• Journal of Nutrition and Health
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• v.24 no.3
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• pp.230-242
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• 1991

This research was conducted on the 10 take-out boxed-lunches commercially prepared in the department stores. chain stores. and the public railroad trains in Korea. Sampling was conducted from February 1990 to March 1990. Nutritive values and sodium contents of the 10 boxed-lunch samples are summarized as follows : 1) The average weight(percentage) of the cooked rice and the side dishes were 304.6g(49.4) and 312.4(506%), respectively. The weight of these samples were significantly heavier than that of Japanese style boxed-lunches. 2) The average number of the side dishes was 12. The average numbers of food items classified by the five food groups were 6.1 in protein food group, 0.3 in calcium food group. 6.0 in vitamin and mineral food group. 1.5 in carbohydrate food group, and 1.5 in oil and fat food group. 3) They contained on the average 840.7kcal of energy, 38.9g of protein, 22.7g of fat, 120.4g of carbohydrate. 300.8mg of calcium. 410.8mg of phosphours, 6.61 mg of iron. 219.8 R.E. of vitamin A, 0.46mg of thiamin, 0.67mg of riboflavin, 10.5mg of niacin, 27.5mg of ascorbic acid. Thus. except vitamin t the content of all the nutrients were higher than the value of 1/3 of the RDA for adults. 4) The high priced group(group 2) had more protein, calcuim. iron and niacin contents than the cheaper group(group 1). Probably, it's because the group 2 had more animal foods than the group 1. 5) The average energy content per unit price(100 won) was 37.3kcal and the average protein content per unit price(100 won) was 1.64g. Korena style boxed-lunches had higher energy and protein contents per unit price than Japanese style, and the group 1 higher than the group 2. 6) The average energy Proportions of Protein, carbohydrate. and fat were 18.3%, 57.4%, and 24.3%, respectively. These proportions are good enough. 7) Frequency of cooking methods for the side dishes were found in the decreasing order : pan-frying, frying, braising, seasoning, kimchi, grilling, pickling, stir-frying, steaming and fermenting. Generally simple cooking methods were used, thus the menus were lack or varieties. 8) Frequency of colors for the side dishes were found in the decreasing order : red, brown. yellow, green, black, white. Too much red pepper was used. 9) The average capacity of the containers for the staples and the side dishes were 468.1ml and 590.6ml, respectively. And the containers could not keep the food items well seperated. 10) The average contensts of sodium and salt were 2.287mg and 5.76g, in the range of 1, 398mg to 3, 489mg and 3.53g to 8.80g, respectively. These are much higher values than the recommended amount of salt.

• 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 Animal Science and Technology
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• v.46 no.4
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• pp.645-658
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• 2004

To investigate the effects of conjugated linoleic acid added diet feeding on CLA accumulation and quality characteristics of manufactured press ham using CLA accwnulated pork loin meat. The CLA used to add in diet was chemically synthesized by alkaline isomerization method with com oil. Pigs were divided into 5 treatment groups(4 pigs/group) and subjected to one of five treatment diets(0, 1.25% CLA for 2weeks, 2.5% CLA for 2weeks, 1.25% CLA for 4weeks and 2.5% CLA for 4weeks, CLA diets; total fed diets) before slaughter. Pork loin were collected from the animals(110kg body weight) slaughtering at the commercial slaughter house. Manufacture press ham using CLA accumulated pork loin meat were vacuum packaged and then stored during 1, 7, 14, 21 and 28 days at 4$^{\circ}C$. Samples were analyzed for general compositions, physico-chemical properties(pH, color, shear force value), TBARS. pH value of CLA treatment(T4) was increased significantly than that of oontrol(P<0.05). pH of control and CLA treatments were increased significantly as the storage period passed(P< 0.05). Crude fat content of CLA treatment groups was significantly higher than the control pork (P<0.05). Meat color(CIE $L^*$, $a^*$$b^*$

• Asia pacific journal of information systems
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• v.24 no.4
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• pp.443-472
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• 2014

To survive in the global competitive environment, enterprise should be able to solve various problems and find the optimal solution effectively. The big-data is being perceived as a tool for solving enterprise problems effectively and improve competitiveness with its' various problem solving and advanced predictive capabilities. Due to its remarkable performance, the implementation of big data systems has been increased through many enterprises around the world. Currently the big-data is called the 'crude oil' of the 21st century and is expected to provide competitive superiority. The reason why the big data is in the limelight is because while the conventional IT technology has been falling behind much in its possibility level, the big data has gone beyond the technological possibility and has the advantage of being utilized to create new values such as business optimization and new business creation through analysis of big data. Since the big data has been introduced too hastily without considering the strategic value deduction and achievement obtained through the big data, however, there are difficulties in the strategic value deduction and data utilization that can be gained through big data. According to the survey result of 1,800 IT professionals from 18 countries world wide, the percentage of the corporation where the big data is being utilized well was only 28%, and many of them responded that they are having difficulties in strategic value deduction and operation through big data. The strategic value should be deducted and environment phases like corporate internal and external related regulations and systems should be considered in order to introduce big data, but these factors were not well being reflected. The cause of the failure turned out to be that the big data was introduced by way of the IT trend and surrounding environment, but it was introduced hastily in the situation where the introduction condition was not well arranged. The strategic value which can be obtained through big data should be clearly comprehended and systematic environment analysis is very important about applicability in order to introduce successful big data, but since the corporations are considering only partial achievements and technological phases that can be obtained through big data, the successful introduction is not being made. Previous study shows that most of big data researches are focused on big data concept, cases, and practical suggestions without empirical study. The purpose of this study is provide the theoretically and practically useful implementation framework and strategies of big data systems with conducting comprehensive literature review, finding influencing factors for successful big data systems implementation, and analysing empirical models. To do this, the elements which can affect the introduction intention of big data were deducted by reviewing the information system's successful factors, strategic value perception factors, considering factors for the information system introduction environment and big data related literature in order to comprehend the effect factors when the corporations introduce big data and structured questionnaire was developed. After that, the questionnaire and the statistical analysis were performed with the people in charge of the big data inside the corporations as objects. According to the statistical analysis, it was shown that the strategic value perception factor and the inside-industry environmental factors affected positively the introduction intention of big data. The theoretical, practical and political implications deducted from the study result is as follows. The frist theoretical implication is that this study has proposed theoretically effect factors which affect the introduction intention of big data by reviewing the strategic value perception and environmental factors and big data related precedent studies and proposed the variables and measurement items which were analyzed empirically and verified. This study has meaning in that it has measured the influence of each variable on the introduction intention by verifying the relationship between the independent variables and the dependent variables through structural equation model. Second, this study has defined the independent variable(strategic value perception, environment), dependent variable(introduction intention) and regulatory variable(type of business and corporate size) about big data introduction intention and has arranged theoretical base in studying big data related field empirically afterwards by developing measurement items which has obtained credibility and validity. Third, by verifying the strategic value perception factors and the significance about environmental factors proposed in the conventional precedent studies, this study will be able to give aid to the afterwards empirical study about effect factors on big data introduction. The operational implications are as follows. First, this study has arranged the empirical study base about big data field by investigating the cause and effect relationship about the influence of the strategic value perception factor and environmental factor on the introduction intention and proposing the measurement items which has obtained the justice, credibility and validity etc. Second, this study has proposed the study result that the strategic value perception factor affects positively the big data introduction intention and it has meaning in that the importance of the strategic value perception has been presented. Third, the study has proposed that the corporation which introduces big data should consider the big data introduction through precise analysis about industry's internal environment. Fourth, this study has proposed the point that the size and type of business of the corresponding corporation should be considered in introducing the big data by presenting the difference of the effect factors of big data introduction depending on the size and type of business of the corporation. The political implications are as follows. First, variety of utilization of big data is needed. The strategic value that big data has can be accessed in various ways in the product, service field, productivity field, decision making field etc and can be utilized in all the business fields based on that, but the parts that main domestic corporations are considering are limited to some parts of the products and service fields. Accordingly, in introducing big data, reviewing the phase about utilization in detail and design the big data system in a form which can maximize the utilization rate will be necessary. Second, the study is proposing the burden of the cost of the system introduction, difficulty in utilization in the system and lack of credibility in the supply corporations etc in the big data introduction phase by corporations. Since the world IT corporations are predominating the big data market, the big data introduction of domestic corporations can not but to be dependent on the foreign corporations. When considering that fact, that our country does not have global IT corporations even though it is world powerful IT country, the big data can be thought to be the chance to rear world level corporations. Accordingly, the government shall need to rear star corporations through active political support. Third, the corporations' internal and external professional manpower for the big data introduction and operation lacks. Big data is a system where how valuable data can be deducted utilizing data is more important than the system construction itself. For this, talent who are equipped with academic knowledge and experience in various fields like IT, statistics, strategy and management etc and manpower training should be implemented through systematic education for these talents. This study has arranged theoretical base for empirical studies about big data related fields by comprehending the main variables which affect the big data introduction intention and verifying them and is expected to be able to propose useful guidelines for the corporations and policy developers who are considering big data implementationby analyzing empirically that theoretical base.

• Applied Biological Chemistry
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• v.17 no.2
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• pp.81-92
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• 1974

In order to prepare the mashing materials for 'Takju', Korean wine, with potatoes, theywere steamed, dryed, and pulverized, and their chemical components were analyzed. As a brewing method of Takju with potatoes, general 2nd stage process with Ipkuk and Bunkuk (enzyme sources), commonly used now, was carried out and the effects of preparing conditions of Ipkuk(koji) with potato flour, mashing materials and brewing conditions on the contents of Takju mash, and of storing time on the contents of Takju, were investigated and the results obtained were summarized as follows, 1. Chemical components of steamed potatoes and potato flour were Moisture; 76.2, 10.8%, Total sugar; 16.1, 69.8%, Reducing sugar; 3.45, 13.4%, Crude protein; 2.1, 11.3%, Total acid; 0.012, 0.023% and Volatile acid; 0.0012, 0.0025% respectively. 2. The most effective preparing conditions of Ipkuk with potato flour were to incubate the potato flour added 40-50% of water for 48 hours by general preparing process of Koji, and liquefying and saccharogenic amylase activities of Ipkuk incubated at above conditions were $D40^{\circ}$ 30' 128 W.V. and 13.2 A.U.. 3. The effects of various brewing conditions on the contents of Takju mashes were as follows; 1) Optimum ratio of mashing water and materials for Takju brewing with potato flour was 140ml of water to 60g of flour in 1st stage and 260ml to 140g in 2nd stage. 2) Optimum fermentating times and temperatures for Takju brewing were at $25^{\circ}C$ for 48 hours in 1st stage and at $30^{\circ}C$ for 48 hours in 2nd stage. 3) Optimum amounts of enzyme sources for Takju brewing were 20-30% of Ipkuk and 0.5% of Bunkuk in 1st stage and 1.0% of Bunkuk in 2nd stage. 4) Methanol content of the Takju mash brewed with raw potato flour was much more than that with steamed potato flour. 5) Alcohol, fusel oil and Formol nitrogen contents of the Takju mash brewed with potato flour were less than that with wheat flour, on the contrary, methanol contents and total acidifies of them were showed conversely above. 4. The changes of chemical components and microflora in the mashes during the brewing potato flour Takju were as follows; 1) The accumulation of ethanol followed rapidly in early stage, being the highest at 72 hours (11.9%). 2) Total sugar content of the mash was decreased considerably within 48-72 hours, being 2.62% at 72 hours, and thereafter slowly. 3) Reducing sugar of the mash had a tendency of decreasing, being 0.29% at 48 hours. 4) Total acidity, volatile acidity and Formol nitrogen content of the mash were increased slowly, being 7.30, 0.20, 2.55 at 48 hours. 5) Total cells of yeast appeared the highest in 72 hours ($2.1{\times}10^8$) and thereafter decreased slowly. 6) Total cells of bacteria appeared the highest in 48 hours ($2.4{\times}10^8$) and thereafter decreased or increased slightly. 5. Takju was made from the fermented mash mixed with water to be 6% of alcohol content, and the change of alcohol content, total acidity, total cells of yeast and bacteria during the storing at $30^{\circ}C$ were as follows; 1) Alcohol content of Takju was increased slightly at 24 hours (6.2%), and thereafter decreased slowly. 2) Total acidity of Takju was increased gradually, being 6.1 at 72 hours 3) Total cells of yeast and bacteria appeared the highest at 48 hours ($2.3{\times}10^8,\;1.5{\times}10^8$), and thereafter decreased slowly. 6. Alcohol content, total acidity and Formol nitrogen content of the Takju brewed with potato flour Ipkuk or wheat flour Ipkuk and steamed potatoes(1:5) were 9.8-11.3%, 5.8-7.4, 2.5-3.3 respectively, and the color of the Takju. was similar to commercial Takju. 7. The results of sensory test for various experimental Takju, showed that the Takjues brewed with the materials combined with wheat flour and steamed potatoes(4:5 or 3.5:7.5) were not significantly different in color, taste and flavor from commercial Takju, However, those with potato flour and wheat flour (1:1 or 7:3) were significantly different from commercial Takju.

• Korean Journal of Agricultural Science
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• v.1 no.1
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• pp.67-81
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• 1974

In order to prepare the mashing materials for "Takju", Korean wine, with potatoes they were steamed, dryed, and pulverized, and their chemical components were analyzed. As a brewing method of Takju with potatoes, general 2nd stage process with Ipkuk and Bunkuk (enzyme sources), commonly used now, was carried out and the effects of preparing conditions of Ipkuk(koji) with potato flour, mashing materials and brewing conditions on the contents of Takju mash and of storing time on the contents of Takju, were investigated and the results obtained were summarized as follows. 1. Chemical components of steamed potatoes and potato flour were Moisture; 76.2, 10.8%, Total sugar; 16.1, 69.8%, Reducing sugar; 3.45, 13.4%, Crude protein; 2.1, 11.3%, Total acid; 0.012, 0.023% and Volatile acid; 0.0012, 0.0025% respectively 2. The most effective preparing conditions of Ipkuk with potato flour were to incubate the potato flour added 40-50% of water for 48 hours by general preparing process of Koji, and liquefying and saccharogenic amylase activities of Ipkuk incubated at above conditions were $D_{40^{\circ}}{^{30{\prime}}}$ 128 W.V. and 13.2 A. U. 3. The effects of various brewing conditions on the contents of Takju mashes wereas follows; 1) Optimum ratio of mashing water and materials for Takju brewing with potato flour was 140ml of water to 60g of flour in 1st stage and 260ml to 140g in 2nd stage. 2) Optimum fermentating times and temperatures for Takju brewing were at $25^{\circ}C$ for 48 hours in 1st stage and at $30^{\circ}C$ for 48 hours in 2nd stage. 3) Optimum amounts of enzyme sources for Takju brewing 20-30% of Ipkuk and 0.5% of Bunkuk in 1st stage and 1.0% of Bunkuk in 2nd stage. 4) Methanol content of the Takju mash brewed with raw potato flour was much more than that with steamed potato flour. 5) Alcohol fusel oil and Formal nitrogen contents of the Takju mash brewed with potato flour were less than that with wheat flour, on the contrary, methanol contents and total acidities of them were showed conversely above. 4. The changes of chemical components and microflora in the mashes during the brewing potato flour Takju were as follows; 1) The accumulation of ethanol followed rapidly in early stage, being the highest at 72 hours (11.9%) 2) Total sugar content of the mash was decreased considerably within 48-72 hours, being 2.62% at 72 hours, and thereafter slowly. 3) Reducing sugar of the mash had a tendency of decreasing, being 0.29% at 48 hours. 4) Total acidity, volatile acidity and Formal nitrogen content of the mash were increased slowly, being 7.30, 0.20, 2.55 at 48 hours. 5) Total cells of yeast appeared the highest in 72 hours ($2.1{\times}10^8$) and thereafter decreased slowly. 6) Total cells of bacteria appeared the highest in 48 hours ($2.4{\times}10^8$) and thereafter decreased or increased slightly. 5. Takju was made from the fermented mash mixed with water to be 6% of alcohol content, and the change of alcohol content, total acidity, total cells of yeast and bateria during the storing at $30^{\circ}C$ were as follows; 1) Alcohol content of Takju was increased slightly at 24 hours (6.2%), and thereafter decreased slowly. 2) Total acidity of Takju was increased gradually, being 6.1 at 72 hours 3) Total cells of yeast and bacteria appeared the highest at 48 hours ($2.3{\times}10^8$, $1.5{\times}10^8$) and thereafter decreased slowly. 6. Alcohol content, total acidity and Formol nitrogen content of the Takju brewed with potato flour Ipkuk or wheat flour Ipkuk and steamed potatoes(1:5) were 9.8-11.3%, 5.8-7.4, 2.5-3.3 respectively, and the color of the Takju was similar to commercial Takju. 7. The results of sensory test for various experimental Takju, showed that the Takjues brewed with the materials combined with wheat flour and steamed potatoes (4:5 or 3.5:7.5) were not significantly different in color, taste and flavor from commercial Takju, However, those with potato flour and wheat flour (1:1 or 7:3) were significantly different from commercial Takju.

• Journal of the Korean Applied Science and Technology
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• v.18 no.3
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• pp.214-232
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• 2001

CTA ester bonds in TG molecules were not attacked by pancreatic lipase and lipases produced by microbes such as Candida cylindracea, Chromobacterium viscosum, Geotricum candidium, Pseudomonas fluorescens, Rhizophus delemar, R. arrhizus and Mucor miehei. An aliquot of total TG of all the seed oils and each TG fraction of the oils collected from HPLC runs were deuterated prior to partial hydrolysis with Grignard reagent, because CTA molecule was destroyed with treatment of Grignard reagent. Deuterated TG (dTG) was hydrolyzed partially to a mixture of deuterated diacylglycerols (dDG), which were subsequently reacted with (S)-(+)-1-(1-naphthyl)ethyl isocyanate to derivatize into dDG-NEUs. Purified dDG-NEUs were resolved into 1, 3-, 1, 2- and 2, 3-dDG-NEU on silica columns in tandem of HPLC using a solvent of 0.4% propan-1-o1 (containing 2% water)-hexane. An aliquot of each dDG-NEU fraction was hydrolyzed and (fatty acid-PFB ester). These derivatives showed a diagnostic carboxylate ion, $(M-1)^{-}$, as parent peak and a minor peak at m/z 196 $(PFB-CH_{3})^{-}$ on NICI mass spectra. In the mass spectra of the fatty acid-PFB esters of dTGs derived from the seed oils of T. kilirowii and M. charantia, peaks at m/z 285, 287, 289 and 317 were observed, which corresponded to $(M-1)^{-}$ of deuterized oleic acid ($d_{2}-C_{18:0}$), linoleic acid ($d_{4}-C_{18:0}$), punicic acid ($d_{6}-C_{18:0}$) and eicosamonoenoic acid ($d_{2}-C_{20:0}$), respectively. Fatty acid compositions of deuterized total TG of each oil measured by relative intensities of $(M-1)^-$ ion peaks were similar with those of intact TG of the oils by GLC. The composition of fatty acid-PFB esters of total dTG derived from the seed oils of T. kilirowii are as follows; $C_{16:0}$, 4.6 mole % (4.8 mole %, intact TG by GLC), $C_{18:0}$, 3.0 mole % (3.1 mole %), $d_{2}C_{18:0}$, 11.9 mole % (12.5 mole %, sum of $C_{18:1{\omega}9}$ and $C_{18:1{\omega}7}$), $d_{4}-C_{18:0}$, 39.3 mole % (38.9 mole %, sum of $C_{18:2{\omega}6}$ and its isomer), $d_{6}-C_{18:0}$, 41.1 mole % (40.5 mole %, sum of $C_{18:3\;9c,11t,13c}$, $C_{18:3\;9c,11t,13r}$ and $C_{18:3\;9t,11t,13c}$), $d_{2}-C_{20:0}$, 0.1 mole % (0.2 mole % of $C_{20:1{\omega}9}$). In total dTG derived from the seed oils of M. charantia, the fatty acid components are $C_{16:0}$, 1.5 mole % (1.8 mole %, intact TG by GLC), $C_{18:0}$, 12.0 mole % (12.3 mole %), $d_{2}-C_{18:0}$, 16.9 mole % (17.4 mole %, sum of $C_{18:1{\omega}9}$), $d_{4}-C_{18:0}$, 11.0 mole % (10.6 mole %, sum of $C_{18:2{\omega}6}$), $d_{6}-C_{18:0}$, 58.6 mole % (57.5 mole %, sum of $C_{18:3\;9c,11t,13t}$ and $C_{18:3\;9c,11t,13c}$). In the case of Aleurites fordii, $C_{16:0}$; 2.2 mole % (2.4 mole %, intact TG by GLC), $C_{18:0}$; 1.7 mole % (1.7 mole %), $d_{2}-C_{18:0}$; 5.5 mole % (5.4 mole %, sum of $C_{18:1{\omega}9}$), $d_{4}-C_{18:0}$ ; 8.3 mole % (8.5 mole %, sum of $C_{18:2{\omega}6}$), $d_{6}-C_{18:0}$; 82.0 mole % (81.2 mole %, sum of $C_{18:3\;9c,11t,13t}$ and $C_{18:3 9c,11t,13c})$. In the stereospecific analysis of fatty acid distribution in the TG species of the seed oils of T. kilirowii, $C_{18:3\;9c,11t,13r}$ and $C_{18:2{\omega}6}$ were mainly located at sn-2 and sn-3 position, while saturated acids were usually present at sn-1 position. And the major molecular species of $(C_{18:2{\omega}6})(C_{18:3\;9c,11t,13c})_{2}$ and $(C_{18:1{\omega}9})(C_{18:2{\omega}6})(C_{18:3\;9c,11t,13c})$ were predominantly composed of the stereoisomer of $sn-1-C_{18:2{\omega}6}$, $sn-2-C_{18:3\;9c,11t,13c}$, $sn-3-C_{18:3\;9c,11t,13c}$, and $sn-1-C_{18:1{\omega}9}$, $sn-2-C_{18:2{\omega}6}$, $sn-3-C_{18:3\;9c,11t,13c}$, respectively, and the minor TG species of $(C_{18:2{\omega}6})_{2}(C_{18:3\;9c,11t,13c})$ and $ (C_{16:0})(C_{18:3\;9c,11t,13c})_{2}$ mainly comprised the stereoisomer of $sn-1-C_{18:2{\omega}6}$, $sn-2-C_{18:2{\omega}6}$, $sn-3-C_{18:3\;9c,11t,13c}$ and $sn-1-C_{16:0}$, $sn-2-C_{18:3\;9c,11t,13c}$, $sn-3-C_{18:3\;9c,11t,13c}$. The TG of the seed oils of Momordica charantia showed that most of CTA, $C_{18:3\;9c,11t,13r}$, occurred at sn-3 position, and $C_{18:2{\omega}6}$ was concentrated at sn-1 and sn-2 compared to sn-3. Main TG species of $(C_{18:1{\omega}9})(C_{18:3\;9c,11t,13t})_{2}$ and $(C_{18:0})(C_{18:3\;9c,11t,13t})_{2}$ were consisted of the stereoisomer of $sn-1-C_{18:1{\omega}9}$, $sn-2-C_{18:3\;9c,11t,13t}$, $sn-3-C_{18:3\;9c,11t,13t}$ and $sn-1-C_{18:0}$, $sn-2-C_{18:3\;9c,11t,13t}$, $sn-3-C_{18:3\;9c,11t,13t}$, respectively, and minor TG species of $(C_{18:2{\omega}6})(C_{18:3\;9c,11t,13c})_{2}$ and $(C_{18:1{\omega}9})(C_{18:2{\omega}6})(C_{18:3\;9c,11t,13c})$ contained mostly $sn-1-C_{18:2{\omega6}$, $sn-2-C_{18:3\;9c,11t,13t}$, $sn-3-C_{18:3\;9c,11t,13t}$ and $sn-1-C_{18:1{\omega}9}$, $sn-2-C_{18:2{\omega}6}$, $sn-3-C_{18:3\;9c,11t,13t}$. The TG fraction of the seed oils of Aleurites fordii was mostly occupied with simple TG species of $(C_{18:3\;9c,11t,13t})_{3}$, along with minor species of $(C_{18:2{\omega}6})(C_{18:3\;9c,11t,13t})_{2}$, $(C_{18:1{\omega}9})(C_{18:3\;9c,11t,13t})_{2}$ and $(C_{16:0})(C_{18:3\;9c,11t,13t})$. The sterospecific species of $sn-1-C_{18:2{\omega}6}$, $sn-2-C_{18:3\;9c,11t,13t}$, sn-3-C_{18:3\;9c,11t,13t}$, $sn-1-C_{18:1{\omega}9}$, $sn-2-C_{18:3\;9c,11t,13t}$, $sn-3-C_{18:3\;9c,11t,13t}$ and $sn-1-C_{16;0}$, $sn-2-C_{18:3\;9c,11t,13t}$, $sn-3-C_{18:3\;9c,11t,13t}$ are the main stereoisomers for the species of $(C_{18:2{\omega}6})(C_{18:3\;9c,11t,13t})_2$, $(C_{18:1{\omega}9})(C_{18:3\;9c,11t,13t})_{2}$ and $(C_{16:0})(C_{18:3\;9c,11t,13t})$, respectively.

• Economic and Environmental Geology
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• v.5 no.4
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• pp.187-209
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• 1972

Drilling position is one of the most important factors affecting on the blasting effects. There has been many reports on several blasting factors of burn-cut by Messrs. Brown and Cook, but in this study the author tried to compare drilling positions of burn-cut to pyramid-cut, and also to correlate burn-cut effects of drilling patterns, not being dealt by Prof. Ito in his theory, which emphasized on dynamical stress analysis between explosion and free face. According to former theories, there break out additional tensile stress reflected at the free face supplemented to primary compressive stress on the blasting with one-free-face. But with these experimented new drilling patterns of burn-cut, more free faces and nearer distance of each drilling holes make blasting effects greater than any other methods. To promote the above explosive effect rationary, it has to be considered two important categories under-mentioned. First, unloaded hole in the key holes should be drilled in wider diameter possibly so that it breaks out greater stress relief. Second, key holes possibly should have closer distances each other to result clean blasting. These two important factors derived from experiments with, theories of that the larger the dia of the unloaded hole, it can be allowed wider secondary free faces and closes distances of each holes make more developed stress relief, between loaded and unloaded holes. It was suggested that most ideal distance between holes is about 4 clearance in U. S. A., but the author, according to the experiments, it results that the less distance allow, the more effective blasting with increased broken rock volume and longer drifted length can be accomplished. Developed large hole burn-cut method aimed to increase drifting length technically under the above considerations, and progressive success resulted to achieve maximum 7 blasting cycles per day with 3.1m drifting length per cycle. This achievement originated high-speed-drifting works, and it was also proven that application of Metallic AN-FO on large hole burn-cut method overcomes resistance of one-free-face. AN-FO which was favored with low price and safety handling is the mixture of the fertilizer or industrial Ammonium-Nitrate and fuel oil, and it is also experienced that it shows insensible property before the initiation, but once it is initiated by the booster, it has equal explosive power of Ammonium Nitrate Explosives (ANE). There was many reports about AN-FO. On AN-FO mixing ratio, according to these experiments, prowdered AN-FO, 93.5 : 6.5 and prilled AN-FO 94 : 6, are the best ratios. Detonation, shock, and friction sensities are all more insensitive than any other explosives. Residual gas is not toxic, too. On initation and propagation of the detonation test, prilled AN-FO is more effective than powered AN-FO. AN-FO has the best explosion power at 7 days elapsed after it has mixed. While AN-FO was used at open pit in past years prior to other conditions, the author developed new improved explosives, Metallic AN-FO and Underwater explosive, based on the experiments of these fundmental characteristics by study on its usage utilizing AN-FO. Metallic AN-FO is the mixture of AN-FO and Al, Fe-Si powder, and Underwater explosive is made from usual explosive and AN-FO. The explanations about them are described in the other paper. In this study, it is confirmed that the blasting effects of utilizing AN-FO explosives are very good.