• Journal of Korean Society for Geospatial Information Science
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• v.8 no.1 s.15
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• pp.51-63
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• 2000

Dynamic traffic assignment(DTA) has been a topic of substantial research during the past decade. While DTA is gradually maturing, many aspects of DTA still need improvement, especially regarding its formulation and solution algerian Recently, with its promise for In(Intelligent Transportation System) and GIS(Geographic Information System) applications, DTA have received increasing attention. This potential also implies higher requirement for DTA modeling, especially regarding its solution efficiency for real-time implementation. But DTA have many mathematical difficulties in searching process due to the complexity of spatial and temporal variables. Although many solution algorithms have been studied, conventional methods cannot iud the solution in case that objective function or constraints is not convex. In this paper, the genetic algorithm to find the solution of DTA is applied and the Merchant-Nemhauser model is used as DTA model because it has a nonconvex constraint set. To handle the nonconvex constraint set the GENOCOP III system which is a kind of the genetic algorithm is used in this study. Results for the sample network have been compared with the results of conventional method.

• Journal of the Korean Institute of Landscape Architecture
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• v.44 no.4
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• pp.22-34
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• 2016

The purpose of this study was to analyze commemoration characteristics of fifty-nine Vietnam war memorials in Korea(VWMK) including monuments and national cemeteries from landscape architectural point of view such as location, spacial characteristic, landscape detail, sculpture, and interpretive text. Based on the commemoration characteristics of the analysis, the commemoration culture among Vietnam, the U.S.A., and Korea were studied and differences compared. The results are as follows. First, monuments were mainly located in public open space such as national cemeteries, parks, and plaza, and some of them were elected along with Korea war memorials to honor Vietnam war veterans at the national level. Second, because the monuments were relatively small and memorial towers were conventionally built on a square platform, the memorial style had been simply standardized to stereotype the commemoration characteristics. Third, outmoded memorial towers, stone plates, emblems, and memorial walls were used as main landscape details and standardized facilities were considered from an artistic and social point of view. Fourth, realistic soldier statues to show heroic and humanitarian image were in majority, while symbolic and abstract sculpture were small in number, they were mostly conventional and unexpressive. Fifth, the causes of participation in the Vietnam War were predominantly expressed as 'defending freedom', 'keeping world peace', and 'national economic development' based on anti-communism and patriotism, and also the collectivity of Vietnam War veterans by troop and local level was emphasized through engraving each veterans's name on towers, plates, and walls. VWMK are mostly conventional and stereotyped in style and show strongly national official memory and the collectivity of veterans from a sociopolitical perspective, and aim for anti-communistic patriotism ideologically. Further study and projects will be required to make creative and innovative memorials and to study how to rethink sublime fundamental themes like war, death, and the individual veteran's experience in VWMK.

• Research in Plant Disease
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• v.14 no.1
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• pp.21-25
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• 2008

This study was conducted to decide disease incidence level of rice leaf blast required for reasonable fungicide application in paddy field. We induced the disease development by inoculating rice blast pathogens on rice seedlings (Jinmibyeo) in the greenhouse and transplanting the infected seedlings in the field two weeks after rice plants were transplanted. We scored the disease incidence, grouped and marked according to degree of percentage of diseased leaf area at maximum stage of disease development. The percent diseased leaf area (PDLA) had negative correlations with panicle number per hill, ripened grain (%), and total yield; their correlation coefficients (r), $-0.97^{**}$, $-1.00^{**}$ and $-0.96^{**}$, respectively. However, it had positive correlations with spikelets per panicle and thousand grain weight; their correlation coefficients (r), $0.98^{**}$ and $0.98^{**}$, respectively. Gain threshold (GT) calculated based on control cost and market price was estimated to be 8.35. Economic injury level (EIL) obtained based on GT and coefficient of damage of regression equation between disease incidence and the different yield components; panicle number per hill, spikelets per panical, ripened grain(%), thousand grain weight and yield were 41.8, 9.7, 19.1, 291.1 and 3.4%, respectively. Economic threshold (ET) for yield was 2.7% ($3.4%(EIL){\times}0.8$) on PDLA. These results suggest that application of fungicide is necessary when two under leaves are almost covered with lesions or contained more than twenty large lesions under leaves at maximum tillering stage.

• International Area Studies Review
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• v.22 no.3
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• pp.121-148
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• 2018

This paper examines the role of accounting conservatism on investment expenditure for non-financial Korean listed firms around the 2007-2008 global financial crisis using a differences-in-differences design. Specifically, this paper examines the association between an ex ante classification of firms by their level of accounting conservatism prior to the credit crisis and the ex post magnitude of the decline in investment. Consistent with prior literature, this study found that firms experienced a decline in their investment when hit by the financial crisis (Campello et al. 2010). And also this study found that firms with more conservative financial reporting experienced a smaller decline in investment activity following the financial crisis than did firms with less conservative financial reporting. Together, the results suggest that negative shocks to the supply of external finance hampers firm-level investment and that conservative financial reporting can lessen the sensitivity of firms' investment to such negative shocks. Next, this study shows that the magnitude of our findings is greater for firms more likely to suffer from underinvestment (as opposed to overinvestment). Firms that are financially constrained or have greater demand for external finance are more likely to experience underinvestment. Consistent with the predictions, this study finds stronger benefits of conservatism for firms that face relatively greater costs in raising external capital (i.e., financially constrained firms) or that have a relatively greater need to do so (i.e., firms that lack internal financial resources). This study also finds that the role for conservatism is greater in firms with a higher level of information asymmetry, consistent with the notion that conservatism mitigates financing frictions arising from information problems.

• Management & Information Systems Review
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• v.38 no.1
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• pp.23-41
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• 2019

Smart Factory is different from existing factory automation in that it aims to produce personalized products with minimum time and cost through ICT. However, previous researches, not from consumers but from product suppliers, have focused on technology trends and technology application methods. In order for Smart Factory to be successful, it must go beyond supplier-focus to meet the needs of consumers. In this study, we surveyed the purchase intention of the personalized product manufactured by smart factory. Influencing factors of purchase intention were drawn as consumers' need for uniqueness, innovativeness, need for touch, and privacy concern, based on previous research. As results of data analysis, it was confirmed that respondents were willing to purchase personalized products, and that consumers' need for uniqueness, innovativeness, and need for touch had a significant impact on purchase intention of personalized products. Our findings can be summarized as follows. First, Consumers' need for uniqueness was found to have positive effects(${\beta}=0.168$) on purchase intention of personalized products. The desire to differentiate themselves from others will be reflected in their personalized products. Therefore, consumers with a higher desire for uniqueness tend to be more willing to purchase personalized products. Second, consumer innovativeness was found to have positive effects(${\beta}=0.233$) on purchase intention of personalized products. Personalized shoes suggested in this study is a new type of personalized product that is manufactured by the latest information and communication technologies such as multi-function robots and 3D printing. Therefore, consumers seeking innovative new experiences are more willing to purchase personalized products. Third, need for touch was found to have positive effects(${\beta}=0.299$) on purchase intention of personalized products. In a smart factory environment, prosuming participation is given to consumers. If consumers participate in the product development process and reflect their requirements on the product, they are expected to increase their purchase intention by virtually satisfying the need for touch. Fourth, privacy concern was found to have no significantly related to purchase intention of personalized products. This is interpreted as a willingness to tolerate the risk of exposing personal information such as home address, telephone number, body size, and preference for consumers who feel highly useful in personalized products.

• Journal of Teachers' Pension
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• v.3
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• pp.69-105
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• 2018

저출산과 고령화 이슈는 우리사회의 경제적 문제뿐만 아니라 공적연금의 재정지속가능성 여부와도 맞물려 있다. 실제로 우리나라 모든 공적연금은 사회보험역설(social insurance paradox)이 지속되기 힘든 새로운 도전에 직면하였다. 즉, 재정지속가능성은 제도 내적 연금개혁 혹은 제도 외적 재정지원이 없다면 항시적 수지불균형 상태가 누적될 것으로 예측된다. 이에 정부는 직접 고용과 관련된 공무원연금과 군인연금에 대해서만 연금충당부채를 산출하도록 규정하고 있다. 발생주의회계를 채택한 국제회계기준(종업원급여)을 참조하여 연금충당부채 산출을 위한 연금회계준칙(2011.8.3. 제정; 2011.1.1. 시행) 그리고 '연금회계 평가 및 공시 지침(2011.8.3. 고시 : 이하 편의상 연금회계지침이라 함)'을 신설하였다. 사학연금에 적용성 여부 논의에 앞서, 이들의 산출방법상의 문제점을 먼저 살펴보았다. 첫째, 공적연금은 공통적으로 세대 간 합의에 의해 운영되는 사회계약에 해당하므로 제도의 연속성을 전제로 한다. 하지만 연금회계준칙 및 지침은 제도의 청산을 전제로 현재 가입자(연금 미수령자, 연금 수령자)에 대해서 연금충당부채를 산출하는 폐쇄형측정(closed group valuation)을 채택하고 있다. 즉, 폐쇄형은 제도의 연속성 속성을 반영하고 있지 못하고 있어 기본 전제와 모순된다. 둘째, 공무원연금과 군인연금은 이미 기금 소진(최소한의 유동성기금만 보유함)이 되었고 정부의 보전금에 의해 수지 균형이 유지되는 순수부과방식 체계로 전환되었다. 따라서 연금충당부채는 해당 적립기금의 과소 여부를 판정하는 재정상태 기준 값에 해당하므로 기금소진이 진행된 현 상황에서는 산출의 목적, 필요성을 찾기가 힘들다. 부언하면, 제도 외적 재정지원(보전금)에 의한 수지균형방식이라면 발생주의회계보다는 현금주의회계가 회계의 목적적합성이 높다. 마지막으로 연금충당부채 산출에 있어 가장 민감한 할인율 설정 권한을 기재부장관에게 위임한 내용은 산출의 객관성, 일관성을 확보하기 힘들다고 판단된다. 이를 해소하기 위한 방안으로 본 연구에서는 5년마다 실시하고 있는 장기재정계산에서 예측된 명목 기금투자수익률을 연도별로 적용할 것을 권고하고 있다. 현행 정부회계기준을 사학연금제도에 그대로 적용하기에는 상당한 무리가 있다. 그 이유와 공시방안에 대해 살펴본다. 현재 사학연금은 기금소진 이슈로부터 상당부분 벗어나기 위해 2015년 연금개혁을 단행한 바가 있고 이를 통해 상당기간 부분적립방식 체계가 유지될 것이다. 물론 제도 외적 재정지원은 사학연금법 제53조의7에서 정부지원의 가능성만을 열어 놓은 상태이므로 미래기금소진의 가능성은 상존한다고 볼 수 있다. 먼 미래에는 순수부과방식 체계로 전환될 개연성이 높다. 이러한 재정의 양면성을 본 연구에서는 이중재정방식(dual financing system)이라고 한다. 이러한 속성을 고려하여 연금충당부채(연금채무라는 표현이 적합할 것으로 사료됨)를 산출하고 공시하여야 한다. 그 주요 연구 결과는 다음과 같이 요약된다. 먼저 현행 부분적립방식의 재정상태 검증을 위해 연금채무를 산정할 필요성이 있다. 이를 위해 본 연구에서는 기발생주의(예측단위방식 적용)에 근거한 폐쇄형 측정I(제도 종료를 전제로 현 가입자의 잠재연금채무(IPD) 산출에 초점을 둠) 그리고 미래발생주의(가입연령방식 적용)에 근거한 폐쇄형 측정II(추가적으로 현 가입자의 일정기간 급여 및 기여 발생 허용)을 제안하고 있다. 이를 통해 미적립채무의 규모 그리고 이를 해소하기 위한 상각부담률을 산출할 수 있다. 최종적으로 미래 가입자들까지 포함하고 기금소진 가능성까지 고려하는 개방형측정(open group valuation)을 다루고 있다. 단, 본 연구에서는 공무원연금처럼 기금부족분에 대해서 향후 정부보전금이 있다는 가정 하에 공시 방법을 제시하고 있다. 요약하면, 현행 사학연금제도는 현재와 미래의 재정 양면성을 모두 고려하여 연금채무 및 미적립채무를 공시하여야 한다. 부언하면, 현재 부분적립방식 재정상태를 반영하는 연금채무는 발생주의회계를 적용하고 미래에 도래할 순수부과방식 재정상태는 현금주의회계를 적용할 것을 최종 결론으로 도출하고 있다. 마지막으로 본 연구의 한계는 정부보전금의 가능성에 대한 법률적 해석과 병행하여 책임준비금 범위의 안정적 확대를 전제로 한 공시 논의 그리고 보전금의 책임한도 범위에 따른 공시 논의 등은 다루고 있지 않다는 점이다. 이러한 논의 사항은 향후 연구과제로 두고자 한다.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.89-105
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• 2014

After emergence of Internet, social media with highly interactive Web 2.0 applications has provided very user friendly means for consumers and companies to communicate with each other. Users have routinely published contents involving their opinions and interests in social media such as blogs, forums, chatting rooms, and discussion boards, and the contents are released real-time in the Internet. For that reason, many researchers and marketers regard social media contents as the source of information for business analytics to develop business insights, and many studies have reported results on mining business intelligence from Social media content. In particular, opinion mining and sentiment analysis, as a technique to extract, classify, understand, and assess the opinions implicit in text contents, are frequently applied into social media content analysis because it emphasizes determining sentiment polarity and extracting authors' opinions. A number of frameworks, methods, techniques and tools have been presented by these researchers. However, we have found some weaknesses from their methods which are often technically complicated and are not sufficiently user-friendly for helping business decisions and planning. In this study, we attempted to formulate a more comprehensive and practical approach to conduct opinion mining with visual deliverables. First, we described the entire cycle of practical opinion mining using Social media content from the initial data gathering stage to the final presentation session. Our proposed approach to opinion mining consists of four phases: collecting, qualifying, analyzing, and visualizing. In the first phase, analysts have to choose target social media. Each target media requires different ways for analysts to gain access. There are open-API, searching tools, DB2DB interface, purchasing contents, and so son. Second phase is pre-processing to generate useful materials for meaningful analysis. If we do not remove garbage data, results of social media analysis will not provide meaningful and useful business insights. To clean social media data, natural language processing techniques should be applied. The next step is the opinion mining phase where the cleansed social media content set is to be analyzed. The qualified data set includes not only user-generated contents but also content identification information such as creation date, author name, user id, content id, hit counts, review or reply, favorite, etc. Depending on the purpose of the analysis, researchers or data analysts can select a suitable mining tool. Topic extraction and buzz analysis are usually related to market trends analysis, while sentiment analysis is utilized to conduct reputation analysis. There are also various applications, such as stock prediction, product recommendation, sales forecasting, and so on. The last phase is visualization and presentation of analysis results. The major focus and purpose of this phase are to explain results of analysis and help users to comprehend its meaning. Therefore, to the extent possible, deliverables from this phase should be made simple, clear and easy to understand, rather than complex and flashy. To illustrate our approach, we conducted a case study on a leading Korean instant noodle company. We targeted the leading company, NS Food, with 66.5% of market share; the firm has kept No. 1 position in the Korean "Ramen" business for several decades. We collected a total of 11,869 pieces of contents including blogs, forum contents and news articles. After collecting social media content data, we generated instant noodle business specific language resources for data manipulation and analysis using natural language processing. In addition, we tried to classify contents in more detail categories such as marketing features, environment, reputation, etc. In those phase, we used free ware software programs such as TM, KoNLP, ggplot2 and plyr packages in R project. As the result, we presented several useful visualization outputs like domain specific lexicons, volume and sentiment graphs, topic word cloud, heat maps, valence tree map, and other visualized images to provide vivid, full-colored examples using open library software packages of the R project. Business actors can quickly detect areas by a swift glance that are weak, strong, positive, negative, quiet or loud. Heat map is able to explain movement of sentiment or volume in categories and time matrix which shows density of color on time periods. Valence tree map, one of the most comprehensive and holistic visualization models, should be very helpful for analysts and decision makers to quickly understand the "big picture" business situation with a hierarchical structure since tree-map can present buzz volume and sentiment with a visualized result in a certain period. This case study offers real-world business insights from market sensing which would demonstrate to practical-minded business users how they can use these types of results for timely decision making in response to on-going changes in the market. We believe our approach can provide practical and reliable guide to opinion mining with visualized results that are immediately useful, not just in food industry but in other industries as well.

• Journal of Korean Home Economics Education Association
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• v.18 no.3 s.41
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• pp.1-22
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• 2006

The purpose of this study is that I should look for a desirous directions about home economics by studying the requirements and perception of the high school parents who have finished the course of home economics. It was about 600 parents whom I have searched Seoul-Pusan, Ganwon. Ghynggi province, Choongcheong-Gyungsang province, Cheonla and Jeju province of 600, I chose only 560 as apparently suitable research. The questions include 61 requirements about home economics and one which we never fail to keep among the contents, whenever possible and one about the perception of home economics aims 11 about the perception of home economics courses and management. The collections were analyzed frequency, percent, mean. standard deviation t-test by using SAS program. The followings is the summary result of studying of it. 1. All the boys and girls learning together about the Idea of healthy lives and desirous human formulation and knowledge together are higher. 2. Among the teaching purposes of home economics, the item of the scientific principle and knowledge for improvements of home life shows 15.7% below average value. 3. The recognition degree about the quality of home economics is highly related with the real life, and about the system. we recognize lacking in periods and contents of home economics field and about guiding content, accomplishment and application qualities are higher regardless of sex. 4. The important term which we should emphasize in the subject of home economics is family part. 5. Among the needs of home economic requirement in freshman, in the middle unit, their growth and development are higher than anything else, representing 4.11, and by contrast the basic principle and actuality is 3.70, which is lowest among them. 6. In the case of second grade requirement of home economics content for parents in the middle unit young man and consuming life is 4.09 highest. 7. In the case of 3rd grade requirement of economics contents in the middle unit the choice of coming direction and job ethics is highest 4.16, and preparing meals and evaluation is lowest 3.50.

• Journal of the Korean Society of Groundwater Environment
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• v.7 no.3
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• pp.103-115
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• 2000

The formation of brown-colored precipitates is one of the serious problems frequently encountered in the development and supply of groundwater in Korea, because by it the water exceeds the drinking water standard in terms of color. taste. turbidity and dissolved iron concentration and of often results in scaling problem within the water supplying system. In groundwaters from the Pajoo area, brown precipitates are typically formed in a few hours after pumping-out. In this paper we examine the process of the brown precipitates' formation using the equilibrium thermodynamic and kinetic approaches, in order to understand the origin and geochemical pathway of the generation of turbidity in groundwater. The results of this study are used to suggest not only the proper pumping technique to minimize the formation of precipitates but also the optimal design of water treatment methods to improve the water quality. The bed-rock groundwater in the Pajoo area belongs to the Ca-$HCO_3$type that was evolved through water/rock (gneiss) interaction. Based on SEM-EDS and XRD analyses, the precipitates are identified as an amorphous, Fe-bearing oxides or hydroxides. By the use of multi-step filtration with pore sizes of 6, 4, 1, 0.45 and 0.2 $\mu\textrm{m}$, the precipitates mostly fall in the colloidal size (1 to 0.45 $\mu\textrm{m}$) but are concentrated (about 81%) in the range of 1 to 6 $\mu\textrm{m}$in teams of mass (weight) distribution. Large amounts of dissolved iron were possibly originated from dissolution of clinochlore in cataclasite which contains high amounts of Fe (up to 3 wt.%). The calculation of saturation index (using a computer code PHREEQC), as well as the examination of pH-Eh stability relations, also indicate that the final precipitates are Fe-oxy-hydroxide that is formed by the change of water chemistry (mainly, oxidation) due to the exposure to oxygen during the pumping-out of Fe(II)-bearing, reduced groundwater. After pumping-out, the groundwater shows the progressive decreases of pH, DO and alkalinity with elapsed time. However, turbidity increases and then decreases with time. The decrease of dissolved Fe concentration as a function of elapsed time after pumping-out is expressed as a regression equation Fe(II)=10.l exp(-0.0009t). The oxidation reaction due to the influx of free oxygen during the pumping and storage of groundwater results in the formation of brown precipitates, which is dependent on time, $Po_2$and pH. In order to obtain drinkable water quality, therefore, the precipitates should be removed by filtering after the stepwise storage and aeration in tanks with sufficient volume for sufficient time. Particle size distribution data also suggest that step-wise filtration would be cost-effective. To minimize the scaling within wells, the continued (if possible) pumping within the optimum pumping rate is recommended because this technique will be most effective for minimizing the mixing between deep Fe(II)-rich water and shallow $O_2$-rich water. The simultaneous pumping of shallow $O_2$-rich water in different wells is also recommended.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.173-198
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• 2020

For a long time, many studies have been conducted on predicting the success of campaigns for customers in academia, and prediction models applying various techniques are still being studied. Recently, as campaign channels have been expanded in various ways due to the rapid revitalization of online, various types of campaigns are being carried out by companies at a level that cannot be compared to the past. However, customers tend to perceive it as spam as the fatigue of campaigns due to duplicate exposure increases. Also, from a corporate standpoint, there is a problem that the effectiveness of the campaign itself is decreasing, such as increasing the cost of investing in the campaign, which leads to the low actual campaign success rate. Accordingly, various studies are ongoing to improve the effectiveness of the campaign in practice. This campaign system has the ultimate purpose to increase the success rate of various campaigns by collecting and analyzing various data related to customers and using them for campaigns. In particular, recent attempts to make various predictions related to the response of campaigns using machine learning have been made. It is very important to select appropriate features due to the various features of campaign data. If all of the input data are used in the process of classifying a large amount of data, it takes a lot of learning time as the classification class expands, so the minimum input data set must be extracted and used from the entire data. In addition, when a trained model is generated by using too many features, prediction accuracy may be degraded due to overfitting or correlation between features. Therefore, in order to improve accuracy, a feature selection technique that removes features close to noise should be applied, and feature selection is a necessary process in order to analyze a high-dimensional data set. Among the greedy algorithms, SFS (Sequential Forward Selection), SBS (Sequential Backward Selection), SFFS (Sequential Floating Forward Selection), etc. are widely used as traditional feature selection techniques. It is also true that if there are many risks and many features, there is a limitation in that the performance for classification prediction is poor and it takes a lot of learning time. Therefore, in this study, we propose an improved feature selection algorithm to enhance the effectiveness of the existing campaign. The purpose of this study is to improve the existing SFFS sequential method in the process of searching for feature subsets that are the basis for improving machine learning model performance using statistical characteristics of the data to be processed in the campaign system. Through this, features that have a lot of influence on performance are first derived, features that have a negative effect are removed, and then the sequential method is applied to increase the efficiency for search performance and to apply an improved algorithm to enable generalized prediction. Through this, it was confirmed that the proposed model showed better search and prediction performance than the traditional greed algorithm. Compared with the original data set, greed algorithm, genetic algorithm (GA), and recursive feature elimination (RFE), the campaign success prediction was higher. In addition, when performing campaign success prediction, the improved feature selection algorithm was found to be helpful in analyzing and interpreting the prediction results by providing the importance of the derived features. This is important features such as age, customer rating, and sales, which were previously known statistically. Unlike the previous campaign planners, features such as the combined product name, average 3-month data consumption rate, and the last 3-month wireless data usage were unexpectedly selected as important features for the campaign response, which they rarely used to select campaign targets. It was confirmed that base attributes can also be very important features depending on the type of campaign. Through this, it is possible to analyze and understand the important characteristics of each campaign type.