• Journal of Nutrition and Health
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• v.3 no.3
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• pp.129-135
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• 1970

From the previous studies, F-P-4 formula was found to be comparable to full fat dry milk in its nutritive value and feeding performance. However, an attempt was made in order to make sure whether or not any possibility might exist, by which further improvement of nutritive quality and simultaneous reduction of product costs may be achieved. Using F-P-4 as a control, modifications were made in new formulas, F-P-5, F-P-6 and F-P-7 by reducing FPC, eliminating yeast from the mixture, and by enriching with methionine as needed. In particular, F-P-7 is completely free of FPC, hydrogenated oil and yeast. Yet, levels of total protein and fat were kept equal to those of F-P-4 in all formulas. An animal feeding test for all formulas using 10 female rats per group for 8 weeks and an infant feeding trial for F-P-5 and F-P-6 with 5 of each female infants under age of one for one month were conducted along with F-P-4 as a control. Almost the same results were obtained with F-P-4, 5 and 6, but F-P-7 showed the lowest body weight gain. FER of F-P-5 and 6 was 0.20 as was with F-P-4, while that of F-P-7 was 0.16. Acceptability to infants was excellent; growth, appearance and biochemical data were normal. As an example F-P-4 packed in 0.04mm polyethylene bags was used for storage study at $25^{\circ}C$ and relative humidity of $65{\sim}85%$ for 8 months. Although viable bacterial counts and vitamin C contents were reduced, peroxide and TBA values were increased gradually during such storage. Since there are also significant changes in color and organoleptic quality, the expected shelf life under the given conditions is considered to be about 2 months and thus further works are needed both on the product and packaging in order to improve the storage stability. Either elimination of yeast form F-P-4, that is F-P-5, or partial replacement of FPC with methionine, that is F-P-6 may well reduce material costs about 10%. Considering blending process of ingredients, F-P-5 is thus found to be the best formula developed. While F-P-7 free of FPC is inferior in its nutritive quality than that of others, but significantly superior than of rice. Furthermore, the material cost of the product can be reduced about 20% from that of F-P-4. And thus this vegetable blend is considered to be useful as a low cost supplementary food mixture for growing children.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.10 no.5
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• pp.73-81
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• 2015

This research is designed to analyze the moderating effect of social capital between organizational slack and managerial practices for open innovation. After controlling the firm size, firm age, and environmental uncertainty, we test two hypotheses. First, we test the hypothesis that organizational slack has a positive effect on managerial practices for open innovation. Especially we focus on the managerial innovation and open innovation because recently managerial innovation and open innovation are more and more important. Second, we test the moderating role of social capital between organizational slack and managerial practices for open innovation. Because social capital is a kind of networking activity, we assume that social capital can contribute to managerial practices for open innovation through the networking activity. For this research, we administered the questionnaire surveys, and got the 250 effective data (companies) in Korea. Then we used the validity, reliability, correlation and multiple regression analysis by means of SPSS 18.0. As a result, we can find the two meaningful results. First, organizational slack, especially not absorbed slack but unabsorbed slack, has positive effect on managerial practices for open innovation. It is because absorbed slack such as excessive facilities, machines, or employees is not useful in managerial practices for open innovation. On the other hand, unabsorbed slack is useful in managerial practices for open innovation because unabsorbed slack such as excessive money or securities is very flexible and active. Taken together, the relationship between managerial practices for open innovation and unabsorbed slack is proven in terms of flexibility. Second, social capital has a moderating effect positively between organizational slack, especially not absorbed slack but unabsorbed slack, and managerial practices for open innovation. A prior study related to the relationship between managerial practices for open innovation and social capital doesn't exist yet, so this analysis result is very meaningful in academic respect. But this research has some limitations. First, this research is analyzed by limited region (Korea) and samples (250 companies), so more global regions and samples are recommended in the future. Second, we focus on managerial practices for open innovation in this paper, so the studies about technological practices for open innovation are recommended in the future.

• Korean Journal of Poultry Science
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• v.8 no.2
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• pp.91-114
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• 1981

This research was carried out from July to August, 1981, to analyse the true state of management, the skill of production, the structure of consciousness about the selected 294 poultry$.$farms, and to know about their bottlenecks and suggestions. The results obtained were as follows: 1. As for manager's ages, 31 to 45 years old men rate was 67.76%. upper 50years old men 15.94%. 2. 79.9% of farm omen possess attainments equal to or higher than those of upper secondary school graduates. 3. In poultry farming career of the investigated person, layer chicken industry was longer than broiler. 4. Occupations of farm owners before. doing poultry farming were farmers(32.35%), company employees, civil servants and soldiers, etc. 5. 58.62% of the person ran only poultry farming and the rest of them held the additional office of a farmer and a public officer. 6. There were many people who made a speciality of poultry farming holding additional jobs as dairy farming, cultivating crops, gardening, etc. 7. 42.35% of the person began poultry farming with under 1,000 layer chickens. And the rate of the ones with 1,000-2,000 broilers for the first time consisted 40.95% 8. Present breeding scale was that the rate of the farmers having 5,000-10,000 layer chickens was 37.13% and the ones having 5,000-10,000 broilers 38.32%. 9. The rate of the person supplying self-labor was 23.16%, the person having 1.3 employees 51.47% and the ones having under 20 employees 1.47%. 10. 74.26% of the poultry farms used very good quality of baby chicks. 11. The rate of the farms which used chicken feed making the point of the quality of it was 65.47% and the ones which bought it on credit 26.62%. 12. 65.47% bought feed directly from factories and 26.62% bought it from commercial agents. 13. The rate of the layer chicken farms paying for feed in cash was 19.39% and the broiler farms 32.74%. Most of the farms bought feed on credit by 30-60 days. 14. They bought the medicine for chicken from animal drug stores or veterinary hospitals. 15. The rate of the person posting up accounts roughly was 47.52% and that of the ones doing them detaily was 43.57%, 40% did not do them because of bother and only 21.22% had their own cashbooks.

• The Korean Journal of Financial Management
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• v.27 no.1
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• pp.181-208
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• 2010

In July 2007, Korean government has passed "The Capital Market and Financial Investment Services Act" to further develop the capital markets and the Act was to become effective in February 2009. Using a large sample of Korean firms, we have examined (i) the effect of underwriting activities on the firm value (bond spread) comparing commercial bank and investment bank, and (ii) the determinants of the firm value changes following underwriting activities of bank. To test our goal, we collected a wide range of samples of data for bond issuing activities executed by Korean firms listed on the Korea Stock Exchange (KSE) between 2000 and 2003. Our paper is distinguished from previous studies on this subject in a way that we analyzed the effect of corporate bond underwriting activities with regard to commercial banking and investment banking. Initially, we set up a hypothesis that "Certification View" and "Conflict-of-interest View" are major driving forces behind cross-firm differences in performance following bond issuance. We find that, in general, underwriting by investment bank (securities company) brings a positive effect on the firm value (spread between bench mark rate and bond issuing rate). This result indicates that firm value has been negatively affected by the bank underwriting and provides the evidence for "Conflict-of-interest View" in Korea. Our studies have also revealed that any change in firm value following bond issuance is positively related with the firm size (total asset), operating performance, liquidity (cashflow), and equity ownership by foreign investors. Overall, our results support the view that bank underwriting activities can play an important role in determining firm value and financial strategies under "The Capital Market and Financial Investment Services Act" of 2007.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.6
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• pp.1634-1647
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• 2007

"To invest or not to invest?" Most business leaders are frequently faced with this question on new and ongoing projects. The challenge lies in deciding what projects to choose, expand, contract, defer, or abandon. The project valuation tools used in this process are vital to making the right decisions. Traditional tools such as discounted cash flow (DCF)/net present value (NPV) assume a "fixed" path ahead, but real world projects face uncertainties, forcing us to change the path often. Comparing to other traditional valuation methods, the real options approach captures the flexibility inherent to investment decisions. The use of real options has gained wide acceptance among practitioners in a number of several industries during the last few decades. Even though the options are present in all types of business decisions, it is still not considered as a proper method of valuation in some industries. Mining has been comparably slow to adopt new valuation techniques over the years. The reason fur this is not entirely clear. One possible reason is the level and types of risks in mining. Not only are these risks high, but they are also more numerous and involve natural risks compared with other industries. That is why the purpose of this study is to deal with a more practical approach to project valuation, known as real options analysis in mining industry. This paper provides a case study approach to the copper mining industry using a real options analysis. It shows how companies can minimize investment risks, exercise flexibility in decision making and maximize returns.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.4
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• pp.163-174
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• 2017

This study analyzed how Korean firms' recapitalization affects their capital structure decision and firm value. Recapitalization was categorized into three groups according to the influence of the debt to equity ratio: debt ratio-increasing-recapitalization(capital reduction with refund, cash dividend), debt ratio-unchanging-recapitalization (capital reduction without refund, retirement of repurchased stocks), and debt ratio-decreasing-recapitalization(exercise the rights for convertible bonds, bond with stock warrants, exchangeable bonds and stock options). This article highlights how the relationship between the firms' recapitalization and the capital structure decision driven by the change in debt to equity ratio through the recapitalization should affect the firm value. The whole recapitalization sample used for this analysis comprised 22,814 enterprises listed on the Korea Exchange that were analyzed over the 16-year period from 2000 to 2015. To summarize the results of this Panel Data Analysis, firstly, when a firm executes debt ratio-increasing-recapitalization and debt ratio-decreasing-recapitalization at the period of t-1, the debt to equity ratio, which is increased or decreased, should affect the firm's debt capacity in the same period, then, at the period of t, the firm establishes a leverage policy to readjust the debt to equity ratio the other way around. These adjustments of debt-paying-ability from the leverage policy, including the capital structure decision, finally affect the firm value. Secondly, when a firm implements the debt ratio-unchanging-recapitalization in the period of t-1, the debt to equity ratio, which is neutral, should not affect the firm's capital structure decision. But, the firm value is positively affected by the influence of that recapitalization. Conclusively, we acknowledge a firm which carries out the recapitalization balances its capital structure to the optimal level of leverage and that the capital structure decision positively affects the corporate value.

• 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.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.111-131
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• 2015

There are only a handful number of research conducted on pattern analysis of corporate distress as compared with research for bankruptcy prediction. The few that exists mainly focus on audited firms because financial data collection is easier for these firms. But in reality, corporate financial distress is a far more common and critical phenomenon for non-audited firms which are mainly comprised of small and medium sized firms. The purpose of this paper is to classify non-audited firms under distress according to their financial ratio using data mining; Self-Organizing Map (SOM). SOM is a type of artificial neural network that is trained using unsupervised learning to produce a lower dimensional discretized representation of the input space of the training samples, called a map. SOM is different from other artificial neural networks as it applies competitive learning as opposed to error-correction learning such as backpropagation with gradient descent, and in the sense that it uses a neighborhood function to preserve the topological properties of the input space. It is one of the popular and successful clustering algorithm. In this study, we classify types of financial distress firms, specially, non-audited firms. In the empirical test, we collect 10 financial ratios of 100 non-audited firms under distress in 2004 for the previous two years (2002 and 2003). Using these financial ratios and the SOM algorithm, five distinct patterns were distinguished. In pattern 1, financial distress was very serious in almost all financial ratios. 12% of the firms are included in these patterns. In pattern 2, financial distress was weak in almost financial ratios. 14% of the firms are included in pattern 2. In pattern 3, growth ratio was the worst among all patterns. It is speculated that the firms of this pattern may be under distress due to severe competition in their industries. Approximately 30% of the firms fell into this group. In pattern 4, the growth ratio was higher than any other pattern but the cash ratio and profitability ratio were not at the level of the growth ratio. It is concluded that the firms of this pattern were under distress in pursuit of expanding their business. About 25% of the firms were in this pattern. Last, pattern 5 encompassed very solvent firms. Perhaps firms of this pattern were distressed due to a bad short-term strategic decision or due to problems with the enterpriser of the firms. Approximately 18% of the firms were under this pattern. This study has the academic and empirical contribution. In the perspectives of the academic contribution, non-audited companies that tend to be easily bankrupt and have the unstructured or easily manipulated financial data are classified by the data mining technology (Self-Organizing Map) rather than big sized audited firms that have the well prepared and reliable financial data. In the perspectives of the empirical one, even though the financial data of the non-audited firms are conducted to analyze, it is useful for find out the first order symptom of financial distress, which makes us to forecast the prediction of bankruptcy of the firms and to manage the early warning and alert signal. These are the academic and empirical contribution of this study. The limitation of this research is to analyze only 100 corporates due to the difficulty of collecting the financial data of the non-audited firms, which make us to be hard to proceed to the analysis by the category or size difference. Also, non-financial qualitative data is crucial for the analysis of bankruptcy. Thus, the non-financial qualitative factor is taken into account for the next study. This study sheds some light on the non-audited small and medium sized firms' distress prediction in the future.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.127-146
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• 2017

Services using artificial intelligence have begun to emerge in daily life. Artificial intelligence is applied to products in consumer electronics and communications such as artificial intelligence refrigerators and speakers. In the financial sector, using Kensho's artificial intelligence technology, the process of the stock trading system in Goldman Sachs was improved. For example, two stock traders could handle the work of 600 stock traders and the analytical work for 15 people for 4weeks could be processed in 5 minutes. Especially, big data analysis through machine learning among artificial intelligence fields is actively applied throughout the financial industry. The stock market analysis and investment modeling through machine learning theory are also actively studied. The limits of linearity problem existing in financial time series studies are overcome by using machine learning theory such as artificial intelligence prediction model. The study of quantitative financial data based on the past stock market-related numerical data is widely performed using artificial intelligence to forecast future movements of stock price or indices. Various other studies have been conducted to predict the future direction of the market or the stock price of companies by learning based on a large amount of text data such as various news and comments related to the stock market. Investing on commodity asset, one of alternative assets, is usually used for enhancing the stability and safety of traditional stock and bond asset portfolio. There are relatively few researches on the investment model about commodity asset than mainstream assets like equity and bond. Recently machine learning techniques are widely applied on financial world, especially on stock and bond investment model and it makes better trading model on this field and makes the change on the whole financial area. In this study we made investment model using Support Vector Machine among the machine learning models. There are some researches on commodity asset focusing on the price prediction of the specific commodity but it is hard to find the researches about investment model of commodity as asset allocation using machine learning model. We propose a method of forecasting four major commodity indices, portfolio made of commodity futures, and individual commodity futures, using SVM model. The four major commodity indices are Goldman Sachs Commodity Index(GSCI), Dow Jones UBS Commodity Index(DJUI), Thomson Reuters/Core Commodity CRB Index(TRCI), and Rogers International Commodity Index(RI). We selected each two individual futures among three sectors as energy, agriculture, and metals that are actively traded on CME market and have enough liquidity. They are Crude Oil, Natural Gas, Corn, Wheat, Gold and Silver Futures. We made the equally weighted portfolio with six commodity futures for comparing with other commodity indices. We set the 19 macroeconomic indicators including stock market indices, exports & imports trade data, labor market data, and composite leading indicators as the input data of the model because commodity asset is very closely related with the macroeconomic activities. They are 14 US economic indicators, two Chinese economic indicators and two Korean economic indicators. Data period is from January 1990 to May 2017. We set the former 195 monthly data as training data and the latter 125 monthly data as test data. In this study, we verified that the performance of the equally weighted commodity futures portfolio rebalanced by the SVM model is better than that of other commodity indices. The prediction accuracy of the model for the commodity indices does not exceed 50% regardless of the SVM kernel function. On the other hand, the prediction accuracy of equally weighted commodity futures portfolio is 53%. The prediction accuracy of the individual commodity futures model is better than that of commodity indices model especially in agriculture and metal sectors. The individual commodity futures portfolio excluding the energy sector has outperformed the three sectors covered by individual commodity futures portfolio. In order to verify the validity of the model, it is judged that the analysis results should be similar despite variations in data period. So we also examined the odd numbered year data as training data and the even numbered year data as test data and we confirmed that the analysis results are similar. As a result, when we allocate commodity assets to traditional portfolio composed of stock, bond, and cash, we can get more effective investment performance not by investing commodity indices but by investing commodity futures. Especially we can get better performance by rebalanced commodity futures portfolio designed by SVM model.

• Journal of agricultural medicine and community health
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• v.25 no.1
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• pp.65-83
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• 2000

To know the relationship of general characteristics with activities of daily living(ADL) and instrumental activities of daily living(IADL), we carried out the study on the elderies living in Chollabuk-Do area during 6 months, from June to December in 1999. Study subjects were 281, women and men were 195(69.6%) and 85(30.4%) respectively. Mean ages of women and men were 71.9 and 70.8 respectively. 81.1% elderies has disease and 18.9% were disease free. Disease prevalences of movement joint disease, others, circulatory disease, digestive disease, dental disease, respiratory disease were 50.1%, 25.0%, 10.5%, 9.4%, 8.5%, and 6.3% respectively. The percentages to the use of medical institution in recent were 40.0% for hospital, 16.8% for oriental hospital, 14.5% for public health center, 10.9% for drug store, 10.0% for others, and 7.8% for dental service. The percentages to the improvement of symptom after the use of medical institution were 62.3% for normal, 19.4% for improvement, and 18.2% for non-improvement. The percentages to the health situation were 37.1% for bad, 35.7% for good, and 27.1% for normal. Activities of daily living were 67.1% for 6 scores, 27.9% for 5 scores, 2.1% for 4 scores and ADL of women was lower than the men's. Instrumental activities of daily living were 50.4% for 5 scores, 19.3% for 3 scores, 12.1% for 4 scores and IADL of women was lower than the men's. Frequencies of disability in ADL were 28.9% for incontinence, 6.1% for bathing, 2.9% for meal, 2.5% for walking around house, 1.8% for toilet use, 1.4% for dressing and disability frequencies of women in 6 items of ADL were higher than the men's. The percentages of high, intermediate, low ADL in activities of daily living were 67.1%, 32.5%, 0.4% respectively and decrease of high ADL, increase of intermediate ADL were found with the increasing of age. Frequencies of disability in IADL were 42.9% for payment in and out, 31.8% for payment of written claim, 21.1% for shopping, 16.4% for preparation of meal, and 11.8% for use of bus. All items of women in IADL was higher than the men's but preparation of meal. The percentages of high, intermediate, low IADL in instrumental activities of daily living were 50.4%, 42.5%, 7.1% and decrease of high IADL, increase of intermediate IADL were found with the increasing of age. Mean of ADL with the general characteristics was 5.56 and 2 variables of level of education, health situation were statistically significant. Mean of IADL with the general characteristics was 3.76 and 8 variables of age, sex, level of education, occupation, presence of spouse, duty of living cost, health situation, category of ADL were statistically significant. With the result of stepwise regression, ADL was statistically related with religion, health situation and ADL was statistically related with level of education, living together with family, duty of living cost, health situation.