• Journal of Global Scholars of Marketing Science
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• v.17 no.3
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• pp.1-19
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• 2007

1. Purpose Rural tourism is made by individuals with different characteristics, needs and wants. It is important to have information on the characteristics and preferences of the consumers of the different types of existing rural accommodation. The stud aims to identify the determinants of consumer preference by type of accommodations. 2. Methodology 2.1 Sample Data were collected from 1000 people by telephone survey with three-stage stratified random sampling in seven metropolitan areas in Korea. Respondents were chosen by sampling internal on telephone book published in 2006. We surveyed from four to ten-thirty 0'clock afternoon so as to systematic sampling considering respondents' life cycle. 2.2 Two-step cluster Analysis Our study is accomplished through the use of a two-step cluster method to classify the accommodation in a reduced number of groups, so that each group constitutes a type. This method had been suggested as appropriate in clustering large data sets with mixed attributes. The method is based on a distance measure that enables data with both continuous and categorical attributes to be clustered. This is derived from a probabilistic model in which the distance between two clusters in equivalent to the decrease in log-likelihood function as a result of merging. 2.3 Multinomial Logit Analysis The estimation of a Multionmial Logit model determines the characteristics of tourist who is most likely to opt for each type of accommodation. The Multinomial Logit model constitutes an appropriate framework to explore and explain choice process where the choice set consists of more than two alternatives. Due to its ease and quick estimation of parameters, the Multinomial Logit model has been used for many empirical studies of choice in tourism. 3. Findings The auto-clustering algorithm indicated that a five-cluster solution was the best model, because it minimized the BIC value and the change in them between adjacent numbers of clusters. The accommodation establishments can be classified into five types: Traditional House, Typical Farmhouse, Farmstay house for group Tour, Log Cabin for Family, and Log Cabin for Individuals. Group 1 (Traditional House) includes mainly the large accommodation establishments, i.e. those with ondoll style room providing meals and one shower room on family tourist, of original construction style house. Group 2 (Typical Farmhouse) encompasses accommodation establishments of Ondoll rooms and each bathroom providing meals. It includes, in other words, the tourist accommodations Known as "rural houses." Group 3 (Farmstay House for Group) has accommodation establishments of Ondoll rooms not providing meals and self cooking facilities, large room size over five persons. Group 4 (Log Cabin for Family) includes mainly the popular accommodation establishments, i.e. those with Ondoll style room with on shower room on family tourist, of western styled log house. While the accommodations in this group are not defined as regards type of construction, the group does include all the original Korean style construction, Finally, group 5 (Log Cabin for Individuals)includes those accommodations that are bedroom western styled wooden house with each bathroom. First Multinomial Logit model is estimated including all the explicative variables considered and taking accommodation group 2 as base alternative. The results show that the variables and the estimated values of the parameters for the model giving the probability of each of the five different types of accommodation available in rural tourism village in Korea, according to the socio-economic and trip related characteristics of the individuals. An initial observation of the analysis reveals that none of variables income, the number of journey, distance, and residential style of house is explicative in the choice of rural accommodation. The age and accompany variables are significant for accommodation establishment of group 1. The education and rural residential experience variables are significant for accommodation establishment of groups 4 and 5. The expenditure and marital status variables are significant for accommodation establishment of group 4. The gender and occupation variable are significant for accommodation establishment of group 3. The loyalty variable is significant for accommodation establishment of groups 3 and 4. The study indicates that significant differences exist among the individuals who choose each type of accommodation at a destination. From this investigation is evident that several profiles of tourists can be attracted by a rural destination according to the types of existing accommodations at this destination. Besides, the tourist profiles may be used as the basis for investment policy and promotion for each type of accommodation, making use in each case of the variables that indicate a greater likelihood of influencing the tourist choice of accommodation.

• Proceedings of the Materials Research Society of Korea Conference
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• 2011.05a
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• pp.5-5
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• 2011

The research and development of hybrid electric vehicle (HEV), plug-in hybrid electric vehicle (PHEV) and electric vehicle (EV) are intensified due to the energy crisis and environmental concerns. In order to meet the challenging requirements of powering HEV, PHEV and EV, the current lithium battery technology needs to be significantly improved in terms of the cost, safety, power and energy density, as well as the calendar and cycle life. One new technology being developed is the utilization of composite cathode by mixing two different types of insertion compounds [e.g., spinel $LiMn_2O_4$ and layered $LiMO_2$ (M=Ni, Co, and Mn)]. Recently, some studies on mixing two different types of cathode materials to make a composite cathode have been reported, which were aimed at reducing cost and improving self-discharge. Numata et al. reported that when stored in a sealed can together with electrolyte at $80^{\circ}C$ for 10 days, the concentrations of both HF and $Mn^{2+}$ were lower in the can containing $LiMn_2O_4$ blended with $LiNi_{0.8}Co_{0.2}O_2$ than that containing $LiMn_2O_4$ only. That reports clearly showed that this blending technique can prevent the decline in capacity caused by cycling or storage at elevated temperatures. However, not much work has been reported on the charge-discharge characteristics and related structural phase transitions for these composite cathodes. In this presentation, we will report our in situ x-ray diffraction studies on this mixed composite cathode material during charge-discharge cycling. The mixed cathodes were incorporated into in situ XRD cells with a Li foil anode, a Celgard separator, and a 1M $LiPF_6$ electrolyte in a 1 : 1 EC : DMC solvent (LP 30 from EM Industries, Inc.). For in situ XRD cell, Mylar windows were used as has been described in detail elsewhere. All of these in situ XRD spectra were collected on beam line X18A at National Synchrotron Light Source (NSLS) at Brookhaven National Laboratory using two different detectors. One is a conventional scintillation detector with data collection at 0.02 degree in two theta angle for each step. The other is a wide angle position sensitive detector (PSD). The wavelengths used were 1.1950 ${\AA}$ for the scintillation detector and 0.9999 A for the PSD. The newly installed PSD at beam line X18A of NSLS can collect XRD patterns as short as a few minutes covering $90^{\circ}$ of two theta angles simultaneously with good signal to noise ratio. It significantly reduced the data collection time for each scan, giving us a great advantage in studying the phase transition in real time. The two theta angles of all the XRD spectra presented in this paper have been recalculated and converted to corresponding angles for ${\lambda}=1.54\;{\AA}$, which is the wavelength of conventional x-ray tube source with Cu-$k{\alpha}$ radiation, for easy comparison with data in other literatures. The structural changes of the composite cathode made by mixing spinel $LiMn_2O_4$ and layered $Li-Ni_{1/3}Co_{1/3}Mn_{1/3}O_2$ in 1 : 1 wt% in both Li-half and Li-ion cells during charge/discharge are studied by in situ XRD. During the first charge up to ~5.2 V vs. $Li/Li^+$, the in situ XRD spectra for the composite cathode in the Li-half cell track the structural changes of each component. At the early stage of charge, the lithium extraction takes place in the $LiNi_{1/3}Co_{1/3}Mn_{1/3}O_2$ component only. When the cell voltage reaches at ~4.0 V vs. $Li/Li^+$, lithium extraction from the spinel $LiMn_2O_4$ component starts and becomes the major contributor for the cell capacity due to the higher rate capability of $LiMn_2O_4$. When the voltage passed 4.3 V, the major structural changes are from the $LiNi_{1/3}Co_{1/3}Mn_{1/3}O_2$ component, while the $LiMn_2O_4$ component is almost unchanged. In the Li-ion cell using a MCMB anode and a composite cathode cycled between 2.5 V and 4.2 V, the structural changes are dominated by the spinel $LiMn_2O_4$ component, with much less changes in the layered $LiNi_{1/3}Co_{1/3}Mn_{1/3}O_2$ component, comparing with the Li-half cell results. These results give us valuable information about the structural changes relating to the contributions of each individual component to the cell capacity at certain charge/discharge state, which are helpful in designing and optimizing the composite cathode using spinel- and layered-type materials for Li-ion battery research. More detailed discussion will be presented at the meeting.

• Asia Marketing Journal
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• v.10 no.2
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• pp.1-29
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• 2008

The objective of our study is to provide an exploratory model for forecasting sales take-off timing of a product in the context of multi-national markets. We evaluated the usefulness of key predictors such as multiple market information, product attributes, price, and sales for the forecasting of sales take-off timing by applying the suggested model to monthly sales data for PDP and LCD TV provided by a Korean electronics manufacturer. We have found some important results for global companies from the empirical analysis. Firstly, innovation coefficients obtained from sales data of a particular product in other markets can provide the most useful information on sales take-off timing of the product in a target market. However, imitation coefficients obtained from the sales data of a particular product in the target market and other markets are not useful for sales take-off timing of the product in the target market. Secondly, price and product attributes significantly influence on take-off timing. It is noteworthy that the ratio of the price of the target product to the average price of the market is more important than the price ofthe target product itself. Lastly, the cumulative sales of the product are still useful for the prediction of sales take-off timing. Our model outperformed the average model in terms of hit-rate.

• Journal of Life Science
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• v.30 no.1
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• pp.45-57
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• 2020

The prenatal period in livestock animals is crucial for meat production because net increase in the number of muscle fibers is finished before birth. However, there is no study on the growth and development mechanism of muscles in Hanwoo during this period. Therefore, to find candidate genes involved in muscle growth and development during this period in Hanwoo, mRNA expression data of longissimus in Hanwoo at 6 and 9 months post-conceptional age (MPA) were analyzed. We independently identified differentially expressed genes (DEGs) using DESeq2 and edgeR which are R software packages, and considered the overlaps of the results as final-DEGs to use in downstream analysis. The DEGs were classified into several modules using WGCNA then the modules' functions were analyzed to identify modules which involved in myogenesis and adipogenesis. Finally, the hub genes which had the highest WGCNA module membership among the top 10% genes of the STRING network maximal clique centrality were identified. 913(6 MPA specific DEGs) and 233(9 MPA specific DEGs) DEGs were figured out, and these were classified into five and two modules, respectively. Two of the identified modules'(one was in 6, and another was in 9 MPA specific modules) functions was found to be related to myogenesis and adipogenesis. One of the hub genes belonging to the 6 MPA specific module was axin1 (AXIN1) which is known as an inhibitor of Wnt signaling pathway, another was succinate-CoA ligase ADP-forming beta subunit (SUCLA2) which is known as a crucial component of citrate cycle.

• Korean Journal of Biological Psychiatry
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• v.12 no.1
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• pp.42-61
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• 2005

Objectives:The ginsenoside Rg1 and Rb1, the major components of ginseng saponin, have neurotrophic and neuroprotective effects including promotion of neuronal survival and proliferation, facilitation of learning and memory, and protection from ischemic injury and apoptosis. In this study, to investigate the molecular basis of the effects of ginsenoside on neuron, we analyzed gene expression profiling of SH-SY5Y human neuroblastoma cells treated with ginsenoside Rg1 or Rb1. Methods:SH-SY5Y cells were cultured and treated in triplicate with ginsenoside Rg1 or Rb1($80{\mu}M$, $40{\mu}M$, $20{\mu}M$). The proliferation rates of SH-SY5Y cells were determined by MTT assay and microscopic examination. We used a high density cDNA microarray chip that contained 8K human genes to analyze the gene expression profiles in SH-SY5Y cells. We analyzed using the Significance Analysis of Microarray(SAM) method for identifying genes on a microarray with statistically significant changes in expression. Results:Treatment of SH-SY5Y cells with $80{\mu}M$ ginsenoside Rg1 or Rb1 for 36h showed maximal proliferation compared with other concentrations or control. The results of the microarray experiment yielded 96 genes were upregulated(${\geq}$3 fold) in Rg1 treated cells and 40 genes were up-regulated(${\geq}$2 fold) in Rb1 treated cells. Treatment with ginsenoside Rg1 for 36h induced the expression of some genes associated with protein biosynthesis, regulation of transcription or translation, cell proliferation and growth, neurogenesis and differentiation, regulation of cell cycle, energy transport and others. Genes associated with neurogenesis and neuronal differentiation such as SCG10 and MLP increased in ginsenoside Rg1 treated cells, but such changes did not occur in Rb1-group. Conclusion:Our data provide novel insights into the gene mechanisms involved in possible role for ginsenoside Rg1 or Rb1 in mediating neuronal proliferation or cell viability, which can elicit distinct patterns of gene expression in neuronal cell line. Ginsenoside Rg1 have more broad and strong effects than ginsenoside Rb1 in gene expression and related cellular physiology. In addition, we suggest that SCG10 gene, which is known to be expressed in neuronal differentiation during development and neuronal regeneration during adulthood, may have a role in enhancement of activity dependent synaptic plasticity or cytoskeletal regulation following treatment of ginsenoside Rg1. Further, ginsenoside Rg1 may have a possible role in regeneration of injured neuron, promotion of memory, and prevention from aging or neuronal degeneration.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.155-175
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• 2017

As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.

• Journal of Korean Society of Forest Science
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• v.30 no.1
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• pp.30-41
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• 1976

The workers involved in breeding the growth of forest trees as well as in the efficiency of breeding work wish to find out the evidence that juvenile-mature correlations are high and that therefore early tests can be profitably employed in relation work. Juvenile-mature correlation denotes in general sense the interdependence between qualitative or quantitative data collected at different intervals during the life cycle. The correlation can also be obtained through the stem analysis if there is the possibility of cutting sample trees needed amount. In the present study, the juvenile-mature correlation coefficients are calculated from the stem analysis data. The every possible values of correlation coefficient between the 5-year age groups as to diameter, height, and volume growth of Pinus koraiensis S. et Z. and Larix leptolepis Gord. grown in the middle district of Korea were calculated. All the sample trees were cut from the man made plantation. The correlation coefficients are presented in tables and figures. In Pinus koraiensis S. et Z., the values of correlation coefficient between the successive age groups of heights growth are lower in general than those values pertaining to diameter growth. This tendencies are indifferent to site quality. In Larix leptolepis Gord., the values were lower thant these of Pinus koraiensis S.etZ. In any species and characteristics studied, the implications that at least 15 years growth character are related to 35 or 40 years size with reliability could be deduced. Through the relative ranking studies of diameter, height and volume growth of Larix leptolepis Gord., the large varieties among individual trees are appeared during 5-year to 35 year old.

• Korean Journal of Occupational Health Nursing
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• v.11 no.1
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• pp.13-30
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• 2002

Industrial shift workers feels suffer mental stresses which are caused by unfamiliar day sleep, noisy environment, sleeping disorder by bright light, unusual contacts with family, difficulty in meeting with friends or having formal social meetings and other social limitations such as the use of transportation. Such stresses influence health of the workers negatively. Thus the health promotion policy for shift workers should be made considering the workers' ways of living and shift work specially. This study attempted to provide basic information for development of the health promotion program for industrial shift workers by examining predictive factors influencing health promotion behaviors of those workers. In designing the study, three power generation plants located in Pusan and south Kyungsang province were randomly selected and therefrom 280 workers at central control, boiler and turbine rooms and environmental chemistry parts whose processes require shift works were sampled as subjects of the study. Data were collected two times from September 17 to October 8, 1999 using questionnaires with helps of safety and health managers of the plants. The questionnaires were distributed through mails or direct visits. Means for the study included the measurement tool of health promotion behavior provided by Park(1995), the tool of self-efficacy measurement by Suh(1995), the tool of internal locus of control measurement by Oh(1987), the measurement tool of perceived health state by Park(1995) and the tool of social support measurement by Paek(1995). The collected data were analyzed using SPSS program. Controlling factors of the subjects were evaluated in terms of frequency and percentage ratio Perceived factors and health promotion behaviors of the subjects were done so in terms of mean and standard deviation, and average mark and standard deviation, respectively. Relations between controlling and perceived factors were analyzed using t-test and ANOVA and those between perceived factors and the performance of health promotion behaviors, using Pearson's Correlation Coefficient. The performance of health promotion behaviors was tested using t-test, ANOVA and post multi-comparison (Scheffe test). Predictive factors of health promotion behavior were examined through the Stepwise Multiple Regression Analysis. Results of the study are summarized as follows. 1. The performance of health promotion behaviors by the subjects was evaluated as having the value of mean, $161.27{\pm}26.73$ points(min.:60, max.:240) and average mark, $2.68{\pm}0.44$ points(min.:1, max.:4). When the performance was analyzed according to related aspects, it showed the highest level in harmonious relation with average mark, $3.15{\pm}.56$ points, followed by hygienic life($3.03{\pm}.55$), self-realization ($2.84{\pm}.55$), emotional support($2.73{\pm}.61$), regular meals($2.71{\pm}.76$), self-control($2.62{\pm}.63$), health diet($2.62{\pm}.56$), rest and sleep($2.60{\pm}.59$), exercise and activity($2.53{\pm}.57$), diet control($2.52{\pm}.56$) and special health management($2.06{\pm}.65$). 2. In relations between perceived factors of the subjects(self-efficacy, internal locus of control, perceived health state) and the performance of health promotion behaviors, the performance was found having significantly pure relations with self-efficacy (r=.524, P=.000), internal locus of control (r=.225, P=.000) and perceived health state(r=.244, P=.000). The higher each evaluated point of the three factors was, the higher the performance was in level. 3. When relations between the controlling factors(demography-based social, health-related, job-related and human relations characteristics) and the performance of health promotion behaviors were analyzed, the performance showed significant differences according to marital status (t=2.09, P= .03), religion(F=3.93, P= .00) and participation in religious activities (F=8.10, P= .00) out of demography-based characteristics, medical examination results (F=7.20, P= .00) and methods of the collection of health knowledge and information(F=3.41, P= .01) and methods of desired health education(F=3.41, P= .01) out of health-related characteristics, detrimental factors perception(F=4.49, P= .01) and job satisfaction(F=8.41, P= .00) out of job-related characteristics and social support(F=14.69, P= .00) out of human relations characteristics. 4. The factor which is a variable predicting best the performance of health promotion behaviors by the subjects was the self-efficacy accounting for 27.4% of the prediction, followed by participation in religious activities, social support, job satisfaction, received health state and internal locus of control in order all of which totally account for 41.0%. In conclusion, the predictive factor which most influence the performance of health promotion behaviors by shift workers was self-efficacy. To promote the sense, therefore, it is necessary to develop the nursing intervention program considering predictive factors as variables identified in this study. Further industrial nurses should play their roles actively to help shift workers increase their capability of self-management of health.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.23-46
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• 2017

Although there have been cases of evaluating the value of specific companies or projects which have centralized on developed countries in North America and Europe from the early 2000s, the system and methodology for estimating the economic value of individual technologies or patents has been activated on and on. Of course, there exist several online systems that qualitatively evaluate the technology's grade or the patent rating of the technology to be evaluated, as in 'KTRS' of the KIBO and 'SMART 3.1' of the Korea Invention Promotion Association. However, a web-based technology valuation system, referred to as 'STAR-Value system' that calculates the quantitative values of the subject technology for various purposes such as business feasibility analysis, investment attraction, tax/litigation, etc., has been officially opened and recently spreading. In this study, we introduce the type of methodology and evaluation model, reference information supporting these theories, and how database associated are utilized, focusing various modules and frameworks embedded in STAR-Value system. In particular, there are six valuation methods, including the discounted cash flow method (DCF), which is a representative one based on the income approach that anticipates future economic income to be valued at present, and the relief-from-royalty method, which calculates the present value of royalties' where we consider the contribution of the subject technology towards the business value created as the royalty rate. We look at how models and related support information (technology life, corporate (business) financial information, discount rate, industrial technology factors, etc.) can be used and linked in a intelligent manner. Based on the classification of information such as International Patent Classification (IPC) or Korea Standard Industry Classification (KSIC) for technology to be evaluated, the STAR-Value system automatically returns meta data such as technology cycle time (TCT), sales growth rate and profitability data of similar company or industry sector, weighted average cost of capital (WACC), indices of industrial technology factors, etc., and apply adjustment factors to them, so that the result of technology value calculation has high reliability and objectivity. Furthermore, if the information on the potential market size of the target technology and the market share of the commercialization subject refers to data-driven information, or if the estimated value range of similar technologies by industry sector is provided from the evaluation cases which are already completed and accumulated in database, the STAR-Value is anticipated that it will enable to present highly accurate value range in real time by intelligently linking various support modules. Including the explanation of the various valuation models and relevant primary variables as presented in this paper, the STAR-Value system intends to utilize more systematically and in a data-driven way by supporting the optimal model selection guideline module, intelligent technology value range reasoning module, and similar company selection based market share prediction module, etc. In addition, the research on the development and intelligence of the web-based STAR-Value system is significant in that it widely spread the web-based system that can be used in the validation and application to practices of the theoretical feasibility of the technology valuation field, and it is expected that it could be utilized in various fields of technology commercialization.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.5
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• pp.728-733
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• 2010

This study was carried out to estimate carbon emission using LCA and to establish LCI database of potato production system. Potato production system was categorized into the fall season potato and the spring season potato according to potato cropping type. The results of collecting data for establishing LCI D/B showed that input of fertilizer for fall season potato production was more than that for spring season potato production. Input of pesticide for spring season potato production was much more than that for fall season potato production. The value of field direct emission ($CO_2$, $CH_4$, $N_2O$) were 2.17E-02 kg $kg^{-1}$ for spring season potato and 2.47E-02 kg $kg^{-1}$ for fall season potato, respectively. The result of LCI analysis focussed on the greenhouse gas (GHG), it was observed that carbon footprint values were 8.38E-01 kg $CO_2$-eq. $kg^{-1}$ for spring season potato and 8.10E-01 kg $CO_2$-eq. $kg^{-1}$ for fall season potato; especially for 90% and 6% of $CO_2$ emission from fertilizer and potato production, respectively. $N_2O$ was emitted from the process of N fertilizer production (76%) and potato production (23%). It was observed that characterization of values of GWP were 8.38E-01 kg $CO_2$-eq. $kg^{-1}$ for spring season potato and 8.10E-01 kg $CO_2$-eq. $kg^{-1}$ for fall season potato.