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Reoperations on the Aortic Root and Ascending Aorta (대동맥근부 혹은 상행대동맥의 재수술)

  • Baek, Man-Jong;Na, Chan-Young;Kim, Woong-Han;Oh, Sam-Se;Kim, Soo-Cheol;Lim, Cheong;Ryu, Jae-Wook;Kong, Joon-Hyuk;Kim, Wook-Sung;Lee, Young-Tak;Moon, Hyun-Soo;Park, Young-Kwan;Kim, Chong-Whan
    • Journal of Chest Surgery
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    • v.35 no.3
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    • pp.188-198
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    • 2002
  • Background: Reoperations on the aortic root or the ascending aorta are being performed with increasing frequency and remain a challenging problem. This study was performed to analyze the results of reoperations on the ascending aorta and aortic root. Material and Method: Between May 1995 and April 2001, 30 patients had reoperations on the ascending aorta and aortic root and were reviewed retrospectively. The mean interval between the previous repair and the actual reoperation was 56 months(range 3 to 142 months). Seven patients(23.3%) had two or more previous operations. The indications for reoperations were true aneurysm in 7 patients(23.3%), prosthetic valve endocarditis in 6(20%), false aneurysm in 5(16.7%), paravalvular leak associated with Behcet's disease in 4(13.3%), malfunction of prosthetic aortic valve in 4(13.3%), aortic dissection in 3(10%), and annuloaortic ectasia in 1(3.3%). The principal reoperations performed were aortic root replacement in 17 patients(56.7%), replacement of the ascending aorta in 8(26.7%), aortic and mitral valve replacement with reconstruction of fibrous trigone in 2(6.6%), patch aortoplasty in 2(6.6%), and aortic valve replacement after Bentall operation in 1 (3.3%). The cardiopulmonary bypass was started before sternotomy in 7 patients and the hypothermic circulatory arrest was used in 16(53.3%). The mean time of circulatory arrest, total bypass, and aortic crossclamp were 20$\pm$ 12 minutes, 228$\pm$56 minutes, and 143$\pm$62 minutes, respectively Result: There were three early deaths(10%). The postoperative complications were reoperation for bleeding in 7 patients(23.3%), cardiac complications in 5(16.7%), transient acute renal failure in 2(6.6%), transient focal seizure in 2(6.6%), and the others in 5. The mean follow-up was 22.8 $\pm$20.5 months. There were two late deaths(7.4%). The actuarial survival was 92.6$\pm$5.0% at 6 years. One patient required reoperation for complication of reoperation on the ascending aorta and aortic root(3.7%). The 1- and 6-year actuarial freedom from reoperation was 100% and 83.3$\pm$15.2%, respectively. One patient with Behcet's disease are waiting for reoperation due to false aneurysm, which developed after aortic root replacement with homograft. There were no thromboembolisms or anticoagulant related complications. Conclusions: This study suggests that reoperations on the ascending aorta and aortic root can be performed with acceptable early mortality and morbidity, and adequate surgical strategies according to the pathologi conditions are critical to the prevention of the reoperation.

Clinical Features and the Natural History of Dietary Protein Induced Proctocolitis: a Study on the Elimination of Offending Foods from the Maternal Diet (식품 단백질 유발성 직결장염의 임상 소견과 식이 조절에 관한 연구)

  • Choi, Seon Yun;Park, Moon Ho;Choi, Won Joung;Kang, Una;Oh, Hoon Kyu;Kam, Sin;Hwang, Jin-Bok
    • Pediatric Gastroenterology, Hepatology & Nutrition
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    • v.8 no.1
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    • pp.21-30
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    • 2005
  • Purpose: The aim of this study was to identify the clinical features and natural history of dietary protein induced proctocolitis (DPIPC) and to detect the causative foods of DPIPC, and to evaluate the effect of elimination of the foods on the course of the disease. Methods: Between March 2003 and July 2004, data from 30 consecutive patients with DPIPC who were followed for over 6 months, was reviewed. The diagnostic criterion used for DPIPC was an increase in the number of eosinophils in the lamina propria (${\geq}60per$ 10 high-power fields). In breast feeding mothers, 5 highly allergenic foods were eliminated from the maternal diet for 7 days, namely, allergenic food groups such as dairy products, eggs, nuts and soybean, fish and shellfish, and wheat and buckwheat. We observed the disappearance or appearance of hematochezia after elimination or challenge with the offending foods. Results: Before diagnosis infants were breast-fed (93.3%) or formula-fed (6.7%). Mean age at symptom onset was $11.5{\pm}5.1$ (5~24) weeks, and mean age at diagnosis was $17.8{\pm}9.5$ (8~56) weeks. Duration from symptom onset to diagnosis was $6.3{\pm}6.7$ (0~36) weeks. Mean peripheral blood eosinophil count was $478{\pm}320$ (40~1,790)/$mm^3$ and eosinophilia (> $250/mm^3$) was observedin 90.0% of patients. None of patients were found to have an increased serum IgE level. Of 15 patients that received sigmoidoscopy, nodular hyperplasia with erosion was observed in 93.3%. Of 27 patients whose mother ate the diet eliminated the 5 food groups, hematochezia diappeared in 74.1% of patients. Offending foods were identified as dairy products (37.5%), wheat and buckwheat (27.5%), fish and shellfish (20.0%), nuts and soybean (7.5%) and eggs (7.5%). A free maternal diet without patient's clinical symptoms was achieved at $29.4{\pm}8.7$ (9~44) weeks of patient's age, and a free baby diet without blood in stools was achieved at $37.5{\pm}9.7$ (12~56) weeks of age. Conclusion: DPIPC commonly occurs in exclusively breast-fed babies. Elimination of the above-mentioned 5 hyper-allergenic food groups from the maternal diet for 7days enables the detection of the offending foods. DPIPC is a transient disorder and 96.0% of patients can tolerate the offending foods at 12 months of age.

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Oxidative Inactivation of Peroxiredoxin Isoforms by H2O2 in Pulmonary Epithelial, Macrophage, and other Cell Lines with their Subsequent Regeneration (폐포상피세포, 대식세포를 비롯한 각종 세포주에서 H2O2에 의한 Peroxiredoxin 동위효소들의 산화에 따른 불활성화와 재생)

  • Oh, Yoon Jung;Kim, Young Sun;Choi, Young In;Shin, Seung Soo;Park, Joo Hun;Choi, Young Hwa;Park, Kwang Joo;Park, Rae Woong;Hwang, Sung Chul
    • Tuberculosis and Respiratory Diseases
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    • v.58 no.1
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    • pp.31-42
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    • 2005
  • Background : Peroxiredoxins (Prxs) are a relatively newly recognized, novel family of peroxidases that reduce $H_2O_2$ and alkylhydroperoxide into water and alcohol, respectively. There are 6 known isoforms of Prxs present in human cells. Normally, Prxs exist in a head-to-tail homodimeric state in a reduced form. However, in the presence of excess $H_2O_2$, it can be oxidized on its catalytically active cysteine site into inactive oxidized forms. This study surveyed the types of the Prx isoforms present in the pulmonary epithelial, macrophage, endothelial, and other cell lines and observed their response to oxidative stress. Methods : This study examined the effect of exogenous, excess $H_2O_2$ on the Prxs of established cell lines originating from the pulmonary epithelium, macrophages, and other cell lines, which are known to be exposed to high oxygen partial pressures or are believed to be subject to frequent oxidative stress, using non-reducing SDS polyacrylamide electrophoresis (PAGE) and 2 dimensional electrophoresis. Result : The addition of excess $H_2O_2$ to the culture media of the various cell-lines caused the immediate inactivation of Prxs, as evidenced by their inability to form dimers by a disulfide cross linkage. This was detected as a subsequent shift to its monomeric forms on the non-reducing SDS PAGE. These findings were further confirmed by 2 dimensional electrophoresis and immunoblot analysis by a shift toward a more acidic isoelectric point (pI). However, the subsequent reappearance of the dimeric Prxs with a comparable, corresponding decrease in the monomeric bands was noted on the non-reducing SDS PAGE as early as 30 minutes after the $H_2O_2$ treatment suggesting regeneration after oxidation. The regenerated dimers can again be converted to the inactivated form by a repeated $H_2O_2$ treatment, indicating that the protein is still catalytically active. The recovery of Prxs to the original dimeric state was not inhibited by a pre-treatment with cycloheximide, nor by a pretreatment with inhibitors of protein synthesis, which suggests that the reappearance of dimers occurs via a regeneration process rather than via the de novo synthesis of the active protein. Conclusion : The cells, in general, appeared to be equipped with an established system for regenerating inactivated Prxs, and this system may function as a molecular "on-off switch" in various oxidative signal transduction processes. The same mechanisms might applicable other proteins associated with signal transduction where the active catalytic site cysteines exist.

Effects of Molecular Weight of Polyethylene Glycol on the Dimensional Stabilization of Wood (Polyethylene Glycol의 분자량(分子量)이 목재(木材)의 치수 안정화(安定化)에 미치는 영향(影響))

  • Cheon, Cheol;Oh, Joung Soo
    • Journal of Korean Society of Forest Science
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    • v.71 no.1
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    • pp.14-21
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    • 1985
  • This study was carried out in order to prevent the devaluation of wood itself and wood products causing by anisotropy, hygroscopicity, shrinkage and swelling - properties that wood itself only have, in order to improve utility of wood, by emphasizing the natural beautiful figures of wood, to develop the dimensional stabilization techniques of wood with PEG that it is a cheap, non-toxic and the impregnation treatment is not difficult, on the effects of PEG molecular weights (200, 400, 600, 1000, 1500, 2000, 4000, 6000) and species (Pinus densiflora S. et Z., Larix leptolepis Gordon., Cryptomeria japonica D. Don., Cornus controversa Hemsl., Quercus variabilis Blume., Prunus sargentii Rehder.). The results were as follows; 1) PEG loading showed the maximum value (137.22%, Pinus densiflora, in PEG 400), the others showed that relatively slow decrease. The lower specific gravity, the more polymer loading. 2) Bulking coefficient didn't particularly show the correlation with specific gravity, for the most part, indicated the maximum values in PEG 600, except that the bulking coefficient of Quercus variabilis distributed between the range of 12-18% in PEG 400-2000. In general, the bulking coefficient of hardwood was higher than that of softwood. 3) Although there was more or less an exception according to species, volumetric swelling reduction was the greatest in PEG 400. That is, its value of Cryptomeria japonica was the greatest value with 95.0%, the others indicated more than 80% except for Prunus sargentii, while volumetric swelling reduction was decreased less than 70% as the molecular weight increase more than 1000. 4) The relative effectiveness of hardwood with high specific gravity was outstandingly higher than softwood. In general, the relative effectiveness of low molecular weight PEG was superior to those of high molecular weight PEG except that Quercus variabilis showed more than 1.6 to the total molecular weight range, while it was no significant difference as the molecular weight increase more than 4000. 5) According to the analysis of the results mentioned above, the dimensional stabilization of hardwood was more effective than softwood. Although volumetric swelling reduction was the greatest at a molecular weight of 400. In the view of polymer loading, bulking coefficiency reduction of swelling and relative effectiveness, it is desirable to use the mixture of PEG of molecular weight in the range of 200-1500. To practical use, it is recommended to study about the effects on the mixed ratio on the bulking coefficient, reduction of swelling and relative effectiveness.

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Context Sharing Framework Based on Time Dependent Metadata for Social News Service (소셜 뉴스를 위한 시간 종속적인 메타데이터 기반의 컨텍스트 공유 프레임워크)

  • Ga, Myung-Hyun;Oh, Kyeong-Jin;Hong, Myung-Duk;Jo, Geun-Sik
    • Journal of Intelligence and Information Systems
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    • v.19 no.4
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    • pp.39-53
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    • 2013
  • The emergence of the internet technology and SNS has increased the information flow and has changed the way people to communicate from one-way to two-way communication. Users not only consume and share the information, they also can create and share it among their friends across the social network service. It also changes the Social Media behavior to become one of the most important communication tools which also includes Social TV. Social TV is a form which people can watch a TV program and at the same share any information or its content with friends through Social media. Social News is getting popular and also known as a Participatory Social Media. It creates influences on user interest through Internet to represent society issues and creates news credibility based on user's reputation. However, the conventional platforms in news services only focus on the news recommendation domain. Recent development in SNS has changed this landscape to allow user to share and disseminate the news. Conventional platform does not provide any special way for news to be share. Currently, Social News Service only allows user to access the entire news. Nonetheless, they cannot access partial of the contents which related to users interest. For example user only have interested to a partial of the news and share the content, it is still hard for them to do so. In worst cases users might understand the news in different context. To solve this, Social News Service must provide a method to provide additional information. For example, Yovisto known as an academic video searching service provided time dependent metadata from the video. User can search and watch partial of video content according to time dependent metadata. They also can share content with a friend in social media. Yovisto applies a method to divide or synchronize a video based whenever the slides presentation is changed to another page. However, we are not able to employs this method on news video since the news video is not incorporating with any power point slides presentation. Segmentation method is required to separate the news video and to creating time dependent metadata. In this work, In this paper, a time dependent metadata-based framework is proposed to segment news contents and to provide time dependent metadata so that user can use context information to communicate with their friends. The transcript of the news is divided by using the proposed story segmentation method. We provide a tag to represent the entire content of the news. And provide the sub tag to indicate the segmented news which includes the starting time of the news. The time dependent metadata helps user to track the news information. It also allows them to leave a comment on each segment of the news. User also may share the news based on time metadata as segmented news or as a whole. Therefore, it helps the user to understand the shared news. To demonstrate the performance, we evaluate the story segmentation accuracy and also the tag generation. For this purpose, we measured accuracy of the story segmentation through semantic similarity and compared to the benchmark algorithm. Experimental results show that the proposed method outperforms benchmark algorithms in terms of the accuracy of story segmentation. It is important to note that sub tag accuracy is the most important as a part of the proposed framework to share the specific news context with others. To extract a more accurate sub tags, we have created stop word list that is not related to the content of the news such as name of the anchor or reporter. And we applied to framework. We have analyzed the accuracy of tags and sub tags which represent the context of news. From the analysis, it seems that proposed framework is helpful to users for sharing their opinions with context information in Social media and Social news.

Changes in blood pressure and determinants of blood pressure level and change in Korean adolescents (성장기 청소년의 혈압변화와 결정요인)

  • Suh, Il;Nam, Chung-Mo;Jee, Sun-Ha;Kim, Suk-Il;Kim, Young-Ok;Kim, Sung-Soon;Shim, Won-Heum;Kim, Chun-Bae;Lee, Kang-Hee;Ha, Jong-Won;Kang, Hyung-Gon;Oh, Kyung-Won
    • Journal of Preventive Medicine and Public Health
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    • v.30 no.2 s.57
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    • pp.308-326
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    • 1997
  • Many studies have led to the notion that essential hypertension in adults is the result of a process that starts early in life: investigation of blood pressure(BP) in children and adolescents can therefore contribute to knowledge of the etiology of the condition. A unique longitudinal study on BP in Korea, known as Kangwha Children's Blood Pressure(KCBP) Study was initiated in 1986 to investigate changes in BP in children. This study is a part of the KCBP study. The purposes of this study are to show changes in BP and to determine factors affecting to BP level and change in Korean adolescents during age period 12 to 16 years. A total of 710 students(335 males, 375 females) who were in the first grade at junior high school(12 years old) in 1992 in Kangwha County, Korea have been followed to measure BP and related factors(anthropometric, serologic and dietary factors) annually up to 1996. A total of 562 students(242 males, 320 females) completed all five annual examinations. The main results are as follows: 1. For males, mean systolic and diastolic BP at age 12 and 16 years old were 108.7 mmHg and 118.1 mmHg(systolic), and 69.5 mmHg and 73.4 mmHg(diastolic), respectively. BP level was the highest when students were at 15 years old. For females, mean systolic and diastolic BP at age 12 and 16 years were 114.4 mmHg and 113.5 mmHg(systolic) and 75.2 mmHg and 72.1 mmHg(diastolic), respectively. BP level reached the highest point when they were 13-14 years old. 2. Anthropometric variables(height, weight and body mass index, etc) increased constantly during the study period for males. However, the rate of increase was decreased for females after age 15 years. Serum total cholesterol decreased and triglyceride increased according to age for males, but they did not show any significant trend fer females. Total fat intake increased at age 16 years compared with that at age 14 years. Compositions of carbohydrate, protein and fat among total energy intake were 66.2:12.0:19.4, 64.1:12.1:21.8 at age 14 and 16 years, respectively. 3. Most of anthropometric measures, especially, height, body mass index(BMI) and triceps skinfold thickness showed a significant correlation with BP level in both sexes. When BMI was adjusted, serum total cholesterol showed a significant negative correlation with systolic BP at age 12 years in males, but at age 14 years the direction of correlation changed to positive. In females serum total cholesterol was negatively correlated with diastolic BP at age 15 and 16 years. Triglyceride and creatinine showed positive correlation with systolic and diastolic BP in males, but they did not show any correlation in females. There was no consistent findings between nutrient intake and BP level. However, protein intake correlated positively with diastolic BP level in males. 4. Blood pressure change was positively associated with changes in BMI and serum total cholesterol in both sexes. Change in creatinine was associated with BP change positively in males and negatively in females. Students whose sodium intake was high showed higher systolic and diastolic BP in males, and students whose total fat intake was high maintained lower level of BP in females. The major determinants on BP change was BMI in both sexes.

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Content-based Recommendation Based on Social Network for Personalized News Services (개인화된 뉴스 서비스를 위한 소셜 네트워크 기반의 콘텐츠 추천기법)

  • Hong, Myung-Duk;Oh, Kyeong-Jin;Ga, Myung-Hyun;Jo, Geun-Sik
    • Journal of Intelligence and Information Systems
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    • v.19 no.3
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    • pp.57-71
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    • 2013
  • Over a billion people in the world generate new news minute by minute. People forecasts some news but most news are from unexpected events such as natural disasters, accidents, crimes. People spend much time to watch a huge amount of news delivered from many media because they want to understand what is happening now, to predict what might happen in the near future, and to share and discuss on the news. People make better daily decisions through watching and obtaining useful information from news they saw. However, it is difficult that people choose news suitable to them and obtain useful information from the news because there are so many news media such as portal sites, broadcasters, and most news articles consist of gossipy news and breaking news. User interest changes over time and many people have no interest in outdated news. From this fact, applying users' recent interest to personalized news service is also required in news service. It means that personalized news service should dynamically manage user profiles. In this paper, a content-based news recommendation system is proposed to provide the personalized news service. For a personalized service, user's personal information is requisitely required. Social network service is used to extract user information for personalization service. The proposed system constructs dynamic user profile based on recent user information of Facebook, which is one of social network services. User information contains personal information, recent articles, and Facebook Page information. Facebook Pages are used for businesses, organizations and brands to share their contents and connect with people. Facebook users can add Facebook Page to specify their interest in the Page. The proposed system uses this Page information to create user profile, and to match user preferences to news topics. However, some Pages are not directly matched to news topic because Page deals with individual objects and do not provide topic information suitable to news. Freebase, which is a large collaborative database of well-known people, places, things, is used to match Page to news topic by using hierarchy information of its objects. By using recent Page information and articles of Facebook users, the proposed systems can own dynamic user profile. The generated user profile is used to measure user preferences on news. To generate news profile, news category predefined by news media is used and keywords of news articles are extracted after analysis of news contents including title, category, and scripts. TF-IDF technique, which reflects how important a word is to a document in a corpus, is used to identify keywords of each news article. For user profile and news profile, same format is used to efficiently measure similarity between user preferences and news. The proposed system calculates all similarity values between user profiles and news profiles. Existing methods of similarity calculation in vector space model do not cover synonym, hypernym and hyponym because they only handle given words in vector space model. The proposed system applies WordNet to similarity calculation to overcome the limitation. Top-N news articles, which have high similarity value for a target user, are recommended to the user. To evaluate the proposed news recommendation system, user profiles are generated using Facebook account with participants consent, and we implement a Web crawler to extract news information from PBS, which is non-profit public broadcasting television network in the United States, and construct news profiles. We compare the performance of the proposed method with that of benchmark algorithms. One is a traditional method based on TF-IDF. Another is 6Sub-Vectors method that divides the points to get keywords into six parts. Experimental results demonstrate that the proposed system provide useful news to users by applying user's social network information and WordNet functions, in terms of prediction error of recommended news.

Analysis of Success Cases of InsurTech and Digital Insurance Platform Based on Artificial Intelligence Technologies: Focused on Ping An Insurance Group Ltd. in China (인공지능 기술 기반 인슈어테크와 디지털보험플랫폼 성공사례 분석: 중국 평안보험그룹을 중심으로)

  • Lee, JaeWon;Oh, SangJin
    • Journal of Intelligence and Information Systems
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    • v.26 no.3
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    • pp.71-90
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    • 2020
  • Recently, the global insurance industry is rapidly developing digital transformation through the use of artificial intelligence technologies such as machine learning, natural language processing, and deep learning. As a result, more and more foreign insurers have achieved the success of artificial intelligence technology-based InsurTech and platform business, and Ping An Insurance Group Ltd., China's largest private company, is leading China's global fourth industrial revolution with remarkable achievements in InsurTech and Digital Platform as a result of its constant innovation, using 'finance and technology' and 'finance and ecosystem' as keywords for companies. In response, this study analyzed the InsurTech and platform business activities of Ping An Insurance Group Ltd. through the ser-M analysis model to provide strategic implications for revitalizing AI technology-based businesses of domestic insurers. The ser-M analysis model has been studied so that the vision and leadership of the CEO, the historical environment of the enterprise, the utilization of various resources, and the unique mechanism relationships can be interpreted in an integrated manner as a frame that can be interpreted in terms of the subject, environment, resource and mechanism. As a result of the case analysis, Ping An Insurance Group Ltd. has achieved cost reduction and customer service development by digitally innovating its entire business area such as sales, underwriting, claims, and loan service by utilizing core artificial intelligence technologies such as facial, voice, and facial expression recognition. In addition, "online data in China" and "the vast offline data and insights accumulated by the company" were combined with new technologies such as artificial intelligence and big data analysis to build a digital platform that integrates financial services and digital service businesses. Ping An Insurance Group Ltd. challenged constant innovation, and as of 2019, sales reached $155 billion, ranking seventh among all companies in the Global 2000 rankings selected by Forbes Magazine. Analyzing the background of the success of Ping An Insurance Group Ltd. from the perspective of ser-M, founder Mammingz quickly captured the development of digital technology, market competition and changes in population structure in the era of the fourth industrial revolution, and established a new vision and displayed an agile leadership of digital technology-focused. Based on the strong leadership led by the founder in response to environmental changes, the company has successfully led InsurTech and Platform Business through innovation of internal resources such as investment in artificial intelligence technology, securing excellent professionals, and strengthening big data capabilities, combining external absorption capabilities, and strategic alliances among various industries. Through this success story analysis of Ping An Insurance Group Ltd., the following implications can be given to domestic insurance companies that are preparing for digital transformation. First, CEOs of domestic companies also need to recognize the paradigm shift in industry due to the change in digital technology and quickly arm themselves with digital technology-oriented leadership to spearhead the digital transformation of enterprises. Second, the Korean government should urgently overhaul related laws and systems to further promote the use of data between different industries and provide drastic support such as deregulation, tax benefits and platform provision to help the domestic insurance industry secure global competitiveness. Third, Korean companies also need to make bolder investments in the development of artificial intelligence technology so that systematic securing of internal and external data, training of technical personnel, and patent applications can be expanded, and digital platforms should be quickly established so that diverse customer experiences can be integrated through learned artificial intelligence technology. Finally, since there may be limitations to generalization through a single case of an overseas insurance company, I hope that in the future, more extensive research will be conducted on various management strategies related to artificial intelligence technology by analyzing cases of multiple industries or multiple companies or conducting empirical research.

A Study on the Yousang-Dae Goksuro(Curve-Waterway) in Gangneung, Yungok-Myun, Yoodung Ri (강릉 연곡면 유등리 '유상대(流觴臺)' 곡수로(曲水路)의 조명(照明))

  • Rho, Jae-Hyun;Shin, Sang-Sup;Lee, Jung-Han;Huh, Jun;Park, Joo-Sung
    • Journal of the Korean Institute of Traditional Landscape Architecture
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    • v.30 no.1
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    • pp.14-21
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    • 2012
  • The object of the study, Yousang-Dae(流觴臺) and engraved Go broad text on the flat rock in Gangneung-si Yungok-myun Yoodung-ri Baemgol, reveals that the place was for appreciating arts like Yusang Goksu and Taoist hermit's games. three times of detail reconnaissance survey brought about the results as follows. There is a the text, Manwolsan(滿月山) Baegundongcheon(白雲洞天), engraved on the rock in Baegunsa(白雲寺) that had been built by Doun at the first year of King Hungang(in 875) of the United Shilla, became in ruins in the middle of Joseon, and then was rebuilt in 1954. The text is an invaluable evidence indicating that the tradition of Taoist hermit and Sunbee(classical scholars) culture has been generated in Baemgol Valley. According to the 2nd vol. of Donghoseungram(東湖勝覽), the chronicle of Gangneung published by Choi Baeksoon in 1934, there is a record saying that 'Baegunsa in Namjeonhyeon is the classroom where famous teachers like Yulgok Lee Yi or Seongje Choi Ok were teaching' that verifies the historic property of the place. In addition, the management of Nujeong(樓亭) and Dongcheon can be traced through Baegunjeong(白雲亭) constructed by Kim Yoonkyung(金潤卿) in Muo year, the 9th year of Cheoljong(1858) according to Donghoseungram and the completed version of Jeungboyimyoungji(增補臨瀛誌). Also, Baegundongdongcheon(白雲亭洞天), the text engraved on the standing stone across the stream from Yousang-Dae stone, was created 3 years after the Baegunjeong construction in the 12th year of Cheoljong(1861), which refers a symbolic sign closely related with Yousang-Dae. Based on this premise and circumstance, with careful studying the remains of 'Yusang-dae' Goksuro, we discovered that the Sebun-seok(細分石) controling the amount and the speed of moving water and the remains of furrows of Keumbae-soek(擒盃石) and Yubae-gong(留盃孔) containing water stream with cups through the mountain stream and rocks around Yusang-Dae. In addition, as 21 people's names engraved under the statement of 'Oh-Seong(午星)' were discovered on the bottom of the rock, this clearly confirms that the place was one of the main cultural footholds of tasting the arts which have characteristics of Yu-Sang-Gok-Su-Yeon(流觴曲水宴) until the middle of the 20th century. It implies that the arts tasting culture of Sunbees had been inherited centering on Yusang-dae in this particular place until the middle of the 20th century. It is necessary to be studied in depth because the place is a historic and unique cultural place where 'Confucianism, Buddhism, and Zen'were combined together. Based on the result of the study, the identification of 23 people as well as the writer of Yusang-Dae text should be carefully studied in depth in terms of the characteristics of the place through gathering data about appreciation of arts like Yusanggoksu. Likewise, we should make efforts to discover the chess board engraved on the rock described on the documents, thus we should consider to establish plans to recover the original shape of the place, for example, breaking the cement pavement of the road, additional excavation, changing the existing route, and so fourth.

A Study on Knowledge Entity Extraction Method for Individual Stocks Based on Neural Tensor Network (뉴럴 텐서 네트워크 기반 주식 개별종목 지식개체명 추출 방법에 관한 연구)

  • Yang, Yunseok;Lee, Hyun Jun;Oh, Kyong Joo
    • 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.