• The Journal of the Korea Contents Association
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• v.16 no.1
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• pp.42-51
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• 2016

For changes in the distribution structure these days, consumer demand is moving rapidly from offline to online. The consumers' mentality to purchase products conveniently is reflected in this phenomenon. Also for agricultural products, safety to protect contents, brand and design which can provide credibility to consumers are recognized as most important than ever. Especially, strawberry is thin-skinned so that the quality of product may deteriorate even with weak impact and shaking, so it is significantly influenced by the structural packaging or material. Also, strawberry is frequently distributed through direct trading, it is the reality that the package design of strawberry is less competitive than that of other products due to inadequate environments of commercial farms. That is, the demand of strawberry increases everyday but the strawberry package cannot fulfill the needs of producers and consumers. In order to reinforce competitiveness in strawberry sales, it is urgent to carry out fundamental studies regarding the development of package. Therefore, the purpose of this study is to supplement and improve issues arising from the usage of current strawberry package. Through the analysis of strawberry package elements (shape, material, design) and understand the points of improvement sought by producers and consumers through IPA MAP (importance, satisfaction level) analysis.

• Journal of Microbiology and Biotechnology
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• v.9 no.6
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• pp.737-743
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• 1999

A conventional thermophilic anaerobic digester was converted into a thermophilic high-rate hybrid anaerobic reactor (THAR) for treating distillery wastewater. The THAR has been operating successfully since May 1995 at a loading rate of 5.45 to $11.52{\;}kg/\textrm{m}^3/d$ (maximum of 15.02). The THAR has demonstrated a soluble Chemical Oxygen Demand (sCOD) removal efficiency of 85 to 91% and a total COD (tCOD) removal efficiency of as much as 72 to 84%. Product gas had a methane content of 59 to 68%. The tCOD removal rates were 4.31 to 5.43, 6.26 to 6.89, and 9.03 to $9.78kg{\;}tCOD/\textrm{m}^3/d$ for tapioca, com, and naked-barley wastewater, respectively. The sCOD removal rates ranged from 3.75 to 4.79,3.28 to 4.89, and 5.57 to 6.21kg $sCOD/\textrm{m}^3/d$ for tapioca, com, and naked-barley wastewater, respectively. There were unknown substances in a naked-barley distillery wastewater that were identified as being toxic for microorganisms. However, the THAR treated naked-barley wastewater continuously for 26 days, operating at an average tCOD loading of $11.08{\;}kg/\textrm{m}^3/d$without any signs of deterioration in either COD removal efficiency or gas production rate. During this period, the average removal efficiencies of tCOD and sCOD were 84% and 91%, respectively, and the gas production rate averaged 6.61 to $7.57{\;}\textrm{m}^3/\textrm{m}^3$ reactor/d which produced 0.57 to $0.69{\;}\textrm{m}^3{\;}biogas/kg{\;}tCOD_{rem}$. From tapioca and com wastewater, the reactor showed an average gas production rate of 3.18 to 3.46 and 4.91 to $5.22{\;}\textrm{m}^3/\textrm{m}^3$ reactor/d which produced 0.53 to 0.69 and 0.62 to $0.71{\;}\textrm{m}^3/kg{\;}tCOD_{rem}$, respectively.

• International Commerce and Information Review
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• v.6 no.2
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• pp.107-127
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• 2004

The rapid development of internet information technology has increased interest in e-Trade these days, but it is not activated greatly up to now. In order to promote e-Trade, it is essential to construct cooperative process such as connecting systems among trade related parties. Building e-Trade platform which is based on the infrastructure of the past trade automatic system is key point of promoting e-Trade. To do this, a study on the basic concept and specific components of e-Trade platform is needed absolutely. At this point of view, after this paper has examined domestic and foreign studies on the fundamental technologies about electronic commerce, it drew several key technologies that could be applied to e-Trade considering the current IT trend. Then it evaluates these technologies according to Technology Reference Model(TRM) of the National Computerization Agency. This will help us to show the operation strategy as well as the concept of future e-Trade platform and its composition. On the basis of the theoretical background, this paper classified NCA's technology model into 6 fields, which are application. data, platform, communication, security and management. Considering the key technologies, e-Trade platform has to be mutually connected and accept international standards such as XML. In the aspect of business side, trade relative agencies' business process as well as trading company's process has to be considered. Therefore, e-Trade platform can be classified into 3 parts which are service, infrastructure and connection. Infrastructure part is compared of circulating and managing system of electronic document, interface and service framework. Connecting service (application service) and additional service (application service) consist of service part. Connecting part is a linking mutual parts and can be divided into B2B service and B20 service. The organization operating this e-trade platform must have few responsibilities and requirements. It needs to positively accept existing infrastructure of trade automatic system and improving the system to complete e-trade platform. It also have to continuously develop new services and possess ability to operate the system for providing proper services to demanders. As a result, private sector that can play a role as TTP(Third Trust Party) is adequate for operating the system. In this case, revising law is necessary to support the responsibility and requirement of private sector.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.14 no.4
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• pp.13-23
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• 2004

Proxy signature scheme based on delegation of warrant is studied in these days. Proxy signature is a signature scheme that the original signer delegates his signing warrant to the proxy signer, and the proxy signer creates a signature on behalf of the original signer. For using this scheme, the security for Protecting from the forgeability or misuse is necessary. There are several security requirements for using the proxy signature schemes. In this paper we suggest the proxy-register protocol scheme that original signer registers to the verifier about the proxy related information. In our scheme, verifier verifies the signature that original signer creates about the proxy information and sets the warrant of proxy signer, validity period for proxy signature and some limitation. Finally, we will show the advantages of our suggestion by comparing with the previous proxy signature schemes.

• Journal of The Korean Society of Grassland and Forage Science
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• v.34 no.4
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• pp.283-287
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• 2014

This experiment was conducted to determine methane production and emission factors for a range of roughage diets fed to Hanwoo cows at a level of maintenance energy requirement. Seven cows were fed mixed hay only, 12 cows were fed mixed hay containing 30~50% rice straw and 6 cows were fed a mixed hay diet supplemented with 1.0 kg of wheat bran. Each cow was placed in a metabolic crate for 10 consecutive days, including last 7 days for sampling of feces and urine. At the end of the sampling period, the cows were transferred to an open-circuit respiration chamber for 24 consecutive hours. Methane conversion rate (5.5~6.2%, mean value = 5.8%) and emission factor (33.6~38.6 kg/head/year, mean value = 35.2) were not significantly affected by the diets although the mixed hay only diet resulted in 11 and 15% higher respective rates than the other two. However, in light of the many assumptions that forage with good quality might reduce methane production, additional experiments should be required for participation in the greenhouse gas emission trading system.

• The Journal of the Korea Contents Association
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• v.15 no.5
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• pp.200-218
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• 2015

The purpose of the present study was to examine daily lives of elderly welfare recipients and their experiences with social welfare services. Researchers collected and analyzed data through individual interviews with 11 elderly welfare recipients. A major theme in the time context was "Daily lives enduring physical and mental sufferings alone and mismatches of social welfare services": 'Starting same tedious days: trading diligent work for basic living assistance', 'Forced ritual of having meals', 'Struggle with depressing night: not attentive welfare services at closing hours', 'Welfare services suspended in holidays', 'Mind and body withered by economic hardship in winter', 'Social support for enduring weary lives'. In the space context, a major themes was "Inadequate welfare services and social interaction in the context of social isolation": 'Unhygienic and unsafe living environment', 'Hiding places: spending tedious days in vacant lots', 'Community welfare centers useful only for healthy elderly', 'Differences and similarities of elderly in urban and rural areas', 'Receiving restricted medical services at hospitals', 'Hard-to-reach public institutions', 'ambivalence about living as welfare recipients'. Based on the findings, the researchers proposed implications for policy and practice to improve elderly welfare recipients' quality of life.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.123-138
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• 2017

Since the stock market is driven by the expectation of traders, studies have been conducted to predict stock price movements through analysis of various sources of text data. In order to predict stock price movements, research has been conducted not only on the relationship between text data and fluctuations in stock prices, but also on the trading stocks based on news articles and social media responses. Studies that predict the movements of stock prices have also applied classification algorithms with constructing term-document matrix in the same way as other text mining approaches. Because the document contains a lot of words, it is better to select words that contribute more for building a term-document matrix. Based on the frequency of words, words that show too little frequency or importance are removed. It also selects words according to their contribution by measuring the degree to which a word contributes to correctly classifying a document. The basic idea of constructing a term-document matrix was to collect all the documents to be analyzed and to select and use the words that have an influence on the classification. In this study, we analyze the documents for each individual item and select the words that are irrelevant for all categories as neutral words. We extract the words around the selected neutral word and use it to generate the term-document matrix. The neutral word itself starts with the idea that the stock movement is less related to the existence of the neutral words, and that the surrounding words of the neutral word are more likely to affect the stock price movements. And apply it to the algorithm that classifies the stock price fluctuations with the generated term-document matrix. In this study, we firstly removed stop words and selected neutral words for each stock. And we used a method to exclude words that are included in news articles for other stocks among the selected words. Through the online news portal, we collected four months of news articles on the top 10 market cap stocks. We split the news articles into 3 month news data as training data and apply the remaining one month news articles to the model to predict the stock price movements of the next day. We used SVM, Boosting and Random Forest for building models and predicting the movements of stock prices. The stock market opened for four months (2016/02/01 ~ 2016/05/31) for a total of 80 days, using the initial 60 days as a training set and the remaining 20 days as a test set. The proposed word - based algorithm in this study showed better classification performance than the word selection method based on sparsity. This study predicted stock price volatility by collecting and analyzing news articles of the top 10 stocks in market cap. We used the term - document matrix based classification model to estimate the stock price fluctuations and compared the performance of the existing sparse - based word extraction method and the suggested method of removing words from the term - document matrix. The suggested method differs from the word extraction method in that it uses not only the news articles for the corresponding stock but also other news items to determine the words to extract. In other words, it removed not only the words that appeared in all the increase and decrease but also the words that appeared common in the news for other stocks. When the prediction accuracy was compared, the suggested method showed higher accuracy. The limitation of this study is that the stock price prediction was set up to classify the rise and fall, and the experiment was conducted only for the top ten stocks. The 10 stocks used in the experiment do not represent the entire stock market. In addition, it is difficult to show the investment performance because stock price fluctuation and profit rate may be different. Therefore, it is necessary to study the research using more stocks and the yield prediction through trading simulation.

• The Journal of Fisheries Business Administration
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• v.40 no.2
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• pp.49-70
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• 2009

This study proviedes GARCH model(Bollerslev, 1986) to analyze the structural characteristics of price volatility in domestic aquacultural fish market of Korea. As a case study, flatfish and rock-fish are analyzed as major species with relatively high portion in an aspect of production volume among fish captured in Korea. For analyzing, this study uses daily market data (dating from Jan 1 2000 to June 30, 2008) published by the Noryangjin Fisheries Wholesale Market which is located in Seoul of Korea. This study performs normality test on trading volume and price volatility of flatfish and rock-fish as an advanced empirical approach. The normality test adopted is Jarque-Bera test statistic. As a result, first, a null hypothesis that "an empirical distribution follows normal distribution" was rejected in both fishes. The distribution of daily market data of them were not only biased toward positive(+) direction in terms of kurtosis and skewness, but also characterized by leptokurtic distribution with long right tail. Secondly, serial correlations were found in data on market trading volume and price volatility of two species during very long period. Thirdly, the results of unit root test and ARCH-LM test showed that all data of time series were very stationary and demonstrated effects of ARCH. These statistical characteristics can be explained as a reasonable ground for supporting the fitness of GARCH model in order to estimate conditional variances that reveal price volatility in empirical analysis. From empirical data analysis above, this study drew the following conclusions. First of all, from an empirical analysis on potential effects of seasonality and the day of week on price volatility of aquacultural fish, Monday effects were found in both species and Thursday and Friday effects were also found in flatfish. This indicates that Monday is effective in expanding price volatility of aquacultural fish market and also Monday has higher effects upon the price volatility of fish than other days of week have since it has more new information for weekend. Secondly, the empirical analysis led to a common conclusion that there was very high price volatility of flatfish and rock-fish. This points out that the persistency parameter($\lambda$), an index of possibility for current volatility to sustain similarly in the future, was higher than 0.8-equivalently nearly to 1-in both flatfish and rock-fish, which presents volatility clustering. Also, this study estimated and compared and model that hypothesized normal distributions in order to determine fitness of respective models. As a result, the fitness of GARCH(1, 1)-t model was better than model where the distribution of error term was hypothesized through-distribution due to characteristics of fat-tailed distribution, was also better than model, as described in the results of basic statistic analysis. In conclusion, this study has an important mean in that it was introduced firstly in Korea to investigate in price volatility of Korean aquacultural fishery products, although there was partially a limited of official statistic data. Therefore, it is expected that the results of this study will be useful as a reference material for making and assessing governmental policies. Also, it is looked forward that the results will be helpful to build a fishery business plan as and aspect of producer, and also to take timely measures to potential price fluctuations of fishery products in market. Hence, it is advisable that further studies related to such price volatility in fishery market will extend and evolve into a wider variety of articles and issues in near future.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.111-126
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• 2017

Recommender systems based on association rule mining significantly contribute to seller's sales by reducing consumers' time to search for products that they want. Recommendations based on the frequency of transactions such as orders can effectively screen out the products that are statistically marketable among multiple products. A product with a high possibility of sales, however, can be omitted from the recommendation if it records insufficient number of transactions at the beginning of the sale. Products missing from the associated recommendations may lose the chance of exposure to consumers, which leads to a decline in the number of transactions. In turn, diminished transactions may create a vicious circle of lost opportunity to be recommended. Thus, initial sales are likely to remain stagnant for a certain period of time. Products that are susceptible to fashion or seasonality, such as clothing, may be greatly affected. This study was aimed at expanding association rules to include into the list of recommendations those products whose initial trading frequency of transactions is low despite the possibility of high sales. The particular purpose is to predict the strength of the direct connection of two unconnected items through the properties of the paths located between them. An association between two items revealed in transactions can be interpreted as the interaction between them, which can be expressed as a link in a social network whose nodes are items. The first step calculates the centralities of the nodes in the middle of the paths that indirectly connect the two nodes without direct connection. The next step identifies the number of the paths and the shortest among them. These extracts are used as independent variables in the regression analysis to predict future connection strength between the nodes. The strength of the connection between the two nodes of the model, which is defined by the number of nodes between the two nodes, is measured after a certain period of time. The regression analysis results confirm that the number of paths between the two products, the distance of the shortest path, and the number of neighboring items connected to the products are significantly related to their potential strength. This study used actual order transaction data collected for three months from February to April in 2016 from an online commerce company. To reduce the complexity of analytics as the scale of the network grows, the analysis was performed only on miscellaneous goods. Two consecutively purchased items were chosen from each customer's transactions to obtain a pair of antecedent and consequent, which secures a link needed for constituting a social network. The direction of the link was determined in the order in which the goods were purchased. Except for the last ten days of the data collection period, the social network of associated items was built for the extraction of independent variables. The model predicts the number of links to be connected in the next ten days from the explanatory variables. Of the 5,711 previously unconnected links, 611 were newly connected for the last ten days. Through experiments, the proposed model demonstrated excellent predictions. Of the 571 links that the proposed model predicts, 269 were confirmed to have been connected. This is 4.4 times more than the average of 61, which can be found without any prediction model. This study is expected to be useful regarding industries whose new products launch quickly with short life cycles, since their exposure time is critical. Also, it can be used to detect diseases that are rarely found in the early stages of medical treatment because of the low incidence of outbreaks. Since the complexity of the social networking analysis is sensitive to the number of nodes and links that make up the network, this study was conducted in a particular category of miscellaneous goods. Future research should consider that this condition may limit the opportunity to detect unexpected associations between products belonging to different categories of classification.

• The Korean Journal of Financial Management
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• v.25 no.1
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• pp.1-22
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• 2008

This study is to evaluate, to the extent to, which advanced currency futures and emerging currency futures markets can predict accurately the future spot rate. To this end, Johansen's the maximum-likelihood cointegration method(1988, 1991) is adopted to test the unbiasedness and efficiency hypothesis. Also, this study is to estimate and compare a quantitative measure of relative efficiency as a ratio of the forecast error variance from the best-fitting quasi-error correction model to the forecast error variance of the futures price as predictor of the spot price in advanced currency futures with in emerging currency futures market. Advanced currency futures is British pound and Japan yen. Emerging currency futures includes Korea won, Mexico peso, and Brazil real. The empirical results are summarized as follows : First, the unbiasedness hypothesis is not rejected for Korea won and Japan yen futures exchange rates. This indicates that the emerging currency Korea won and the advanced currency Japan yen futures exchange rates are likely to predict accurately realized spot exchange rate at a maturity date without the trader having to pay a risk premium for the privilege of trading the contract. Second, in emerging currency futures markets, the unbiasedness hypothesis is not rejected for Korea won futures market apart from Mexico peso and Brazil real futures markets. This indicates that in emerging currency futures markets, Korea won futures market is more efficient than Mexico peso and Brazil real futures markets and is likely to predict accurately realized spot exchange rate at a maturity date without risk premium. Third, this findings show that the results of unbiasedness hypothesis tests can provide conflicting finding. according to currency futures class and forecasts horizon period, Fourth, from the best-fitting quasi-error correction model with forecast horizons of 14 days, the findings suggest the Japan yen futures market is 27.06% efficient, the British pound futures market is 26.87% efficient, the Korea won futures market is 20.77% efficient, the Mexico peso futures market is 11.55%, and the Brazil real futures market is 4.45% efficient in the usual order. This indicates that the Korea won-dollar futures market is more efficient than Mexico peso, and Brazil real futures market. It is therefore possible to concludes that the Korea won-dollar currency futures market has relatively high efficiency comparing with Mexico peso and Brazil real futures markets of emerging currency futures markets.