• Journal of Bio-Environment Control
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• v.20 no.4
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• pp.399-405
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• 2011

In this study, we evaluated the fruit quality indices and the incidence of physiological disorders of Korean new pear cultivar 'Whasan' to determine appropriate harvest time for exportation and to enhance storability and shelf-life of the fruits during simulated exportation and extending market environment under different temperature conditions. In the experiment of simulated exportation headed for North America including Canada and U.S.A., the fruits transported at $1^{\circ}C$ showed less weight loss than those of $5^{\circ}C$. Market temperature appeared as a key factor for keeping freshness of exported pear fruits rather than transportation temperature. Quality factors such as high flesh firmness and low incidence of fruit rot and physiological disorders including core breakdown and pithiness were attained at the fruits maintained at $18^{\circ}C$ when we compared with $25^{\circ}C$. The fruits of harvested early maturity at 135 day after full bloom showed 28.6 N of flesh firmness when the fruits stored at $1^{\circ}C$ of transportation and $18^{\circ}C$ of market temperature, while the fruits progressed $5^{\circ}C$ of transportation and $25^{\circ}C$ of market temperature dropped to 24.2 N during 30 days of shelf life. Also, a high incidences of physiological disorders and of fruit decay rates were obvious in the fruits distributed at $25^{\circ}C$ were observed approximately two times higher than the those of $18^{\circ}C$. Therefore, temperature management during marketing resulted as an important point for maintaining fruits quality in the process of pear fruit exportation.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.43 no.4
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• pp.349-355
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• 2017

Skin tone plays a key role in one of the determinant for facial attractiveness. Most female customers have an interest in choosing skin color and improving their skin tone and their needs have been contributed the expansion of cosmetic products in the market. Recently, cosmetic customers, who want bright skin, are also interested in healthy and lively-looking skin. However, there is no method to evaluate the skin tone with the complexion-describing adjectives (CDAs). Therefore, this study was conducted to find the ways to objectify and digitize the CDA. We obtained that quasi $L^*$ at dark skin is 65 and quasi $L^*$ at bright skin is 74 for standard images, which are selected from our data base. To match the following seven CDAs: pale, clear, radiant, lively, healthy, rosy and dull, the colors of both images were adjusted by 30 panels. The quasi $L^*$, $a^*$ and $b^*$ were converted from the RGB values of the manipulated images. The differences between the quasi $L^*$, $a^*$ and $b^*$ values of standard images and manipulated images reflecting each CDA were statistically significant (p < 0.05). However, there were no statistical significances between the $L^*$ values of dark and bright skin images that were modified in accordance with each CDA and there also were no statistical significances between the quasi $a^*$ values of dark and bright skin for pale and clear CDAs. From the statistical analysis, the CDAs were observed to form three groups: (i) pale-clear-radiant, (ii) lively-healthy-rosy and (iii) dull. We recognized that people have a similar opinion about perception of CDAs. Following our results of this study, we establish new standard method for sensibility evaluation which is difficult to carry out scientifically or objectively.

• KSBB Journal
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• v.23 no.6
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• pp.463-469
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• 2008

During the last decade, monacolin-K biosynthesized by fermentation of red yeast rice (Monascus strains) was proved to have an efficient cholesterol lowering capability, leading to rapid increase in the market demand for the functional red yeast rice. In this study, the production medium composition and components were optimized on a shake flask scale for monacolin-K production by Monascus pilosus (KCCM 60160). The effect of three different soybean flours on the monacolin-K production were studied in order to replace the nitrogen sources of basic production medium (yeast extract, malt extract and beef extract). Among the several experiments, the production medium with dietary soybean flour to replace a half of yeast extract was very good for monacolin-K production. Plackett-Burman experimental design was used to determine the key factors which are critical to produce the biological products in the fermentation. According to the result of Plackett-Burman experimental design, a second order response surface design was applied using yeast extract, beef extract and $(NH_4)_2SO_4$ as factors. Applying this model, the optimum concentration of the three variables was obtained. The maximum monacolin-K production (369.6 mg/L) predicted by model agrees well with the experimental value (418 mg/L) obtained from the experimental verification at the optimal medium. The yield of monacolin-K was increased by 67% as compared to that obtained with basic production medium in shake flasks.

• Journal of the Korean Geographical Society
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• v.29 no.2
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• pp.117-136
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• 1994

Contemporary global space economy is so dynamic that any one specific structural force can not explain the whole dynamic processes or trajectories of spatial industrial development. The major purpose of this paper is extending the traditional notion of industrial districts to functioning and development of new industrial districts with relation to the development of high technology industries. Several dynamic forces, which are dominated in new industrial districts in the modern space economy, are incorporated in the formation and dynamic aspects of new industrial districts. Even though key forces governing Marshallian industrial district are localization of small firms, division of labor between firms, constructive cooperation, and industrial atmosphere, Marshall points out a possibility of growing importance of large firms and non-local networks in the districts with changes of external environments. Some of Italian industrial districts can be regarded as Marshallian industrial districts in broader context, but the role of local authorities or institutions and local embeddedness seem to be more important in the Italian industrial districts. More critical implication form the review of Marshallian industrial districts and Italian industrial districts is that the industrial districts are not a static concept but a dynamic one: small firm based industrial districts can be regarded as only a specific feature evolved over time. Dynamic aspects of new industrial districts are resulting from coexistence of contrasting forces governing the functioning and formation of the districts in contemporary global space economy. The contrasting forces governing new industrial districts are coexistence of flexible and mass production systems, local and global networks, local and non-local embeddedness, and small and large firms. Because of these coexistence of contrasting forces, there are various types of new industrial districts. Nine types of industrial districts are identified based on local/non-local networks and intensity of networks in both suppliers and customers linkages. The different types of new industrial districts are described by differences in production systems, embeddedness, governance, cooperation and competition, and institutional factors. Out of nine types of industrial districts, four types - Marshallian; suppliers hub and spoke; customers hub and spoke; and satellite - are regarded as distinctive new industrial districts and four additional types - advanced hub and spoke types (suppliers and customers) and mature satellites (suppliers and customers) - can be evolved from the distinctive types and may be regarded as hybrid types. The last one - pioneering high technology industrial district - can be developed from the advanced hub and spoke types and this type is a most advanced modern industrial district in the era of globalization and high technology. The dynamic aspects of the districts are related with the coexistence of the contrasting forces in the contemporary global space economy. However, the development trajectory is not a natural one and not all the industrial districts can develop to the other hybrid types. Traditionally, localization of industries was developed by historical chances. In the process of high technology industrial development in contemporary global space economy, however, policy and strategies are critical for the formation and evolution of new industrial districts. It needs formation of supportive tissues of institutions for evolution of dyamic pattern of high technology related new industrial districts. Some of the original distinctive types of new industrial districts can not follow the path or trajectory suggested in this paper and may be declined without advancing, if there is no formation of supportive social structure or policy. Provision of information infrastructure and diffusion of an entrepreneurship through the positive supports of local government, public institutions, universities, trade associations and industry associations are important for the evolution of the dynamic new industrial districts. Reduction of sunk costs through the supports for training and retraining of skilled labor, the formation of flexible labor markets, and the establishment of cheap and available telecommunication networks is also regarded as a significant strategies for dynamic progress of new industrial districts in the era of high technology industrial development. In addition, development of intensive international networks in production, technology and information is important policy issue for formation and evolution of the new industrial districts which are related with high technology industrial development.

• Economic and Environmental Geology
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• v.44 no.3
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• pp.229-238
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• 2011

S-wave, which provides lithology and pore fluid information, plays a key role in estimating gas-hydrate saturation. In general, P- and S-wave velocities increase in the presence of gas-hydrate and the P-wave velocity decreases in the presence of free gas under the gas-hydrate layer. Whereas there are very small changes, even slightly increases, in the S-wave velocity in the free gas layer because S-wave is not affected by the pore fluid when propagating in the free gas layer. To verify those velocity properties of the BSR (bottom-simulating reflector) depth in the gas-hydrate prospect area in the Ulleung Basin, P- and S-wave velocity profiles were derived from multi-component ocean-bottom seismic data which were acquired by Korea Institute of Geoscience and Mineral Resources (KIGAM) in May 2009. OBS (ocean-bottom seismometer) hydrophone component data were modeled and inverted first through the traveltime inversion method to derive P-wave velocity and depth model of survey area. 2-D multichannel stacked data were incorporated as an initial model. Two horizontal geophone component data, then, were polarization filtered and rotated to make radial component section. Traveltimes of main S-wave events were picked and used for forward modeling incorporating Poisson's ratio. This modeling provides S-wave profiles and Poisson's ratio profiles at every OBS site. The results shows that P-wave velocities in most OBS sites decrease beneath the BSR, whereas S-wave velocities slightly increase. Consequently, Poisson's ratio decreased strongly beneath the BSR indicating the presence of a free gas layer under the BSR.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.161-177
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• 2015

With the rapid evolution of technology, the size, number, and the type of databases has increased concomitantly, so data mining approaches face many challenging applications from databases. One such application is discovery of fraud patterns from agricultural product wholesale transaction instances. The agricultural product wholesale market in Korea is huge, and vast numbers of transactions have been made every day. The demand for agricultural products continues to grow, and the use of electronic auction systems raises the efficiency of operations of wholesale market. Certainly, the number of unusual transactions is also assumed to be increased in proportion to the trading amount, where an unusual transaction is often the first sign of fraud. However, it is very difficult to identify and detect these transactions and the corresponding fraud occurred in agricultural product wholesale market because the types of fraud are more intelligent than ever before. The fraud can be detected by verifying the overall transaction records manually, but it requires significant amount of human resources, and ultimately is not a practical approach. Frauds also can be revealed by victim's report or complaint. But there are usually no victims in the agricultural product wholesale frauds because they are committed by collusion of an auction company and an intermediary wholesaler. Nevertheless, it is required to monitor transaction records continuously and to make an effort to prevent any fraud, because the fraud not only disturbs the fair trade order of the market but also reduces the credibility of the market rapidly. Applying data mining to such an environment is very useful since it can discover unknown fraud patterns or features from a large volume of transaction data properly. The objective of this research is to empirically investigate the factors necessary to detect fraud transactions in an agricultural product wholesale market by developing a data mining based fraud detection model. One of major frauds is the phantom transaction, which is a colluding transaction by the seller(auction company or forwarder) and buyer(intermediary wholesaler) to commit the fraud transaction. They pretend to fulfill the transaction by recording false data in the online transaction processing system without actually selling products, and the seller receives money from the buyer. This leads to the overstatement of sales performance and illegal money transfers, which reduces the credibility of market. This paper reviews the environment of wholesale market such as types of transactions, roles of participants of the market, and various types and characteristics of frauds, and introduces the whole process of developing the phantom transaction detection model. The process consists of the following 4 modules: (1) Data cleaning and standardization (2) Statistical data analysis such as distribution and correlation analysis, (3) Construction of classification model using decision-tree induction approach, (4) Verification of the model in terms of hit ratio. We collected real data from 6 associations of agricultural producers in metropolitan markets. Final model with a decision-tree induction approach revealed that monthly average trading price of item offered by forwarders is a key variable in detecting the phantom transaction. The verification procedure also confirmed the suitability of the results. However, even though the performance of the results of this research is satisfactory, sensitive issues are still remained for improving classification accuracy and conciseness of rules. One such issue is the robustness of data mining model. Data mining is very much data-oriented, so data mining models tend to be very sensitive to changes of data or situations. Thus, it is evident that this non-robustness of data mining model requires continuous remodeling as data or situation changes. We hope that this paper suggest valuable guideline to organizations and companies that consider introducing or constructing a fraud detection model in the future.

• Asia pacific journal of information systems
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• v.19 no.4
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• pp.47-75
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• 2009

Recently, researches on Management Information Systems (MIS) have laid out theoretical foundation and academic paradigms by introducing diverse theories, themes, and methodologies. Especially, academic paradigms of MIS encourage a user-friendly approach by developing the technologies from the users' perspectives, which reflects the existence of strong causal relationships between information systems and user's behavior. As in other areas in social science the use of structural equation modeling (SEM) has rapidly increased in recent years especially in the MIS area. The SEM technique is important because it provides powerful ways to address key IS research problems. It also has a unique ability to simultaneously examine a series of casual relationships while analyzing multiple independent and dependent variables all at the same time. In spite of providing many benefits to the MIS researchers, there are some potential pitfalls with the analytical technique. The research objective of this study is to provide some guidelines for an appropriate use of SEM based on the assessment of current practice of using SEM in the MIS research. This study focuses on several statistical issues related to the use of SEM in the MIS research. Selected articles are assessed in three parts through the meta analysis. The first part is related to the initial specification of theoretical model of interest. The second is about data screening prior to model estimation and testing. And the last part concerns estimation and testing of theoretical models based on empirical data. This study reviewed the use of SEM in 164 empirical research articles published in four major MIS journals in Korea (APJIS, ISR, JIS and JITAM) from 1991 to 2007. APJIS, ISR, JIS and JITAM accounted for 73, 17, 58, and 16 of the total number of applications, respectively. The number of published applications has been increased over time. LISREL was the most frequently used SEM software among MIS researchers (97 studies (59.15%)), followed by AMOS (45 studies (27.44%)). In the first part, regarding issues related to the initial specification of theoretical model of interest, all of the studies have used cross-sectional data. The studies that use cross-sectional data may be able to better explain their structural model as a set of relationships. Most of SEM studies, meanwhile, have employed. confirmatory-type analysis (146 articles (89%)). For the model specification issue about model formulation, 159 (96.9%) of the studies were the full structural equation model. For only 5 researches, SEM was used for the measurement model with a set of observed variables. The average sample size for all models was 365.41, with some models retaining a sample as small as 50 and as large as 500. The second part of the issue is related to data screening prior to model estimation and testing. Data screening is important for researchers particularly in defining how they deal with missing values. Overall, discussion of data screening was reported in 118 (71.95%) of the studies while there was no study discussing evidence of multivariate normality for the models. On the third part, issues related to the estimation and testing of theoretical models on empirical data, assessing model fit is one of most important issues because it provides adequate statistical power for research models. There were multiple fit indices used in the SEM applications. The test was reported in the most of studies (146 (89%)), whereas normed-test was reported less frequently (65 studies (39.64%)). It is important that normed- of 3 or lower is required for adequate model fit. The most popular model fit indices were GFI (109 (66.46%)), AGFI (84 (51.22%)), NFI (44 (47.56%)), RMR (42 (25.61%)), CFI (59 (35.98%)), RMSEA (62 (37.80)), and NNFI (48 (29.27%)). Regarding the test of construct validity, convergent validity has been examined in 109 studies (66.46%) and discriminant validity in 98 (59.76%). 81 studies (49.39%) have reported the average variance extracted (AVE). However, there was little discussion of direct (47 (28.66%)), indirect, and total effect in the SEM models. Based on these findings, we suggest general guidelines for the use of SEM and propose some recommendations on concerning issues of latent variables models, raw data, sample size, data screening, reporting parameter estimated, model fit statistics, multivariate normality, confirmatory factor analysis, reliabilities and the decomposition of effects.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.5
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• pp.79-96
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• 2021

Green infrastructure planning represents landscape planning measures to reduce particulate matter. This study aimed to derive factors that may be used in planning green infrastructure for particulate matter reduction using text mining techniques. A range of analyses were carried out by focusing on keywords such as 'particulate matter reduction plan' and 'green infrastructure planning elements'. The analyses included Term Frequency-Inverse Document Frequency (TF-IDF) analysis, centrality analysis, related word analysis, and topic modeling analysis. These analyses were carried out via text mining by collecting information on previous related research, policy reports, and laws. Initially, TF-IDF analysis results were used to classify major keywords relating to particulate matter and green infrastructure into three groups: (1) environmental issues (e.g., particulate matter, environment, carbon, and atmosphere), target spaces (e.g., urban, park, and local green space), and application methods (e.g., analysis, planning, evaluation, development, ecological aspect, policy management, technology, and resilience). Second, the centrality analysis results were found to be similar to those of TF-IDF; it was confirmed that the central connectors to the major keywords were 'Green New Deal' and 'Vacant land'. The results from the analysis of related words verified that planning green infrastructure for particulate matter reduction required planning forests and ventilation corridors. Additionally, moisture must be considered for microclimate control. It was also confirmed that utilizing vacant space, establishing mixed forests, introducing particulate matter reduction technology, and understanding the system may be important for the effective planning of green infrastructure. Topic analysis was used to classify the planning elements of green infrastructure based on ecological, technological, and social functions. The planning elements of ecological function were classified into morphological (e.g., urban forest, green space, wall greening) and functional aspects (e.g., climate control, carbon storage and absorption, provision of habitats, and biodiversity for wildlife). The planning elements of technical function were classified into various themes, including the disaster prevention functions of green infrastructure, buffer effects, stormwater management, water purification, and energy reduction. The planning elements of the social function were classified into themes such as community function, improving the health of users, and scenery improvement. These results suggest that green infrastructure planning for particulate matter reduction requires approaches related to key concepts, such as resilience and sustainability. In particular, there is a need to apply green infrastructure planning elements in order to reduce exposure to particulate matter.

• Journal of Navigation and Port Research
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• v.42 no.6
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• pp.507-517
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• 2018

The probability of T/S cargo volume to decrease is the most notable problem associated with inappropriate mix of terminal operators in Busan port. Other problems include, the deterioration of the national carriers' competitiveness from non-operation of own terminal, excessively high proportion of financial operators in the engagement of operation which may result in their passiveness in timely investment, additional cost burden to carriers' in the handling inter-terminal T/S cargo transportation and inefficiency in terminal operation by the multiplicity of operators proved to be same recognized as so through the analysis. Therefore, in order to provide solutions for the problems and to strengthen Busan port's competitiveness, this research suggests the restructuring of operators mix as follows. To achieve sustainable growth of T/S cargo, global carriers' participation in terminal operation should be of utmost priority. To enhance the operational efficiency, the operators should be integrated. Similarly, the integration of operators will play a key role in verifying that national carriers' own terminal operation is an important factor in raising its competence. Finally, BPA's active engagement in the entire operation of port is also critical in public-oriented operation of the port. Whereas in the interactive analysis by taking the merits of Busan port into consideraion, global carrier's participation in operation, integration of operators and BPA's engagement in operation proved to contribute to the increase of T/S cargo and strengthening of operational efficiencies of Busan port.

• Journal of Climate Change Research
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• v.2 no.1
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• pp.55-68
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• 2011

The Intergovernmental Panel on Climate Change(IPCC) has identified the causes of climate change and come up with measures to address it at the global level. Its key component of the work involves developing and assessing future climate change scenarios. The IPCC Expert Meeting in September 2007 identified a new greenhouse gas concentration scenario "Representative Concentration Pathway(RCP)" and established the framework and development schedules for Climate Modeling (CM), Integrated Assessment Modeling(IAM), Impact Adaptation Vulnerability(IAV) community for the fifth IPCC Assessment Reports while 130 researchers and users took part in. The CM community at the IPCC Expert Meeting in September 2008, agreed on a new set of coordinated climate model experiments, the phase five of the Coupled Model Intercomparison Project(CMIP5), which consists of more than 30 standardized experiment protocols for the shortterm and long-term time scales, in order to enhance understanding on climate change for the IPCC AR5 and to develop climate change scenarios and to address major issues raised at the IPCC AR4. Since early 2009, fourteen countries including the Korea have been carrying out CMIP5-related projects. Withe increasing interest on climate change, in 2009 the COdinated Regional Downscaling EXperiment(CORDEX) has been launched to generate regional and local level information on climate change. The National Institute of Meteorological Research(NIMR) under the Korea Meteorological Administration (KMA) has contributed to the IPCC AR4 by developing climate change scenarios based on IPCC SRES using ECHO-G and embarked on crafting national scenarios for climate change as well as RCP-based global ones by engaging in international projects such as CMIP5 and CORDEX. NIMR/KMA will make a contribution to drawing the IPCC AR5 and will develop national climate change scenarios reflecting geographical factors, local climate characteristics and user needs and provide them to national IAV and IAM communites to assess future regional climate impacts and take action.