• Korean Journal of Veterinary Research
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• v.41 no.3
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• pp.305-310
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• 2001

Iron deficient anemia in piglets could be overcome by supplementary iron. Overloaded iron induced peroxidation of cell membrane and increased malonaldehyde (MDA). Antioxidant activity of vitamin C has been studied in iron-overloaded swine plasma. Erythrocyte fragility, MDA, glutathione, vitamin A, and vitamin E were measured in swine plasma with or without iron (0~1mg/dl) and vitamin C (0~10mg/dl). Erythrocyte fragility increased from 8% to 45% in iron group and reduced from 57% to 43% in vitamin C group with dose dependant response. MDA was $0.94{\pm}0.05$ and $1.86{\pm}0.10$ nmol/ml in piglet and pig, respectively, and significantly high in pig (p<0.05). Iron increased MDA from $1.86{\pm}0.10$ to $9.46{\pm}0.04$ nmol/ml in pig, but not in piglet (p<0.05). Vitamin C reduced MDA from $9.46{\pm}0.04$ to $4.80{\pm}0.10$ nmol/ml in pig. Iron increased glutathione from $90.12{\pm}0.10$ to $108.52{\pm}5.29$ nmol/dl in pig, and vitamin C reduced glutathione from $108.52{\pm}5.29$ to $93.52{\pm}2.44$ nmol/dl (p<0.05). Vitamin A and E were $24.86{\pm}2.70$ to $138.29{\pm}6.70{\mu}g/dl$, respectively in iron group, and $35.76{\pm}0.60$ to $177.21{\pm}2.95{\mu}g/dl$, respectively in supplementary vitamin C group (p<0.05). These data indicated an antioxidant activity of vitamin C in iron-overloaded swine plasma.

• Asian-Australasian Journal of Animal Sciences
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• v.20 no.6
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• pp.962-970
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• 2007

A total of 1,200 LinNan Chinese color-feathered chicks were used to study the effects of methionine source [DL-2-hydroxy-4-methylthio-butanoic acid (HMTBa) or DL-methionine (DLM)] and dietary crude protein (CP) level on growth performance, carcass traits, and whole-body nitrogen and fat retention. The trial was designed as a $2{\times}2$ factorial arrangement, including two CP levels (adequate and low) and two methionine sources (HMTBa and DL-methionine). Diets were formulated for three phases, starter (0-21 d), grower (21-42 d), and finisher (42-63 d). Chicks fed HMTBa had higher daily gain and improved feed efficiency than DLM during the grower phase (p<0.05). A significant two-way interaction was observed for growth performance during the finisher phase and overall (0-63 d). Growth performance was greater for chicks fed HMTBa than DLM on adequate-CP diets (p<0.05), but this was not observed at low-CP level (p>0.05). Chicks fed low-CP diets grew slower, used feed less efficiently during the grower, finisher phase and overall. On d 42, regardless of dietary CP levels, birds fed HMTBa had higher carcass weights, breast and thigh weights than DLM-fed birds (p<0.04). Birds fed low-CP diet had lighter carcass weights and less breast muscle, thigh muscle, and dressing percentage at the end of starter, grower and finisher phases (p<0.05). Whole body composition analyses found that birds fed HMTBa tended to contain more protein and less fat compared to those chicks fed DLM at the end of the starter phase (p<0.10). Low-CP diets increased CP concentration in the whole body at the end of the finisher phase (p = 0.05). HMTBa supplementation increased whole-body N retention rate during the finisher phase and overall (p<0.01), and low-CP diets reduced N intake and whole-body fat retention during the finisher phase and overall (p<0.05). In summary, HMTBa was better than DLM on an equimolar basis for growth performance, carcass traits, and N retention in Chinese color-feathered chicks. Low-CP diets lowered growth performance as well as carcass traits in color-feathered birds, probably due to imbalanced AA profiles.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.177-192
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• 2016

Machine learning is a field of artificial intelligence. It refers to an area of computer science related to providing machines the ability to perform their own data analysis, decision making and forecasting. For example, one of the representative machine learning models is artificial neural network, which is a statistical learning algorithm inspired by the neural network structure of biology. In addition, there are other machine learning models such as decision tree model, naive bayes model and SVM(support vector machine) model. Among the machine learning models, we use SVM model in this study because it is mainly used for classification and regression analysis that fits well to our study. The core principle of SVM is to find a reasonable hyperplane that distinguishes different group in the data space. Given information about the data in any two groups, the SVM model judges to which group the new data belongs based on the hyperplane obtained from the given data set. Thus, the more the amount of meaningful data, the better the machine learning ability. In recent years, many financial experts have focused on machine learning, seeing the possibility of combining with machine learning and the financial field where vast amounts of financial data exist. Machine learning techniques have been proved to be powerful in describing the non-stationary and chaotic stock price dynamics. A lot of researches have been successfully conducted on forecasting of stock prices using machine learning algorithms. Recently, financial companies have begun to provide Robo-Advisor service, a compound word of Robot and Advisor, which can perform various financial tasks through advanced algorithms using rapidly changing huge amount of data. Robo-Adviser's main task is to advise the investors about the investor's personal investment propensity and to provide the service to manage the portfolio automatically. In this study, we propose a method of forecasting the Korean volatility index, VKOSPI, using the SVM model, which is one of the machine learning methods, and applying it to real option trading to increase the trading performance. VKOSPI is a measure of the future volatility of the KOSPI 200 index based on KOSPI 200 index option prices. VKOSPI is similar to the VIX index, which is based on S&P 500 option price in the United States. The Korea Exchange(KRX) calculates and announce the real-time VKOSPI index. VKOSPI is the same as the usual volatility and affects the option prices. The direction of VKOSPI and option prices show positive relation regardless of the option type (call and put options with various striking prices). If the volatility increases, all of the call and put option premium increases because the probability of the option's exercise possibility increases. The investor can know the rising value of the option price with respect to the volatility rising value in real time through Vega, a Black-Scholes's measurement index of an option's sensitivity to changes in the volatility. Therefore, accurate forecasting of VKOSPI movements is one of the important factors that can generate profit in option trading. In this study, we verified through real option data that the accurate forecast of VKOSPI is able to make a big profit in real option trading. To the best of our knowledge, there have been no studies on the idea of predicting the direction of VKOSPI based on machine learning and introducing the idea of applying it to actual option trading. In this study predicted daily VKOSPI changes through SVM model and then made intraday option strangle position, which gives profit as option prices reduce, only when VKOSPI is expected to decline during daytime. We analyzed the results and tested whether it is applicable to real option trading based on SVM's prediction. The results showed the prediction accuracy of VKOSPI was 57.83% on average, and the number of position entry times was 43.2 times, which is less than half of the benchmark (100 times). A small number of trading is an indicator of trading efficiency. In addition, the experiment proved that the trading performance was significantly higher than the benchmark.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.185-188
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• 2016

The percentage share of mobile gift card certificate in the gift card market has increased significantly each year. But from a consumer perspective mobile gift card certificate has several problems. Specifying unfair terms in Fair Trade Commission has improved slightly, but the problem is not replaced with the equivalent authority that issued the vouchers can not be solved. The exchange between users the most realistic way to solve this problem is to create an environment as possible. In conclusion, The deal will be possible to build a mobile gift card certificate brokerage trading in a convenient and reliable P2P-based. If the System for mediating transactions of a mobile gift certificate has created a healthy retail environment, such as the expansion of the voucher market, reduce social costs may be creating.

• Archives of Pharmacal Research
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• v.21 no.2
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• pp.217-222
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• 1998

A stereospecific HPLC method has been developed for the resolution of the enantiomers of salbutamol in human urine. After solid-phase extraction and derivatization with 2,3,4,6-tetra-O-acetyl-$\beta$-D-glucopyranosyl isothiocyanate, the diastereomeric derivatives were resolved (Rs=1.83) on $5{\mu}m$ octadecylsilan column using 35% acetonitrile in 0.05M ammonium acetate buffer (pH=6) as a mobile phase with electrochemical detection. The diastereomeric derivatives were formed within 30 min. The detection limit of each enantiomer was 20 ng/ml (S/N=3).

• Preventive Nutrition and Food Science
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• v.10 no.1
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• pp.11-16
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• 2005

Enzymatic hydrolysis of dark muscle of skipjack was optimized by using response surface methodology. Three factors of independent values were pH (4.2 to 9.8), time (0.6 to 3.4 hrs) and temperature (34℃ to 76℃), and independent values were optical density and brix. The optimum conditions for enzymatic hydrolysis were pH 7.0 to 8.0, 55℃ and 3 hrs. The headspace volatile compounds of reaction flavors using the enzymatic hydrolysate, cysteine and xylose were identified by using the combination of a canister system, gas chromatography and mass selective detector. Among 67 compounds, we identified 8 sulfur-containing compounds and 7 furans which were thought to be highly related to meat-like flavors.

• Journal of Information Technology Applications and Management
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• v.26 no.6
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• pp.79-87
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• 2019

Blockchain is a distributed network in a decentralized P2P infrastructure. In this paper, we propose and implement a blockchain-based pet trade service DApp(Decentralized Application). In the existing trading services, there is no way to know the status of dogs in interpersonal transactions and an additional distribution cost has been incurred. As a solution to this problem, we introduce a blockchain technology for a pet trade service where users can check whether an individual pet is healthy or not by its registered biometric data in order to have an efficient and confident trade service. The registered users can purchase puppies or registering information for their dogs to sell through a pet trade service DApp. It is also possible to make a reliable trade by verifying whether the dog is actually the same one through an inscription information of a dog.

• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.3
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• pp.1-9
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• 2017

Recently, Bitcoin which is digital currency and cryptocurrency is getting worldwide attention since Bitcoin has an ability to replace legal tender unlike other existing cyber currency. Especially, most Bitcoin trading is done between two traders such as P2P method and it does not require a third-party to make sure reliability and it records every transaction details, so it is more transparent then traditional financial trade, so the number of users is increasing. However, Bitcoin, which has been recognized for transparency, confidentiality and stability among traders has recently been threatened by illegal transactions such as money laundering and the attack on the exchange. These threats to Bitcoin are becoming social problems. At first, it seems that most of the digital currency is difficult to get hacked due to the Blockchain technology. However, threats such as digital money leaks by user account hacking and paralyzing the servers are increasing. In this paper, it will examine the features of the Bitcoin and the threatening elements to secure marketability of digital currency such as Bitcoin and receive more interest from public in domestic. The paper will examine the problems of Blockchain technology on speculative transactions and fraudulent behavior by analyzing the problems of Bitcoin transaction. Lastly, it will propose ways to make transparent and secure digital currency transactions.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.3
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• pp.125-140
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• 2018

According to statistics, it is shown that domestic SMEs rely on bank loans for the majority of fund procurement. From financial information shortage (Thin file) that does not provide information necessary for credit evaluation from banks such as financial statements. In order to overcome these problems, recently, in alternative finance such as P2P, using differentiated information such as demographics, trading information and the like utilizing Fintech instead of existing financial information, small funds A new credit evaluation method has been expanding to provide SMEs with small amounts of money. In this paradigm of environmental change, in this research, credit evaluation which can expand fund supply to SMEs by utilizing big data based on trade area information such as sales fluctuation, location conditions etc. In this research, we try to find such a solution. By analyzing empirically the big data generated in the trade area, we verify the effectiveness as a credit evaluation factor and try to derive the main parameters necessary for the business performance evaluation of the founder of SMEs. In this research, for 17,116 material businesses in Seoul City that operate the service industry from 2009 to February 2018, we collect trade area information generated for each business location from Big Data specialized company NICE Zini Data Co., Ltd.. We collected and analyzed the data on the locations and commercial areas of the facilities that were difficult to obtain from SMEs and analyzed the data that affected the Corporate financial Distress. It is possible to refer to the variable of the existing unused big data and to confirm the possibility of utilizing it for efficient financial support for SMEs, This is to ensure that commercial lenders, even in general commercial banks, are made to be more prominent in one sector of the financing of SMEs. In this research, it is not the traditional financial information about raising fund of SMEs who have basically the problem of information asymmetry, but a trade area analysis variable is derived, and this variable is evaluated by credit evaluation There is differentiation of research in that it verified through analysis of big data from Trading-area whether or not there is an effect on.

• Journal of the Korean Society of Food Science and Nutrition
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• v.33 no.6
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• pp.1034-1042
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• 2004

This study was carried out to investigate preparation of reconstructed red peppers, effects of pungency and redness of red peppers on the Kimchi quality using central composite design and response surfaces methodology. Capsaicinoids and ASTA (American Spice Trading Association) value put in X$_1$, X$_2$ of independent variable. The result of response surface regression analysis of reconstructed red peppers, correlation coefficient ($R^2$) of overall pungency intensity, persistence and degree of redness was 0.935, 0.935 and 0.821, respectively. After it was made Kimchi samples with reconstructed red peppers, it was examined pH, titratable acidity and lactic acid bacteria of its during fermentation. In the initial fermentation period of Kimchi, it showed pH of 5.46∼5.78, titratable acidity of 0.27∼0.31%, salt content of 2.26∼2.48% and lactic acid bacteria of 4.05${\times}$10$^{5}$ ∼6.23${\times}$10$^{5}$ , respectively. And it showed traditional fermentation pattern in the pH, titratable acidity and microbes of the middle (appropriate fermentation) and last (excessive) fermentation period. While capsaicinoids content in the Kimchi decreased a little according to extend fermentation period, ASTA value showed low correlation reconstructed red pepper and fermentation period. Also, it was analyzed correlation coefficient ($R^2$) of independent variables (capsaicinoids, X$_1$; ASTA value, X$_2$) between sensory attribute in the Kimchi during fermentation. The result of regression analysis, $R^2$ in the overall pungency intensity, persistence and degree of redness showed 0.515, 0.675, 0.784, respectively.