• Journal of the Korean Magnetics Society
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• v.11 no.3
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• pp.85-96
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• 2001

Experimental magnetization-temperature curves for melt-spun ribbons of amorphous alloys (Dy$\_$0.33/Fe$\_$0.67/)$\_$1-x/B$\_$x/(x=0 ,0.05, 0.1, and 0.15) and (Sm$\_$0.33/Fe$\_$0.67/)$\_$1-x/B$\_$x/(x=0, 0.01, 0.02, and 0.03) (in atomic fraction) are fitted with theoretical equations based on the mean field theory in order to calculate exchange couplings between constituent elements as a function of the B content. In the case of the DyFe$_2$-B system, the sign of the exchange coupling between Dy and Fe is negative, indicating that the magnetization direction of Dy is antiparallel to that of Fe. The sign of the other two couplings are positive indicating a parallel alignment. The exchange coupling between Fe ions are greatest, while that between Dy ions is negligible. In the case of the SmFe$_2$B alloys, the sign of all the couplings are positive, indicating ferromagnetic coupling between the spins. The exchange couplings between Fe ions, and Fe and Sm are comparable to each other, but they are much greater than that between Sm ions. The high exchange coupling between Fe and Sm, which is considered to occur indirectly, is rather unexpected, but it is considered to be unique characteristics of amorphous Sm-Fe alloys. In both alloy systems, the exchange coupling between Fe ions increases with increasing B content. and this may be explained by the increase of the Fe-Fe separation with increasing B content. The exchange coupling between Fe and RE also increases with increasing B content. As the B content increases, the magnetization decreases over the whole temperature range, and the Curie temperature also decreases.

• Management & Information Systems Review
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• v.31 no.4
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• pp.559-592
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• 2012

In spite of the transitional changes in the shoe industry in Busan area, regular academic studies on the management plan to improve the practical competitiveness of footwear industry focused in the materials, bio-dynamics, components, and designs, etc. in the engineering viewpoint are very rare. Many reports of policies were published from late 190's to 2000's but they were limited to the identification of practical situations and the measures for strategic alternatives and were not developed to be the academic studies to improve the competitiveness in terms of management control. It is intended to seek for the measures to be reviewed as the alternatives to improve the self-competitiveness of footwear companies by approaching the problems limited to such specific area in the viewpoint of management control. The core of this study is to provide the alternative plans for expansion of the industrial foundation by seeking for the measures to improve competitiveness with application of knowledge management as an alternative for improvement of not transient but sustainable industrial competitiveness, in order to help the export of shoes from Busan area which has been rapidly increased since the Korea-USA FTA and Korea-EU FTA. In such viewpoint, in the study, a questionnaire survey was performed related with the issues of Busan's footwear industry and the plan to implement knowledge management was discussed for improvement of the competitiveness of footwear industry based on the result of such questionnaire survey. As most of studies and directions have been focused in functional shoes, designs, materials, and components, etc., which are related with the properties of human dynamics, as the alternatives for improvement of the footwear industry of Busan area and did not suggest the measures to make basic changes in the management of companies, the implementation of knowledge management was emphasized in order to seek for the direction of such plan. The purpose of this study is to suggest an alternative for construction of industrial eco-system for high added value by seeking for the probability of knowledge management for conversion of footwear industry into knowledge industry. In order to accomplish the effect of increased export as the result of FTA, current management method of footwear companies is limited and the effect of FTA should be maximized by improving the competitiveness with implementation of knowledge management methods. Settlement of such knowledge management will act as the momentum to improve the competitiveness of footwear companies and, in a long-term viewpoint, will be able to maximize the improvement of knowledge industry and creation of job opportunities.

• Tuberculosis and Respiratory Diseases
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• v.44 no.3
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• pp.493-504
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• 1997

Background : Non-small cell lung cancer is one of the most frequent cause of death due to cancer in men, and its incidence among women is rapidly increasing. Although there has been a recent surge of interest in combined modality therapy for stageIII non-small cell lung cancer(NSCLC), the optimal treatment is still not well established. Thoracic irradiation has long been the gold standard for locally advanced unresectable NSCLC. However, although conventional radiotherapy(XRT) can palliate symptom and improve local control of disease, it has at most only a modest effect on survival. Recently, cisplatin(cis-diamminedichloroplatinum) has been reported to enhance the cell-killing effect of radiation For patients with unresectable NSCLC, cisplatin-based concurrent chemoradiotherapy(CCRT) had the advantage of therapeutic response over XRT alone and therapeutic side effect more commonly occurred in CCRT group in EORTC(European Organization for Research and Treatment of Cancer) and other trials. Objectives : We compared therapeutic response, compliance, and side effects between CCRT and XRT in patients with advanced NSCLC. Patients and Method : Thirty patients with biopsy-proven inoperable NSCLC were randomized to one of two treatment arms. Arm A consisted of XRT, radiotherapy for 4~6 weeks(1.8 Gy given 20~33 times, in five fractions a week), and arm B consisted of CCRT, radiotherapy for 2 weeks(3 Gy given to times, in five fractions a week), followed by 3 week rest period and then radiotherapy 2 more weeks(2.5 Gy given 10 times, in five fractions a week), combined with 6mg cisplatin per square meter, given daily before radiotherapy. We evaluate therapeutic response, compliance, change of performance status, side effects, and radiation pneumonitis by using the author's made scoring system. Results : There was no significant difference in therapeutic response and compliance. But there was a significantly lower laboratory complication and radiation pneumonitis in CCRT group (p < 0.05). There's significant negative correlation between stage and therapeutic response score in both groups(R=0.353, p < 0.05) In both groups, patients with squamous cell carcinoma had a tendency to higher therapeutic response score than those with adenocarcinoma. Conclusion : There was no difference between CCRT and XRT in respect to therapeutic response and compliance. But CCRT had a advantage of decreased side effects.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.119-138
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• 2017

Recently, SNS has become an important channel for marketing as well as personal communication. However, cybercrime has also evolved with the development of information and communication technology, and illegal advertising is distributed to SNS in large quantity. As a result, personal information is lost and even monetary damages occur more frequently. In this study, we propose a method to analyze which sentences and documents, which have been sent to the SNS, are related to financial fraud. First of all, as a conceptual framework, we developed a matrix of conceptual characteristics of cybercriminality on SNS and emergency management. We also suggested emergency management process which consists of Pre-Cybercriminality (e.g. risk identification) and Post-Cybercriminality steps. Among those we focused on risk identification in this paper. The main process consists of data collection, preprocessing and analysis. First, we selected two words 'daechul(loan)' and 'sachae(private loan)' as seed words and collected data with this word from SNS such as twitter. The collected data are given to the two researchers to decide whether they are related to the cybercriminality, particularly financial fraud, or not. Then we selected some of them as keywords if the vocabularies are related to the nominals and symbols. With the selected keywords, we searched and collected data from web materials such as twitter, news, blog, and more than 820,000 articles collected. The collected articles were refined through preprocessing and made into learning data. The preprocessing process is divided into performing morphological analysis step, removing stop words step, and selecting valid part-of-speech step. In the morphological analysis step, a complex sentence is transformed into some morpheme units to enable mechanical analysis. In the removing stop words step, non-lexical elements such as numbers, punctuation marks, and double spaces are removed from the text. In the step of selecting valid part-of-speech, only two kinds of nouns and symbols are considered. Since nouns could refer to things, the intent of message is expressed better than the other part-of-speech. Moreover, the more illegal the text is, the more frequently symbols are used. The selected data is given 'legal' or 'illegal'. To make the selected data as learning data through the preprocessing process, it is necessary to classify whether each data is legitimate or not. The processed data is then converted into Corpus type and Document-Term Matrix. Finally, the two types of 'legal' and 'illegal' files were mixed and randomly divided into learning data set and test data set. In this study, we set the learning data as 70% and the test data as 30%. SVM was used as the discrimination algorithm. Since SVM requires gamma and cost values as the main parameters, we set gamma as 0.5 and cost as 10, based on the optimal value function. The cost is set higher than general cases. To show the feasibility of the idea proposed in this paper, we compared the proposed method with MLE (Maximum Likelihood Estimation), Term Frequency, and Collective Intelligence method. Overall accuracy and was used as the metric. As a result, the overall accuracy of the proposed method was 92.41% of illegal loan advertisement and 77.75% of illegal visit sales, which is apparently superior to that of the Term Frequency, MLE, etc. Hence, the result suggests that the proposed method is valid and usable practically. In this paper, we propose a framework for crisis management caused by abnormalities of unstructured data sources such as SNS. We hope this study will contribute to the academia by identifying what to consider when applying the SVM-like discrimination algorithm to text analysis. Moreover, the study will also contribute to the practitioners in the field of brand management and opinion mining.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.139-153
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• 2017

Corporate bankruptcy can cause great losses not only to stakeholders but also to many related sectors in society. Through the economic crises, bankruptcy have increased and bankruptcy prediction models have become more and more important. Therefore, corporate bankruptcy has been regarded as one of the major topics of research in business management. Also, many studies in the industry are in progress and important. Previous studies attempted to utilize various methodologies to improve the bankruptcy prediction accuracy and to resolve the overfitting problem, such as Multivariate Discriminant Analysis (MDA), Generalized Linear Model (GLM). These methods are based on statistics. Recently, researchers have used machine learning methodologies such as Support Vector Machine (SVM), Artificial Neural Network (ANN). Furthermore, fuzzy theory and genetic algorithms were used. Because of this change, many of bankruptcy models are developed. Also, performance has been improved. In general, the company's financial and accounting information will change over time. Likewise, the market situation also changes, so there are many difficulties in predicting bankruptcy only with information at a certain point in time. However, even though traditional research has problems that don't take into account the time effect, dynamic model has not been studied much. When we ignore the time effect, we get the biased results. So the static model may not be suitable for predicting bankruptcy. Thus, using the dynamic model, there is a possibility that bankruptcy prediction model is improved. In this paper, we propose RNN (Recurrent Neural Network) which is one of the deep learning methodologies. The RNN learns time series data and the performance is known to be good. Prior to experiment, we selected non-financial firms listed on the KOSPI, KOSDAQ and KONEX markets from 2010 to 2016 for the estimation of the bankruptcy prediction model and the comparison of forecasting performance. In order to prevent a mistake of predicting bankruptcy by using the financial information already reflected in the deterioration of the financial condition of the company, the financial information was collected with a lag of two years, and the default period was defined from January to December of the year. Then we defined the bankruptcy. The bankruptcy we defined is the abolition of the listing due to sluggish earnings. We confirmed abolition of the list at KIND that is corporate stock information website. Then we selected variables at previous papers. The first set of variables are Z-score variables. These variables have become traditional variables in predicting bankruptcy. The second set of variables are dynamic variable set. Finally we selected 240 normal companies and 226 bankrupt companies at the first variable set. Likewise, we selected 229 normal companies and 226 bankrupt companies at the second variable set. We created a model that reflects dynamic changes in time-series financial data and by comparing the suggested model with the analysis of existing bankruptcy predictive models, we found that the suggested model could help to improve the accuracy of bankruptcy predictions. We used financial data in KIS Value (Financial database) and selected Multivariate Discriminant Analysis (MDA), Generalized Linear Model called logistic regression (GLM), Support Vector Machine (SVM), Artificial Neural Network (ANN) model as benchmark. The result of the experiment proved that RNN's performance was better than comparative model. The accuracy of RNN was high in both sets of variables and the Area Under the Curve (AUC) value was also high. Also when we saw the hit-ratio table, the ratio of RNNs that predicted a poor company to be bankrupt was higher than that of other comparative models. However the limitation of this paper is that an overfitting problem occurs during RNN learning. But we expect to be able to solve the overfitting problem by selecting more learning data and appropriate variables. From these result, it is expected that this research will contribute to the development of a bankruptcy prediction by proposing a new dynamic model.

• Journal of Korean Society of Environmental Engineers
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• v.22 no.6
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• pp.1159-1170
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• 2000

It is necessary to improve the ambient air quality through the proper treatment and control of pollutants by designating air pollutants to regulatory ones. Especially, human took a concern for particulate matters which raised visibility reduction, public health effects and injury of property for urban areas. In order to reduce the effect of particulate matters, we need to establish proper control strategies based on the concentration characteristics of particulate matters. In this study. to evaluate the characteristics of $PM_{2.5}$ and $PM_{10}$. thirty-eight samples of $PM_{2.5}$ and $PM_{10}$ were collected at Nam-Gu sampling site where continuous air monitoring system has been operated, from May, 1999 to November, 1999, and their concentrations for the mass and anion components($Cl^-$, $NO_3{^-}$, $SO_4{^{2-}}$) were analyzed. The important conclusions obtained in this study were as followings. Total average mass concentrations of $PM_{2.5}$ and $PM_{10}$ were 35.016 and $50.293{\mu}g/m^3$ respectively. and $PM_{2.5}/PM_{10}$ ratio was calculated 0.692. Total average concentrations of anion components in $PM_{2.5}$ were $1.581(Cl^-)$, $3.690(NO_3{^-})$ and $12.825(SO_4{^{2-}}){\mu}g/m^3$ and those in $PM_{10}$ were $2.471(Cl^-)$, $5.819(NO_3{^-})$ and $14.414(SO_4{^{2-}}){\mu}g/m^3$ respectively. From the correlations analysis. the correlation coefficient between mass concentration of $PM_{2.5}$ and $PM_{10}$ was calculated as 0.945. The correlation coefficients between $PM_{2.5}$ and anion components were analyzed as $Cl^-$(0.025), $NO_3{^-}$(0.788) and $SO_4{^{2-}}$(0.500) respectively, and the correlation coefficients between $PM_{10}$ and anion components were analyzed as $Cl^-$(-0.019), $NO_3{^-}$(0.806) and $SO_4{^{2-}}$)(0.535) respectively.

• Journal of the Korean Institute of Landscape Architecture
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• v.39 no.1
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• pp.35-45
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• 2011

The landscape of Seoul was dynamically changed and developed with the rapid post-war economic growth. Seoul city designated a height regulation district to preserve and manage the city landscape and protect it from haphazard construction. The designation of a maximum height regulation district has obvious purpose and simple regulations which makes the implementation and management easy to apply yet the altitude restriction lacks an objective basis for its enforcement. Many studies have been done and the current uniform height regulation requires more objective and logical guidelines. This study selected the Bukhan Mountain area, a National Park designated to protect the environment, to present a new landscape height guideline to minimize environmental degradation and to harmonize the artificial and natural landscapes of the area. Document research was done to identify the regulation types(absolute height regulation, view line regulation, oblique line restriction regulation) and principles for height regulation district establishment, acknowledge the current status and issues of the Bukhan Mountain area's maximum height regulation district. Gangbuk-Gu was chosen as the site and survey was conducted on outstanding view points and view corridors of residents. From document research, an appropriate landscape height guideline was selected and applied to Gangbuk-Gu. According to the guideline, suitable heights for buildings were suggested. These were then applied to three-dimensional simulations and a final guideline was suggested.

• Journal of the Korean Institute of Landscape Architecture
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• v.39 no.1
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• pp.96-105
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• 2011

This study analyzed literary works and references related to Dok-Rak-Dang(獨樂堂) and the attributes of managing the landscape in Dok-Rak-Dang Garden based on the assumption of position and the spatial structure revealed in the site. Hoe-Jae Lee Eon-Jeok(1491-1553), a distinguished scholar of Neo-Confusionism, built Dok-Rak-Dang and managed the surrounding areas during his retirement years. He called the mountains, stream, and rock along and near the Ja-Ge Stream Four Mountains and Five Platforms(四山五臺). Before he named these, they were not considered special. The Four Mountains which are Do-Duk in north, Mu-Hak in south, Hwa-Gae in east, and Ja-Ok in west enclose Dok-Rak-Dang and the surrounding areas. The Five Platforms, Se-Sim, Gwan-Eo, Yeong-Gue, Jing-Sim, and Tak-Yeong, in order from downstream, are places with beautiful scenery in Ja-Ge Stream. The attributes of managing the landscape in Dok-Rak-Dang Garden are the following: One is the spatial integration of what is natural and artificial as the attitude of aesthetic experience in accord with nature. Another is flexible territorialization as the way of organizing spaces in nature from the experiential aspect. The other is place making of personalized nature through a series of processes such as observing, choosing, and naming landscapes in nature. Four Mountains and Five Platforms function as landscape bases and elements to appreciate nature aesthetically. Those attributes are different from the attitude of constructing spaces. Rather, they originate from the traditional view on the appreciation of nature. Above all, place-making in nature was acquired from designed spatial structure and experiential aesthetic appreciation in the space through observing, choosing, and naming landscapes in nature reflecting creator's own ideological and aesthetic thoughts, and it might be explained as one of practical ways of Korean traditional gardening.

• Journal of Navigation and Port Research
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• v.26 no.3
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• pp.323-328
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• 2002

Soil-steel structures have been used for the underpass, or drainage systems in the road embankment. This type of structures sustain external load using the correlations with the steel wall and engineered backfill materials. Buried flexible conduits made of corrugated steel plates for the coastal road was tested under vehicle loading to investigate the effects of live load. Testing conduits was a circular structure with a diameter of 6.25m. Live-load tests were conducted on two sections, one of which an attempt was made to reinforce the soil cover with the two layers of geo-gird. Hoop fiber strains of corrugated plate, normal earth pressures exerted outside the structure, and deformations of structure were instrumented during the tests. This paper describes the measured static and dynamic load responses of structure. Wall thrust by vehicle loads increased mainly at the crown and shoulder part of the conduit. However additional bending moment by vehicle loads was neglectable. The effectiveness of geogrid-reinforced soil cover on reducing hoop thrust is also discussed based on the measurements in two sections of the structure. The maximum thrusts at the section with geogrid-reinforced soil cover was 85-92% of those with un-reinforced soil cover in the static load tests of the circular structure; this confirms the beneficial effect of soil cover reinforcement on reducing the hoop thrust. However, it was revealed that the two layers of geogrid had no effect on reducing the overburden pressure at the crown level of structure. The obtained values of DLA decrease approximately in proportion to the increase in soil cover from 0.9m to 1.5m. These values are about 1.2-1.4 times higher than those specified in CHBDC.

• Korean Journal of Poultry Science
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• v.23 no.1
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• pp.27-37
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• 1996

This experiment was carried out to study the effects of feeding split diets for a.m. and p.m. on laying hen performance and feed cost with 480 ISA Brown layers for three periods during 32∼36, 52∼56 and 72∼76 wk of age, respectively. The control group(C) was fed a conventional single diet throughout the day and split diet groups (T$_1$, T$_2$, T$_3$, T$_4$ and T$\_$5/) were offered high energy-high protein-low Ca diets, and low energy-low protein-high Ca diets in a.m. and p.m., respectively. In split diet groups, feed intake, ME and CP consumption, and feed cost were significantly reduced(P<0.05) compared to the C, while the hen-day egg production was significantly improved. However, the average egg weight was not influenced by the feeding system. Due to the reduced daily feed, ME, and CP intakes, and the improved egg production, the conversions of feed, ME, CP, and feed cost required per kg egg mass were also significantly improved (P<0.05) in splits diet groups. Among split diet groups, the T$_2$ group fed the diet devoid of Ca supplement from the conventional laying hen diet in a.m., and the diet containing the Ca supplement 2 times the conventional diet in p.m., was superior in conversion of nutrients and feed cost per kg egg mass to the other split diet groups. It was concluded that daily feed and nutrients cousumption and daily feed cost could be reduced 5∼6％ while hen-day egg production could be improved about 4％, so that about 10％ of the feed and nutrients and feed cost per kg egg mass could be spared by introducing the split diet feeding for a.m. and p.m. based on T$_2$ treatment in laying hens.