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APICAL FITNESS OF NON-STANDARDIZED GUTTA-PERCHA CONES IN SIMULATED ROOT CANALS PREPARED WITH ROTARY ROOT CANAL INSTRUMENTS (전동화일로 형성된 근관에서 비표준화 Gutta-percha Cone의 적합성)

  • Kwon, O-Sang;Kim, Sung-Kyo
    • Restorative Dentistry and Endodontics
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    • v.25 no.3
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    • pp.390-398
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    • 2000
  • The purpose of this study was to evaluate the apical fitness of non-standardized gutta-percha cones in root canals prepared with rotary Ni-Ti root canal instruments of various tapers and apical tip sizes. Simulated sixty curved root canals of plastic blocks were prepared with crown-down technique using rotary root canal instruments of Maillefer ProFile$^{(R)}$ .04 and .06 taper (Maillefer Instrument SA, Switzerland). Specimens were divided into six groups and prepared as follows: Group 1, prepared up to size 25 of .04 taper ; Group 2, prepared up to size 30 of .04 taper ; Group 3, prepared up to size 35 of .04 taper ; Group 4, prepared up to size 25 of .06 taper ; Group 5, prepared up to size 30 of .06 taper ; Group 6 ; prepared up to size 35 of .06 taper. After cutting off the coronal portion of plastic, blocks perpendicular to the long axis of the canal with the use of a diamond saw, apical 5mm of canal space was analyzed. Prepared apical canal spaces were duplicated using rubber base impression material to evaluate two dimensional total area of apical canal space. Various sized gutta-percha cones were applied in the 5mm-apical canal space, which were size 25, size 30 and size 35 standardized gutta-percha cone, Diadent Dia-Pro ISO-.04$^{TM}$ and .06$^{TM}$(Diadent, Korea), and medium-fine (MF), fine (F), fine-medium (FM) and medium (M) sized non-standardized gutta-percha cones (Diadent, Korea). Coronal excess gutta-percha were cut off with a sharp blade. Photographs of impressed apical canal spaces and gutta-percha cones were taken with a CCD camera under a stereomicroscope and stored in a computer. Areas of the total canal space and gutta-percha cones were calculated using a digitalized image analysing program, CompuScope (Sungjin Multimedia Co., Korea). Ratio of apical fitness was obtained by calculating the area of gutta-percha cone to the total area of the canal space. The data were analysed statistically using One-way Analysis of Variance and Duncan's Multiple Range Test. The results were as follows: 1. In canals prepared up to size 25 ProFile$^{(R)}$ of .04 taper, non-standardized MF and F cones occupied significantly more canal space than Dia-Pro ISO-.04$^{TM}$ or size 25 standardized ones (p<0.05). 2. In canals prepared up to size 30 ProFile$^{(R)}$ of .04 taper, non-standardized F cones occupied significantly more canal space than Dia-Pro ISO-.04$^{TM}$ or size 30 standardized ones (p<0.05), and non-standardized MF cones occupied more canal space than size 30 standardized ones (p<0.05). 3. In canals prepared up to size 35 ProFile$^{(R)}$ of .04 taper, there was no significant difference in canal space occupation among non-standardized MF and F, size 35 standardized, and Dia-Pro ISO-.04$^{TM}$ cones (p>0.05). 4. In canals prepared up to size 25 ProFile$^{(R)}$ of .06 taper, non-standardized MF and F cones occupied significantly more canal space than Dia-Pro ISO-.06$^{TM}$, or size 25 standardized ones (p<0.05), and Dia-Pro ISO-.06$^{TM}$, cones occupied significantly more space than size 25 standardized ones (p<0.05). 5. In canals prepared up to size 30 ProFile$^{(R)}$ of .06 taper, non-standardized FM cones occupied significantly more canal space than Dia-Pro ISO-.06$^{TM}$ or size 30 standardized ones (p<0.05), and non-standardized F cones occupied significantly more canal space than size 30 standardized ones (p<0.05). 6. In canals prepared up to size 35 ProFile$^{(R)}$ of .06 taper, non-standardized M and FM, Dia-Pro ISO-.06$^{TM}$ occupied significantly more canal space than size 35 standardized ones (p<0.05). In summary, in both canals prepared with .04 or .06 taper ProFile$^{(R)}$, non-standardized cones showed better fitness than Dia-Pro ISO$^{TM}$ or standardized ones, which was more characteristic in smaller canals.

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The Empirical Exploration of the Conception on Nursing (간호개념에 대한 기초조사)

  • 백혜자
    • Journal of Korean Academy of Nursing
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    • v.11 no.1
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    • pp.65-87
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    • 1981
  • The study is aimed at exploring concept held by clinical nurses of nursing. The data were collected from 225 nurses conviniently selected from the population of nurses working in Kang Won province. Findings include. 1) Nurse's Qualification. The respondents view that specialized knowledge is more important qualification of the nurse. Than warm personality. Specifically, 92.9% of the respondents indicated specialized knowledge as the most important qualification while only 43.1% indicated warm personality. 2) On Nursing Profession. The respondents view that nursing profession as health service oriented rather than independent profession specifically. This suggests that nursing profession is not consistentic present health care delivery system nor support nurses working independently. 3) On Clients of Nursing Care The respondents include patients, family and the community residents in the category of nursing care. Specifically, 92.0% of the respondents view that patient is the client, while only 67.1% of nursing student and 74.7% of herself. This indicates the lack of the nurse's recognition toward their clients. 4) On the Priority of Nursing care. Most of the respondents view the clients physical psychological respects as important component of nursing care but not the spiritual ones. Specially, 96.0% of the respondents indicated the physical respects, 93% psychological ones, while 64.1% indicated the spiritual ones. This means the lack of comprehensive conception on nursing aimension. 5) On Nursing Care. 91.6% of the respondents indicated that nursing care is the activity decreasing pain or helping to recover illness, while only 66.2% indicated earring out the physicians medical orders. 6) On Purpose of Nursing Care. 89.8% of the respondents indicated preventing illness and than 76.6% of them decreasing 1;ai of clients. On the other hand, maintaining health has the lowest selection at the degree of 13.8%. This means the lack of nurses' recognition for maintaining health as the most important point. 7) On Knowledge Needed in Nursing Care. Most of the respondents view that the knowledge faced with the spot of nursing care is needed. Specially, 81.3% of the respondents indicated simple curing method and 75.1%, 73.3%, 71.6% each indicated child nursing, maternal nursing and controlling for the communicable disease. On the other hand, knowledge w hick has been neglected in the specialized courses of nursing education, that is, thinking line among com-w unity members, overcoming style against between stress and personal relation in each home, and administration, management have a low selection at the depree of 48.9%,41.875 and 41.3%. 8) On Nursing Idea. The highest degree of selection is that they know themselves rightly, (The mean score measuring distribution was 4.205/5) In the lowest degree,3.016/5 is that devotion is the essential element of nursing, 2.860/5 the religious problems that human beings can not settle, such as a fatal ones, 2,810/5 the nursing profession is worth trying in one's life. This means that the peculiarly essential ideas on the professional sense of value. 9) On Nursing Services. The mean score measuring distribution for the nursing services showed that the inserting of machine air way is 2.132/5, the technique and knowledge for surviving heart-lung resuscitating is 2.892/s, and the preventing air pollution 3.021/5. Specially, 41.1% of the respondents indicated the lack of the replied ratio. 10) On Nurses' Qualifications. The respondents were selected five items as the most important qualifications. Specially, 17.4% of the respondents indicated specialized knowledge, 15.3% the nurses' health, 10.6% satisfaction for nursing profession, 9.8% the experience need, 9.2% comprehension and cooperation, while warm personality as nursing qualifications have a tendency of being lighted. 11) On the Priority of Nursing Care The respondents were selected three items as the most important component. Most of the respondents view the client's physical, spiritual: economic points as important components of nursing care. They showed each 36.8%, 27.6%, 13.8% while educational ones showed 1.8%. 12) On Purpose of Nursing Care. The respondents were selected four items as the most important purpose. Specially,29.3% of the respondents indicated curing illness for clients, 21.3% preventing illness for client 17.4% decreasing pain, 15.3% surviving. 13) On the Analysis of Important Nursing Care Ranging from 5 point to 25 point, the nurses' qualification are concentrated at the degree of 95.1%. Ranging from 3 point to 25, the priorities of nursing care are concentrated at the degree of 96.4%. Ranging from 4 point to 16, the purpose of nursing care is concentrated at the degree of 84.0%. 14) The Analysis, of General Characteristics and Facts of Nursing Concept. The correlation between the educational high level and nursing care showed significance. (P < 0.0262). The correction between the educational low level and purpose of nursing care showed significance. (P < 0.002) The correlation between nurses' working yeras and the degree of importance for the purpose of nursing care showed significance (P < 0.0155) Specially, the most affirmative answers were showed from two years to four ones. 15) On Nunes' qualification and its Degree of Importance The correlation between nurses' qualification and its degree of importance showed significance. (r = 0.2172, p< 0.001) 0.005) B. General characteristics of the subjects The mean age of the subject was 39 ; with 38.6% with in the age range of 20-29 ; 52.6% were male; 57.9% were Schizophrenia; 35.1% were graduated from high school or high school dropouts; 56.l% were not have any religion; 52.6% were unmarried; 47.4% were first admission; 91.2% were involuntary admission patients. C. Measurement of anxiety variables. 1. Measurement tools of affective anxiety in this study demonstrated high reliability (.854). 2. Measurement tools of somatic anxiety in this study demonstrated high reliability (.920). D. Relationship between the anxiety variables and the general characteristics. 1. Relationship between affective anxiety and general characteristics. 1) The level of female patients were higher than that of the male patient (t = 5.41, p < 0.05). 2) Frequencies of admission were related to affective anxiety, so in the first admission the anxiety level was the highest. (F = 5.50, p < 0.005). 2, Relationship between somatic anxiety and general characteristics. 1) The age range of 30-39 was found to have the highest level of the somatic anxiety. (F = 3.95, p < 0.005). 2) Frequencies of admission were related to the somatic anxiety, so .in first admission the anxiety level was the highest. (F = 9.12, p < 0.005) 0. Analysis of significant anxiety symptoms for nursing intervention. 1. Seven items such as dizziness, mental integration, sweating, restlessness, anxiousness, urinary frequency and insomnia, init. accounted for 96% of the variation within the first 24 hours after admission. 2. Seven items such as fear, paresthesias, restlessness, sweating insomnia, init., tremors and body aches and pains accounted for 84% of the variation on the 10th day after admission.

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The Influences of Maintenance Hemodialysis on Sleep Architecture and Sleep Apnea in the Patients with Chronic Renal Failure (만성신부전 환자에서 혈액투석 유지요법이 수면구조 및 수면 무호흡에 미치는 영향)

  • Park, Yong-Geun;Lee, Sang-Haak;Choi, Young-Mee;Ahn, Seok-Joo;Kwon, Soon-Seog;Kim, Young-Kyoon;Kim, Kwan-Hyoung;Song, Jeong-Sup;Park, Sung-Hak;Moon, Hwa-Sik
    • Tuberculosis and Respiratory Diseases
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    • v.47 no.6
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    • pp.824-835
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    • 1999
  • Background: Sleep-related breathing disorders are commonly found in patients with chronic renal failure and particularly, sleep apnea may have an influence on the long-term mortality rates in these patients. Maintenance hemodialysis is the mainstay of medical measures for correcting the metabolic derangements of chronic renal failure but it is uncertain whether it may alleviate sleep disorders including sleep apnea. Methods: Forty seven patients on maintenance hemodialysis were surveyed with the sleep questionnaire about their clinical symptoms related to sleep disorders. Among them, 15 patients underwent the polysomnography and their blood levels of urea nitrogen, creatinine, electrolytes and the arterial blood gases in the nights before and following hemodialysis were measured. Results: Forty(85.1%) of the 47 patients complained of the symptoms associated with sleep-wake cycle disturbances, 55.3% experienced snoring and 27.7% reported witnessed apneas. The duration of REM sleep increased significantly in the nights after hemodialysis compared to the nights without hemodialysis(p<0.05) and the percentage of total sleep time comprising NREM sleep decreased significantly in the nights following hemodialysis compared to the nights before hemodialysis(p<0.05). The percentage of total sleep time consisting of the stage 1 and 2 NREM sleep showed the trend for a decrease in the nights after hemodialysis(p=0.051), while the percentage of total sleep time comprising the stage 3 and 4 NREM sleep did not change between nights. The obstructive sleep apnea was more predominant type than the central one in both nights and there were no differences in the apnea index and the apnea-hypopnea index between the nights. The decrease in the blood level of urea nitrogen, creatinine, potassium and phosphorus was observed after hemodialysis(p<0.05), but the differences of parameters measured during polysomnography between the nights did not correlate with the changes of biochemical factors obtained on the two nights. Arterial blood gas analysis showed that pH was significantly greater in the nights after hemodialysis than in the nights before hemodialysis(p<0.05), but there were no correlations between the parameters examined during polysomnography and the parameters of arterial blood gas analysis(p<0.05). Conclusion: These results suggest that chronic renal failure is an important systemic disorder which is strongly associated with sleep disorders. Maintenance hemodialysis, although it is a widely accepted measure to treat chronic renal failure, did not significantly modulate the sleep architecture and the severity of sleep apnea. Thus, taking the patients with chronic renal failure into account, it is advisable to try not only to find a substantial way for correcting metabolic derangements but also to consider the institution of more effective treatments for sleep disorders.

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Lipid Contents Characteristics of Gene Accumulate in Rice (벼 유전자 집적에 따른 지질함량 특성)

  • 윤경민;홍순관
    • Korean Journal of Plant Resources
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    • v.15 no.3
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    • pp.177-187
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    • 2002
  • In our experiment, selected mutants were used which showed not only the phenotype of a specific unpolished rice but also phenotypes of EM 40, LO 1050, and TAL 214. Reciprocal crosses between the mutants were conducted to select strains which would have more quantity of lipids than before. The constitution of fatty acid was also tested to figure out nutritional aspects of the mutants. In the crossing between EM 40 mutants and mutants (LO 1050) having a thick aleurone layer, the expression of EM 40 mutants has no relation with the thickness of the aleurone layer. And the lipid content of new F$_2$ strains through the crossing is 4.15 %. The lipid content is larger than those of the parents including Kinmaze and in other crossings of this experiment. This is attributed to the fact that the new F$_2$ strains are the products of the crossing between genes responsible for the size of buds, where lipid is accumulated, and genes accountable for the thickness of the aleurone layer. In the crossing between EM 40 mutants and TAL 214 mutants, lipid content of the new F$_2$ strains is 3.8 %, higher than 2.92 % of TAL 214 mutants. But the degree of lipid increase is smaller than in two other crossings. This is probably because genes expressing the phenotypes of TAL 214 affect the size of EM 40, which gets smaller. The aleurone layer of the new F$_2$ strains is 12 $\mu\textrm{m}$ thicker than the layer of TAL 214 mutants, but 6 $\mu\textrm{m}$ thinner than that of parents (LO 1050) having a thick aleurone layer. This seems to be affected by the size of a microscope. The phenotype of the new F$_2$ strains appears to be similar to that of TAL 214. The lipid content of the new F$_2$ strains is 3.85 %, larger than 2.92 % of TAL 214 and 3.01 % of LO 1050. The increase may be due to the aleurone layer of LO 1050. And the size of the bud of the unpolished rice, though it is not big enough like that of LO 1050, seems to be affected by the accumulation of genes in the thick aleurone layer. The accumulation may contribute to the increase in the content of lipid. When it comes to the constitution of fatty acid, there is little difference between parents like Kinmaze and the new F$_2$ strains. But oleic acid increases while linoleic acid decreases. And the decrease in the linolenic acid seems to contribute to the increase in lipid content. This fact also raises the possibility that genes accountable for specific phenotypes could change the quality of rice if the genes are accumulated. Now, experiments on strains which have large lipid content in EM 40 type 1(ge-1, 3.68 %), EM type 2(ge-2, 2.91 %), thick aleurone layer(4.63 %), and starch layer(3.44 %) are under way to figure out the effects of gene accumulation. These experiments are likely to present the ways for increasing the lipid content.

Genetic Counseling in Korean Health Care System (한국 의료제도와 유전상담 서비스의 구축)

  • Kim, Hyon-J.
    • Journal of Genetic Medicine
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    • v.8 no.2
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    • pp.89-99
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    • 2011
  • Over the years Korean health care system has improved in delivery of quality care to the general population for many areas of the health problems. The system is now being recognized in the world as the most cost effective one. It is covered by the uniform national health insurance policy for which most people in Korea are mandatory policy holders. Genetic counseling service, however, which is well recognized as an integral part of clinical genetics service deals with diagnosis and management of genetic condition as well as genetic information presentation and family support, is yet to be delivered in comprehensive way for the patients and families in need. Two major obstacles in providing genetic counseling service in korean health care system are identified; One is the lack of recognition for the need for genetic counseling service as necessary service by the national health insurance. Genetic counseling consumes a significant time in delivery and the current very low-fee schedule for physician service makes it very difficult to provide meaningful service. Second is the critical shortage of qualified professionals in the field of medical genetics and genetic counseling who can provide the service of genetic counseling in clinical setting. However, recognition and understanding of the fact that the scope and role of genetic counseling is expanding in post genomic era of personalized medicine for delivery of quality health care, will lead to the efforts to overcome obstacles in providing genetic counseling service in korean health care system. Only concerted efforts from health care policy makers of government on clinical genetics service and genetic counseling for establishing adequate reimbursement coverage and professional communities for developing educational program and certification process for professional genetic counselors, are necessary for the delivery of much needed clinical genetic counseling service in Korea.

Construction of Consumer Confidence index based on Sentiment analysis using News articles (뉴스기사를 이용한 소비자의 경기심리지수 생성)

  • Song, Minchae;Shin, Kyung-shik
    • Journal of Intelligence and Information Systems
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    • v.23 no.3
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    • pp.1-27
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    • 2017
  • It is known that the economic sentiment index and macroeconomic indicators are closely related because economic agent's judgment and forecast of the business conditions affect economic fluctuations. For this reason, consumer sentiment or confidence provides steady fodder for business and is treated as an important piece of economic information. In Korea, private consumption accounts and consumer sentiment index highly relevant for both, which is a very important economic indicator for evaluating and forecasting the domestic economic situation. However, despite offering relevant insights into private consumption and GDP, the traditional approach to measuring the consumer confidence based on the survey has several limits. One possible weakness is that it takes considerable time to research, collect, and aggregate the data. If certain urgent issues arise, timely information will not be announced until the end of each month. In addition, the survey only contains information derived from questionnaire items, which means it can be difficult to catch up to the direct effects of newly arising issues. The survey also faces potential declines in response rates and erroneous responses. Therefore, it is necessary to find a way to complement it. For this purpose, we construct and assess an index designed to measure consumer economic sentiment index using sentiment analysis. Unlike the survey-based measures, our index relies on textual analysis to extract sentiment from economic and financial news articles. In particular, text data such as news articles and SNS are timely and cover a wide range of issues; because such sources can quickly capture the economic impact of specific economic issues, they have great potential as economic indicators. There exist two main approaches to the automatic extraction of sentiment from a text, we apply the lexicon-based approach, using sentiment lexicon dictionaries of words annotated with the semantic orientations. In creating the sentiment lexicon dictionaries, we enter the semantic orientation of individual words manually, though we do not attempt a full linguistic analysis (one that involves analysis of word senses or argument structure); this is the limitation of our research and further work in that direction remains possible. In this study, we generate a time series index of economic sentiment in the news. The construction of the index consists of three broad steps: (1) Collecting a large corpus of economic news articles on the web, (2) Applying lexicon-based methods for sentiment analysis of each article to score the article in terms of sentiment orientation (positive, negative and neutral), and (3) Constructing an economic sentiment index of consumers by aggregating monthly time series for each sentiment word. In line with existing scholarly assessments of the relationship between the consumer confidence index and macroeconomic indicators, any new index should be assessed for its usefulness. We examine the new index's usefulness by comparing other economic indicators to the CSI. To check the usefulness of the newly index based on sentiment analysis, trend and cross - correlation analysis are carried out to analyze the relations and lagged structure. Finally, we analyze the forecasting power using the one step ahead of out of sample prediction. As a result, the news sentiment index correlates strongly with related contemporaneous key indicators in almost all experiments. We also find that news sentiment shocks predict future economic activity in most cases. In almost all experiments, the news sentiment index strongly correlates with related contemporaneous key indicators. Furthermore, in most cases, news sentiment shocks predict future economic activity; in head-to-head comparisons, the news sentiment measures outperform survey-based sentiment index as CSI. Policy makers want to understand consumer or public opinions about existing or proposed policies. Such opinions enable relevant government decision-makers to respond quickly to monitor various web media, SNS, or news articles. Textual data, such as news articles and social networks (Twitter, Facebook and blogs) are generated at high-speeds and cover a wide range of issues; because such sources can quickly capture the economic impact of specific economic issues, they have great potential as economic indicators. Although research using unstructured data in economic analysis is in its early stages, but the utilization of data is expected to greatly increase once its usefulness is confirmed.

Suggestion of Urban Regeneration Type Recommendation System Based on Local Characteristics Using Text Mining (텍스트 마이닝을 활용한 지역 특성 기반 도시재생 유형 추천 시스템 제안)

  • Kim, Ikjun;Lee, Junho;Kim, Hyomin;Kang, Juyoung
    • Journal of Intelligence and Information Systems
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    • v.26 no.3
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    • pp.149-169
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    • 2020
  • "The Urban Renewal New Deal project", one of the government's major national projects, is about developing underdeveloped areas by investing 50 trillion won in 100 locations on the first year and 500 over the next four years. This project is drawing keen attention from the media and local governments. However, the project model which fails to reflect the original characteristics of the area as it divides project area into five categories: "Our Neighborhood Restoration, Housing Maintenance Support Type, General Neighborhood Type, Central Urban Type, and Economic Base Type," According to keywords for successful urban regeneration in Korea, "resident participation," "regional specialization," "ministerial cooperation" and "public-private cooperation", when local governments propose urban regeneration projects to the government, they can see that it is most important to accurately understand the characteristics of the city and push ahead with the projects in a way that suits the characteristics of the city with the help of local residents and private companies. In addition, considering the gentrification problem, which is one of the side effects of urban regeneration projects, it is important to select and implement urban regeneration types suitable for the characteristics of the area. In order to supplement the limitations of the 'Urban Regeneration New Deal Project' methodology, this study aims to propose a system that recommends urban regeneration types suitable for urban regeneration sites by utilizing various machine learning algorithms, referring to the urban regeneration types of the '2025 Seoul Metropolitan Government Urban Regeneration Strategy Plan' promoted based on regional characteristics. There are four types of urban regeneration in Seoul: "Low-use Low-Level Development, Abandonment, Deteriorated Housing, and Specialization of Historical and Cultural Resources" (Shon and Park, 2017). In order to identify regional characteristics, approximately 100,000 text data were collected for 22 regions where the project was carried out for a total of four types of urban regeneration. Using the collected data, we drew key keywords for each region according to the type of urban regeneration and conducted topic modeling to explore whether there were differences between types. As a result, it was confirmed that a number of topics related to real estate and economy appeared in old residential areas, and in the case of declining and underdeveloped areas, topics reflecting the characteristics of areas where industrial activities were active in the past appeared. In the case of the historical and cultural resource area, since it is an area that contains traces of the past, many keywords related to the government appeared. Therefore, it was possible to confirm political topics and cultural topics resulting from various events. Finally, in the case of low-use and under-developed areas, many topics on real estate and accessibility are emerging, so accessibility is good. It mainly had the characteristics of a region where development is planned or is likely to be developed. Furthermore, a model was implemented that proposes urban regeneration types tailored to regional characteristics for regions other than Seoul. Machine learning technology was used to implement the model, and training data and test data were randomly extracted at an 8:2 ratio and used. In order to compare the performance between various models, the input variables are set in two ways: Count Vector and TF-IDF Vector, and as Classifier, there are 5 types of SVM (Support Vector Machine), Decision Tree, Random Forest, Logistic Regression, and Gradient Boosting. By applying it, performance comparison for a total of 10 models was conducted. The model with the highest performance was the Gradient Boosting method using TF-IDF Vector input data, and the accuracy was 97%. Therefore, the recommendation system proposed in this study is expected to recommend urban regeneration types based on the regional characteristics of new business sites in the process of carrying out urban regeneration projects."

Chinese relationship between animation and best pole - Focused on the aesthetic principles of the Cultural Revolution period (중국 애니메이션과 모범극의 상관관계 연구 - 문화대혁명 시기의 미학 원칙을 중심으로)

  • Kong, De Wei
    • Cartoon and Animation Studies
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    • s.39
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    • pp.215-231
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    • 2015
  • The Cultural Revolution in the history of Chinese animation hinder the development of the initial animation, and after a negative assessment instrument provided the cause is to become sluggish growth of the Chinese animation. So this time animation are things that are the subject of academic research studies or analysis has been depreciating almost uniformly without evaluation. However, of all the cultural and artistic creation it is developing in its own specific historical conditions and has the aesthetic results. This paper puts the primary purpose is to hold in consideration the aesthetic principles that led to cultural and artistic creativity and objective perspective the achievements the Chinese animation of the time period of the Cultural Revolution. Cultural Revolution is avoided to the previous period in accordance with the socialist ideology of Mao Ze-dong(毛澤東) sikindaneun highlight the culture of the proletariat and placed our goal to create a new class culture. Therefore, cultural and artistic creation of this period is often inconsistent with this part of our aesthetic principles generally accepted character has a non- elitist and anti properties. Best drama is a creative one hand as a model to implement the principles of aesthetics, art and culture Cultural Revolution period kkophimyeo reference for understanding the aesthetic principles that animated the Chinese Cultural Revolution period of orientation. This paper has San Tu Chu(三突出), Hong Guang Liang(紅光亮), and Gao Da Quan(高大全) at the time of the Cultural Revolution aesthetic principles are reflected in how the concrete work, the Cultural Revolution when the animation is how to accommodate these aesthetic principles and placed emphasis on comparative studies on best pole and correlation of the Cultural Revolution when the Chinese animation to ensure that adaptation in own way. First, after analyzing whether the aesthetic principles of focusing on the similarities of the best pole time of the Cultural Revolution and China, and how to implement animation in the works, these aesthetic principles according to the analysis of positive and negative influence on the creation of Chinese animation It was described as neutral. The detailed analysis and comparative study courses were trying to access in two significant aspects of the characters and scenes directing. In terms of character animation of the Cultural Revolution in China when a young boy or girl, emphasis should emphasize the health tinged with red lips and cheek blush to highlight the desired Gong Nong Bing(工農兵) shape as the main character and smooth texture and sophisticated highlights the glittering feeling to the touch, it was confirmed focused hayeoteum to implement the principle of 'Hong Guang Liang', highlighting the brilliant colors with a clean, bright colors. Highlighting a number of protagoniste compared to the antagonist in the animated scene of the Cultural Revolution a few times in terms of production and, among a number of protagoniste also emphasizes the outstanding hero figure, "yet three outstanding heroes heroic figures also emphasize the leading figures among the the director of the extrusion step-by-step approach "('San Tu Chu')was used. In addition, the hero figure is generally high and low angle by directing a large and perfect aesthetic appearance was to faithfully implement the principle of 'high-charged'('Gao Da Quan').

Ensemble Learning with Support Vector Machines for Bond Rating (회사채 신용등급 예측을 위한 SVM 앙상블학습)

  • Kim, Myoung-Jong
    • Journal of Intelligence and Information Systems
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    • v.18 no.2
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    • pp.29-45
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    • 2012
  • Bond rating is regarded as an important event for measuring financial risk of companies and for determining the investment returns of investors. As a result, it has been a popular research topic for researchers to predict companies' credit ratings by applying statistical and machine learning techniques. The statistical techniques, including multiple regression, multiple discriminant analysis (MDA), logistic models (LOGIT), and probit analysis, have been traditionally used in bond rating. However, one major drawback is that it should be based on strict assumptions. Such strict assumptions include linearity, normality, independence among predictor variables and pre-existing functional forms relating the criterion variablesand the predictor variables. Those strict assumptions of traditional statistics have limited their application to the real world. Machine learning techniques also used in bond rating prediction models include decision trees (DT), neural networks (NN), and Support Vector Machine (SVM). Especially, SVM is recognized as a new and promising classification and regression analysis method. SVM learns a separating hyperplane that can maximize the margin between two categories. SVM is simple enough to be analyzed mathematical, and leads to high performance in practical applications. SVM implements the structuralrisk minimization principle and searches to minimize an upper bound of the generalization error. In addition, the solution of SVM may be a global optimum and thus, overfitting is unlikely to occur with SVM. In addition, SVM does not require too many data sample for training since it builds prediction models by only using some representative sample near the boundaries called support vectors. A number of experimental researches have indicated that SVM has been successfully applied in a variety of pattern recognition fields. However, there are three major drawbacks that can be potential causes for degrading SVM's performance. First, SVM is originally proposed for solving binary-class classification problems. Methods for combining SVMs for multi-class classification such as One-Against-One, One-Against-All have been proposed, but they do not improve the performance in multi-class classification problem as much as SVM for binary-class classification. Second, approximation algorithms (e.g. decomposition methods, sequential minimal optimization algorithm) could be used for effective multi-class computation to reduce computation time, but it could deteriorate classification performance. Third, the difficulty in multi-class prediction problems is in data imbalance problem that can occur when the number of instances in one class greatly outnumbers the number of instances in the other class. Such data sets often cause a default classifier to be built due to skewed boundary and thus the reduction in the classification accuracy of such a classifier. SVM ensemble learning is one of machine learning methods to cope with the above drawbacks. Ensemble learning is a method for improving the performance of classification and prediction algorithms. AdaBoost is one of the widely used ensemble learning techniques. It constructs a composite classifier by sequentially training classifiers while increasing weight on the misclassified observations through iterations. The observations that are incorrectly predicted by previous classifiers are chosen more often than examples that are correctly predicted. Thus Boosting attempts to produce new classifiers that are better able to predict examples for which the current ensemble's performance is poor. In this way, it can reinforce the training of the misclassified observations of the minority class. This paper proposes a multiclass Geometric Mean-based Boosting (MGM-Boost) to resolve multiclass prediction problem. Since MGM-Boost introduces the notion of geometric mean into AdaBoost, it can perform learning process considering the geometric mean-based accuracy and errors of multiclass. This study applies MGM-Boost to the real-world bond rating case for Korean companies to examine the feasibility of MGM-Boost. 10-fold cross validations for threetimes with different random seeds are performed in order to ensure that the comparison among three different classifiers does not happen by chance. For each of 10-fold cross validation, the entire data set is first partitioned into tenequal-sized sets, and then each set is in turn used as the test set while the classifier trains on the other nine sets. That is, cross-validated folds have been tested independently of each algorithm. Through these steps, we have obtained the results for classifiers on each of the 30 experiments. In the comparison of arithmetic mean-based prediction accuracy between individual classifiers, MGM-Boost (52.95%) shows higher prediction accuracy than both AdaBoost (51.69%) and SVM (49.47%). MGM-Boost (28.12%) also shows the higher prediction accuracy than AdaBoost (24.65%) and SVM (15.42%)in terms of geometric mean-based prediction accuracy. T-test is used to examine whether the performance of each classifiers for 30 folds is significantly different. The results indicate that performance of MGM-Boost is significantly different from AdaBoost and SVM classifiers at 1% level. These results mean that MGM-Boost can provide robust and stable solutions to multi-classproblems such as bond rating.

Multi-Dimensional Analysis Method of Product Reviews for Market Insight (마켓 인사이트를 위한 상품 리뷰의 다차원 분석 방안)

  • Park, Jeong Hyun;Lee, Seo Ho;Lim, Gyu Jin;Yeo, Un Yeong;Kim, Jong Woo
    • Journal of Intelligence and Information Systems
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    • v.26 no.2
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    • pp.57-78
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    • 2020
  • With the development of the Internet, consumers have had an opportunity to check product information easily through E-Commerce. Product reviews used in the process of purchasing goods are based on user experience, allowing consumers to engage as producers of information as well as refer to information. This can be a way to increase the efficiency of purchasing decisions from the perspective of consumers, and from the seller's point of view, it can help develop products and strengthen their competitiveness. However, it takes a lot of time and effort to understand the overall assessment and assessment dimensions of the products that I think are important in reading the vast amount of product reviews offered by E-Commerce for the products consumers want to compare. This is because product reviews are unstructured information and it is difficult to read sentiment of reviews and assessment dimension immediately. For example, consumers who want to purchase a laptop would like to check the assessment of comparative products at each dimension, such as performance, weight, delivery, speed, and design. Therefore, in this paper, we would like to propose a method to automatically generate multi-dimensional product assessment scores in product reviews that we would like to compare. The methods presented in this study consist largely of two phases. One is the pre-preparation phase and the second is the individual product scoring phase. In the pre-preparation phase, a dimensioned classification model and a sentiment analysis model are created based on a review of the large category product group review. By combining word embedding and association analysis, the dimensioned classification model complements the limitation that word embedding methods for finding relevance between dimensions and words in existing studies see only the distance of words in sentences. Sentiment analysis models generate CNN models by organizing learning data tagged with positives and negatives on a phrase unit for accurate polarity detection. Through this, the individual product scoring phase applies the models pre-prepared for the phrase unit review. Multi-dimensional assessment scores can be obtained by aggregating them by assessment dimension according to the proportion of reviews organized like this, which are grouped among those that are judged to describe a specific dimension for each phrase. In the experiment of this paper, approximately 260,000 reviews of the large category product group are collected to form a dimensioned classification model and a sentiment analysis model. In addition, reviews of the laptops of S and L companies selling at E-Commerce are collected and used as experimental data, respectively. The dimensioned classification model classified individual product reviews broken down into phrases into six assessment dimensions and combined the existing word embedding method with an association analysis indicating frequency between words and dimensions. As a result of combining word embedding and association analysis, the accuracy of the model increased by 13.7%. The sentiment analysis models could be seen to closely analyze the assessment when they were taught in a phrase unit rather than in sentences. As a result, it was confirmed that the accuracy was 29.4% higher than the sentence-based model. Through this study, both sellers and consumers can expect efficient decision making in purchasing and product development, given that they can make multi-dimensional comparisons of products. In addition, text reviews, which are unstructured data, were transformed into objective values such as frequency and morpheme, and they were analysed together using word embedding and association analysis to improve the objectivity aspects of more precise multi-dimensional analysis and research. This will be an attractive analysis model in terms of not only enabling more effective service deployment during the evolving E-Commerce market and fierce competition, but also satisfying both customers.