Purposes: The objective of this study was to develop a management program for Korean elementary school students suffering from asthma, which would be based on the Australian Asthma-Friendly Schools (AFS) program. Methods: On the basis of the AFS program, we designed a 6-month pilot project for asthmatic students in two elementary schools in a rural area and one elementary school in an urban area of Korea. The pilot project consisted of the following processes: identifying students with asthma in a school, educating school staffs and the parents of an asthmatic child, registering those with asthma, and installing emergency kits for asthma attacks in school health rooms. In order to evaluate these processes, group discussions were held between project team members and school staffs in each area. In addition, we conducted a postal survey of 144 households having an asthmatic child. Results: The screening process adopted in this program resulted in the early diagnosis in asthma; however, it needs to be evaluated economically due to expensive diagnostic test for asthma. For the school nurses, asthma lessons were evaluated as being very helpful for their tasks, while teachers tended to take less interest in the program with only 45% of all teachers attending these lessons. Almost all participating parents reported that such lessons would be beneficial for the care of their child, even though only 24.2% of the survey respondents (122 households) attended the lessons. Installing emergency kits in school health rooms was regarded as a key feature of this project. The introduction of a register card containing more specific health records of asthmatic students was considered necessary to replace the existing list of students with asthma. Conclusion: This study has merit in that a Korean asthma-friendly schools program was developed for the first time, despite the many obstacles to such programs becoming more common.
As a way of enhancing the intercultural ability needed for diverse cultural eras, this study focuses on the "narration" of the Italian education scholar Maddalena De Carlo in order to determine the "diverse values" created by the "symbolic representation" based on the folktales narrated by immigrants living in Korea. Through this, it specifically presents educational elements and contents that can raise relative sensitivity. The authors of this paper have connected, empathized, and communicated with people of various cultures in order to go beyond Carlo's discussion. The paper discusses the expansion of cultural sensitivity as an element of education through narrative topics using the folktales of immigrant narrators in Korea. It also recognizes the limitations of a desire for a homogeneous union within an intercultural society and thus formulates educational contents for creating a relationship with heterogeneous ideas through the elimination of communication barriers through heterogeneity and a consideration of the surface and the back. This is systemized in six steps. Step 1: Listening to oral folktales of immigrants, Step 2: Finding heterogeneous motifs imprinted in the immigrants' memories, Step 3: Understanding the meaning of the opposing qualities symbolized by heterogeneous motifs, Step 4: Creating narrative topics containing the key motifs, Step 5: Generating the value of symbolic representation as a narrative topic, and Step 6: Expanding the value of life into a cultural symbol. In Chapter 3, this study focuses on educational contents using immigrants' folktales by applying these six steps. The class contents include the recognition of the limitations of desire for a homogeneous union within an intercultural society and the consideration of how to create a relationship with heterogeneous ideas through the elimination of communication barriers through heterogeneity and consideration of the surface and the back. This paper then compares the Indonesian folktale, The Inverted Ship Mountain and the Mom's Mountain, with the world-famous Oedipus myth, to determine what the symbolic representation of these heterogeneous motifs is. In Step 6, when the symbolic system is culturally extended, the incestuous desire that appears in the "inverted ship" is interpreted as a fixation that was created when the character sought to unite with homogenous idea. The Cambodian folktale, The Girl and the Tiger, is a story that is reminiscent of the Korean folktale, The Old Man with a Lump. Through the motif in "Tiger," this paper generates a narrative topic that will enhance the students' intercultural abilities by culturally expanding their skills in how to relate with a heterogeneous being that is usually represented as an animal. The Vietnamese folktale, The Coconut Bowl, similar to the Korean folktale, GureongDeongDeong SinSeonBi, is a story that draws a variety of considerations about the surface and theback, and it shows readers how to build a relationship with a heterogeneous idea and how to develop and grow with such a relationship. Thus, if a narrative topic is generated and readers are able to empathize using an opposing feature formed by the core motif of the folktale, it becomes possible, through immigrant folklore, to construct a possibility of a new life through the formation of a relationship with an unfamiliar and heterogeneous culture.
A lien is the right to possession the thing until receiving repayment of its bonds in some cases that the property of other person or the occupant for marketable securities receive the bond that has occurred on that property or marketable securities. This has own purpose to break 'principle of creditor equality' to protect especially the bond of the subject occupant in terms of justice. These lien on our civil law come according to the law in prepared certain requirements. However, an incomplete real rights granted by way of security that does not have a preferential performance right or seniority on the exchange value of the object suffer from the problems a lot in the real estate auction process because of the feature that is not announced in the register unlike the mortgage. In addition, the lien of real estate is not lapsed in an auction process. There is no preferential performance righ in a positive law as providing that can oppose to the buyer(a successful bidder) until received repayment the secured bond price to be compliant with the lien(Civil Case Execution Law the 91st clause of Article 5). However, as asserted the super preferential performance righ to a buyer in real terms, acts as primary cause of breaking unexpected loss and according unfair law relation to a senior mortgagee and seizor, etc. and the principles of the creditors equality to the persons concerned in other words, the principles of justice. All of these issues are the establishment of the lien and theory conflict on the effects. In spite of the fluctuations of a real right about real estate is announced as a registration by the current law, only the lien come into unclear announcement means for possession. In addition, Civil Case Execution Law argument is caused by the adoption abernahmeprinzip about the lien (Civil Case Execution Law the 91st clause of Article 5). Therefore, this paper was examined briefly the significance and purpose, history and law-making examples of each country and the valid requirements and effect of the lien that is basic principle of law about the lien system above all. And then, it will be reviewed the improvement plan for de lege ferenda to improve the issues about this after reviewing the objection, theory and judicial precedent about opposing power and preferential performance right of the lien in the real estaKey Words : Lien, Oppose Power, Mortgage right, Preferential Performance right, Seizure, Real Estate Auction, Lien who can not Opposing against Successful Bidder, Lien who can Oppose against Successful Bidder, Possessionte auction that is a fundamental problem on requirement and effect of the lien.
Criticism of the postmodern philosophy of the system of representation, which has continued since the Renaissance, is based on a critique of the dichotomy that separates the subjects and objects and the environment from the human being. Interactivity, highlighted in a series of works emerging as postmodern trends in the 1960s, was transmitted to an interactive aspect of digital art in the late 1990s. The key feature of digital art is the possibility of infinite variations reflecting unpredictable changes based on public participation on the spot. In this process, the importance of computer programs is highlighted. Instead of using the existing program as it is, more and more artists are creating and programming their own algorithms or creating unique algorithms through collaborations with programmers. We live in an era of paradigm shift in which programming itself must be considered as a creative act. Simulation technology and VR technology draw attention as a technique to represent the meaning of reality. Simulation technology helps artists create experimental works. In fact, Baudrillard's concept of Simulation defines the other reality that has nothing to do with our reality, rather than a reality that is extremely representative of our reality. His book Simulacra and Simulation refers to the existence of a reality entirely different from the traditional concept of reality. His argument does not concern the problems of right and wrong. There is no metaphysical meaning. Applying the concept of simulation to algorithmic art, the artist models the complex attributes of reality in the digital system. And it aims to build and integrate internal laws that structure and activate the world (specific or individual), that is to say, simulate the world. If the images of the traditional order correspond to the reproduction of the real world, the synthesized images of algorithmic art and simulated space-time are the forms of art that facilitate the experience. The moment of seeing and listening to the work of Ian Cheng presented in this article is a moment of personal experience and the perception is made at that time. It is not a complete and closed process, but a continuous and changing process. It is this active and situational awareness that is required to the audience for the comprehension of post-representation's forms.
During the Incipient and Early Silla phases, which witnessed the establishment and development of the ancient Silla state, the Wolseong North Burial Ground functioned as not only the central burial ground in the Gyeongju region of the capital of Silla but also as the central burial ground of the whole Silla state. Wolseong North Burial Ground is where transformations in Silla funerary architecture first occurred. As such, an empirical study of the tombs constructed at this burial ground can be regarded as a starting point from which an understanding of the development of the tomb culture of the Silla state may be achieved. This paper therefore aims to examine the changing nature of the tomb culture of the Early Silla phase through the burial data of Wolseong North Burial Ground and the Gyeongju region. Wooden chamber tombs were constructed from the late phase of Saroguk. At Wolseong North Burial Ground, which eventually developed into the central burial ground of the Gyeongju region, wooden chamber tombs embellished with stone packing emerged during the Incipient Silla phase; wooden chamber tombs with stone mounds, on the other hand, first appeared in the Early Silla phase and eventually became established as the central tomb type. A key difference between the wooden chamber tomb embellished with stone packing and the wooden chamber tomb with stone mound is that, in the case of the latter, stones were packed not only around sides of the wooden structure that acted as the burial chamber but also on top of this structure. The addition of a high earthen mound surrounded by protective ring of stones is another distinctive feature of the latter, presenting a contrast to the low mound of the former. During the Early Silla phase, two types of wooden chamber tombs with stone mounds were constructed at Wolseong North Burial Ground: those with burial chambers located above ground and those with subterranean burial chambers. Also constructed during this phase were the wooden chamber tomb embellished with packed stones, the wooden chamber tomb embellished with packed clay, simple earth cut burials, which had been used since the Incipient Silla phase, as well as the stone-lined burials with vertical entrance which first appeared in the Early Silla phase. However, of these different types of burials, it was only the wooden chamber tomb with stone mound that was covered with a 'high mound.' Differentiation between the different tomb types can also be observed in terms of location, type of burial chamber used, construction method, and tomb size. It is therefore possible to surmise that stratification between the different tomb types, which first emerged in the Incipient Silla phase, became intensified during the Early Silla phase.
Korean Government Budget Supports for startups have been spiked and resulted in increasing the number and scaling up Startup Accelerating managers. It have skyrocketed the strong demand for their qualified roles. However, unclear role description and gap between required role and their capability have discouraged startup manager's self-efficacy resulted in declining their full commitment and causing poor role performance. The focus of this research falls on empirical analysis to the effect of startup accelerating manager's capability characteristics on their full commitment and performance to start-up support groups. This research is expected to deliver diverse policy alternatives to build up manager's core competencies to accelerate their self-efficacy leading their full role commitments and finally pushing up policy performance. In addition, this research will found more strong literature review for the following researches in this emerging fields. This research is brought four highlighting results with respect to four research problems. First, it propose proper concept of startup accelerating manager based upon its legal entitlement. Second, it drive required core competencies of manager for successful their accountability. Third, it analyze the unique features of startup accelerating manger's capabilities against business incubation manger. Fourth, it empirically analyze in coming with government startup funding, the effect of self-efficacy including employment status, job environment, etc. on their organizational commitment and job performance. This research reveal the required unique core competencies of manger into founder sourcing ability, project managing ability, startup proving and pivoting ability, consulting ability for successful investment raising. As of this empirical research results, First, manager's ability have positively effect on their job performance, full commitment, and self-efficacy. Second, self-efficacy have a mediating effect on manager's ability, job performance, full commitment. This research derive key policy implication of requiring to build up more accelerating ability, of manager from the basics to advance level by customized and algorithm based traing program. This accelerating ability buildup program will not only surge self-efficacy of manger resulting in making full commitment and better job performance, but also devote to categorizing the unique new feature and position of manger as seed investment and supporter.
As the era of space technology utilization is approaching, the launch of CAS (Compact Advanced Satellite) 500-1/2 satellites is scheduled during 2021 for acquisition of high-resolution images. Accordingly, the increase of image usability and processing efficiency has been emphasized as key design concepts of the CAS 500-1/2 ground station. In this regard, "CAS 500-1/2 Image Acquisition and Utilization Technology Development" project has been carried out to develop core technologies and processing systems for CAS 500-1/2 data collecting, processing, managing and distributing. In this paper, we introduce the results of the above project. We developed an operation system to generate precision images automatically with GCP (Ground Control Point) chip DB (Database) and DEM (Digital Elevation Model) DB over the entire Korean peninsula. We also developed the system to produce ortho-rectified images indexed to 1:5,000 map grids, and hence set a foundation for ARD (Analysis Ready Data)system. In addition, we linked various application software to the operation system and systematically produce mosaic images, DSM (Digital Surface Model)/DTM (Digital Terrain Model), spatial feature thematic map, and change detection thematic map. The major contribution of the developed system and technologies includes that precision images are to be automatically generated using GCP chip DB for the first time in Korea and the various utilization product technologies incorporated into the operation system of a satellite ground station. The developed operation system has been installed on Korea Land Observation Satellite Information Center of the NGII (National Geographic Information Institute). We expect the system to contribute greatly to the center's work and provide a standard for future ground station systems of earth observation satellites.
Recently, channels like social media and SNS create enormous amount of data. In all kinds of data, portions of unstructured data which represented as text data has increased geometrically. But there are some difficulties to check all text data, so it is important to access those data rapidly and grasp key points of text. Due to needs of efficient understanding, many studies about text summarization for handling and using tremendous amounts of text data have been proposed. Especially, a lot of summarization methods using machine learning and artificial intelligence algorithms have been proposed lately to generate summary objectively and effectively which called "automatic summarization". However almost text summarization methods proposed up to date construct summary focused on frequency of contents in original documents. Those summaries have a limitation for contain small-weight subjects that mentioned less in original text. If summaries include contents with only major subject, bias occurs and it causes loss of information so that it is hard to ascertain every subject documents have. To avoid those bias, it is possible to summarize in point of balance between topics document have so all subject in document can be ascertained, but still unbalance of distribution between those subjects remains. To retain balance of subjects in summary, it is necessary to consider proportion of every subject documents originally have and also allocate the portion of subjects equally so that even sentences of minor subjects can be included in summary sufficiently. In this study, we propose "subject-balanced" text summarization method that procure balance between all subjects and minimize omission of low-frequency subjects. For subject-balanced summary, we use two concept of summary evaluation metrics "completeness" and "succinctness". Completeness is the feature that summary should include contents of original documents fully and succinctness means summary has minimum duplication with contents in itself. Proposed method has 3-phases for summarization. First phase is constructing subject term dictionaries. Topic modeling is used for calculating topic-term weight which indicates degrees that each terms are related to each topic. From derived weight, it is possible to figure out highly related terms for every topic and subjects of documents can be found from various topic composed similar meaning terms. And then, few terms are selected which represent subject well. In this method, it is called "seed terms". However, those terms are too small to explain each subject enough, so sufficient similar terms with seed terms are needed for well-constructed subject dictionary. Word2Vec is used for word expansion, finds similar terms with seed terms. Word vectors are created after Word2Vec modeling, and from those vectors, similarity between all terms can be derived by using cosine-similarity. Higher cosine similarity between two terms calculated, higher relationship between two terms defined. So terms that have high similarity values with seed terms for each subjects are selected and filtering those expanded terms subject dictionary is finally constructed. Next phase is allocating subjects to every sentences which original documents have. To grasp contents of all sentences first, frequency analysis is conducted with specific terms that subject dictionaries compose. TF-IDF weight of each subjects are calculated after frequency analysis, and it is possible to figure out how much sentences are explaining about each subjects. However, TF-IDF weight has limitation that the weight can be increased infinitely, so by normalizing TF-IDF weights for every subject sentences have, all values are changed to 0 to 1 values. Then allocating subject for every sentences with maximum TF-IDF weight between all subjects, sentence group are constructed for each subjects finally. Last phase is summary generation parts. Sen2Vec is used to figure out similarity between subject-sentences, and similarity matrix can be formed. By repetitive sentences selecting, it is possible to generate summary that include contents of original documents fully and minimize duplication in summary itself. For evaluation of proposed method, 50,000 reviews of TripAdvisor are used for constructing subject dictionaries and 23,087 reviews are used for generating summary. Also comparison between proposed method summary and frequency-based summary is performed and as a result, it is verified that summary from proposed method can retain balance of all subject more which documents originally have.
In addition to stakeholders including managers, employees, creditors, and investors of bankrupt companies, corporate defaults have a ripple effect on the local and national economy. Before the Asian financial crisis, the Korean government only analyzed SMEs and tried to improve the forecasting power of a default prediction model, rather than developing various corporate default models. As a result, even large corporations called 'chaebol enterprises' become bankrupt. Even after that, the analysis of past corporate defaults has been focused on specific variables, and when the government restructured immediately after the global financial crisis, they only focused on certain main variables such as 'debt ratio'. A multifaceted study of corporate default prediction models is essential to ensure diverse interests, to avoid situations like the 'Lehman Brothers Case' of the global financial crisis, to avoid total collapse in a single moment. The key variables used in corporate defaults vary over time. This is confirmed by Beaver (1967, 1968) and Altman's (1968) analysis that Deakins'(1972) study shows that the major factors affecting corporate failure have changed. In Grice's (2001) study, the importance of predictive variables was also found through Zmijewski's (1984) and Ohlson's (1980) models. However, the studies that have been carried out in the past use static models. Most of them do not consider the changes that occur in the course of time. Therefore, in order to construct consistent prediction models, it is necessary to compensate the time-dependent bias by means of a time series analysis algorithm reflecting dynamic change. Based on the global financial crisis, which has had a significant impact on Korea, this study is conducted using 10 years of annual corporate data from 2000 to 2009. Data are divided into training data, validation data, and test data respectively, and are divided into 7, 2, and 1 years respectively. In order to construct a consistent bankruptcy model in the flow of time change, we first train a time series deep learning algorithm model using the data before the financial crisis (2000~2006). The parameter tuning of the existing model and the deep learning time series algorithm is conducted with validation data including the financial crisis period (2007~2008). As a result, we construct a model that shows similar pattern to the results of the learning data and shows excellent prediction power. After that, each bankruptcy prediction model is restructured by integrating the learning data and validation data again (2000 ~ 2008), applying the optimal parameters as in the previous validation. Finally, each corporate default prediction model is evaluated and compared using test data (2009) based on the trained models over nine years. Then, the usefulness of the corporate default prediction model based on the deep learning time series algorithm is proved. In addition, by adding the Lasso regression analysis to the existing methods (multiple discriminant analysis, logit model) which select the variables, it is proved that the deep learning time series algorithm model based on the three bundles of variables is useful for robust corporate default prediction. The definition of bankruptcy used is the same as that of Lee (2015). Independent variables include financial information such as financial ratios used in previous studies. Multivariate discriminant analysis, logit model, and Lasso regression model are used to select the optimal variable group. The influence of the Multivariate discriminant analysis model proposed by Altman (1968), the Logit model proposed by Ohlson (1980), the non-time series machine learning algorithms, and the deep learning time series algorithms are compared. In the case of corporate data, there are limitations of 'nonlinear variables', 'multi-collinearity' of variables, and 'lack of data'. While the logit model is nonlinear, the Lasso regression model solves the multi-collinearity problem, and the deep learning time series algorithm using the variable data generation method complements the lack of data. Big Data Technology, a leading technology in the future, is moving from simple human analysis, to automated AI analysis, and finally towards future intertwined AI applications. Although the study of the corporate default prediction model using the time series algorithm is still in its early stages, deep learning algorithm is much faster than regression analysis at corporate default prediction modeling. Also, it is more effective on prediction power. Through the Fourth Industrial Revolution, the current government and other overseas governments are working hard to integrate the system in everyday life of their nation and society. Yet the field of deep learning time series research for the financial industry is still insufficient. This is an initial study on deep learning time series algorithm analysis of corporate defaults. Therefore it is hoped that it will be used as a comparative analysis data for non-specialists who start a study combining financial data and deep learning time series algorithm.
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70