• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.25-38
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• 2019

Selecting high-quality information that meets the interests and needs of users among the overflowing contents is becoming more important as the generation continues. In the flood of information, efforts to reflect the intention of the user in the search result better are being tried, rather than recognizing the information request as a simple string. Also, large IT companies such as Google and Microsoft focus on developing knowledge-based technologies including search engines which provide users with satisfaction and convenience. Especially, the finance is one of the fields expected to have the usefulness and potential of text data analysis because it's constantly generating new information, and the earlier the information is, the more valuable it is. Automatic knowledge extraction can be effective in areas where information flow is vast, such as financial sector, and new information continues to emerge. However, there are several practical difficulties faced by automatic knowledge extraction. First, there are difficulties in making corpus from different fields with same algorithm, and it is difficult to extract good quality triple. Second, it becomes more difficult to produce labeled text data by people if the extent and scope of knowledge increases and patterns are constantly updated. Third, performance evaluation is difficult due to the characteristics of unsupervised learning. Finally, problem definition for automatic knowledge extraction is not easy because of ambiguous conceptual characteristics of knowledge. So, in order to overcome limits described above and improve the semantic performance of stock-related information searching, this study attempts to extract the knowledge entity by using neural tensor network and evaluate the performance of them. Different from other references, the purpose of this study is to extract knowledge entity which is related to individual stock items. Various but relatively simple data processing methods are applied in the presented model to solve the problems of previous researches and to enhance the effectiveness of the model. From these processes, this study has the following three significances. First, A practical and simple automatic knowledge extraction method that can be applied. Second, the possibility of performance evaluation is presented through simple problem definition. Finally, the expressiveness of the knowledge increased by generating input data on a sentence basis without complex morphological analysis. The results of the empirical analysis and objective performance evaluation method are also presented. The empirical study to confirm the usefulness of the presented model, experts' reports about individual 30 stocks which are top 30 items based on frequency of publication from May 30, 2017 to May 21, 2018 are used. the total number of reports are 5,600, and 3,074 reports, which accounts about 55% of the total, is designated as a training set, and other 45% of reports are designated as a testing set. Before constructing the model, all reports of a training set are classified by stocks, and their entities are extracted using named entity recognition tool which is the KKMA. for each stocks, top 100 entities based on appearance frequency are selected, and become vectorized using one-hot encoding. After that, by using neural tensor network, the same number of score functions as stocks are trained. Thus, if a new entity from a testing set appears, we can try to calculate the score by putting it into every single score function, and the stock of the function with the highest score is predicted as the related item with the entity. To evaluate presented models, we confirm prediction power and determining whether the score functions are well constructed by calculating hit ratio for all reports of testing set. As a result of the empirical study, the presented model shows 69.3% hit accuracy for testing set which consists of 2,526 reports. this hit ratio is meaningfully high despite of some constraints for conducting research. Looking at the prediction performance of the model for each stocks, only 3 stocks, which are LG ELECTRONICS, KiaMtr, and Mando, show extremely low performance than average. this result maybe due to the interference effect with other similar items and generation of new knowledge. In this paper, we propose a methodology to find out key entities or their combinations which are necessary to search related information in accordance with the user's investment intention. Graph data is generated by using only the named entity recognition tool and applied to the neural tensor network without learning corpus or word vectors for the field. From the empirical test, we confirm the effectiveness of the presented model as described above. However, there also exist some limits and things to complement. Representatively, the phenomenon that the model performance is especially bad for only some stocks shows the need for further researches. Finally, through the empirical study, we confirmed that the learning method presented in this study can be used for the purpose of matching the new text information semantically with the related stocks.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.35 no.2
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• pp.26-44
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• 2017

Regarded as Korea's traditional pond, Gungnamj Pond was surmised to be "Gungnamji" due to its geological positioning in the south of Hwajisan (花枝山) and relics of the Gwanbuk-ri (官北里) suspected of being components to the historical records of Muwang (武王)'s pond of The Chronicles of the Three States [三國史記] and Sabi Palace, respectively, yet was subjected to a restoration following a designation to national historic site. This study is focused on the distortion of authenticity identified in the course of the "Gungnamji Pond" restoration and the invention of tradition, whose summarized conclusions are as follows. 1. Once called Maraebangjuk (마래방죽), or Macheonji (馬川池) Pond, Gungnamji Pond was existent in the form of a low-level swamp of vast area encompassing 30,000 pyeong during the Japanese colonial period. Hong, Sa-jun, who played a leading role in the restoration of "Gungnamji Pond," said that even during the 1940s, the remains of the island and stone facilities suspected of being the relics of Gungnamji Pond of the Baekje period were found, and that the traces of forming a royal palace and garden were discovered on top of them. Hong, Sa-jun also expressed an opinion of establishing a parallel between "Gungnamji Pond" and "Maraebangjuk" in connection with a 'tale of Seodong [薯童說話]' in the aftermath of the detached palace of Hwajisan, which ultimately operated as a theoretical ground for the restoration of Gungnamj Pond. Assessing through Hong, Sa-jun's sketch, the form and scale of Maraebangjuk were visible, of which the form was in close proximity to that photographed during the Japanese colonial period. 2. The minimized restoration of Gungnamji Pond faced deterrence for the land redevelopment project implemented in the 1960s, and the remainder of the land size is an attestment. The fundamental problem manifest in the restoration of Gungnamji Pond numerously attempted from 1964 through 1967 was the failure of basing the restorative work in the archaeological facts yet in the perspective of the latest generations, ultimately yielding a replication of Hyangwonji Pond of Gyeongbok Palace. More specifically, the methodologies employed in setting an island and a pavilion within a pond, or bridging an island with a land evidenced as to how Gungnamji Pond was modeled after Hyangwonji Pond of Gyeongbok Palace. Furthermore, Chihyanggyo (醉香橋) Bridge referenced in the designing of the bridge was hardly conceived as a form indigenous to the Joseon Dynasty, whose motivation and idea of the misguided restoration design at the time all the more devaluated Gungnamji Pond. Such an utterly pure replication of the design widely known as an ingredient for the traditional landscape was purposive towards the aesthetic symbolism and preference retained by Gyeongbok Palace, which was intended to entitle Gungnamji Pond to a physical status of the value in par with that of Gyeongbok Palace. 3. For its detachment to the authenticity as a historical site since its origin, Gungnamji Pond represented distortions of the landscape beauty and tradition even through the restorative process. The restorative process for such a historical monument, devoid of constructive use and certain of distortion, maintains extreme intimacy with the nationalistic cultural policy promoted by the Park, Jeong-hee regime through the 1960s and 1970s. In the context of the "manipulated discussions of tradition," the Park's cultural policy transformed the citizens' recollection into an idealized form of the past, further magnifying it at best. Consequently, many of the historical sites emerged as fancy and grand as they possibly could beyond their status quo across the nation, and "Gungnamji Pond" was a victim to this monopolistic government-led cultural policy incrementally sweeping away with new buildings and structures instituted regardless of their original space, and hence, their value.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.1-33
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• 2019

The small and medium sized enterprises (hereinafter SMEs) are already at a competitive disadvantaged when compared to large companies with more abundant resources. Manufacturing SMEs not only need a lot of information needed for new product development for sustainable growth and survival, but also seek networking to overcome the limitations of resources, but they are faced with limitations due to their size limitations. In a new era in which connectivity increases the complexity and uncertainty of the business environment, SMEs are increasingly urged to find information and solve networking problems. In order to solve these problems, the government funded research institutes plays an important role and duty to solve the information asymmetry problem of SMEs. The purpose of this study is to identify the differentiating characteristics of SMEs that utilize the public information support infrastructure provided by SMEs to enhance the innovation capacity of SMEs, and how they contribute to corporate performance. We argue that we need an infrastructure for providing information support to SMEs as part of this effort to strengthen of the role of government funded institutions; in this study, we specifically identify the target of such a policy and furthermore empirically demonstrate the effects of such policy-based efforts. Our goal is to help establish the strategies for building the information supporting infrastructure. To achieve this purpose, we first classified the characteristics of SMEs that have been found to utilize the information supporting infrastructure provided by government funded institutions. This allows us to verify whether selection bias appears in the analyzed group, which helps us clarify the interpretative limits of our study results. Next, we performed mediator and moderator effect analysis for multiple variables to analyze the process through which the use of information supporting infrastructure led to an improvement in external networking capabilities and resulted in enhancing product competitiveness. This analysis helps identify the key factors we should focus on when offering indirect support to SMEs through the information supporting infrastructure, which in turn helps us more efficiently manage research related to SME supporting policies implemented by government funded institutions. The results of this study showed the following. First, SMEs that used the information supporting infrastructure were found to have a significant difference in size in comparison to domestic R&D SMEs, but on the other hand, there was no significant difference in the cluster analysis that considered various variables. Based on these findings, we confirmed that SMEs that use the information supporting infrastructure are superior in size, and had a relatively higher distribution of companies that transact to a greater degree with large companies, when compared to the SMEs composing the general group of SMEs. Also, we found that companies that already receive support from the information infrastructure have a high concentration of companies that need collaboration with government funded institution. Secondly, among the SMEs that use the information supporting infrastructure, we found that increasing external networking capabilities contributed to enhancing product competitiveness, and while this was no the effect of direct assistance, we also found that indirect contributions were made by increasing the open marketing capabilities: in other words, this was the result of an indirect-only mediator effect. Also, the number of times the company received additional support in this process through mentoring related to information utilization was found to have a mediated moderator effect on improving external networking capabilities and in turn strengthening product competitiveness. The results of this study provide several insights that will help establish policies. KISTI's information support infrastructure may lead to the conclusion that marketing is already well underway, but it intentionally supports groups that enable to achieve good performance. As a result, the government should provide clear priorities whether to support the companies in the underdevelopment or to aid better performance. Through our research, we have identified how public information infrastructure contributes to product competitiveness. Here, we can draw some policy implications. First, the public information support infrastructure should have the capability to enhance the ability to interact with or to find the expert that provides required information. Second, if the utilization of public information support (online) infrastructure is effective, it is not necessary to continuously provide informational mentoring, which is a parallel offline support. Rather, offline support such as mentoring should be used as an appropriate device for abnormal symptom monitoring. Third, it is required that SMEs should improve their ability to utilize, because the effect of enhancing networking capacity through public information support infrastructure and enhancing product competitiveness through such infrastructure appears in most types of companies rather than in specific SMEs.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.107-122
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• 2017

Volatility in the stock market returns is a measure of investment risk. It plays a central role in portfolio optimization, asset pricing and risk management as well as most theoretical financial models. Engle(1982) presented a pioneering paper on the stock market volatility that explains the time-variant characteristics embedded in the stock market return volatility. His model, Autoregressive Conditional Heteroscedasticity (ARCH), was generalized by Bollerslev(1986) as GARCH models. Empirical studies have shown that GARCH models describes well the fat-tailed return distributions and volatility clustering phenomenon appearing in stock prices. The parameters of the GARCH models are generally estimated by the maximum likelihood estimation (MLE) based on the standard normal density. But, since 1987 Black Monday, the stock market prices have become very complex and shown a lot of noisy terms. Recent studies start to apply artificial intelligent approach in estimating the GARCH parameters as a substitute for the MLE. The paper presents SVR-based GARCH process and compares with MLE-based GARCH process to estimate the parameters of GARCH models which are known to well forecast stock market volatility. Kernel functions used in SVR estimation process are linear, polynomial and radial. We analyzed the suggested models with KOSPI 200 Index. This index is constituted by 200 blue chip stocks listed in the Korea Exchange. We sampled KOSPI 200 daily closing values from 2010 to 2015. Sample observations are 1487 days. We used 1187 days to train the suggested GARCH models and the remaining 300 days were used as testing data. First, symmetric and asymmetric GARCH models are estimated by MLE. We forecasted KOSPI 200 Index return volatility and the statistical metric MSE shows better results for the asymmetric GARCH models such as E-GARCH or GJR-GARCH. This is consistent with the documented non-normal return distribution characteristics with fat-tail and leptokurtosis. Compared with MLE estimation process, SVR-based GARCH models outperform the MLE methodology in KOSPI 200 Index return volatility forecasting. Polynomial kernel function shows exceptionally lower forecasting accuracy. We suggested Intelligent Volatility Trading System (IVTS) that utilizes the forecasted volatility results. IVTS entry rules are as follows. If forecasted tomorrow volatility will increase then buy volatility today. If forecasted tomorrow volatility will decrease then sell volatility today. If forecasted volatility direction does not change we hold the existing buy or sell positions. IVTS is assumed to buy and sell historical volatility values. This is somewhat unreal because we cannot trade historical volatility values themselves. But our simulation results are meaningful since the Korea Exchange introduced volatility futures contract that traders can trade since November 2014. The trading systems with SVR-based GARCH models show higher returns than MLE-based GARCH in the testing period. And trading profitable percentages of MLE-based GARCH IVTS models range from 47.5% to 50.0%, trading profitable percentages of SVR-based GARCH IVTS models range from 51.8% to 59.7%. MLE-based symmetric S-GARCH shows +150.2% return and SVR-based symmetric S-GARCH shows +526.4% return. MLE-based asymmetric E-GARCH shows -72% return and SVR-based asymmetric E-GARCH shows +245.6% return. MLE-based asymmetric GJR-GARCH shows -98.7% return and SVR-based asymmetric GJR-GARCH shows +126.3% return. Linear kernel function shows higher trading returns than radial kernel function. Best performance of SVR-based IVTS is +526.4% and that of MLE-based IVTS is +150.2%. SVR-based GARCH IVTS shows higher trading frequency. This study has some limitations. Our models are solely based on SVR. Other artificial intelligence models are needed to search for better performance. We do not consider costs incurred in the trading process including brokerage commissions and slippage costs. IVTS trading performance is unreal since we use historical volatility values as trading objects. The exact forecasting of stock market volatility is essential in the real trading as well as asset pricing models. Further studies on other machine learning-based GARCH models can give better information for the stock market investors.

• Journal of Animal Science and Technology
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• v.47 no.6
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• pp.963-974
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• 2005

This study was conducted to examine the growth performance, carcass characteristics, physico-chemical properties and fatty acid composition of muscle tissues of Hanwoo steers when they were fed diets containing four levels of E. ulmoides leaves. Steers were allotted to one of four dietary treatments, which were designed to progressively substitute Eucommia ulmoides for 0, 3, 5 and 10% of the rice straw in the basal diet. Seventy two Hanwoo steers (321±13kg) were used. Average daily gain (0.81-0.86kg) and feed conversion (10.05-10.59) were not changed by feeding E. ulmoides leaves. Emission of fecal ammonia gas was decreased by increasing substitution levels of E. ulmoides leaves. Emission of ammonia gas in feces of steers were significantly (p<0.05) decreased in the 5% and 10% treatments at 40℃ compared with in control (30.6ppm) and 3% treatment (29.8ppm), respectively 20.3 and 21.6ppm. Back fat thickness was higher (p<0.05) in steers fed control diet (15.0mm) than 5 and 10% E. ulmoides diets (10.2 and 10.5mm respectively). The grade ‘A’ appearances of meat yield of steers were increased up to 20% by the 3% substitution of E. ulmoides leaves, and the grades ‘1+’ and ‘1’ appearances of meat quality were significantly improved (p<0.05) by the 5 and 10% Eucommia ulmoides feeding. There was no statistical difference in meat color of loin and top round among all treatments. It appeared that the 5% and 10% E. ulmoides leaves feeding affected (p<0.05) a increase in oleic acid concentration in loin and top round muscles. The concentration of serum cholesterol was lower (p<0.05) in steers fed 10% E. ulmoides (53.3mg/100g) than that of the other treatments (55.7-57.0mg/100g). The diarrhea incidence was about 20.26% in control, while it was lower (p<0.05) in the 5 and 10% E. ulmoides leaves treatments (10.4-12.5%) than control. There was no statistical difference in the occurrences of respiratory disease among all treatments. It is concluded that E. ulmoides leaves should be a prospective feed additive because it contains various functional substances. It is likely that air-dried E. ulmoides leaves can reduce the back fat thickness of Hanwoo steers and the occurrences of diarrhea. Therefore, the 5 and 10% substitution of E. ulmoides for roughage are highly recommended to be used in practice.

• Journal of the Korean Society of Food Science and Nutrition
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• v.44 no.8
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• pp.1165-1171
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• 2015

In this study, we examined the effects of cultivation adaptability and product quality of aronia (fruit of Aronia melanocarpa) cultivated in various domestic regions. Extracts of aronia cultivated in various domestic regions and Poland were measured for their total sugar contents, acidities, total polyphenol contents, anthocyanin contents, and antioxidant activities using 1,1-diphenyl-2-picrylhydrazyl (DPPH) and ferric reducing antioxidant power (FRAP) assays. Our results showed that aronia extracts from the two countries had similar sugar contents, acidities, and anthocyanin contents. Anthocyanin is an important functional component of Aronia melanocarpa. Extracts of aronia from the two countries contained cyanidin-3-galactoside (65.5~69.1%) as the major anthocyanin compound. Aronia cultivated in C region showed higher polyphenol content (121.5%) than Poland aronia and we measured of antioxidant activities by DPPH ($IC_{50}$) and FRAP assay. Aronia cultivated in C region showed the highest antioxidant activity and polyphenol contents. Cultivation conditions of C region had sufficient sunshine and soil with pH of 6.5. From the above results, Korean aronia had similar activities with Poland aronia, which suggests that it can be a new potential development source and high technological foods.

• Korean Journal of Agricultural Science
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• v.18 no.1
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• pp.74-79
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• 1991

In order to use of new organic matter source, soil samples collected from paddy, upland and orchard treated with kraft and paper board mill sludge were analysed comparing with non-treated soil in view of some soil properties, soil microorganisms and soil enzyme activities. Also, the value of fertilizer was estimated with kraft and paper board mill sludge. 1. Paper mill sludge showed more than 55% of organic matter content, and higher total nitrogen and phosphorus, and CEC. 2. Soils treated with kraft sludge were higher contents than non-treated 2.5-3 for organic matter, 1.5-2 for total-nitrogen, 2 for $NO_3$-N, 1.5 for phosphorus and 1.4 times for CEC. Also, 12-1.9 for bacteria and 3 times for fungi, and 1.4-1.5 of cellulase, 1.5-1.8 of phosphatase and 1.5-1.8 times of urease activities. 3. Organic matter contents, number of fungi, and activities of cellulase and phosphatase in soil treated with paper board sludge were 1.4-22, 2.4, 1.5-1.6 and 1.3-1.4 times higher than non-treated soil, respectively. 4. Paper mill sludge was evaluated as a good organic matter source to increase of soil organic matter, CEC, inorganic components, soil microbes and enzyme activities.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.49 no.3
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• pp.160-166
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• 2004

This study was carried out to get the basic informations regarding the varietal variations for the physicochemical properties such as protein content, amylose content, fatty acid content, grain quality values and color properties such as lightness value, chroma and hue for the 164 recombinant inbred lines(RILs) of Milyang 23 and Gihobyeo(M/G) at the experimental farm in the Sangji University. The principal component analysis and heritability study were conducted for this experiments. The rapidity of grain filling(RCF) for the 164 M/G RILs could be classified into four groups such as slow maturing group less than 41％, mid-slow maturing group 41∼60％, fast maturing group 61∼80％ and very fast maturing group more than 81％ based on the rapidity of grain filling rate. The slow maturing group of RGF showed a little bit higher protein content 9.1％, compared to the other RGF groups. However, the amylose content of all the RGF groups revealed the same content by the groups. The very fast maturing group of RGF showed longer grain length in brown rice compared to other RGF varietal groups, in case of grain width in brown rice showed shorter than any other groups. The alkali digestive value which was so much related to gelatinization temperature showed 3.40 degree at fast maturing group of RGF in M/G RILs. However, the very fast maturing group of RGF revealed 4.31 degree of alkali digestive value. The principal component analysis was performed by the chemical and color properties such as quality value, protein content, amylose content, alkali digestive value, fatty acid content, lightness value, chroma and hue for M/G RILs. The first principal component was able to explained upto 36％ to total informations. It was corresponded to quality value, protein content, amylose content, fatty acid content, lightness value and a-value(green -1 red). The characters regarding grain quality showed high heritable properties more than 75％ of heritability, but color characters appeared relatively lower heritability compared to grain quality.

• Korean Journal of Medicinal Crop Science
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• v.13 no.3
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• pp.93-100
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• 2005

This research was performed to investigate the possibilities of industrial usage of camellia (Camellia japonica L.) by examining the antioxidant and antimicrobial effects of methanol extract with different sections. Content of total phenolics, DPPH radical scavenging activities and antibacterial activity of young leaf, mature leaf, flower bud, flower, bark, and seed of camellia were compared in vitro experimental models. Total phenolics was contained the higher in young leaf (74.62 mg), flower bud (65.02 mg) and flower (62.42 mg) but less than 20.95 mg per 100 g of dry weight in other parts of Camellia japonica L. And effects of antioxidant measured by DPPH radical scavenger activity ($RC_{50}$, reduce concentration 50%), was shown higher $7.16{\sim}18.14\;{\mu}g/m{\ell}$ in methanol extract of young leaf, flower bud and flower than $61.23\;{\mu}g/m{\ell}$ of BHT as a chemical oxidant. Also, the antimicrobial activity of Camellia japonica L. extracts determined using a paper disc method against food-borne pathogen and food spoilage bacteria, the young leaves extracts showed the most active antimicrobial activity against 7 kinds of harmful microorganisms. Flower bud extracts showed the highest antibacterial activity against P. aeruginosa and Enterobacter spp. C1036. In addition, the minimum inhibitory concentration (MIC) of young leaf extract against B. subtillis,S. fradiae,S. aureus,E. coli,P. aeruginosa, Enterobacter spp. C1036, and S. typhimurium were revealed 1 to 15 ${\mu}g/m{\ell}$. As a result, antimicrobial activity of camellia extracts was shown higher gram positive bacteria than gram negative bacteria.

• Korean Journal of Clinical Laboratory Science
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• v.49 no.3
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• pp.187-202
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• 2017

The Korean Society for Clinical Laboratory Science publishes the Korean Journal of Clinical Laboratory Science (KJCLS) as the official journal for the Korean Association of Medical Technologists. This year, 2017, marks the 50th anniversary of KJCLS. The original name was "the Korean Journal of Medical Technologists" (Volume 1, 1967~Volume 26, 1994), which was replaced with the "Korean Journal of the Clinical Laboratory Science" (Volume 27, 1995~Volume 35, 2003) and "the Korean Journal of Clinical Laboratory Science" (Volume 26, 2004~Present). The purpose of this study was to provide a framework for further development of KJCLS. In 1998, the National Research Foundation of Korea began the journal assessment service. The major domestic databases are KCI, KOFST, and KAMJE; the major international databases are SCI Index; SCI Core, SCI-Extended), SCOPUS, MEDLINE, and PUBMED. KJCLS has been registered with KCI of the National Research Foundation of Korea since 2014. More than 1,300 articles have been published, which all have made tremendous contributions to the field. To index KJCLS in the journal databases, we measured the value to understand the vocational level and social position. KJCLS is faced with a great challenge; immense effort will be needed to accomplish the original goal of KJCLS to become an internationally recognized journal. Ultimately, the goal of the Korean Society for Clinical Laboratory Science and the Korean Association of Medical Technologists should be to register KJCLS in databases such as KCI and SCOPUS.