• Korean Journal of Cognitive Science
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• v.2 no.2
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• pp.405-428
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• 1990

Language has a social function to communicate information. Linguists have gradually paid their attention to the function of language since the nineteen sixties, especially to the relationship of form, meaning and the function. The relationship could be more clearly grasped through disciyrse-based analysis than through sentence-based analysis. Many researches were centered on the discourse functional notion of topic. In the early 1970's the subject was defined as the grammatiocalized topic the topic as a discrete single constituent of the clause. In the late 1970's several lingusts including Givon suggerted that the topic was not an atomic, disctete entity, and that the clause could have more than one topic. The purpose of the present study is, following Givon, to study grammatical coding devices of topic and to measure the relative topic continuity/discontinuity of participant argu, ents in Korean narratives. By so doing, I would like to shed some light on effective ways of communicating information. The grammatical coding devices analyzed are the following eight structures: zero-anaphora, personal pronous, demonstrative pronouns, names, noun phrases following demonstratives, noun phrases following possessives, definite noun phrases and indefinite referentials. The narrative studied for the count was taken from the KoreanCIA chief's Testiomny:Revolution and Idol by Hyung Wook Kim. It was chosen because it was assumed that Kim's purpose in the novel was to tell a true story, which would not distort the natural use of language for literary effect. The measures taken in the analysis wre those of 'lookback', 'persistence', ambiguity'. The first of these, 'lookback', is a measure of the size of gap between the previous occurrence of a referent and its current occurence in the clause. The meausure of persistence, which is a measure of the speaker's topocal intent, reflects the topic's importance in the discourse. The third measure is a measure of ambiguity. This is necessary for assessing the disruptive effects that other topics within five previous clauses may have on topic identification. The more other topics are present within five previous clauses, the more difficult is the task of correct identification of a topic. The results of the present study show that the humanness of entities is the most powerful factior in topic continutiy in narrative discourse. The semantic roles of human arguments in narrative discourse tend to be agents or experiences. Since agents and experiences have high topicality in discourse, human entities clearly become clausal or discoursal topics. The results also show that the grammatical devices signal varying degrees of topic continuity discontinuity in continuous discourse. The more continuous a topic argument is, the less it is coded. For example, personal pronouns have the most continutiy and indefinite referentials have the least continutiy. The study strongly shows that topic continuity discontinutiy is controlled not only by grammatical devices available in the language but by socio-cultural factors and writer's intentions.

• Journal of The Korean Association For Science Education
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• v.39 no.2
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• pp.161-171
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• 2019

The purposes of this study are: 1) to verify the systems thinking factor structure of elementary school students and 2) to compare systems thinking according to their preferred subjects in order to get implications for following research. For the study, pre-tests analyze data from 732 elementary school students using the STMI (Systems Thinking Measuring Instrument) developed by Lee et al. (2013). And exploratory factor analysis was conducted to identify the factor structure of the students. Based on the results of the pre-test, the expert group council revised the STMI so that elementary school students could respond to the 5-factor structure that STMI intended. In the post-test, 503 data were analyzed by modified STMI and exploratory factor analysis was performed. The results of the study are as follows: First, in the pre-test, elementary school students responded to the STMI with a test paper consisting of two factors (personal internal factors and personal external factors). The total reliability of the instrument was .932 and the reliability of each factor was analyzed as .857 and .894. Second, for modified STMI, elementary school students responded a 4-factor instrument. Team learning, Shared Vision, and Personal Mastery were derived independent factors, and mental model and systems analysis were derived 1-factor. The total reliability of the instrument was .886 and the reliability of each factor was analyzed as .686 to .864. Finally, a comparison of systems thinking according to preferred subjects showed a significant difference between students who selected science (engineering) group and art (music and physical education). In conclusion, it was confirmed that statistically meaningful results could be obtained using STMI modified by term and sentence structure appropriate for elementary school students, and it is a necessary to study the relation of systems thinking with various student variables such as the preferred subjects.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.23-43
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• 2016

As a result of the growth of Internet data and the rapid development of Internet technology, "big data" analysis has gained prominence as a major approach for evaluating and mining enormous data for various purposes. Especially, in recent years, people tend to share their experiences related to their leisure activities while also reviewing others' inputs concerning their activities. Therefore, by referring to others' leisure activity-related experiences, they are able to gather information that might guarantee them better leisure activities in the future. This phenomenon has appeared throughout many aspects of leisure activities such as movies, traveling, accommodation, and dining. Apart from blogs and social networking sites, many other websites provide a wealth of information related to leisure activities. Most of these websites provide information of each product in various formats depending on different purposes and perspectives. Generally, most of the websites provide the average ratings and detailed reviews of users who actually used products/services, and these ratings and reviews can actually support the decision of potential customers in purchasing the same products/services. However, the existing websites offering information on leisure activities only provide the rating and review based on one stage of a set of evaluation criteria. Therefore, to identify the main issue for each evaluation criterion as well as the characteristics of specific elements comprising each criterion, users have to read a large number of reviews. In particular, as most of the users search for the characteristics of the detailed elements for one or more specific evaluation criteria based on their priorities, they must spend a great deal of time and effort to obtain the desired information by reading more reviews and understanding the contents of such reviews. Although some websites break down the evaluation criteria and direct the user to input their reviews according to different levels of criteria, there exist excessive amounts of input sections that make the whole process inconvenient for the users. Further, problems may arise if a user does not follow the instructions for the input sections or fill in the wrong input sections. Finally, treating the evaluation criteria breakdown as a realistic alternative is difficult, because identifying all the detailed criteria for each evaluation criterion is a challenging task. For example, if a review about a certain hotel has been written, people tend to only write one-stage reviews for various components such as accessibility, rooms, services, or food. These might be the reviews for most frequently asked questions, such as distance between the nearest subway station or condition of the bathroom, but they still lack detailed information for these questions. In addition, in case a breakdown of the evaluation criteria was provided along with various input sections, the user might only fill in the evaluation criterion for accessibility or fill in the wrong information such as information regarding rooms in the evaluation criteria for accessibility. Thus, the reliability of the segmented review will be greatly reduced. In this study, we propose an approach to overcome the limitations of the existing leisure activity information websites, namely, (1) the reliability of reviews for each evaluation criteria and (2) the difficulty of identifying the detailed contents that make up the evaluation criteria. In our proposed methodology, we first identify the review content and construct the lexicon for each evaluation criterion by using the terms that are frequently used for each criterion. Next, the sentences in the review documents containing the terms in the constructed lexicon are decomposed into review units, which are then reconstructed by using the evaluation criteria. Finally, the issues of the constructed review units by evaluation criteria are derived and the summary results are provided. Apart from the derived issues, the review units are also provided. Therefore, this approach aims to help users save on time and effort, because they will only be reading the relevant information they need for each evaluation criterion rather than go through the entire text of review. Our proposed methodology is based on the topic modeling, which is being actively used in text analysis. The review is decomposed into sentence units rather than considering the whole review as a document unit. After being decomposed into individual review units, the review units are reorganized according to each evaluation criterion and then used in the subsequent analysis. This work largely differs from the existing topic modeling-based studies. In this paper, we collected 423 reviews from hotel information websites and decomposed these reviews into 4,860 review units. We then reorganized the review units according to six different evaluation criteria. By applying these review units in our methodology, the analysis results can be introduced, and the utility of proposed methodology can be demonstrated.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.125-148
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• 2018

Recently, as the demand for big data analysis increases, cases of analyzing unstructured data and using the results are also increasing. Among the various types of unstructured data, text is used as a means of communicating information in almost all fields. In addition, many analysts are interested in the amount of data is very large and relatively easy to collect compared to other unstructured and structured data. Among the various text analysis applications, document classification which classifies documents into predetermined categories, topic modeling which extracts major topics from a large number of documents, sentimental analysis or opinion mining that identifies emotions or opinions contained in texts, and Text Summarization which summarize the main contents from one document or several documents have been actively studied. Especially, the text summarization technique is actively applied in the business through the news summary service, the privacy policy summary service, ect. In addition, much research has been done in academia in accordance with the extraction approach which provides the main elements of the document selectively and the abstraction approach which extracts the elements of the document and composes new sentences by combining them. However, the technique of evaluating the quality of automatically summarized documents has not made much progress compared to the technique of automatic text summarization. Most of existing studies dealing with the quality evaluation of summarization were carried out manual summarization of document, using them as reference documents, and measuring the similarity between the automatic summary and reference document. Specifically, automatic summarization is performed through various techniques from full text, and comparison with reference document, which is an ideal summary document, is performed for measuring the quality of automatic summarization. Reference documents are provided in two major ways, the most common way is manual summarization, in which a person creates an ideal summary by hand. Since this method requires human intervention in the process of preparing the summary, it takes a lot of time and cost to write the summary, and there is a limitation that the evaluation result may be different depending on the subject of the summarizer. Therefore, in order to overcome these limitations, attempts have been made to measure the quality of summary documents without human intervention. On the other hand, as a representative attempt to overcome these limitations, a method has been recently devised to reduce the size of the full text and to measure the similarity of the reduced full text and the automatic summary. In this method, the more frequent term in the full text appears in the summary, the better the quality of the summary. However, since summarization essentially means minimizing a lot of content while minimizing content omissions, it is unreasonable to say that a "good summary" based on only frequency always means a "good summary" in its essential meaning. In order to overcome the limitations of this previous study of summarization evaluation, this study proposes an automatic quality evaluation for text summarization method based on the essential meaning of summarization. Specifically, the concept of succinctness is defined as an element indicating how few duplicated contents among the sentences of the summary, and completeness is defined as an element that indicating how few of the contents are not included in the summary. In this paper, we propose a method for automatic quality evaluation of text summarization based on the concepts of succinctness and completeness. In order to evaluate the practical applicability of the proposed methodology, 29,671 sentences were extracted from TripAdvisor 's hotel reviews, summarized the reviews by each hotel and presented the results of the experiments conducted on evaluation of the quality of summaries in accordance to the proposed methodology. It also provides a way to integrate the completeness and succinctness in the trade-off relationship into the F-Score, and propose a method to perform the optimal summarization by changing the threshold of the sentence similarity.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.25-38
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• 2019

Selecting high-quality information that meets the interests and needs of users among the overflowing contents is becoming more important as the generation continues. In the flood of information, efforts to reflect the intention of the user in the search result better are being tried, rather than recognizing the information request as a simple string. Also, large IT companies such as Google and Microsoft focus on developing knowledge-based technologies including search engines which provide users with satisfaction and convenience. Especially, the finance is one of the fields expected to have the usefulness and potential of text data analysis because it's constantly generating new information, and the earlier the information is, the more valuable it is. Automatic knowledge extraction can be effective in areas where information flow is vast, such as financial sector, and new information continues to emerge. However, there are several practical difficulties faced by automatic knowledge extraction. First, there are difficulties in making corpus from different fields with same algorithm, and it is difficult to extract good quality triple. Second, it becomes more difficult to produce labeled text data by people if the extent and scope of knowledge increases and patterns are constantly updated. Third, performance evaluation is difficult due to the characteristics of unsupervised learning. Finally, problem definition for automatic knowledge extraction is not easy because of ambiguous conceptual characteristics of knowledge. So, in order to overcome limits described above and improve the semantic performance of stock-related information searching, this study attempts to extract the knowledge entity by using neural tensor network and evaluate the performance of them. Different from other references, the purpose of this study is to extract knowledge entity which is related to individual stock items. Various but relatively simple data processing methods are applied in the presented model to solve the problems of previous researches and to enhance the effectiveness of the model. From these processes, this study has the following three significances. First, A practical and simple automatic knowledge extraction method that can be applied. Second, the possibility of performance evaluation is presented through simple problem definition. Finally, the expressiveness of the knowledge increased by generating input data on a sentence basis without complex morphological analysis. The results of the empirical analysis and objective performance evaluation method are also presented. The empirical study to confirm the usefulness of the presented model, experts' reports about individual 30 stocks which are top 30 items based on frequency of publication from May 30, 2017 to May 21, 2018 are used. the total number of reports are 5,600, and 3,074 reports, which accounts about 55% of the total, is designated as a training set, and other 45% of reports are designated as a testing set. Before constructing the model, all reports of a training set are classified by stocks, and their entities are extracted using named entity recognition tool which is the KKMA. for each stocks, top 100 entities based on appearance frequency are selected, and become vectorized using one-hot encoding. After that, by using neural tensor network, the same number of score functions as stocks are trained. Thus, if a new entity from a testing set appears, we can try to calculate the score by putting it into every single score function, and the stock of the function with the highest score is predicted as the related item with the entity. To evaluate presented models, we confirm prediction power and determining whether the score functions are well constructed by calculating hit ratio for all reports of testing set. As a result of the empirical study, the presented model shows 69.3% hit accuracy for testing set which consists of 2,526 reports. this hit ratio is meaningfully high despite of some constraints for conducting research. Looking at the prediction performance of the model for each stocks, only 3 stocks, which are LG ELECTRONICS, KiaMtr, and Mando, show extremely low performance than average. this result maybe due to the interference effect with other similar items and generation of new knowledge. In this paper, we propose a methodology to find out key entities or their combinations which are necessary to search related information in accordance with the user's investment intention. Graph data is generated by using only the named entity recognition tool and applied to the neural tensor network without learning corpus or word vectors for the field. From the empirical test, we confirm the effectiveness of the presented model as described above. However, there also exist some limits and things to complement. Representatively, the phenomenon that the model performance is especially bad for only some stocks shows the need for further researches. Finally, through the empirical study, we confirmed that the learning method presented in this study can be used for the purpose of matching the new text information semantically with the related stocks.

• Journal of Korean Public Health Nursing
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• v.3 no.1
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• pp.74-100
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• 1989

Inspite of the lots of studies on the harmfulness of cigarette smoking to the body published by many researchers since 1950, cigarette smoking people are increasing in number especially, cigarette smoking by young and women causes a serious problem. Examining the physiological motives of youth shows that, impulse which the youth want to immitate the adults, alluring curiousity, and defiant physiology of escaping from the norm of traditional groups which has been banned are cooperated well compoundly. As the period of the youth is the one which they accumulate knowledge and charactor by learning as well as the period of growth mentally, and physically they should be rightly educated about smoking before they addicted to smoking and it is desirable for us to make the youth to understand how harmfully the smoking is to effect to their growth and mental soundness simply not as a social norm which they should not smoke. The main motive of this study on the attitude of smoking by the youth is to give basic materials related on this field. For this study, 647 questionnaires were used as studying material which were able to analyze among 720 questionnaires of 2 classes of each grade of 3 high schools among the high schools of boys, girls and co-educated in Seoul from Oct. 21, 1988 through Oct. 26, 1988. Study Instrument are graded in Likert's 5 point from 40 questions which are 20 questions m affirmations and 20 questions in negations after analyzing the factors on 60 simple sentence questions which the students showed in preliminary studies. And these are systemized to be measured from 1 point which means they think smoking IS very bad to 5points which means they think smoking is really good. In these collected materials, technical statistics of frequency. percentage, average, standard deviation are used for general character and smoking attitude, $X^2-test$ for examinning Independant variables of physical. emotional, ethical and other areas pearson's coefficient of correlation for related direction and degree" and step­regression analysis for the degree of relative contribution of all variables which effect smoking attitude. The results of this study are as follows; 1. The smoking attitude of high school boys and girls showed average of 1.78 in physical area, 2.63 in emotional area, 2.61 in ethical area, 2.29 in other area respectively in a negative attitude generally also the negative attitude are expressed most strongly in physical area. I've can also say by this results that smoking is harmful to their health and further more it can be judged that this proves the youth in the period of preparation be adults have a strong curiousity in the emotional, ethical and other areas. 2. The most influential variables in each field as related factors effecting smoking attitude of the student can be explained from 13.2 in physical area the lowest experienced variables to 25.2 in emotional area the highest of degree of smoking experience. The fact that the more the smoking experienced students are increasing in number the higher tendency which accept the' smoking tells as the importance of health education about the population of latest student's smoking as important variables shown equally in each area. Those of grade, age, numbers of smoking people in house are showed meaningful in pure interrelation. Those related to the acceptance of teacher's smoking, sex, mothors education are shown meaningful in opposite interrelations. This means that the' increasing number' of smoking people in grade age, the number of smoker in family have a affirmative attitude. And people who are not interested in teacher's smoking wants to quit it, and whose mother's education is higher have a negative attitude. 3. The most negatively answered questions of the smoking attitude In physical, emotional, ethical and other areas are as belows; Firstly too much smoking is harmful to our health is 1.12 point. Secondly smoking have a ill-effect on pregnancy and embryo is 1.13 point. Thirdly smoking is harmful· to our health is 1.27 point. Fourthly smoking in crowed area with the people such as In a bus or subway should be prohibited is 1.27point. Fifthly smoking can ruin lungs is 1.31 point. And the most affirmatively answered questions are also as below; Firstly we showed smoke depending on time and place is 3.96 points. Secondly smoking is just habit is 3.83 points. Thirdly smoking people seem to be unable and deplorable is 3.69 point. Fourthly smoking should be prohibited by law is 3.56 points. Fifthly high school student's smoking is immitation of adults is 3.52 points.

• Journal of Sasang Constitutional Medicine
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• v.18 no.3
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• pp.75-93
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• 2006

1. Objectives and Methods Sasang Constitutional Medicine is the original Korean Medicine. The purpose of this study was to objectify the diagnosis of Sasang Constitution. 212 Women's sentences were analyzed into 228 factors like Pitch, APQ, Shimmer, Octave and Energy, etc. Women's sentences were classified into 3 categories: total group, under 54 years old group and over 55 years old group. 2. Results 1) In Total group Soyangin's Center feq.(3) was significantly high compared with Taeyangin and Taeumin groups. Taeumin's Pitch2 was significantly high compared with Soeumin and Taeyangin groups. Taeyangin's Pitch S.D. was significantly high compared with Soyangin group. Taeyangin's Octave6 was significantly high compared with Soeumin group. There were no significant differences among constitutional groups in APQ and Shimmer segment. On the point of Energy, Taeyangin's G Tot E(1), G# Tot E(1), G dev.(1), G# dev.(1), G Tot E(2), G# Tot E(2), G dev.(4) and G# dev.(4) were significantly high compared with other groups. Soyangin's A#S.D.(2) was significantly high compared with Taeyangin group. Taeyangin's A#S.D.(3) was significantly high compared with Taeumin group. Taeyangin's F S.D.(5), F# S.D.(5) and Max Average were significantly high compared with Soeumin group. Taeumin's Peak3 and Peak4 were significantly high compared with Taeyangin group. Taeumin's PeakValue1 was significantly high compared with Soeumin group. Taeyangin's PeakValue2 was significantly high compared with Soeumin group. Taeyangin's PeakValue3 and PeakValue5 were significantly high compared with Other groups. 2) In Under 54 years old group, there were no significant differences among constitutional groups in APQ, Shimmer and Octave segment. Taeumin's Center freq.(2) was significantly high compared with Taeyangin and Soyangin groups. Taeumin's Pitch(2) and Pitch(3) were significantly high compared with Taeyangin and Soeumin groups. Taeyangin's and Taeumin's Pitch S.D. were significantly high compared with Soyangin group. Taeyangin's and Soyangin's Octave2 were significantly high compared with Taeumin group. On the point of Energy, Taeyangin's and Soyangin's A# S.D.(2) were significantly high compared with Soeumin group. Taeyangin's and Soyangin's G# dev.(1), G# dev.(2) were significantly high compared with Taeumin group. Taeyangin's and Taeumin's F# S.D.(3) were significantly high compared with Soeumin group. Taeyangin's and Soyangin's Max Average were significantly high compared with Soeumin group. Taeumin's Peak3 was significantly high compared with Taeyangin and Soeumin groups. Taeyangin's and Taeumin's PeakValue2 were significantly high compared with Soeumin group. Taeyangin's and Soeumin's PeakValue3 were significantly high compared with Taeumin group. Taeyangin's and Soyangin's PeakValue5 were significantly high compared with Soeumin group. Taeyangin's and Soyangin's PeakValue9 were significantly high compared with Taeumin group 3) In Over 55 years old group, there were no significant differences among constitutional groups in Pitch, APQ, and Peak segment. Soeumin's F Shimmer(1) and F Shimmer(2) were significantly high compared with Taeyangin and Taeumin groups. Soeumin's G# Shimmer(1) and G# Shimmer(2) were significantly high compared with Soyangin group. Taeyangin's Octave5 and Octave6 were significantly high compared with Soeumin group. On the point of Energy, Soyangin's C S.D., F# S.D.(1), F# S.D.(2) and G dev.(2) were significantly high compared with other groups. Soyangin's F# S.D.(3) was significantly high compared with Taeumin and Soeumin groups. Taeyangin's and Taeumin's G# S.D.(2) and G# S.D.(3) were significantly high compared with Soyangin group 3. Conclusions From above result, there is the possibility of efficient standard guide for constitution diagnosis by analysis of voice

• The Korean Society of Law and Medicine
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• v.13 no.1
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• pp.199-247
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• 2012

According to the review and analysis of medical cases that are assigned to the Supreme Court and all local High Court in 2011 and that are presented in the media, it was found that the following categories were taken seriously, medical and pharmaceutical product liability, the third principle of trust between medical institutions, negligence and causation estimation, responsibility limit, the meaning of medical records and related judgment of disturbed substantiation, Oriental doctors' duties to explain the procedures, IMS events, whether one can claim for each medical care operated by non-physician health care institutions to the nonmedical domain in the National Health Insurance Corporation, and the basis of norms for each claim. In the cases related to medical pharmaceutical product liability, Supreme Court alleviated burden of proof for accidents with medical and pharmaceutical products prior to the practice of Product Liability Law and onset the point of negative prescription as the time of damage strikes to condition feasibility of the specific situation. In the cases related to the 3rd principle of trust between medical institutions, the Supreme Court refused to sentence the doctor who has trusted the judgment of the same third-party doctors the violations of the care duty. With respect to proof of a causal relationship and damages in a medical negligence case, the Supreme Court decided that it is unjust to deny negligence by the materials of causal relationship rejecting the original verdict and clarified that the causal relationship shall not deny the reasons to limit doctors' responsibilities. In order not put burden on patients with disadvantages in which medical records and the description of the practice or the most fundamental and important evidence to prove negligence and causation are being neglected, the Supreme Court admitted in the hospital's responsibility for the case of the neonate death of suffocation without properly listed fetal heart rate and uterine contraction monitor. On the other hand, the Seoul Western District Court has admitted alimony for altering and forging medical records. With respect to doctors' obligations to description, the Supreme Court decided that it is necessary to explain the foreseen risks by the combination of oriental and western medicines emphasizing the right of patient's self-determination. However, questions have arisen whether it is realistically feasible or not. In a case of an unlicensed doctor performing intramuscular stimulation treatment (IMS), the Supreme Court put off its decision if it was an unlicensed medical practice as to put limitation of eastern and western medical practices, but it declared that IMS practice was an acupuncture treatment therefore the plaintiff's conduct being an illegal act. In the future, clear judgment on this matter should be made. With respect to the claim of bills from non-physical health care institutions, the Supreme Court decided to void it for the implementation of the arrangement is contrary to the commitments made in the medical law and therefore, it is invalid to claim. In addition, contrast to the private healthcare professionals, who are subject to redemption according to the National Healthcare Insurance Law, the Seoul High Court explicitly confirmed that the non-professionals who receive the tort operating profit must return the unjust enrichment and have the liability for damages. As mentioned above, a relatively wide range of topics were discussed in medical field of 2011. In Korea's health care environment undergoing complex changes day by day, it is expected to see more diverse and in-depth discussions striding out to the development in the field of health care.

• Journal of The Korean Association For Science Education
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• v.42 no.3
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• pp.311-324
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• 2022

This study analyzed the types of scientific emoticons made by science-gifted elementary school students and their perceptions on making scientific emoticons. To do this, 71 students from 4th to 6th graders of two gifted science education center in Seoul were selected. Scientific emoticons made by the students were analyzed according to the number and types. Their perceptions on making scientific emoticons were also analyzed through a questionnaire and group interviews. In the analyses for types of text in the scientific emoticons, 'word type' and 'sentence type' were made more than 'question and answer type'. And the majority of students made more 'pun using pronunciation type' and 'mixed type' than other types. They also made more 'graphic type' and 'animation type' than 'text type' in the images of the scientific emoticons. In the analyses for the information of the scientific emoticons, 'positive emotion type' and 'negative emotion type' of scientific emoticons were made evenly. The students made more 'new creation type' than 'partial correction type' and 'entire reconstruction type'. They also used scientific knowledge that preceded the knowledge of science curriculum in their grade level. The scientific knowledge of chemistry was used more than physics, biology, earth science, and combination field. 'Name utilization type' was more than 'characteristic utilization type' and 'principle utilization type'. Students had various positive perceptions in making scientific emoticons such as 'increase of scientific knowledge', 'increase of various higher-order thinking abilities', 'ease of explanation, use, memory, and understanding of scientific knowledge', 'increase of fun, enjoyment, and interest about science and science learning', and 'increase of opportunity to express emotions'. They were also aware of some limitations related to 'difficulties in the process of making scientific emoticons', 'lack of time', and 'limit that it may end just for fun'. Educational implications of these findings are discussed.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.127-146
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• 2022

Recently, as word embedding has shown excellent performance in various tasks of deep learning-based natural language processing, researches on the advancement and application of word, sentence, and document embedding are being actively conducted. Among them, cross-language transfer, which enables semantic exchange between different languages, is growing simultaneously with the development of embedding models. Academia's interests in vector alignment are growing with the expectation that it can be applied to various embedding-based analysis. In particular, vector alignment is expected to be applied to mapping between specialized domains and generalized domains. In other words, it is expected that it will be possible to map the vocabulary of specialized fields such as R&D, medicine, and law into the space of the pre-trained language model learned with huge volume of general-purpose documents, or provide a clue for mapping vocabulary between mutually different specialized fields. However, since linear-based vector alignment which has been mainly studied in academia basically assumes statistical linearity, it tends to simplify the vector space. This essentially assumes that different types of vector spaces are geometrically similar, which yields a limitation that it causes inevitable distortion in the alignment process. To overcome this limitation, we propose a deep learning-based vector alignment methodology that effectively learns the nonlinearity of data. The proposed methodology consists of sequential learning of a skip-connected autoencoder and a regression model to align the specialized word embedding expressed in each space to the general embedding space. Finally, through the inference of the two trained models, the specialized vocabulary can be aligned in the general space. To verify the performance of the proposed methodology, an experiment was performed on a total of 77,578 documents in the field of 'health care' among national R&D tasks performed from 2011 to 2020. As a result, it was confirmed that the proposed methodology showed superior performance in terms of cosine similarity compared to the existing linear vector alignment.