to develop an advanced morpheme analyzer. Second, it is a problem of entity ambiguity. The information extraction system of this study can not distinguish the same name that has different intention. If several people with the same name appear in the news, the system may not extract information about the intended query. In future research, it is necessary to take measures to identify the person with the same name. Third, it is a problem of evaluation query data. In this study, we selected 400 of user queries collected from SK Telecom 's interactive artificial intelligent speaker to evaluate the performance of the information extraction system. n this study, we developed evaluation data set using 800 documents (400 questions * 7 articles per question (1 Wikipedia, 3 Naver encyclopedia, 3 Naver news) by judging whether a correct answer is included or not. To ensure the external validity of the study, it is desirable to use more queries to determine the performance of the system. This is a costly activity that must be done manually. Future research needs to evaluate the system for more queries. It is also necessary to develop a Korean benchmark data set of information extraction system for queries from multi-source web documents to build an environment that can evaluate the results more objectively.

• 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.

• Journal of Nutrition and Health
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• v.42 no.1
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• pp.78-96
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• 2009

The purpose of this study was to analyze and evaluate the menu served in government offices foodservice by using Kasavana & Smith's Menu-Engineering. Sales and food costs were collected from the daily sales reports for a year from Jan 2 to Dec 31 in 2007. Calculation for menu analysis and customer's data were done by computer using the MS 2003 Excel spreadsheet program and SPSS 12.0 package program. Menu mix% (MM%) and unit contribution margin were used as variables by Kasavana & Smith. Four possible classifications by Menu-Engineering technique were turned out as 'STAR', 'PLOWHORSE', 'PUZZLE', 'DOG'. The main menus served during a year were 128 dishes and about 141 peoples visited this restaurant daily. The mean age of the men was $44.1\;{\pm}\;6.3$, women were $32.7\;{\pm}\;6.4$ and showed that was statistically higher than that of women (p < .0001). The rates of STAR menus were 'Western style (75.0%)', 'guk/tang-ryu (48.1%)', 'jjigae/ jeongol-ryu (23.1%)', 'bap-ryu (17.2%)' in sequence. There were no STAR menus in gui/jorim/jjim-ryu. PLOWHORSE menus were 'gui-ryu (75.0%)', 'guk/tang-ryu (29.6%)', 'bap-ryu (27.6%)' in sequence. There were no PUZZLE or DOG menus in 'jjigae/jeongol-ryu'. PUZZLE menus were 'jorim/jjim-ryu and Myeonryu (each 33.3%)', 'bap-ryu (31.0%)' in sequence. PUZZLE menus were a lots of 'Chinese food (75.0%)' and 'myeonryu (55.6%)'. This study provides the basic data based on regularly menu analysis method applied the scientific menu analysis techniques in government offices food services, I'd like to suggest that the menu management must be done based on the necessity and result of menu analysis according to the seasonal and middle, long-term plans.

• Journal of Bio-Environment Control
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• v.30 no.1
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• pp.77-84
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• 2021

This study attempted to find a way to maintain the quality of mixing baby wild leaf vegetables with existing baby leaf vegetables in various ratios. The crops for mixing baby leaf vegetables were Peucedanum japoincum Thunberg and Ligularia stenocephala, as wild vegetables, and red romaine, which is widely used in young leafy vegetables. The mixing ratio of red romaine and wild vegetables was red romaine 0: mantilla oil 5: L. stenocephala ratio 5 (R0: P5: L5), red romaine 3.3: P. japoincum 3.3: L. stenocephala ratio 3.3 (R3.3: P3.3: L3.3), red romaine 5: P. japoincum 2.5: L. stenocephala 2.5 (R5: P2.5: L2.5), red romaine 8: P. japoincum 1: L. stenocephala 1 (R8: P1: L1), red romaine 10: P. japoincum 0: L. stenocephala 0 (R10: P0: L0). All treatments were packaged in OTR (oxygen transmittance) 10,000 cc m-2·day-1·atm-1 film and stored for 27 days at 2℃/85% RH conditions. Fresh weight, carbon dioxide, oxygen, and ethylene concentrations of the baby leaf packages were examined approximately every 3 days, and visual quality, chlorophyll content, and chromaticity were examined on the 27th day of storage. The oxygen and carbon dioxide concentration in the packages were affected by the respiration rate of the crop. As the mixing ratio of lettuce, which had a low respiration rate, increased, the oxygen concentration in the packages was higher and the carbon dioxide concentration was lower. Oxygen concentration decreased significantly after 15 days, but was remained above 16%, and on the contrary, carbon dioxide concentration was kept at 1-4% until the 15th, and then gradually increased to 2-5% on the 27th day. The concentration of ethylene was maintained at 3-6 µL·L-1 until the end of storage (27th day). Visual quality score measured at the end of storage was slightly less than 3.0, which is the limit of marketability of all treatments. Although there was no significant difference, the chlorophyll content (SPAD) of red romaine and P. japoincum were most similar with an initial value in R8:P1:1 treatment, and L. stenocephala was higher value in R8:P1:L1 and R5:P2.5:L2.5 treatments at the end of storage. The leaf color (L∗, a∗, b∗, chroma) of the three crops at end of storage compared with the heat map showed the least change in the R5:P2.5:L2.5 and R8:P1:L1 treatments at the end of storage. Among them, R8:P1:L1 treatment maintained the highest chlorophyll content, the second lowest ethylene concentration, and adequate carbon dioxide concentration of 2-3%. Therefore, it is judged that the mixed ratio of red romaine 8: P. japoincum 1: L. stenocephala 1 (R8: P1: L1) is most suitable for the mixed package of baby leaf vegetables of these three crops.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.2
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• pp.26-32
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• 2010

Purpose: It is to find the way to minimize occupationally exposed dose for workers in vivo tests in each working stage within the range of the working environment which does not ruin the examination and the performance efficiency. Materials and Methods: The process of the nuclear tests in vivo using a radioactive isotope consists of radioisotope distribution, a radioisotope injection ($^{99m}Tc$, $^{18}F$-FDG), and scanning and guiding patients. Using a measuring instrument of RadEye-G10 gamma survey meter (Thermo SCIENTIFIC), the exposure doses in each working stage are measured and evaluated. Before the radioisotope injection the patients are explained about the examination and educated about matters that require attention. It is to reduce the meeting time with the patients. In addition, workers are also educated about the outside exposure and have to put on the protected devices. When the radioisotope is injected to the patients the exposure doses are measured due to whether they are in the protected devices or not. It is also measured due to whether there are the explanation about the examination and the education about matters that require attention or not. The total exposure dose is visualized into the graph in using Microsoft office excel 2007. The difference of this doses are analyzed by wilcoxon signed ranks test in using SPSS (statistical package for the social science) program 12.0. In this case of p<0.01, this study is reliable in the statistics. Results: It was reliable in the statistics that the exposure dose of injecting $^{99m}Tc$-DPD 20 mCi in wearing the protected devices showed 88% smaller than the dose of injecting it without the protected devices. However, it was not reliable in the statistics that the exposure dose of injecting $^{18}F$-FDG 10 mCi with wearing protected devices had 26% decrease than without them. Training before injecting $^{99m}Tc$-DPD 20 mCi to patient made the exposure dose drop to 63% comparing with training after the injection. The dose of training before injecting $^{18}F$-FDG 10 mCi had 52% less then the training after the injection. Both of them were reliable in the statistics. Conclusion: In the examination of using the radioisotope $^{99m}Tc$, wearing the protected devices are more effective to reduce the exposure dose than without wearing them. In the case of using $^{18}F$-FDG, reducing meeting time with patients is more effective to drop the exposure dose. Therefore if we try to protect workers from radioactivity according to each radioisotope characteristic it could be more effective and active radiation shield from radioactivity.

• Investigative Magnetic Resonance Imaging
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• v.8 no.2
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• pp.79-85
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• 2004

Purpose : To evaluate the usefulness and reproducibility of $^1H$ MRS in different 1.5 T MR machines with different coils to compare the SNR, scan time and the spectral patterns in different brain regions in normal volunteers. Materials and Methods : Localized $^1H$ MR spectroscopy ($^1H$ MRS) was performed in a total of 10 normal volunteers (age; 20-45 years) with spectral parameters adjusted by the autoprescan routine (PROBE package). In all volunteers, MRS was performed in a three times using conventional MRS (Signa Horizon) with 1 channel coil and upgraded MRS (Echospeed plus with EXCITE) with both 1 channel and 8 channel coil. Using these three different machines and coils, SNRs of the spectra in both phantom and volunteers and (pre)scan time of MRS were compared. Two regions of the human brain (basal ganglia and deep white matter) were examined and relative metabolite ratios (NAA/Cr, Cho/Cr, and mI/Cr ratios) were measured in all volunteers. For all spectra, a STEAM localization sequence with three-pulse CHESS $H_2O$ suppression was used, with the following acquisition parameters: TR=3.0/2.0 sec, TE=30 msec, TM=13.7 msec, SW=2500 Hz, SI=2048 pts, AVG : 64/128, and NEX=2/8 (Signa/Echospeed). Results : The SNR was about over $30\%$ higher in Echospeed machine and time for prescan and scan was almost same in different machines and coils. Reliable spectra were obtained on both MRS systems and there were no significant differences in spectral patterns and relative metabolite ratios in two brain regions (p>0.05). Conclusion : Both conventional and new MRI systems are highly reliable and reproducible for $^1H$ MR spectroscopic examinations in human brains and there are no significant differences in applications for $^1H$ MRS between two different MRI systems.

• Journal of the East Asian Society of Dietary Life
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• v.19 no.6
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• pp.891-908
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• 2009

This study was performed to investigate the dietary habits, body weight satisfaction and eating disorder tendencies of female university students in Kyungnam province. Anthropometric measurements, dietary habits, body weight satisfaction, food preferences, disordered eating, and nutrient intakes were assessed in 132 female students at Kaya University. The results were analyzed with $x^2$- and ANOVA tests using the SPSS package program. The average age of the subjects was 20.1 years and average body mass index (BMI) were $21.1\;kg/m^2$. According to BMI, the percentages of students who were underweight, normal weight and overweight by BMI were 21.2, 55.3, and 23.5, respectively. Duration of exercise was significantly different by BMI. Index scores for a mini dietary assessment were significantly higher in the normal and overweight groups than in the underweight group. Scores for sweet, salty, and meat preferences were highest and scores for bean and vegetable preferences were lowest, in the underweight group. Satisfaction for present body weight was lowest, and self-perception of body image and weight control experiences were highest in the overweight group. All subjects in the overweight group wanted to be slim, and those in the normal and underweight groups, preferred to be more slim despite their current body weight being in the normal or below normal range. The percentage of the subjects who were at risk for eating disorders (based on scores from the Eating Attitude Test-26, EAT-$26{\geqq}20$) was 11.3%. Scores for EAT-26 were higher in the overweight group than in the underweight and normal weight groups. Nutrient intakes were not different among the groups. Therefore, dietary habits, taste and food preferences, satisfaction for present body weight, and disordered eating were significantly different according to BMI. These results suggest that overweight female university students need help correcting disordered eating, and nutrition counseling should be established to aid desirable weight control methods. Those who are underweight and normal weight need help establishing proper perceptions of their normal body weight and body image as well as nutrition counseling for health.