• 대한공업교육학회지
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• v.42 no.2
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• pp.67-88
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• 2017

The purpose of this research was educational needs of experts for revitalizing youth entrepreneurship education and creating effective conditions for such education. The subjects of the survey were chosen 100 teachers who had participated in entrepreneurship-related professional training for teachers were selected and surveyed. A total of 100 questionnaires were collected, of which 92 (92.00%) were used for the analysis. Eight were excluded as they were not properly answered. As for the used survey tool, a total of 8 areas and 30 items were derived from the review of the literature, and the validity of the contents was examined through expert meetings. The data were analyzed using the SPSS (ver. 20.0) statistical program. The analysis was conducted in terms of the required competency level, perceived competency level and educational needs. As for the used analytical methods, first, the averages of the required competency level and perceived competency level were calculated and the education needs were calculated using Borich's formula, and then the averages were compared through paired t-test. The results turned out to be statistically significant (p<.000). The details are as follows: As a result of the calculation of the educational needs the educational needs in all areas turned out to be very high with the average being 4.94 points, which indicates that the teachers strongly feel the need for educational strengthening in relation to entrepreneurship. These results show that all the educational conditions such as entrepreneurship-related curriculum, teacher professionalism, educational environment, educational support and the perception among school community members are insufficient in the current school settings. For the improvement of the current status, the education conditions in the following areas should be improved: the cooperation from school community members including principals, teacher support such as an exclusive responsibility teacher system, the development of an entrepreneurship curriculum, the securing of teacher professionalism through the implementation of the curriculum, teacher training support for the enhancement of their professionalism and the provision of educational environment and facilities. For enhancing the perception of parents and society regarding entrepreneurship, it is necessary to establish the precise concept of entrepreneurship and promote it based on such work.

• Journal of the Korean Institute of Landscape Architecture
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• v.37 no.1
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• pp.78-86
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• 2009

Recently, there seems to besome problems in the urban visual landscape as a result of continuous economic growth and industrial development. At the same time, the public has begun to be aware of the importance of visual resources, and the necessity for visual landscape conservation and improvement. Therefore, the development of evaluative indicators for systematic visual landscape planning and design is urgent. The purpose ofthis study is to discover evaluative models and indicators for the diagnosis of urban visual landscapes. This study included the selection of 18 physical indicators(statistical data) by literature reviews, adoption of field and questionnaire surveys at 12 autonomous districts in Seoul and surrounding major mountain valleys and river streams(i.e. Mt. Nam and Han-River). The content of the questionnaire is scenic beauty. Moreover, the linear regression analysis between the scenic beauty mean scores and the physical indicator scores figure out the scenic beauty prediction model. As this study suggests, the most important indicators in urban visual landscapes are 'Greens', 'Park' and 'the number of apartment buildings(higher than 20 stories).' Based on the results, greens and parks should be priority elements to considerin urban landscape planning and design. Moreover, since the number of apartment buildings that are higher than 20 stories has a negative correlation with the scenic beauty score, it can be used as basic data for landscape planning. For the scenic beauty prediction models and evaluative indicators suggest a direction of urban management, each indicator becomes basic data for visual landscape planning and design. In following studies, if physical indicators and case studies are added, the scenic beauty prediction models and evaluative indicators could be more synthetic and systematic. Moreover, the development of physical indicators in three dimensions(3D)(i.e. results from visual district analysis, view surface analysis) could be expected to obtain more general and varied results.

• Journal of Korean Society of Forest Science
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• v.107 no.1
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• pp.96-107
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• 2018

This study analyzed the linkage between the Forestry sector Official Development Assistance (ODA) Project in South Korea and the Sustainable Development Goals (SDGs) of United Nations (UN), Suggested direction of ODA project focusing on the implementation of the SDGs. Forestry sector ODA project data in South Korea have collected from Economic Development Cooperation Fund (EDCF) statistical inquiry system developed by The Export-Import Bank of Korea. According to the analysis result, Forestry sector ODA project in South Korea have been actively implemented in the fields of forestry development, forestry policy and administration. In both fields, Korea Forest Service and Korea International Cooperation Agency (KOICA) carried out the most projects. The Forestry sector ODA project data in South Korea are classified technical development, capacity building, construction of infrastructure and afforestation based on their objectives and contents. SDGs emphasizes the importance of national implementation assessment and this study analyze linkage between ODA activity content in each classification item and 2016 Korea Forest Service Performance Management Plan indicator. Analyzed the 2016 Korea Forest Service Performance Management Plan indicator and SDGs target and SDGs indicator were identified. finally, SDGs goals were recognized. In conclusion, Forestry sector ODA project in South Korea are associated with the SDGs Goal 1 (No Poverty), Goal 2 (Zero Hunger), Goal 6 (Clean Water and Sanitation), Goal 13 (Climate Action), Goal 15 (Life on Land) and Goal 17 (Partnership for The Goals). Therefore, With the launch of the SDGs, This study analyzed the linkage among the Forestry sector ODA Project in South Korea, the 2016 Korea Forest Service Performance Management Plan and the SDGs. it presented the limitations of Forestry sector ODA Project in South Korea and made proposals for the implementation of the SDGs.

• Korean Journal of Social Welfare
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• v.57 no.3
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• pp.51-72
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• 2005

The purpose of this article is to empirically testify three hypotheses on the relation between married women's employment and the allocation of unpaid domestic work within households - i.e., adaptive partnership (AP), dual burden (DB) and lagged adaptation (LA) models. The AP hypothesis assumes that, when wives are employed, husbands spend more time doing housework in order to compensate for their wives' increased responsibility. The DB model, by contrast, indicates that, even if married women are employed, their burden on domestic work does not decrease. In this case, therefore, the dual burden of married women can be expected. Between these two opposite views, the third, alternative hypothesis has been suggested recently. The LA model argues that the behaviours of households are adaptive to the changing environments but over a period of many years and even across generations. The article has analysed the total work time as well as unpaid domestic work time to testify these three hypotheses, utilising 1999 Time Use Survey data of the National Statistical Office. The research results can be summarised as follows. First, married working women worked 100 minutes more than their male spouses. Second, the average domestic work time of married men, 23-25 minutes per day, was no more than 5-10% of that of women. Third, the effects of age and women's employment were not statistically significant in multiple regression models, which means that the DB hypothesis explains the situation of married working women in Korea. Based on these findings, the article suggested the expansion of the public social service system to mitigate the dual burden of married working women, the introduction of compensatory credit for caring work, and the directions of further empirical research using the time use survey data.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.157-178
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• 2009

Corporate credit rating is a very important factor in the market for corporate debt. Information concerning corporate operations is often disseminated to market participants through the changes in credit ratings that are published by professional rating agencies, such as Standard and Poor's (S&P) and Moody's Investor Service. Since these agencies generally require a large fee for the service, and the periodically provided ratings sometimes do not reflect the default risk of the company at the time, it may be advantageous for bond-market participants to be able to classify credit ratings before the agencies actually publish them. As a result, it is very important for companies (especially, financial companies) to develop a proper model of credit rating. From a technical perspective, the credit rating constitutes a typical, multiclass, classification problem because rating agencies generally have ten or more categories of ratings. For example, S&P's ratings range from AAA for the highest-quality bonds to D for the lowest-quality bonds. The professional rating agencies emphasize the importance of analysts' subjective judgments in the determination of credit ratings. However, in practice, a mathematical model that uses the financial variables of companies plays an important role in determining credit ratings, since it is convenient to apply and cost efficient. These financial variables include the ratios that represent a company's leverage status, liquidity status, and profitability status. Several statistical and artificial intelligence (AI) techniques have been applied as tools for predicting credit ratings. Among them, artificial neural networks are most prevalent in the area of finance because of their broad applicability to many business problems and their preeminent ability to adapt. However, artificial neural networks also have many defects, including the difficulty in determining the values of the control parameters and the number of processing elements in the layer as well as the risk of over-fitting. Of late, because of their robustness and high accuracy, support vector machines (SVMs) have become popular as a solution for problems with generating accurate prediction. An SVM's solution may be globally optimal because SVMs seek to minimize structural risk. On the other hand, artificial neural network models may tend to find locally optimal solutions because they seek to minimize empirical risk. In addition, no parameters need to be tuned in SVMs, barring the upper bound for non-separable cases in linear SVMs. Since SVMs were originally devised for binary classification, however they are not intrinsically geared for multiclass classifications as in credit ratings. Thus, researchers have tried to extend the original SVM to multiclass classification. Hitherto, a variety of techniques to extend standard SVMs to multiclass SVMs (MSVMs) has been proposed in the literature Only a few types of MSVM are, however, tested using prior studies that apply MSVMs to credit ratings studies. In this study, we examined six different techniques of MSVMs: (1) One-Against-One, (2) One-Against-AIL (3) DAGSVM, (4) ECOC, (5) Method of Weston and Watkins, and (6) Method of Crammer and Singer. In addition, we examined the prediction accuracy of some modified version of conventional MSVM techniques. To find the most appropriate technique of MSVMs for corporate bond rating, we applied all the techniques of MSVMs to a real-world case of credit rating in Korea. The best application is in corporate bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. For our study the research data were collected from National Information and Credit Evaluation, Inc., a major bond-rating company in Korea. The data set is comprised of the bond-ratings for the year 2002 and various financial variables for 1,295 companies from the manufacturing industry in Korea. We compared the results of these techniques with one another, and with those of traditional methods for credit ratings, such as multiple discriminant analysis (MDA), multinomial logistic regression (MLOGIT), and artificial neural networks (ANNs). As a result, we found that DAGSVM with an ordered list was the best approach for the prediction of bond rating. In addition, we found that the modified version of ECOC approach can yield higher prediction accuracy for the cases showing clear patterns.

• The Journal of Korean Academy of Sensory Integration
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• v.16 no.2
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• pp.1-14
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• 2018

Objective : The present study investigated the effects of group play activities based on Ayres Sensory $Integration^{(R)}$ (ASI) on sensory processing ability, social skill ability and self-esteem of low-income children with attention deficit hyperactivity disorder (ADHD). Methods : A total of 20 low-income participants with children with ADHD were recruited and divided into an experimental group (n=10) and a control group (n=10). Sensory processing ability was measured via the Short Sensory Profile (SSP). Social skill ability was measured via the Social Skills Rating System (SSRS). To measure self-esteem, the Rosenberg's self- esteem scale was used. The experimental group received the $ASI^{(R)}$ group play activities for 50 minutes, twice per week for six weeks, while the control group did not receive an intervention. Level of significance of all statistical analyses was .05. Results : Social skill ability (F=4.443, p=.05), cooperation (F=5.328, p=.035) and self-esteem (F=5.358, p=.033) differed significantly between groups after the intervention. Conclusion : Our findings indicate that the group play activities based on $ASI^{(R)}$ are effective in improving social skill ability and self-esteem. This study provided a theoretical basis for the claim that sensory integration therapy should be applied in general elementary schools.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.63-88
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• 2019

The goal of this paper is to investigate changes in North Korea's domestic and foreign policies through automated text analysis over North Korea represented in South Korean mass media. Based on that data, we then analyze the status of text mining research, using a text mining technique to find the topics, methods, and trends of text mining research. We also investigate the characteristics and method of analysis of the text mining techniques, confirmed by analysis of the data. In this study, R program was used to apply the text mining technique. R program is free software for statistical computing and graphics. Also, Text mining methods allow to highlight the most frequently used keywords in a paragraph of texts. One can create a word cloud, also referred as text cloud or tag cloud. This study proposes a procedure to find meaningful tendencies based on a combination of word cloud, and co-occurrence networks. This study aims to more objectively explore the images of North Korea represented in South Korean newspapers by quantitatively reviewing the patterns of language use related to North Korea from 2016. 11. 1 to 2019. 5. 23 newspaper big data. In this study, we divided into three periods considering recent inter - Korean relations. Before January 1, 2018, it was set as a Before Phase of Peace Building. From January 1, 2018 to February 24, 2019, we have set up a Peace Building Phase. The New Year's message of Kim Jong-un and the Olympics of Pyeong Chang formed an atmosphere of peace on the Korean peninsula. After the Hanoi Pease summit, the third period was the silence of the relationship between North Korea and the United States. Therefore, it was called Depression Phase of Peace Building. This study analyzes news articles related to North Korea of the Korea Press Foundation database(www.bigkinds.or.kr) through text mining, to investigate characteristics of the Kim Jong-un regime's South Korea policy and unification discourse. The main results of this study show that trends in the North Korean national policy agenda can be discovered based on clustering and visualization algorithms. In particular, it examines the changes in the international circumstances, domestic conflicts, the living conditions of North Korea, the South's Aid project for the North, the conflicts of the two Koreas, North Korean nuclear issue, and the North Korean refugee problem through the co-occurrence word analysis. It also offers an analysis of South Korean mentality toward North Korea in terms of the semantic prosody. In the Before Phase of Peace Building, the results of the analysis showed the order of 'Missiles', 'North Korea Nuclear', 'Diplomacy', 'Unification', and ' South-North Korean'. The results of Peace Building Phase are extracted the order of 'Panmunjom', 'Unification', 'North Korea Nuclear', 'Diplomacy', and 'Military'. The results of Depression Phase of Peace Building derived the order of 'North Korea Nuclear', 'North and South Korea', 'Missile', 'State Department', and 'International'. There are 16 words adopted in all three periods. The order is as follows: 'missile', 'North Korea Nuclear', 'Diplomacy', 'Unification', 'North and South Korea', 'Military', 'Kaesong Industrial Complex', 'Defense', 'Sanctions', 'Denuclearization', 'Peace', 'Exchange and Cooperation', and 'South Korea'. We expect that the results of this study will contribute to analyze the trends of news content of North Korea associated with North Korea's provocations. And future research on North Korean trends will be conducted based on the results of this study. We will continue to study the model development for North Korea risk measurement that can anticipate and respond to North Korea's behavior in advance. We expect that the text mining analysis method and the scientific data analysis technique will be applied to North Korea and unification research field. Through these academic studies, I hope to see a lot of studies that make important contributions to the nation.

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

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

• Journal of the Korean Institute of Landscape Architecture
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• v.41 no.6
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• pp.20-28
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• 2013

The purpose of this study was to compare the ultra-violet(UV) radiation under the landscaping shade facilities and tree with natural solar UV of the outdoor space at summer middays. The UVA+B and UVB were recorded every minute from the $20^{th}$ of June to the $26^{th}$ of September 2012 at a height of 1.1m above in the four different shading conditions, with fours same measuring system consisting of two couple of analog UVA+B sensor(220~370nm, Genicom's GUVA-T21GH) and UVB sensor(220~320nm, Genicom's GUVA-T21GH) and data acquisition systems(Comfile Tech.'s Moacon). Four different shading conditions were under an wooden shelter($W4.2m{\times}L4.2m{\times}H2.5m$), a polyester membrane structure ($W4.9m{\times}L4.9m{\times}H2.6m$), a Salix koreensis($H11{\times}B30$), and a brick-paved plot without any shading material. Based on the 648 records of 17 sunny days, the time serial difference of natural solar UVA+B and UVB for midday periods were analysed and compared, and statistical analysis about the difference between the four shading conditions was done based on the 2,052 records of daytime period from 10 A.M. to 4 P.M.. The major findings were as follows; 1. The average UVA+B under the wooden shelter, the membrane and the tree were $39{\mu}W/cm^2$(3.4%), $74{\mu}W/cm^2$(6.4%), $87{\mu}W/cm^2$(7.6%) respectively, while the solar UVA+B was $1.148{\mu}W/cm^2$. Which means those facilities and tree screened at least 93% of solar UV+B. 2. The average UVB under the wooden shelter, the membrane and the tree were $12{\mu}W/cm^2$(5.8%), $26{\mu}W/cm^2$(13%), $17{\mu}W/cm^2$(8.2%) respectively, while the solar UVB was $207{\mu}W/cm^2$. The membrane showed the highest level and the wooden shelter lowest. 3. According to the results of time serial analysis, the difference between the three shaded conditions around noon was very small, but the differences of early morning and late afternoon were apparently big. Which seems caused by the matter of the formal and structural characteristics of the shading facilities and tree, not by the shading materials itself. In summary, the performance of the four landscaping shade facilities and tree were very good at screening the solar UV at outdoor of summer middays, but poor at screening the lateral UV during early morning and late afternoon. Therefore, it can be apparently said that the more delicate design of shading facilities and big tree or forest to block the additional lateral UV, the more effective in conditioning the outdoor space reducing the useless or even harmful radiation for human activities.

• Journal of Oral Medicine and Pain
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• v.33 no.4
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• pp.339-352
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• 2008

Aims: The aims of this study were to identify the association between cervical muscle pain and TMD by pressure pain response, and to find cervical muscles showing moderate to severe pressure pain that are correlated with masticatory muscle pain. Methods: Patients(n=129, female 65.9%, mean age 28.8 years) answered a TMD questionnaire asking about headache, neck pain, emotional stress, sleep disturbance, parafunction habits, and pain intensity. A clinical examination of the masticatory system was performed. Of the neck muscles, (1) the upper sternocleidomastoid, (2) the middle sternocleidomastoid, (3) the upper trapezius, (4) the splenius capitis, (5) the semispinalis capitis, (6) the scalene medius, and (7) the levator scapulae muscles were examined by palpation. Pressure pain or tenderness of all palpation sites was scored from 0 to 3 according to the pain response. The variables of sum of pressure pain scores were calculated from pressure pain scores and were used for statistical analyses. Results: Eighty patients(62.0%) answered that they suffer from neck pain in the TMD questionnaire. More than 40% of sternocleidomastoid and upper trapezius examination sites showed moderate to severe tenderness in the cervical muscles, and 36% of middle masseter in the masticatory muscles. For the 129 patients, the sum of cervical muscle pain scores(mean=12.88, SD=8.06) and the sum of TMD pain scores(mean=5.36, SD=5.10) were moderately correlated($\rho$ = 0.502, P < 0.001). The sum of TMD pain scores tends to increase as the sum of cervical muscle pain scores increases(Y = 0.395${\cdot}$X, $R^2$ = 0.659, P < 0.001). In the patients with masticatory muscle disorders, the sum of sternocleidomastoid and upper trapezius pain scores(mean = 8.67, SD = 4.95) and the sum of temporalis and masseter pain scores(mean = 3.37, SD = 3.56) showed moderate correlation($\rho$ = 0.375, P < 0.001). Those two variables were in a proportionate relationship(Y = 0.359${\cdot}$X, $R^2$ = 0.538, P < 0.001). In a partial correlation analysis of the sum of unilateral pain scores, the sum of right cervical muscle pain scores and the sum of left cervical muscle pain scores showed the highest correlation(r = 0.802, P < 0.001). The sum of right TMD pain scores and the sum of left TMD pain scores were moderately correlated(r = 0.481, P < 0.001). For the twenty patients with unilateral TMD pain, the partial correlation coefficient between the sum of ipsilateral cervical muscle pain scores and the sum of contralateral cervical muscle pain scores was the largest(r = 0.597, P = 0.009). A partial correlation between the sum of primary TMD side pain scores and the sum of ipsilateral cervical muscle pain scores was 0.564(P = 0.015). Conclusions: TMD is associated with cervical muscle pain on condition of pressure pain response to palpation. Of the cervical muscles, sternocleidomastoid and upper trapezius frequently exhibit moderate to severe pressure pain, and they are closely related to the masticatory muscle pain. The characteristic of symmetric involvement of pain is prominent in cervical muscles; however, TMD can affect the level of cervical muscle pain to modify its symmetric nature.