• Journal of the Mineralogical Society of Korea
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• v.18 no.4 s.46
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• pp.277-288
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• 2005

Perlite, a hydrated volcanic glass, occurs mainly as a bed-like body, and is distributed intermittently along the unconformity surface between the Beomgockri Group and its lower formations, viz. Janggi Group. The perlite is intimately associated with surrounding pumiceous welded tuff and rhyodacites in space and time. Compared to the typical perlite, the perlite is rather silica-poor and impure, and thus, includes lots of phenocrysts and rock fragments. Nearly the perlite is compositionally rather close to a pitchstone than a perlite in water contents. Petrographic comparison between perlite and associated volcanic to volcaniclastic rocks indicates that pumiceous welded tuff and rhyodacite seem to be Protolith of the Perlite. A Zr/$TiO_{2}$-Nb/Y diagram and field occurrence of perlite and their protolithic rocks also conforms the above interpretation. Kn addition, remnant vesicles in perlite strongly reflect that the precursor of perlitic glass appeared to be pumice fragment as well as volcanic glass. The perlite was diagenetically formed by way of a pervasive water-rock interaction at the deposition of the Manghaesan Formation in lacustrine environment. During perlitization, $SiO_{2}$ and alkali tend to be consistently depleted. Preexisting system of the Beomgockri Group based on the perlite formation should be corrected, because the perlite was formed diagenetically without lateral persistence in its occurrence.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.8 no.4
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• pp.95-109
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• 2013

The practices and processes of HRM (Human Resource Management) for university faculty in Korea depend heavily on assessment of research and teaching rather than the UIC (University-Industry Cooperation) performance. In this regard, HRM of Korean universities is said to be far distant from UIC. Although policy initiatives by the Korean government, notably the MoE (Ministry of Education) have implemented in most universities, the desirable level of UIC could not be achieved yet. Moreover, the very notion of 'university' in Korea is much more to do with 'pure' education and research institution than with 'applied' and 'vocational' purpose. Considering upon HRM practices and organizational culture, for enhancing UIC in Korea, the government's policy should be linked to alter deep-rooted university culture. So the aims of the research are to describe the current state of HRM in Korean and foreign universities; to find out the critical factors of UIC in Korean universities; to analyze the gaps between university research and industrial commercialization based on a conceptual framework, the 'valley of the death'; and to recommend HRM policies fostering UIC for the MoE. For achieving these objectives, we deploy multiple methodologies, namely, in-depth interview, literature survey, and statistical data analysis with regard to UIC. Analyzing the data we have collected, the present research sheds light on all aspects of HRM processes and UICs. And the main policy implication is restricted to the Korean universities, even if we have collected and analyzed foreign universities, notably universities in the USA. The research findings are mainly two folds. Firstly, the HRM practices among Korean universities are very similar due to the legally institutionalized framework and the government's regulations. Secondly, the difficulties of UIC can be explained by notion of the 'valley of death' ways in which both parties of university and industry are looking for different purposes and directions. In order to overcome the gap in the valley of death, the HRM policy is better to be considered as leverage. Finally, the policy recommendations are as follows. Firstly, various kinds of UIC programs are able to enhance the performances of not only UIC, but also education and research outcome. Secondly, fostering organizational climate and culture for UIC, employing various UIC programs, and hiring industry-experienced faculty are all very important for enhancing the high performance of university. We recommend the HRM policies fostering UIC by means of indirect way rather than funding directly for university. The HRM policy of indirect support is more likely to have long-term effectiveness while the government's direct intervention to UIC will have likely short-term effectiveness as the previous policy initiatives have shown. The MEST's policy means of indirect support might vary from financial incentives to the universities practicing HRM for UIC voluntarily, to information disclosure for UIC. The benefits of the present research can be found in suggesting HRM policy for UIC, highlighting the significance of industry-experienced faculty for UIC, and providing statistical analysis and evidences of UIC in Korean universities.

• Korean Chemical Engineering Research
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• v.54 no.3
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• pp.394-403
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• 2016

$H_2$ production by chemical looping is an efficient method to convert hydrocarbon fuel into hydrogen with the simultaneous capture of concentrated $CO_2$. This process involves the use of an iron based oxygen carrier that transfers pure oxygen from oxidizing gases to fuels by alternating reduction and oxidation (redox) reactions. The enhanced reactivities of copper oxide doped iron-based oxygen carrier were reported, however, the fundamental understandings on the interaction between $Fe_2O_3$ and CuO are still lacking. In this study, we studied the effect of dopant of CuO to $Fe_2O_3/ZrO_2$ particle on the morphological changes and the associated reactivity using various methods such as SEM/EDX, XRD, BET, TPR, XPS, and TGA. It was found that copper oxide acted as a chemical promoter that change chemical environment in the iron based oxygen carrier as well as a structural promoter which inhibit the agglomeration. The enhanced reduction reactivity was mainly ascribed to the increase in concentration of $Fe^{2+}$ on the surface, resulting in formation of charge imbalance and oxygen vacancies. The CuO doped $Fe_2O_3/ZrO_2$ particle also showed the improved reactivity in the steam oxidation compared to $Fe_2O_3/ZrO_2$ particle probably due to acting as a structural promoter inhibiting the agglomeration of iron species.

• Journal of Gifted/Talented Education
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• v.11 no.3
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• pp.131-153
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• 2001

The importance of identifying gifted children during early childhood is becoming recognized. Nonetheless, most researchers preferred to study the primary and secondary levels where children are already and more clearly demonstrating what talents they have, and where more reliable predictions of gifted may be made. Comparatively lisle work has been done in this area. When we identify giftedness during early childhood, we have to consider the potential of the young children rather than on actual achievement. Giftedness during early childhood is still developing and less stable than that of older children and this prevents us from making firm and accurate predictions based on children's actual achievement. Dynamic assessment, based on Vygotsky's concept of the zone of proximal development(ZPD), suggests a new idea in the way the gifted young children are identified. In light of dynamic assessment, for identifying the potential giftedness of young children. we need to involve measuring both unassisted and assisted performance. Dynamic assessment usually consists of a test-intervene-retest format that focuses attention on the improvement in child performance when an adult provides mediated assistance on how to master the testing task. The advantages of the dynamic assessment are as follows: First, the dynamic assessment approach can provide a useful means for assessing young gifted child who have not demonstrated high ability on traditional identification method. Second, the dynamic assessment approach can assess the learning process of young children. Third, the dynamic assessment can lead an individualized education by the early identification of young gifted children. Fourth, the dynamic assessment can be a more accurate predictor of potential by linking diagnosis and instruction. Thus, it can make us provide an educational treatment effectively for young gifted children.

• Korean Journal of Ecology and Environment
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• v.49 no.3
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• pp.153-175
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• 2016

Daecheong Reservoir has suffered eutrophication and water-blooms by blue-green algae from initial impoundment, and algae alert system (AAS) was introduced in 1997. The purpose of this study was to investigate the effect of rainfall and hydrological factors in increase or decrease variability of green-tide and prolonged AAS, studied and analyzed the current situation of AAS has been operating for 19 years (1997~2015) in Daecheong Reservoir. The total issued number of AAS was 46 times, the most frequent period in August and September were 22 times (752 days) and 16 times (431 days), respectively, it accounted for 82.6%. Many number and frequency during this period were significantly associated with rainfall, various discharge and water level. Rainfall and hydrological events are associated with the rainy season of monsoon-Changma and the typhoon, it was concentrated in June~September, total rainfall in this period accounted for 69.9% of the annual rainfall. An increase in inflows was dependent on the intensity, frequency and the amount of rainfall. Accounted for 68.4% of the total annual inflow, it was a time when the most rapidly changing hydrological variability in the reservoir. The total outflow was closely related to rainfall, and compared the distinctive characteristics of hydropower generation and watergate-spillway discharge. In addition, the upreservoir zone of Daecheong Reservoir could be vulnerable to green-tide by regulating discharge of the upstream dam. The issue of AAS was strongly related to the with and without of watergate-spillway discharge. The watergate-spillway discharge had a total of 25 times, it was maximum 17 days from July to September in the year. And the opening times and each duration of the watergate were 1~4 times and the range of 3~37 days, respectively. When the watergate opened, the issue of AAS was maintained to 13 years and the movement of water bodies and green-tide was great about five times than that of non-open, had a profound effect on prolonged AAS within reservoir. In Daecheong Reservoir, Chusori (CHU) area of the So-ok Stream was still showing serious symptoms green-tide levels in the summer, but Janggye (JAN) waters of the main reservoir was pointed out that more important. AAS will be operated by an absolutely consider the rainfall and hydrological effects around the watergate-spillway discharge. The measures of green-tide will be included in the limnological studies more suited to the characteristics of the watershed and reservoir of the our country. Finally, from now on, we will prepare the systematic management and guidelines for vulnerable zone water-blooms that are the source within the reservoir before the monsoon rather than waiting for the arrival of green-tide on the operating stations of AAS.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.3
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• pp.215-231
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• 2020

Forest landscape models (FLMs) can be used to investigate the complex interactions of various ecological processes and patterns, which makes them useful tools to evaluate how environmental and anthropogenic variables can influence forest ecosystems. However, due to the large spatio-temporal scales in FLMs studies, parameterization and validation can be extremely challenging when applying to new study areas. To address this issue, we focused on the parameterization and application of a spatially explicit forest landscape model, LANDIS-II, to Mt. Gyebang, South Korea, with the use of the National Forest Inventory (NFI) and long-term ecological research (LTER) site data. In this study, we present the followings for the biomass succession extension of LANDIS-II: 1) species-specific and spatial parameters estimation for the biomass succession extension of LANDIS-II, 2) calibration, and 3) application and validation for Mt. Gyebang. For the biomass succession extension, we selected 14 tree species, and parameterized ecoregion map, initial community map, species growth characteristics. We produced ecoregion map using elevation, aspect, and topographic wetness index based on digital elevation model. Initial community map was produced based on NFI and sub-alpine survey data. Tree species growth parameters, such as aboveground net primary production and maximum aboveground biomass, were estimated from PnET-II model based on species physiological factors and environmental variables. Literature data were used to estimate species physiological factors, such as FolN, SLWmax, HalfSat, growing temperature, and shade tolerance. For calibration and validation purposes, we compared species-specific aboveground biomass of model outputs and NFI and sub-alpine survey data and calculated coefficient of determination (R²) and root mean square error (RMSE). The final model performed very well, with 0. 98 R² and 8. 9 RMSE. This study can serve as a foundation for the use of FLMs to other applications such as comparing alternative forest management scenarios and natural disturbance effects.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.8
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• pp.555-564
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• 2013

Innovative evolution in mobile devices along with recent spread of Tablet PCs and Smart Phones makes a new change not only in individual life but also in enterprise applications. Especially, in the case of medium-large mobile applications for large enterprises which generally takes more than 3 months of development periods, importance and complexity increase significantly. Generally Agile-methodology is used for a development process for the medium-large scale mobile applications, but some issues arise such as high dependency on skilled developers and lack of detail development directives. In this paper, S-MADP (Smart Mobile Application Development Process) is proposed to mitigate these issues. S-MADP is a service oriented development process extending a object-oriented development process, for medium-large scale mobile applications. S-MADP provides detail development directives for each activities during the entire process for defining services as server-based or client-based and providing the way of reuse of services. Also, in order to support various user interfaces, S-MADP provides detail UI development directives. To evaluate the performance of S-MADP, three mobile application development projects were conducted and the results were analyzed. The projects are 'TBS(TB Mobile Service) 3.0' in TB company, mobile app-store in TS company, and mobile groupware in TG group. As a result of the projects, S-MADP accounts for more detailed design information about 'Minimizing the use of resources', 'Service-based designing' and 'User interface optimized for mobile devices' which are needed to be largely considered for mobile application development environment when we compare with existing Agile-methodology. Therefore, it improves the usability, maintainability, efficiency of developed mobile applications. Through field tests, it is observed that S-MADP outperforms about 25% than a Agile-methodology in the aspect of the required man-month for developing a medium-large mobile application.

• 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.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.33-56
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• 2016

Many researchers have focused on developing bankruptcy prediction models using modeling techniques, such as statistical methods including multiple discriminant analysis (MDA) and logit analysis or artificial intelligence techniques containing artificial neural networks (ANN), decision trees, and support vector machines (SVM), to secure enhanced performance. Most of the bankruptcy prediction models in academic studies have used financial ratios as main input variables. The bankruptcy of firms is associated with firm's financial states and the external economic situation. However, the inclusion of qualitative information, such as the economic atmosphere, has not been actively discussed despite the fact that exploiting only financial ratios has some drawbacks. Accounting information, such as financial ratios, is based on past data, and it is usually determined one year before bankruptcy. Thus, a time lag exists between the point of closing financial statements and the point of credit evaluation. In addition, financial ratios do not contain environmental factors, such as external economic situations. Therefore, using only financial ratios may be insufficient in constructing a bankruptcy prediction model, because they essentially reflect past corporate internal accounting information while neglecting recent information. Thus, qualitative information must be added to the conventional bankruptcy prediction model to supplement accounting information. Due to the lack of an analytic mechanism for obtaining and processing qualitative information from various information sources, previous studies have only used qualitative information. However, recently, big data analytics, such as text mining techniques, have been drawing much attention in academia and industry, with an increasing amount of unstructured text data available on the web. A few previous studies have sought to adopt big data analytics in business prediction modeling. Nevertheless, the use of qualitative information on the web for business prediction modeling is still deemed to be in the primary stage, restricted to limited applications, such as stock prediction and movie revenue prediction applications. Thus, it is necessary to apply big data analytics techniques, such as text mining, to various business prediction problems, including credit risk evaluation. Analytic methods are required for processing qualitative information represented in unstructured text form due to the complexity of managing and processing unstructured text data. This study proposes a bankruptcy prediction model for Korean small- and medium-sized construction firms using both quantitative information, such as financial ratios, and qualitative information acquired from economic news articles. The performance of the proposed method depends on how well information types are transformed from qualitative into quantitative information that is suitable for incorporating into the bankruptcy prediction model. We employ big data analytics techniques, especially text mining, as a mechanism for processing qualitative information. The sentiment index is provided at the industry level by extracting from a large amount of text data to quantify the external economic atmosphere represented in the media. The proposed method involves keyword-based sentiment analysis using a domain-specific sentiment lexicon to extract sentiment from economic news articles. The generated sentiment lexicon is designed to represent sentiment for the construction business by considering the relationship between the occurring term and the actual situation with respect to the economic condition of the industry rather than the inherent semantics of the term. The experimental results proved that incorporating qualitative information based on big data analytics into the traditional bankruptcy prediction model based on accounting information is effective for enhancing the predictive performance. The sentiment variable extracted from economic news articles had an impact on corporate bankruptcy. In particular, a negative sentiment variable improved the accuracy of corporate bankruptcy prediction because the corporate bankruptcy of construction firms is sensitive to poor economic conditions. The bankruptcy prediction model using qualitative information based on big data analytics contributes to the field, in that it reflects not only relatively recent information but also environmental factors, such as external economic conditions.

• Korean Journal of Heritage: History & Science
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• v.54 no.4
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• pp.232-245
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• 2021

The present study is about a brand development strategy that utilizes Korean traditional patterns. The global culturenomics phenomenon confirms the value of the cultural aspects of design when a national brand is established. People succeed with their unique aesthetic sense and reinterpret it in a modern view, and this design acts as today's national brands. In this way, people used traditional patterns and original designs, along with regional characteristics and formative style, in developing their designs. However, due to recent changes in the global environment, modern people live in an "untact" world, and consumption culture shifted toward online marketing. In this environment, where one is isolated from social activities, there needs to be a strong image that can dramatically change the mood of one's home. I would like to re-examine the Dan-Chung pattern, whose painting depends on the aesthetic characteristics of architecture to protect the wooden members of the framework in traditional architecture. The pattern and color of Dan-Chung, coated in traditional architecture, differs by the type of construction used, which includes a palace, a Buddhist temple, and a Confucianism Dan Chung. The Geummoon pattern contains aesthetic factors to add solemnity to the Main Buddhist Halls, which contain Buddha. This is a new medium that continues the current traditions instead of remaining in the past. Among different Dan Chung patterns, Geummoon has magnificent decoration consisting of the highest grade materials and unique composition; therefore, it is suitable to be reinterpreted in modern terms. The same pattern can be interpreted in different ways with different colors, so there is a great aesthetic impression in the Geummoon pattern. The value of preservation for exploration and theoretical study of the traditional pattern is important, but recreating the pattern into modern formative art can present a new angle of view and national brand, bearing pride in our cultural assets. The study used multidimensional molding methods for realistic presentation after going through the two-dimensional design process. The significant value of Korean molding beauty which hangs onto the past will play a crucial role in establishing our national brand.