• Korean Journal of Food Science and Technology
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• v.31 no.2
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• pp.465-474
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• 1999

RNase activity of Saccharomyces cerevisiae ATCC 7754 was investigated to obtain strains with high ribonucleic acid (RNA) content. The yeast strain contained two RNase activities; an acidic RNase with a optima of pH $3{\sim}4$ and an alkaline RNase with a optima pH 9. The acidic RNase activity was inhibited by $0.08\;M\;HgCl_{2}$ most drastically. The alkaline RNase activity was inhibited by 2.0 M NaCl or KCl, while enhanced by addition of $0.05\;M\;CaCl_{2},\;0.02\;M\;ZnSO_{4},\;or\;0.008\;M\;HgCl_{2}$. Various mutants of Saccharomyces cerevisiae ATCC 7754 were isolated by ethylmethane sulfonate (EMS) treatment or $\gamma$-ray/ultra violet irradiation. Among the mutants that were sensitive to high concentration of KCl which inhibits alkaline RNase, B24 was selected for high RNA content per culture volume. Growth characteristics of the mutant were comparable to those of the mother strain with optimum growth at pH $4.5{\sim}5.5$. The mutant accumulated higher content of RNA than the mother strain when glucose was used as the carbon source. However, both growth rate and total RNA content of the mutant were higher in molasses medium than in glucose medium. RNA content of the mutant increased rapidly during the early stage of growth, and then decreased gradually until the culture reached stationary phase by a fed-batch culture in a 5 L jar fermenter. Maximal cell harvest and the final RNA content using the mutant B24 were 69.6 g/L culture broth and 19.8 g/100 g of the dry cell while those using the mother strain were 68 g/L culture broth and 16.1 g/100 g of dry cell, respectively.

• Korean journal of communication and information
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• v.43
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• pp.173-208
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• 2008

This study analyses the business performance according to the business diversification of Korean mass media enterprises from year 2003 to 2006. The conclusions drawn which could be divided into five main parts are the followings: First, newspaper companies pursue unrelated diversification in various industrial areas, in order to gain maximum profit while broadcasting companies exert themselves to provide better service by diversifying the major contents. Second, overall the interviewed companies display a constant decline in profit gained from their major business area thus establishing strategies to broaden their focus on diversification of any sort. Third, the researcher completed group analysis in regard of diversification measure resulting in division of three groups. The group which had the most immense diversification range gained the highest ROE, the lowest ROE volatility, and lesser probability of risk taking. The analysis adresses the companies broadening their business areas by researching and focusing on diversification are relatively stable in terms of the profit they gain. Fourth, the middle level group in terms of sales scale, debts, enterprise history, major share rate and high ROE group carry out diversification progressively. The sales scale affects positively to diversification, while the major share rate affects negatively to diversification. Fifth, in accordance to the research, diversification overall contributes to obtainance of successful outcome. Since there was not an immense amount of studies to be referred in the media area, the researcher interviewed and did panel discussion with numerous strategists and managers who are in charge of diversification of media companies. However, collection of only 4 years of data limits the research to be considered to be a generalized study, and does not reflect time gap between business diversification and business performance. Development is required in future studies to be established regarding the media companies' specificity different to other industries, classified the media companies into media types, and consider the time gap in the diversification activities and business performance.

• Cartoon and Animation Studies
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• s.37
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• pp.413-437
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• 2014

As the public Japanese art, print can be said to have started from Ukiyo-e print of Edo period(江戶時代, 1603~1867). Ukiyo-e(浮世繪) print, which 3 persons jointly produce, henceforth has gradually declined since the meiji period(明治時代, 1868~1912) due to the development of new print technique and introduction of western art. Since then, during the daiso period(大正時代 1912~1926), creative print movement grew up. Creative print is, differently from Ukiyo-e print, to be produced by one person, from the original picture to print, focusing on creating the artist's own work by being the main agent of the work. During before and after 1900s, print was evaluated low in Japan, compared to western painting, sculpture, etc. Nevertheless, the facts that several Japanese print artists received awards from international exhibits since 1950s became a big topic internationally, which became an opportunity to hold Tokyo International Print Biennale in 1957 in Japan, the first international art festival. From then on, print was recognized as an art genre while new recognition on it was gradually accepted also in Japan. In 1970, a controversy on it arose, while the characteristic of print as a medium of modern art became strong, accordingly, a controversy on it arose. However, in 1980, it firmly established itself as an art genre by overcoming the crisis through various efforts in the dimension of print artists and university education. Since then, print artists who produce new works with completeness by applying traditional technique and modern expression mode emerged, and until now Japanese modern print art is highly recognized by the world through the continuous overseas activities, research on print art, and cultivation of young print artists. This research looked back on the historical process when Japanese modern print art was created, which represents Asia, and investigated the cause that it could have win an international fame.

• Journal of Korea Water Resources Association
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• v.46 no.4
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• pp.401-412
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• 2013

Water footprint of a product and service is the volume of freshwater used to produce the product, measured in the life cycle or over the full supply chain. Since water footprint assessment helps us to understand how human activities and products relate to water scarcity and pollution, it can contribute to seek a sustainable way of water use in the consumption perspective. For the introduction of WFP scheme, it is indispensable to construct water inventory/accounting for the assessment, but there is no database in Korea to cover all industry sectors. Therefore, the aim of the study is to develop water footprint inventory within a nation at 403 industrial sectors using Input-Output Analysis. Water uses in the agricultural sector account for 79% of total water, and industrial sector have higher indirect water at most sectors, which is accounting for 82%. Most of the crop water is consumptive and direct water except rice. The greatest water use in the agricultural sectors is in rice paddy followed by aquaculture and fruit production, but the greatest water use intensity was not in the rice. The greatest water use intensity was 103,263 $m^3$/million KRW for other inedible crop production, which was attributed to the low economic value of the product with great water consumption in the cultivation. The next was timber tract followed by iron ores, raw timber, aquaculture, water supply and miscellaneous cereals like corn and other edible crops in terms of total water use intensity. In holistic view, water management considering indirect water in the industrial sector, i.e. supply chain management in the whole life cycle, is important to increase water use efficiency, since more than 56% of total water was indirect water by humanity. It is expected that the water use intensity data can be used for a water inventory to estimate water footprint of a product for the introduction of water footprint scheme in Korea.

• KDI Journal of Economic Policy
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• v.12 no.2
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• pp.51-79
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• 1990

Research on technical efficiency, an important dimension of market performance, had received little attention until recently by most industrial organization empiricists, the reason being that traditional microeconomic theory simply assumed away any form of inefficiency in production. Recently, however, an increasing number of research efforts have been conducted to answer questions such as: To what extent do technical ineffciencies exist in the production activities of firms and plants? What are the factors accounting for the level of inefficiency found and those explaining the interindustry difference in technical inefficiency? Are there any significant international differences in the levels of technical efficiency and, if so, how can we reconcile these results with the observed pattern of international trade, etc? As the first in a series of studies on the technical efficiency of Korea's manufacturing industries, this paper attempts to answer some of these questions. Since the estimation of technical efficiency requires the use of plant-level data for each of the five-digit KSIC industries available from the Census of Manufactures, one may consture the findings of this paper as empirical evidence of technical efficiency in Korea's manufacturing industries at the most disaggregated level. We start by clarifying the relationship among the various concepts of efficiency-allocative effciency, factor-price efficiency, technical efficiency, Leibenstein's X-efficiency, and scale efficiency. It then becomes clear that unless certain ceteris paribus assumptions are satisfied, our estimates of technical inefficiency are in fact related to factor price inefficiency as well. The empirical model employed is, what is called, a stochastic frontier production function which divides the stochastic term into two different components-one with a symmetric distribution for pure white noise and the other for technical inefficiency with an asymmetric distribution. A translog production function is assumed for the functional relationship between inputs and output, and was estimated by the corrected ordinary least squares method. The second and third sample moments of the regression residuals are then used to yield estimates of four different types of measures for technical (in) efficiency. The entire range of manufacturing industries can be divided into two groups, depending on whether or not the distribution of estimated regression residuals allows a successful estimation of technical efficiency. The regression equation employing value added as the dependent variable gives a greater number of "successful" industries than the one using gross output. The correlation among estimates of the different measures of efficiency appears to be high, while the estimates of efficiency based on different regression equations seem almost uncorrelated. Thus, in the subsequent analysis of the determinants of interindustry variations in technical efficiency, the choice of the regression equation in the previous stage will affect the outcome significantly.

• Asia pacific journal of information systems
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• v.20 no.2
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• pp.63-86
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• 2010

Personalized services directly and indirectly acquire personal data, in part, to provide customers with higher-value services that are specifically context-relevant (such as place and time). Information technologies continue to mature and develop, providing greatly improved performance. Sensory networks and intelligent software can now obtain context data, and that is the cornerstone for providing personalized, context-specific services. Yet, the danger of overflowing personal information is increasing because the data retrieved by the sensors usually contains privacy information. Various technical characteristics of context-aware applications have more troubling implications for information privacy. In parallel with increasing use of context for service personalization, information privacy concerns have also increased such as an unrestricted availability of context information. Those privacy concerns are consistently regarded as a critical issue facing context-aware personalized service success. The entire field of information privacy is growing as an important area of research, with many new definitions and terminologies, because of a need for a better understanding of information privacy concepts. Especially, it requires that the factors of information privacy should be revised according to the characteristics of new technologies. However, previous information privacy factors of context-aware applications have at least two shortcomings. First, there has been little overview of the technology characteristics of context-aware computing. Existing studies have only focused on a small subset of the technical characteristics of context-aware computing. Therefore, there has not been a mutually exclusive set of factors that uniquely and completely describe information privacy on context-aware applications. Second, user survey has been widely used to identify factors of information privacy in most studies despite the limitation of users' knowledge and experiences about context-aware computing technology. To date, since context-aware services have not been widely deployed on a commercial scale yet, only very few people have prior experiences with context-aware personalized services. It is difficult to build users' knowledge about context-aware technology even by increasing their understanding in various ways: scenarios, pictures, flash animation, etc. Nevertheless, conducting a survey, assuming that the participants have sufficient experience or understanding about the technologies shown in the survey, may not be absolutely valid. Moreover, some surveys are based solely on simplifying and hence unrealistic assumptions (e.g., they only consider location information as a context data). A better understanding of information privacy concern in context-aware personalized services is highly needed. Hence, the purpose of this paper is to identify a generic set of factors for elemental information privacy concern in context-aware personalized services and to develop a rank-order list of information privacy concern factors. We consider overall technology characteristics to establish a mutually exclusive set of factors. A Delphi survey, a rigorous data collection method, was deployed to obtain a reliable opinion from the experts and to produce a rank-order list. It, therefore, lends itself well to obtaining a set of universal factors of information privacy concern and its priority. An international panel of researchers and practitioners who have the expertise in privacy and context-aware system fields were involved in our research. Delphi rounds formatting will faithfully follow the procedure for the Delphi study proposed by Okoli and Pawlowski. This will involve three general rounds: (1) brainstorming for important factors; (2) narrowing down the original list to the most important ones; and (3) ranking the list of important factors. For this round only, experts were treated as individuals, not panels. Adapted from Okoli and Pawlowski, we outlined the process of administrating the study. We performed three rounds. In the first and second rounds of the Delphi questionnaire, we gathered a set of exclusive factors for information privacy concern in context-aware personalized services. The respondents were asked to provide at least five main factors for the most appropriate understanding of the information privacy concern in the first round. To do so, some of the main factors found in the literature were presented to the participants. The second round of the questionnaire discussed the main factor provided in the first round, fleshed out with relevant sub-factors. Respondents were then requested to evaluate each sub factor's suitability against the corresponding main factors to determine the final sub-factors from the candidate factors. The sub-factors were found from the literature survey. Final factors selected by over 50% of experts. In the third round, a list of factors with corresponding questions was provided, and the respondents were requested to assess the importance of each main factor and its corresponding sub factors. Finally, we calculated the mean rank of each item to make a final result. While analyzing the data, we focused on group consensus rather than individual insistence. To do so, a concordance analysis, which measures the consistency of the experts' responses over successive rounds of the Delphi, was adopted during the survey process. As a result, experts reported that context data collection and high identifiable level of identical data are the most important factor in the main factors and sub factors, respectively. Additional important sub-factors included diverse types of context data collected, tracking and recording functionalities, and embedded and disappeared sensor devices. The average score of each factor is very useful for future context-aware personalized service development in the view of the information privacy. The final factors have the following differences comparing to those proposed in other studies. First, the concern factors differ from existing studies, which are based on privacy issues that may occur during the lifecycle of acquired user information. However, our study helped to clarify these sometimes vague issues by determining which privacy concern issues are viable based on specific technical characteristics in context-aware personalized services. Since a context-aware service differs in its technical characteristics compared to other services, we selected specific characteristics that had a higher potential to increase user's privacy concerns. Secondly, this study considered privacy issues in terms of service delivery and display that were almost overlooked in existing studies by introducing IPOS as the factor division. Lastly, in each factor, it correlated the level of importance with professionals' opinions as to what extent users have privacy concerns. The reason that it did not select the traditional method questionnaire at that time is that context-aware personalized service considered the absolute lack in understanding and experience of users with new technology. For understanding users' privacy concerns, professionals in the Delphi questionnaire process selected context data collection, tracking and recording, and sensory network as the most important factors among technological characteristics of context-aware personalized services. In the creation of a context-aware personalized services, this study demonstrates the importance and relevance of determining an optimal methodology, and which technologies and in what sequence are needed, to acquire what types of users' context information. Most studies focus on which services and systems should be provided and developed by utilizing context information on the supposition, along with the development of context-aware technology. However, the results in this study show that, in terms of users' privacy, it is necessary to pay greater attention to the activities that acquire context information. To inspect the results in the evaluation of sub factor, additional studies would be necessary for approaches on reducing users' privacy concerns toward technological characteristics such as highly identifiable level of identical data, diverse types of context data collected, tracking and recording functionality, embedded and disappearing sensor devices. The factor ranked the next highest level of importance after input is a context-aware service delivery that is related to output. The results show that delivery and display showing services to users in a context-aware personalized services toward the anywhere-anytime-any device concept have been regarded as even more important than in previous computing environment. Considering the concern factors to develop context aware personalized services will help to increase service success rate and hopefully user acceptance for those services. Our future work will be to adopt these factors for qualifying context aware service development projects such as u-city development projects in terms of service quality and hence user acceptance.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.41 no.4
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• pp.40-48
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• 2023

This study is part of a foundational research effort aimed at developing a suitability index for breeding grounds related to avian activities along the domestic South and West coasts, including islands. Focus Group Interviews (FGI) and Analytic Hierarchy Process (AHP) analyses were conducted. The results are as follows. First, as a result of determining the value of the suitability of coastal bird breeding sites, the 'Natural Value(0.763)' was higher than the 'Artificial Value(0.237)'. Other artificial values were identified as sub-ranked except for 'Protected Areas' to ensure continuous integrity of breeding spaces. Second, as a result of re-establishing the 25 evaluation items classified in the two-time FGI as higher concepts, nine natural values and five artificial values were finally selected as a total of 14. Third, the results of the mid-classification evaluation of the importance of the suitability of coastal bird breeding sites were identified in the order of 'Ecological Value(0.392)', 'Topographic Value(0.251)', 'Passive Interference(0.124)', 'Geological Value(0.120)', and 'Active Interference(0.113)'. Fourth, the results of the priority of evaluation items of coastal bird breeding sites were in the order of 'Vegetation Distribution (0.187)', 'Area of Mudflats(0.118)', 'Presence or Absence of Mudflats(0.092)', 'Appearance of Natural Enemies(0.087)', 'Protected Areas(0.08)', 'Island Area (0.069)', 'Over-Breeding devastation(0.064)', 'Soil Composition Ratio(0.056)', 'Distance from Land(0.054)', 'Ocean farm area (0.045)', 'Cultivated land area(0.041)', 'Cultivation behavior(0.038)', 'Angle of the Surface(0.036)', and 'Land Use(0.033)'. It is judged that the weighting result value of the evaluation items derived in this study can be used for priority evaluation focusing on the coastal bird breeding area space. However, it seems that the correlation with the unique habitat suitability of bird individuals needs to be supplemented, and spatial analysis research incorporating species-specific characteristics will be left as a future task.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.73-85
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• 2013

Nowadays, in today's information society, the importance of the knowledge service using the information to creative value is getting higher day by day. In addition, depending on the development of IT technology, it is ease to collect and use information. Also, many companies actively use customer information to marketing in a variety of industries. Into the 21st century, companies have been actively using the culture arts to manage corporate image and marketing closely linked to their commercial interests. But, it is difficult that companies attract or maintain consumer's interest through their technology. For that reason, it is trend to perform cultural activities for tool of differentiation over many firms. Many firms used the customer's experience to new marketing strategy in order to effectively respond to competitive market. Accordingly, it is emerging rapidly that the necessity of personalized service to provide a new experience for people based on the personal profile information that contains the characteristics of the individual. Like this, personalized service using customer's individual profile information such as language, symbols, behavior, and emotions is very important today. Through this, we will be able to judge interaction between people and content and to maximize customer's experience and satisfaction. There are various relative works provide customer-centered service. Specially, emotion recognition research is emerging recently. Existing researches experienced emotion recognition using mostly bio-signal. Most of researches are voice and face studies that have great emotional changes. However, there are several difficulties to predict people's emotion caused by limitation of equipment and service environments. So, in this paper, we develop emotion prediction model based on vision-based interface to overcome existing limitations. Emotion recognition research based on people's gesture and posture has been processed by several researchers. This paper developed a model that recognizes people's emotional states through body gesture and posture using difference image method. And we found optimization validation model for four kinds of emotions' prediction. A proposed model purposed to automatically determine and predict 4 human emotions (Sadness, Surprise, Joy, and Disgust). To build up the model, event booth was installed in the KOCCA's lobby and we provided some proper stimulative movie to collect their body gesture and posture as the change of emotions. And then, we extracted body movements using difference image method. And we revised people data to build proposed model through neural network. The proposed model for emotion prediction used 3 type time-frame sets (20 frames, 30 frames, and 40 frames). And then, we adopted the model which has best performance compared with other models.' Before build three kinds of models, the entire 97 data set were divided into three data sets of learning, test, and validation set. The proposed model for emotion prediction was constructed using artificial neural network. In this paper, we used the back-propagation algorithm as a learning method, and set learning rate to 10%, momentum rate to 10%. The sigmoid function was used as the transform function. And we designed a three-layer perceptron neural network with one hidden layer and four output nodes. Based on the test data set, the learning for this research model was stopped when it reaches 50000 after reaching the minimum error in order to explore the point of learning. We finally processed each model's accuracy and found best model to predict each emotions. The result showed prediction accuracy 100% from sadness, and 96% from joy prediction in 20 frames set model. And 88% from surprise, and 98% from disgust in 30 frames set model. The findings of our research are expected to be useful to provide effective algorithm for personalized service in various industries such as advertisement, exhibition, performance, etc.

• Journal of Music and Human Behavior
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• v.1 no.1
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• pp.11-32
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• 2004

According to Edwin Gordon(1987, 1997, 2003), music aptitude is a product of interaction of innate potential and early environmental experiences. He referred to music aptitude of children up to nine years of age as developmental music aptitude which fluctuates due to musical environment. Music aptitude stabilizes at age nine, and the music aptitude after age nine is called "stabilized music aptitude". This research is to examine Gorden's hypothesis that the younger a child receives music education, the higher music aptitude. Also, this research is to experiment the effect of Audiation activities developed in Audie Music Curriculum on music aptitude. The researcher and another Audie teacher as a co-teacher guided children together for 30 minutes once a week. The pedagogy guidelines for informal guidance in music learning theory were kept throughout the classes. Also, Audie's teaching method which had been developed for Korean Kindergarten educational environment was also applied. Five-year-old subjects in Experimental group 1 experienced the Audie Music Curriculum of one year; five-year-old subjects in Experimental group 2 experienced it for two years. Primary Measures of Music Audiation was administered three times during their last year of Kindergarten. Subjects in the Control groups, one examined at the beginning and the other at the end of their last year in Kindergarten, received no Audie instruction. There was no significant difference in tonal aptitude, but there was significant difference in rhythmic aptitude(p< .05) among the experiemental groups. Because both Experimental groups showed statistical significance (p< .001) in the music aptitude increase during their academic years, the significant differences of the year-end music aptitude between control group and experimental groups were the expected result.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.111-126
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• 2020

Most industries have recently become aware of the importance of customer lifetime value as they are exposed to a competitive environment. As a result, preventing customers from churn is becoming a more important business issue than securing new customers. This is because maintaining churn customers is far more economical than securing new customers, and in fact, the acquisition cost of new customers is known to be five to six times higher than the maintenance cost of churn customers. Also, Companies that effectively prevent customer churn and improve customer retention rates are known to have a positive effect on not only increasing the company's profitability but also improving its brand image by improving customer satisfaction. Predicting customer churn, which had been conducted as a sub-research area for CRM, has recently become more important as a big data-based performance marketing theme due to the development of business machine learning technology. Until now, research on customer churn prediction has been carried out actively in such sectors as the mobile telecommunication industry, the financial industry, the distribution industry, and the game industry, which are highly competitive and urgent to manage churn. In addition, These churn prediction studies were focused on improving the performance of the churn prediction model itself, such as simply comparing the performance of various models, exploring features that are effective in forecasting departures, or developing new ensemble techniques, and were limited in terms of practical utilization because most studies considered the entire customer group as a group and developed a predictive model. As such, the main purpose of the existing related research was to improve the performance of the predictive model itself, and there was a relatively lack of research to improve the overall customer churn prediction process. In fact, customers in the business have different behavior characteristics due to heterogeneous transaction patterns, and the resulting churn rate is different, so it is unreasonable to assume the entire customer as a single customer group. Therefore, it is desirable to segment customers according to customer classification criteria, such as loyalty, and to operate an appropriate churn prediction model individually, in order to carry out effective customer churn predictions in heterogeneous industries. Of course, in some studies, there are studies in which customers are subdivided using clustering techniques and applied a churn prediction model for individual customer groups. Although this process of predicting churn can produce better predictions than a single predict model for the entire customer population, there is still room for improvement in that clustering is a mechanical, exploratory grouping technique that calculates distances based on inputs and does not reflect the strategic intent of an entity such as loyalties. This study proposes a segment-based customer departure prediction process (CCP/2DL: Customer Churn Prediction based on Two-Dimensional Loyalty segmentation) based on two-dimensional customer loyalty, assuming that successful customer churn management can be better done through improvements in the overall process than through the performance of the model itself. CCP/2DL is a series of churn prediction processes that segment two-way, quantitative and qualitative loyalty-based customer, conduct secondary grouping of customer segments according to churn patterns, and then independently apply heterogeneous churn prediction models for each churn pattern group. Performance comparisons were performed with the most commonly applied the General churn prediction process and the Clustering-based churn prediction process to assess the relative excellence of the proposed churn prediction process. The General churn prediction process used in this study refers to the process of predicting a single group of customers simply intended to be predicted as a machine learning model, using the most commonly used churn predicting method. And the Clustering-based churn prediction process is a method of first using clustering techniques to segment customers and implement a churn prediction model for each individual group. In cooperation with a global NGO, the proposed CCP/2DL performance showed better performance than other methodologies for predicting churn. This churn prediction process is not only effective in predicting churn, but can also be a strategic basis for obtaining a variety of customer observations and carrying out other related performance marketing activities.