• Korean Chemical Engineering Research
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• v.57 no.1
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• pp.90-104
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• 2019

In this study, CALPUFF modeling was performed, using a real surface and upper air meterological data to predict trustworthy modeling-results. Pollutant-releases from windscreen chambers of enclosed poultry farms, P1 and P2, and from a open poultry farm, P3, and their diffusing behavior were modeled by CALPUFF modeling with volume sources as well as by finally-adjusted CALPUFF modeling where a linear velocity of upward-exit gas averaged with the weight of each directional-emitting area was applied as a model-linear velocity ($u^M_y$) at a stack, with point sources. In addition, based upon the scenario of poultry farm-releasing odor and particulate matter (PM) removal efficiencies of 0, 20, 50 and 80% or their corresponding emission rates of 100, 80, 50 and 20%, respectively, CALPUFF modeling was performed and concentrations of odor and PM were predicted at the region as a discrete receptor where civil complaints had been frequently filed. The predicted concentrations of ammonia, hydrogen sulfide, $PM_{2.5}$ and $PM_{10}$ were compared with those required to meet according to the offensive odor control law or the atmospheric environmental law. Subsequently their required removal efficiencies at poultry farms of P1, P2 and P3 were estimated. As a result, a priori assumption that pollutant concentrations at their discrete receptors are reduced by the same fraction as pollutant concentrations at P1, P2 and P3 as volume source or point source, were controlled and reduced, was proven applicable in this study. In case of volume source-adopted CALPUFF modeling, its required removal efficiencies of P1 compared with those of point source-adopted CALPUFF modeling, were predicted similar each other. However, In case of volume source-adopted CALPUFF modeling, its required removal efficiencies of both ammonia and $PM_{10}$ at not only P2 but also P3 were predicted higher than those of point source-adopted CALPUFF modeling. Nonetheless, the volume source-adopted CALPUFF modeling was preferred as a safe approach to resolve civil complaints. Accordingly, the required degrees of pollution prevention against ammonia, hydrogen sulfide, $PM_{2.5}$ and $PM_{10}$ at P1 and P2, were estimated in a proper manner.

• Maritime Security
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• v.3 no.1
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• pp.141-185
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• 2021

The growing U.S.-China rivalry has placed the countries of Southeast Asia in exceedingly precarious positions. The Republic of Korea (ROK) likewise has been tasked with the challenge of "navigating the waters" between deepening geopolitical divides. It is in this context that the "New Southern Policy" (hereafter NSP) has become a key word in Korea's foreign policy circles. Through NSP, ROK aims to diversify its economic and security interests by strengthening ties with its southern partners, focusing on three key areas (termed as the "3 Ps"): People, Prosperity, and Peace. At the same time, the NSP seeks cooperation with other key diplomatic agendas such as the U.S.'s "Free and Open Indo-Pacific," rendering it crucial for the overall stability of the region. Considering such strategic significance, deeper analysis of the policy is more timely than ever. A brief assessment of the policy's outcome so far, however, reveals that relatively, the "Peace" pillar has been insufficient in achieving satisfactory outcomes. Here, this paper asks the question of: 1) How can the "Peace" pillar of South Korea's New Southern Policy be strengthened? Based on an analysis on the causes of the "Peace" pillar's weakness, this paper identifies counter-piracy cooperation as a solution. This paper then proceeds to answer the next question of: 2) How can ROK and ASEAN cooperate on counter-piracy, and how can these efforts be integrated into ROK's NSP? To answer the above question, this paper conducts in-depth case studies on ASEAN's and ROK's approaches to counter-piracy and identifies specific mechanisms of cooperation. In Chapter I, the paper begins with an overview of the NSP's strategic significance and an evaluation of its "Peace" pillar. Chapter II conducts a literature review on the causes of, and prescriptions for, the weakness of the "Peace" pillar. The paper then justifies why counter-piracy may be a solution. Chapter III examines ASEAN's and ROK's approaches to counter-piracy. By analyzing the general framework and each region's cases, the paper displays the strengths and weaknesses of each region's piracy responses. Based on this analysis, Chapter IV suggests ways to incorporate counter-piracy cooperation into the "Peace" pillar of the NSP. This research bears significance in that it identifies a specific area of cooperation (counter-piracy) to strengthen the "Peace" pillar of ROK's NSP. Such identification is based on a comprehensive study into the two parties' past and current experience in counter-piracy, making it contextual in nature. Furthermore, the study suggests practical mechanisms of cooperation, and considers ways of incorporation into the existing framework of NSP. This approach differs from existing literature that failed to generate case-specific, policy-oriented solutions. The COVID-19 pandemic has exacerbated piracy issues and deepened geopolitical divides. Turbulent seas such as these call for careful navigation. When it comes to promoting "peace," the key lies in combating the pirates that sail those very waters.

• Korean Association of Arts Management
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• no.53
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• pp.127-151
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• 2020

In this study, the announced in 2010 was used to identify the flow of social value expansion on the culture and art education and to provide the future direction. In the context of culture and art education, cultural diversity is an important agenda, and thus the case of cultural diversity program by the National Museum of Contemporary Art was analyzed to discuss the social role of culture and art education. To summarize the findings, it is a program of promoting understanding on the diversity of art in the same period and various identifies of the members of our society through the exhibition of «Artist of the Year», and it is a program on cultural diversity of understanding the diversity and identity of various members in our society through the contemporary artwork. Through theme-based approach, education on cultural diversity and cooperative learning were applied to develop the sense of community. Based on the core values of education on cultural diversity, the contents of the education program on performed total of 80 times on 14 programs in 2017-2019 were analyzed. As a result, the analysis showed 9 core values, and the core values of education on cultural diversity derived through the content analysis of the education program on were ① Engagement, ② Conversation, ③ Citizenship, ④ Coexistence, ⑤ Human Rights, ⑥ Difference, ⑦ Equality, ⑧ Cooperation, ⑨ Solidarity. As the space enhancing the cultural engagement, the art museum is a place for realizing the value on cultural diversity, so it has significance as the space that embraces both cultural diversity and culture and art education. In this sense, it was identified that the discussion on the cultural diversity and culture and art education was being expanded into the perspective of various groups and communities in our society through the core values of engagement, conversation, citizenship, coexistence, human rights, difference, equality, cooperation, solidarity and direction, which were provided by the analysis of the contents on the art museum education program on cultural diversity in the National Museum of Contemporary Art.

• Journal of Korean Academy of Nursing
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• v.20 no.3
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• pp.324-340
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• 1990

Support has always been considered an important nursing concept. However, there is no agreement among nurse researchers as to a conceptual definition of supportive nursing or meaningful supportive behaviors. Clarification of the concept, support in nursing, is necessary to promote communication among nurses on nursing behaviors that are effective in providing support and on understanding the relevant properties and charcteristics of the concept, supportive nursing care. The objectives of the study were : 1. to analyse the concept, support in nursing, in order to provide a definition of supportive nursing care, and 2. to operationalize the definition of supportive nursing care and use it as an experimental nursing intervention for patients with low back pain. The first part of the study used the concept analysis approach developed by Walker and Avant(1983) to define the concept of supportive nursing care. The properties of supportive nursing care, defined by this analysis, included perception of supportive need, reciprocal interaction(Transaction), listening, providing empathy and information related to health, and confirmation of the patient's verbal and non - verbal response. The second part, the experimental part of the study, was done using King's(1970) Interpersonal Theory for Nursing. The concept, supportive nursing care, as defined in the concept analysis was operationalized and used as the experimental intervention. The experiment tested the effectiveness of the independent variable, supportive nursing care on the dependent variables, depression, mood and patient satisfaction, in the patients with low back pain in army hospitals. The instruments used to measure the dependent variables were Zung's(1965) Self- Rating Depression Scale, Ryman and Colleagues'(1974) Mood Questionnaire and LaMonica and Colleagues'(1986) Patient Satisfaction Scale. The experimental design used for this study was a Solomon 4 group experimental design. This design has the strength of allowing for observation of the main effects of supportive nursing care and pretesting, and for observation of the interaction effects of pretesting and supportive nursing care. The design includes one experimental group and three control groups. The Subjects of this study were 150 young male patients with low back pain on Neuro - Surgical Wards in three general army hospitals. There were 35 in the experimental group, 39 in the pre - posttest control group, 36 in the treatment - posttest control group and 40 in the posttest only control group. Supportive nursing care, as operationalized by the researcher according to the concept analysis, was given to the patients in the experimental group and the treatment -posttest control group, individually for 30 minute sessions, every other day for 5 days. Data collection was done using a questionnaire. The data were collected in a pretest one week before the supportive nursing care sessions, a posttest immediately after the sessions and follow- up test one week later. Hypotheses testing was done using 2×2 factorial analysis of variance and Meta analysis(Stouffer's Z method). The results of this study are summarized as follows : 1. Hypothesis Ⅰ, “There will be a difference on depression level between the patients with low back pain who receive supportive nursing care and those who do not receive supportive nursing care”, was supported (F＝8.49, p＜.05). 2. Hypothesis Ⅱ, “There will be a difference on mood level between the patients with low back pain who receive supportive nursing care and those who to not receive supportive nursing care”, was supported (Z meta＝2.17, p＜.05). 3. Hypothesis Ⅲ, “There will be a difference on satisfaction level between the patients with low back pain who receive supportive nursing care and those who do not receive supportive nursing care”, was supported (F＝13.67, p＜.05). 4. ANOVA, done to examine the interaction effect of history and maturation, showed no significant difference on the dependent variables between the observations of the pretest scores of the experimental group, the pretest scores of the pre- posttest control group and the posttest score of the posttest only control group. 5. To test for continuing effect of supportive nursing care, paired t-test was done to compare the scores for the dependent variables at the posttest and at the one week later follow-up test. No significant difference on the scores for the dependent variables was found between the posttest scores and the follow-up test scores for the two groups that received supportive nursing care, the experimental group and the treatment-posttest control group. In conclusion, it was found that in the case of young soldiers with low back pain in army hospitals, their depression level was decreased, their mood state was changed positively and their satisfaction level was increased by receiving supportive nursing care. Further, the effectiveness of the supportive nursing care lasted for at least one week in this study. The significance of this study to nursing is in the analysis of the concept of supportive nursing care and the demonstration of the effectiveness of supportive nursing care as an intervention within the limits of the study.

• Asia pacific journal of information systems
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• v.19 no.1
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• pp.33-62
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• 2009

Internet computing is a disruptive IT innovation. Semantic Web can be considered as an IT innovation because the Semantic Web technology possesses the potential to reduce information overload and enable semantic integration, using capabilities such as semantics and machine-processability. How should organizations adopt the Semantic Web? What factors affect the adoption and diffusion of Semantic Web innovation? Most studies on adoption and diffusion of innovation use empirical analysis as a quantitative research methodology in the post-implementation stage. There is criticism that the positivist requiring theoretical rigor can sacrifice relevance to practice. Rapid advances in technology require studies relevant to practice. In particular, it is realistically impossible to conduct quantitative approach for factors affecting adoption of the Semantic Web because the Semantic Web is in its infancy. However, in an early stage of introduction of the Semantic Web, it is necessary to give a model and some guidelines and for adoption and diffusion of the technology innovation to practitioners and researchers. Thus, the purpose of this study is to present a model of adoption and diffusion of the Semantic Web and to offer propositions as guidelines for successful adoption through a qualitative research method including multiple case studies and in-depth interviews. The researcher conducted interviews with 15 people based on face-to face and 2 interviews by telephone and e-mail to collect data to saturate the categories. Nine interviews including 2 telephone interviews were from nine user organizations adopting the technology innovation and the others were from three supply organizations. Semi-structured interviews were used to collect data. The interviews were recorded on digital voice recorder memory and subsequently transcribed verbatim. 196 pages of transcripts were obtained from about 12 hours interviews. Triangulation of evidence was achieved by examining each organization website and various documents, such as brochures and white papers. The researcher read the transcripts several times and underlined core words, phrases, or sentences. Then, data analysis used the procedure of open coding, in which the researcher forms initial categories of information about the phenomenon being studied by segmenting information. QSR NVivo version 8.0 was used to categorize sentences including similar concepts. 47 categories derived from interview data were grouped into 21 categories from which six factors were named. Five factors affecting adoption of the Semantic Web were identified. The first factor is demand pull including requirements for improving search and integration services of the existing systems and for creating new services. Second, environmental conduciveness, reference models, uncertainty, technology maturity, potential business value, government sponsorship programs, promising prospects for technology demand, complexity and trialability affect the adoption of the Semantic Web from the perspective of technology push. Third, absorptive capacity is an important role of the adoption. Fourth, suppler's competence includes communication with and training for users, and absorptive capacity of supply organization. Fifth, over-expectance which results in the gap between user's expectation level and perceived benefits has a negative impact on the adoption of the Semantic Web. Finally, the factor including critical mass of ontology, budget. visible effects is identified as a determinant affecting routinization and infusion. The researcher suggested a model of adoption and diffusion of the Semantic Web, representing relationships between six factors and adoption/diffusion as dependent variables. Six propositions are derived from the adoption/diffusion model to offer some guidelines to practitioners and a research model to further studies. Proposition 1 : Demand pull has an influence on the adoption of the Semantic Web. Proposition 1-1 : The stronger the degree of requirements for improving existing services, the more successfully the Semantic Web is adopted. Proposition 1-2 : The stronger the degree of requirements for new services, the more successfully the Semantic Web is adopted. Proposition 2 : Technology push has an influence on the adoption of the Semantic Web. Proposition 2-1 : From the perceptive of user organizations, the technology push forces such as environmental conduciveness, reference models, potential business value, and government sponsorship programs have a positive impact on the adoption of the Semantic Web while uncertainty and lower technology maturity have a negative impact on its adoption. Proposition 2-2 : From the perceptive of suppliers, the technology push forces such as environmental conduciveness, reference models, potential business value, government sponsorship programs, and promising prospects for technology demand have a positive impact on the adoption of the Semantic Web while uncertainty, lower technology maturity, complexity and lower trialability have a negative impact on its adoption. Proposition 3 : The absorptive capacities such as organizational formal support systems, officer's or manager's competency analyzing technology characteristics, their passion or willingness, and top management support are positively associated with successful adoption of the Semantic Web innovation from the perceptive of user organizations. Proposition 4 : Supplier's competence has a positive impact on the absorptive capacities of user organizations and technology push forces. Proposition 5 : The greater the gap of expectation between users and suppliers, the later the Semantic Web is adopted. Proposition 6 : The post-adoption activities such as budget allocation, reaching critical mass, and sharing ontology to offer sustainable services are positively associated with successful routinization and infusion of the Semantic Web innovation from the perceptive of user organizations.

• Journal of Chest Surgery
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• v.43 no.3
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• pp.254-259
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• 2010

Background: Diagnosing chronic pulmonary embolism at an early stage is difficult because of the patient’s nonspecific symptoms. This condition is not prevalent in Korea, and in fact, there have been only a few case reports on this in the Korean medical literature. We analyzed the surgical outcome of performing pulmonary thromboendarterectomy in patients with chronic pulmonary embolism. Material and Method: The study subjects included those patients who underwent surgery for chronic pulmonary embolism from 1996 to 2008. For making the diagnosis, echocardiography, chest CT and a pulmonary perfusion scan were performed on the patients who complained of chronic dyspnea. Result: Pulmonary endarterectomy was performed as follows: by incision via a mid-sternal approach (7 patients); by incision via a left posterolateral approach (1 patient); using the deep hypothermic circulatory arrest technique (4 patients); under ventricular fibrillation (3 patients); and under cardioplegic arrest (1 patient). The postoperative systolic pulmonary artery blood pressure significantly decreased from a preoperative value of $78.9{\pm}14.5\;mmHg$ to $45.6{\pm}17.6\;mmHg$ postoperatively (p=0.000). The degree of tricuspid regurgitation was less than grade II after surgery. Two patients died early on, including one patient who had persistent pulmonary hypertension without improvement and right heart failure. Conclusion: Patients who have chronic pulmonary embolism are known to have a poor prognosis. However, we think that early surgical treatment along with making the proper diagnosis before the aggravation of right heart failure can help improve the quality of a patient's life.

• Journal of Korean Society of Forest Science
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• v.35 no.1
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• pp.1-8
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• 1977

Forest soil fertility was evaluated through the approach of numerical method. In this study, the soil chemical properties analyzed for 35 different soil series as table 2 were cited in numerical analysis. Minimum contents of essential nutrients in the surface soil for a satisfactory growth of tree in the plantation were evaluated by comparing with Wild's standard as table 1. Demanding level of fertilization were evaluated by using the formula 1 as table 5. Similar relation of soil chemical properties between soil series were calculated through formula 2, and then classified into 5 groups in soil chemical properties. 1. General chemical properties of surface soil in case of 35 soil series. About 40 percent of 35 different soil series are less than 2 percent in organic matter, 10 ppm in available phosphorus, 1.25m.e/l00g in exchangeable calcium and 0.5m.e/l00g in exchangeable magnesium. Generally, shortage of exchangeable potash are not found. CEC less than 10m.e/l00g are in two thirds and strong acid soil less than PH 5.5 are in about four fifths. 2. Soil series requested or not the fertilization are indirectly evaluated from the formula 1 using the relative figure of chemical components of CEC, OM and MgO. Through this analysis, 8 different soil series have very poor quality in soil chemical capacity so that demands highly the fertilization. On the other hand, other 13 different soil series group have not been thought to need the fertilization according to chemical guality. 3. By the results comparing the similarity of chemical properties of forest soil, it is thought to be suitable that the forest soil fertility are divided into 5 groups as follows: 1. Low CEC soil 1-1 Low organic matter soil less than 2 percent 1-2 Medium organic matter soil less than 4 percent 2. High CEC and organic matter soil 2-1 Low magnesium soil 2-2 High magnesium soil 3. High magnesium and calcium soil as lime stone.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.19-41
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• 2019

According to the rapidly increasing demand for text data analysis, research and investment in text mining are being actively conducted not only in academia but also in various industries. Text mining is generally conducted in two steps. In the first step, the text of the collected document is tokenized and structured to convert the original document into a computer-readable form. In the second step, tasks such as document classification, clustering, and topic modeling are conducted according to the purpose of analysis. Until recently, text mining-related studies have been focused on the application of the second steps, such as document classification, clustering, and topic modeling. However, with the discovery that the text structuring process substantially influences the quality of the analysis results, various embedding methods have actively been studied to improve the quality of analysis results by preserving the meaning of words and documents in the process of representing text data as vectors. Unlike structured data, which can be directly applied to a variety of operations and traditional analysis techniques, Unstructured text should be preceded by a structuring task that transforms the original document into a form that the computer can understand before analysis. It is called "Embedding" that arbitrary objects are mapped to a specific dimension space while maintaining algebraic properties for structuring the text data. Recently, attempts have been made to embed not only words but also sentences, paragraphs, and entire documents in various aspects. Particularly, with the demand for analysis of document embedding increases rapidly, many algorithms have been developed to support it. Among them, doc2Vec which extends word2Vec and embeds each document into one vector is most widely used. However, the traditional document embedding method represented by doc2Vec generates a vector for each document using the whole corpus included in the document. This causes a limit that the document vector is affected by not only core words but also miscellaneous words. Additionally, the traditional document embedding schemes usually map each document into a single corresponding vector. Therefore, it is difficult to represent a complex document with multiple subjects into a single vector accurately using the traditional approach. In this paper, we propose a new multi-vector document embedding method to overcome these limitations of the traditional document embedding methods. This study targets documents that explicitly separate body content and keywords. In the case of a document without keywords, this method can be applied after extract keywords through various analysis methods. However, since this is not the core subject of the proposed method, we introduce the process of applying the proposed method to documents that predefine keywords in the text. The proposed method consists of (1) Parsing, (2) Word Embedding, (3) Keyword Vector Extraction, (4) Keyword Clustering, and (5) Multiple-Vector Generation. The specific process is as follows. all text in a document is tokenized and each token is represented as a vector having N-dimensional real value through word embedding. After that, to overcome the limitations of the traditional document embedding method that is affected by not only the core word but also the miscellaneous words, vectors corresponding to the keywords of each document are extracted and make up sets of keyword vector for each document. Next, clustering is conducted on a set of keywords for each document to identify multiple subjects included in the document. Finally, a Multi-vector is generated from vectors of keywords constituting each cluster. The experiments for 3.147 academic papers revealed that the single vector-based traditional approach cannot properly map complex documents because of interference among subjects in each vector. With the proposed multi-vector based method, we ascertained that complex documents can be vectorized more accurately by eliminating the interference among subjects.

• Journal of the Korean Society of Radiology
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• v.13 no.1
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• pp.111-118
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• 2019

Chest digital tomosynthesis has become a practical imaging modality because it can solve the problem of anatomy overlapping in conventional chest radiography. However, because of both limited scan angle and finite-size detector, a portion of chest cannot be represented in some or all of the projection. These bring a discontinuity in intensity across the field of view boundaries in the reconstructed slices, which we refer to as the truncation artifacts. The purpose of this study was to reduce truncation artifacts using a weighted normalization approach and to investigate the performance of this approach for our prototype chest digital tomosynthesis system. The system source-to-image distance was 1100 mm, and the center of rotation of X-ray source was located on 100 mm above the detector surface. After obtaining 41 projection views with ${\pm}20^{\circ}$ degrees, tomosynthesis slices were reconstructed with the filtered back projection algorithm. For quantitative evaluation, peak signal to noise ratio and structure similarity index values were evaluated after reconstructing reference image using simulation, and mean value of specific direction values was evaluated using real data. Simulation results showed that the peak signal to noise ratio and structure similarity index was improved respectively. In the case of the experimental results showed that the effect of artifact in the mean value of specific direction of the reconstructed image was reduced. In conclusion, the weighted normalization method improves the quality of image by reducing truncation artifacts. These results suggested that weighted normalization method could improve the image quality of chest digital tomosynthesis.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.107-120
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• 2014

This study proposes a novel recommender system using the structural hole analysis to reflect qualitative and emotional information in recommendation process. Although collaborative filtering (CF) is known as the most popular recommendation algorithm, it has some limitations including scalability and sparsity problems. The scalability problem arises when the volume of users and items become quite large. It means that CF cannot scale up due to large computation time for finding neighbors from the user-item matrix as the number of users and items increases in real-world e-commerce sites. Sparsity is a common problem of most recommender systems due to the fact that users generally evaluate only a small portion of the whole items. In addition, the cold-start problem is the special case of the sparsity problem when users or items newly added to the system with no ratings at all. When the user's preference evaluation data is sparse, two users or items are unlikely to have common ratings, and finally, CF will predict ratings using a very limited number of similar users. Moreover, it may produces biased recommendations because similarity weights may be estimated using only a small portion of rating data. In this study, we suggest a novel limitation of the conventional CF. The limitation is that CF does not consider qualitative and emotional information about users in the recommendation process because it only utilizes user's preference scores of the user-item matrix. To address this novel limitation, this study proposes cluster-indexing CF model with the structural hole analysis for recommendations. In general, the structural hole means a location which connects two separate actors without any redundant connections in the network. The actor who occupies the structural hole can easily access to non-redundant, various and fresh information. Therefore, the actor who occupies the structural hole may be a important person in the focal network and he or she may be the representative person in the focal subgroup in the network. Thus, his or her characteristics may represent the general characteristics of the users in the focal subgroup. In this sense, we can distinguish friends and strangers of the focal user utilizing the structural hole analysis. This study uses the structural hole analysis to select structural holes in subgroups as an initial seeds for a cluster analysis. First, we gather data about users' preference ratings for items and their social network information. For gathering research data, we develop a data collection system. Then, we perform structural hole analysis and find structural holes of social network. Next, we use these structural holes as cluster centroids for the clustering algorithm. Finally, this study makes recommendations using CF within user's cluster, and compare the recommendation performances of comparative models. For implementing experiments of the proposed model, we composite the experimental results from two experiments. The first experiment is the structural hole analysis. For the first one, this study employs a software package for the analysis of social network data - UCINET version 6. The second one is for performing modified clustering, and CF using the result of the cluster analysis. We develop an experimental system using VBA (Visual Basic for Application) of Microsoft Excel 2007 for the second one. This study designs to analyzing clustering based on a novel similarity measure - Pearson correlation between user preference rating vectors for the modified clustering experiment. In addition, this study uses 'all-but-one' approach for the CF experiment. In order to validate the effectiveness of our proposed model, we apply three comparative types of CF models to the same dataset. The experimental results show that the proposed model outperforms the other comparative models. In especial, the proposed model significantly performs better than two comparative modes with the cluster analysis from the statistical significance test. However, the difference between the proposed model and the naive model does not have statistical significance.