• Journal of the Korean Society for Marine Environment & Energy
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• v.13 no.1
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• pp.18-29
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• 2010

Offshore subsurface storage of $CO_2$ is regarded as one of the most promising options to response severe climate change. Marine geological storage of $CO_2$ is to capture $CO_2$ from major point sources, to transport to the storage sites and to store $CO_2$ into the offshore subsurface geological structure such as the depleted gas reservoir and deep sea saline aquifer. Since 2005, we have developed relevant technologies for marine geological storage of $CO_2$. Those technologies include possible storage site surveys and basic designs for $CO_2$ transport and storage processes. To design a reliable $CO_2$ marine geological storage system, we devised a hypothetical scenario and used a numerical simulation tool to study its detailed processes. The process of transport $CO_2$ from the onshore capture sites to the offshore storage sites can be simulated with a thermodynamic equation of state. Before going to main calculation of process design, we compared and analyzed the relevant equation of states. To evaluate the predictive accuracies of the examined equation of states, we compare the results of numerical calculations with experimental reference data. Up to now, process design for this $CO_2$ marine geological storage has been carried out mainly on pure $CO_2$. Unfortunately the captured $CO_2$ mixture contains many impurities such as $N_2$, $O_2$, Ar, $H_{2}O$, $SO_{\chi}$, $H_{2}S$. A small amount of impurities can change the thermodynamic properties and then significantly affect the compression, purification and transport processes. This paper analyzes the major design parameters that are useful for constructing onshore and offshore $CO_2$ transport systems. On the basis of a parametric study of the hypothetical scenario, we suggest relevant variation ranges for the design parameters, particularly the flow rate, diameter, temperature, and pressure.

• Archives of design research
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• v.19 no.2 s.64
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• pp.241-250
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• 2006

Hangeul as the Korean unique characters were invented according to some character-making principles and based on scholars' exhaustive researches. While most of the characters in the world evolved naturally, Hangeul was invented based on a precise linguistic analysis of the time, and therefore, it is most scientific and reasonable among various characters throughout the world. Nevertheless, Hangeul typeface designs do not seem to inherit the ideology of scientific and reasonable Hangeul correctly. For the square forms have been used intact due to the influences from the Chinese characters which prevailed during the time. If a single set of square characters should be designed, as much as 11,172 fonts should be designed, which suggests that advantages of Mangeul may not well be used fully; Hangeul was invented to visualize every sound with the combinations of 28 vowels and consonants. Problems of such square fonts began to be identified since 1900's when typewriters were introduced first from the West. Since a typewriter is designed with 28 characters laid out on its keyboard by using such combinations, the letters may be easily combined on it. The so-called the flexibility square-format typeface was born as such. Specially, the three-pairs fonts of these can be combined up to 67 letters including vowels and consonants. The three-pairs fonts system can help to solve the problems arising form the conventional square fonts and inherit the original ideology of Hangeul invention. This study aims to review the history of the three-pairs fonts designs facilitated by mechanic encoding of Hangeul and thereupon, suggest some desirable directions for future Hangeul fonts. Since the flexibility square-format typeface is expected to evolve more and more owing to development of the digital technology, they would serve our age of information in terms of both functions and convenience. Just as Hunminjongum tried to be literally independent from the Chinese characters, so the flexibility square-format typeface designs would serve to recover identity of our Hangeul font designs.

• Restorative Dentistry and Endodontics
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• v.20 no.2
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• pp.699-720
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• 1995

This study was conducted to evaluate the effect of benzalkonium chloride solution as a wetting agent instead of water on dentin bonding with NTG-GMA/BPDM system (All-bond 2, Bisco.) and DSDM system (Aelitebond, Bisco.). Benzalkonium chloride solution is a chemical disinfectant widely used in medical and dental clinics for preoperative preparation of skin and mucosa due to its strong effect of cationic surface active detergent. Eighty freshly extracted bovine lower incisor were grinded labially to expose flat dentin surface, and then were acid-etched with 10 % phosphoric acid for 15 second, water-rinsed, and dried for 10 second with air syringe. The specimens were randomly divided into 8 groups of 10 teeth. The specimens of control group were remoistured with water and the specimens of experimental groups were remoistured with 0.1 %, 0.5 %, and 1.0 % benzalkonium chloride solution respectively. And then, the Aelitefil composite resin was bonded to the pretreated surface of the specimens by use of All-bond 2 dentin bonding system or Aelitebond dentin bonding system in equal number of the specimens. The bonded specimens were stored in $37^{\circ}C$ distilled water for 24 hours, then the tensile bond strength was measured, the mode of failure was observed, the fractured dentin surface were examined under scanning electron microscopy, and FT-IR spectroscopy was taken for the purpose of investigating the changes of the dentin surface pretreated with benzal konium chloride solution followed by each primer of the dentin bonding systems. The results were as follows : In the group of bonding with NTG-GMA/BPDM dentin bonding agent(All-bond 2), higher tensile bond strength was only seen in the experimental group remoistured with 0.1 % benzal konium chloride solution than that in water-remoistured control group(p<0.05). In the group of bonding with DSDM dentin bonding agent (Aelitebond), no significant differences were seen between the control and each one of the experimental group(p<0.05). Higher tensile bond strength were seen in NTG-GMAIBPDM dentin bonding agent group than in DSDM dentin bonding agent group regardless of remoistur ization with benzal konium chloride solution. On the examination of failure mode, cohesive and mixed failure were predominantly seen in the group of bonding with NTG-GMAIBPDM dentin bonding agent, while adhesive failure was predominantly seen in the group of bonding with DSDM dentin bonding agent. On SEM examination of fractured surfaces, no differences of findings of primed dentin surface between the groups with and without remoisturization with benzal konium chloride solution. FT-IR spectroscopy taken from the control and the experimental group reve::.led that some higher absorbance derived from the primers binding to dentin surface was seen at the group pretreated with 0.1 % benzal konium chloride solution than at the control group of remoisturizing with water.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.65-82
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• 2015

Recently, there has been a surge of interest in finding core issues and analyzing emerging trends for the future. This represents efforts to devise national strategies and policies based on the selection of promising areas that can create economic and social added value. The existing studies, including those dedicated to the discovery of future promising fields, have mostly been dependent on qualitative research methods such as literature review and expert judgement. Deriving results from large amounts of information under this approach is both costly and time consuming. Efforts have been made to make up for the weaknesses of the conventional qualitative analysis approach designed to select key promising areas through discovery of future core issues and emerging trend analysis in various areas of academic research. There needs to be a paradigm shift in toward implementing qualitative research methods along with quantitative research methods like text mining in a mutually complementary manner. The change is to ensure objective and practical emerging trend analysis results based on large amounts of data. However, even such studies have had shortcoming related to their dependence on simple keywords for analysis, which makes it difficult to derive meaning from data. Besides, no study has been carried out so far to develop core issues and analyze emerging trends in special domains like the aviation industry. The change used to implement recent studies is being witnessed in various areas such as the steel industry, the information and communications technology industry, the construction industry in architectural engineering and so on. This study focused on retrieving aviation-related core issues and emerging trends from overall research papers pertaining to aviation through text mining, which is one of the big data analysis techniques. In this manner, the promising future areas for the air transport industry are selected based on objective data from aviation-related research papers. In order to compensate for the difficulties in grasping the meaning of single words in emerging trend analysis at keyword levels, this study will adopt topic analysis, which is a technique used to find out general themes latent in text document sets. The analysis will lead to the extraction of topics, which represent keyword sets, thereby discovering core issues and conducting emerging trend analysis. Based on the issues, it identified aviation-related research trends and selected the promising areas for the future. Research on core issue retrieval and emerging trend analysis for the aviation industry based on big data analysis is still in its incipient stages. So, the analysis targets for this study are restricted to data from aviation-related research papers. However, it has significance in that it prepared a quantitative analysis model for continuously monitoring the derived core issues and presenting directions regarding the areas with good prospects for the future. In the future, the scope is slated to expand to cover relevant domestic or international news articles and bidding information as well, thus increasing the reliability of analysis results. On the basis of the topic analysis results, core issues for the aviation industry will be determined. Then, emerging trend analysis for the issues will be implemented by year in order to identify the changes they undergo in time series. Through these procedures, this study aims to prepare a system for developing key promising areas for the future aviation industry as well as for ensuring rapid response. Additionally, the promising areas selected based on the aforementioned results and the analysis of pertinent policy research reports will be compared with the areas in which the actual government investments are made. The results from this comparative analysis are expected to make useful reference materials for future policy development and budget establishment.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.1-13
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• 2015

As opinion mining in big data applications has been highlighted, a lot of research on unstructured data has made. Lots of social media on the Internet generate unstructured or semi-structured data every second and they are often made by natural or human languages we use in daily life. Many words in human languages have multiple meanings or senses. In this result, it is very difficult for computers to extract useful information from these datasets. Traditional web search engines are usually based on keyword search, resulting in incorrect search results which are far from users' intentions. Even though a lot of progress in enhancing the performance of search engines has made over the last years in order to provide users with appropriate results, there is still so much to improve it. Word sense disambiguation can play a very important role in dealing with natural language processing and is considered as one of the most difficult problems in this area. Major approaches to word sense disambiguation can be classified as knowledge-base, supervised corpus-based, and unsupervised corpus-based approaches. This paper presents a method which automatically generates a corpus for word sense disambiguation by taking advantage of examples in existing dictionaries and avoids expensive sense tagging processes. It experiments the effectiveness of the method based on Naïve Bayes Model, which is one of supervised learning algorithms, by using Korean standard unabridged dictionary and Sejong Corpus. Korean standard unabridged dictionary has approximately 57,000 sentences. Sejong Corpus has about 790,000 sentences tagged with part-of-speech and senses all together. For the experiment of this study, Korean standard unabridged dictionary and Sejong Corpus were experimented as a combination and separate entities using cross validation. Only nouns, target subjects in word sense disambiguation, were selected. 93,522 word senses among 265,655 nouns and 56,914 sentences from related proverbs and examples were additionally combined in the corpus. Sejong Corpus was easily merged with Korean standard unabridged dictionary because Sejong Corpus was tagged based on sense indices defined by Korean standard unabridged dictionary. Sense vectors were formed after the merged corpus was created. Terms used in creating sense vectors were added in the named entity dictionary of Korean morphological analyzer. By using the extended named entity dictionary, term vectors were extracted from the input sentences and then term vectors for the sentences were created. Given the extracted term vector and the sense vector model made during the pre-processing stage, the sense-tagged terms were determined by the vector space model based word sense disambiguation. In addition, this study shows the effectiveness of merged corpus from examples in Korean standard unabridged dictionary and Sejong Corpus. The experiment shows the better results in precision and recall are found with the merged corpus. This study suggests it can practically enhance the performance of internet search engines and help us to understand more accurate meaning of a sentence in natural language processing pertinent to search engines, opinion mining, and text mining. Naïve Bayes classifier used in this study represents a supervised learning algorithm and uses Bayes theorem. Naïve Bayes classifier has an assumption that all senses are independent. Even though the assumption of Naïve Bayes classifier is not realistic and ignores the correlation between attributes, Naïve Bayes classifier is widely used because of its simplicity and in practice it is known to be very effective in many applications such as text classification and medical diagnosis. However, further research need to be carried out to consider all possible combinations and/or partial combinations of all senses in a sentence. Also, the effectiveness of word sense disambiguation may be improved if rhetorical structures or morphological dependencies between words are analyzed through syntactic analysis.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.117-129
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• 2015

As the Internet becomes ubiquitous, a large volume of information is posted on the Internet with exponential growth every day. Accordingly, it is not unusual that investors in stock markets gather and compile firm-specific or market-wide information through online searches. Importantly, it becomes easier for investors to acquire value-relevant information for their investment decision with the help of powerful search tools on the Internet. Our study examines whether or not the Internet helps investors assess a firm's value better by using firm-level data over long periods spanning from January 2004 to December 2013. To this end, we construct weekly-based search volume for information technology (IT) services firms on the Internet. We limit our focus to IT firms since they are often equipped with intangible assets and relatively less recognized to the public which makes them hard-to measure. To obtain the information on those firms, investors are more likely to consult the Internet and use the information to appreciate the firms more accurately and eventually improve their investment decisions. Prior studies have shown that changes in search volumes can reflect the various aspects of the complex human behaviors and forecast near-term values of economic indicators, including automobile sales, unemployment claims, and etc. Moreover, search volume of firm names or stock ticker symbols has been used as a direct proxy of individual investors' attention in financial markets since, different from indirect measures such as turnover and extreme returns, they can reveal and quantify the interest of investors in an objective way. Following this line of research, this study aims to gauge whether the information retrieved from the Internet is value relevant in assessing a firm. We also use search volume for analysis but, distinguished from prior studies, explore its impact on return comovements with market returns. Given that a firm's returns tend to comove with market returns excessively when investors are less informed about the firm, we empirically test the value of information by examining the association between Internet searches and the extent to which a firm's returns comove. Our results show that Internet searches are negatively associated with return comovements as expected. When sample is split by the size of firms, the impact of Internet searches on return comovements is shown to be greater for large firms than small ones. Interestingly, we find a greater impact of Internet searches on return comovements for years from 2009 to 2013 than earlier years possibly due to more aggressive and informative exploit of Internet searches in obtaining financial information. We also complement our analyses by examining the association between return volatility and Internet search volumes. If Internet searches capture investors' attention associated with a change in firm-specific fundamentals such as new product releases, stock splits and so on, a firm's return volatility is likely to increase while search results can provide value-relevant information to investors. Our results suggest that in general, an increase in the volume of Internet searches is not positively associated with return volatility. However, we find a positive association between Internet searches and return volatility when the sample is limited to larger firms. A stronger result from larger firms implies that investors still pay less attention to the information obtained from Internet searches for small firms while the information is value relevant in assessing stock values. However, we do find any systematic differences in the magnitude of Internet searches impact on return volatility by time periods. Taken together, our results shed new light on the value of information searched from the Internet in assessing stock values. Given the informational role of the Internet in stock markets, we believe the results would guide investors to exploit Internet search tools to be better informed, as a result improving their investment decisions.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.19-36
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• 2015

Social media is an emerging issue in content services and in current business environment. YouTube is the most representative social media service in the world. YouTube is different from other conventional content services in its open user participation and contents creation methods. To promote a content in YouTube, it is important to understand the diffusion phenomena of contents and the network structural characteristics. Most previous studies analyzed impact factors of contents diffusion from the view point of general behavioral factors. Currently some researchers use network structure factors. However, these two approaches have been used separately. However this study tries to analyze the general impact factors on the view count and content based network structures all together. In addition, when building a content based network, this study forms the network structure by analyzing user comments on 22,370 contents of YouTube not based on the individual user based network. From this study, we re-proved statistically the causal relations between view count and not only general factors but also network factors. Moreover by analyzing this integrated research model, we found that these factors affect the view count of YouTube according to the following order; Uploader Followers, Video Age, Betweenness Centrality, Comments, Closeness Centrality, Clustering Coefficient and Rating. However Degree Centrality and Eigenvector Centrality affect the view count negatively. From this research some strategic points for the utilizing of contents diffusion are as followings. First, it is needed to manage general factors such as the number of uploader followers or subscribers, the video age, the number of comments, average rating points, and etc. The impact of average rating points is not so much important as we thought before. However, it is needed to increase the number of uploader followers strategically and sustain the contents in the service as long as possible. Second, we need to pay attention to the impacts of betweenness centrality and closeness centrality among other network factors. Users seems to search the related subject or similar contents after watching a content. It is needed to shorten the distance between other popular contents in the service. Namely, this study showed that it is beneficial for increasing view counts by decreasing the number of search attempts and increasing similarity with many other contents. This is consistent with the result of the clustering coefficient impact analysis. Third, it is important to notice the negative impact of degree centrality and eigenvector centrality on the view count. If the number of connections with other contents is too much increased it means there are many similar contents and eventually it might distribute the view counts. Moreover, too high eigenvector centrality means that there are connections with popular contents around the content, and it might lose the view count because of the impact of the popular contents. It would be better to avoid connections with too powerful popular contents. From this study we analyzed the phenomenon and verified diffusion factors of Youtube contents by using an integrated model consisting of general factors and network structure factors. From the viewpoints of social contribution, this study might provide useful information to music or movie industry or other contents vendors for their effective contents services. This research provides basic schemes that can be applied strategically in online contents marketing. One of the limitations of this study is that this study formed a contents based network for the network structure analysis. It might be an indirect method to see the content network structure. We can use more various methods to establish direct content network. Further researches include more detailed researches like an analysis according to the types of contents or domains or characteristics of the contents or users, and etc.

• Journal of Korean Society of Forest Science
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• v.101 no.1
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• pp.7-19
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• 2012

After having announced legislation for threatened or endangered species on the List of Endangered and Threatened Wildlife and Plants in 2005, the Korea Ministry of Environment proposed (in June 2011) amending the list, thereby delisting or reclassifying endangered species using new quantitative criteria for two levels (I and II), as well as status reviews. The new legislation included 40 species remained in their original endangered status, but 19 species were delisted, 5 species were proposed as candidates for delisting, 29 species were given a new endangered listing, and 3 species were proposed for an endangered listing in Korea. We assessed the threatened status of 98 plants using the IUCN Red List Criteria (version 3.1) at the global level, and compared the Ministry's revised criteria with the IUCN Red List Criteria and ESA criteria used in the USA. Most species proposed by the Ministry do not qualify as threatened and one of the major difficulties found in applying IUCN Red List Criteria at the global scale was a lack of knowledge on the status of species at broader geographic scales and the perceived difficulty this causes. Under the current classification process, many endangered species, such as Abeliophyllum distichum, Leontice microrhyncha, Echinosophora koreensis, Leontopodium coreanum, Iris odaesanensis, and Corylopsis coreana at global level were excluded here. Knowledge gaps and uncertainties mean that the number of taxa at high risk of extinction may be substantially greater than is currently understood. Due to a lack of information on its taxonomic status, currently there is controversy over the Red List status of Physocarpus insularis. Also, Caragana koreana, which was an invalidly published name, should be excluded here. Although the Korea Ministry of Environment insisted this procedure was conducted by applying the modified IUCN threat categories and definitions, this evaluation has been carried out based only on subjective views and misapplication of the IUCN Red List Criteria. The current listings by the Korea Ministry of Environment should be challenged. We suggest that broad species concepts on endemic species are applied and also criteria that adequately address the proper quantitative knowledge should be used. It is suggested that the highest priorities for the Red List should be given to endemic species at least in the Korean peninsula first at global scale.

• Korean Journal of Remote Sensing
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• v.30 no.5
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• pp.597-605
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• 2014

The continuous observations for atmospheric aerosols were conducted during 3 years (2009 to 2011) by using Gwangju Institute of Science and Technology (GIST) multi-wavelength Raman lidar at Gwangju, Korea ($35.10^{\circ}N$, $126.53^{\circ}E$). The aerosol depolarization ratios calculated from lidar data were used to identify the Asian dust layer. The optical properties of Asian dust layer were different according to its vertical distribution. In order to investigate the difference between the optical properties of each individual dust layers, the transport pathway and the transport altitude of Asian dust were analyzed by Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. We consider that the variation of optical properties were influenced not only their transport pathway but also their transport height when it passed over anthropogenic pollution source regions in China. The lower particle depolarization ratio values of $0.12{\pm}0.01$, higher lidar ratio of $67{\pm}9sr$ and $68{\pm}9sr$ at 355 nm and 532 nm, respectively, and higher ${\AA}ngstr\ddot{o}m$ exponent of $1.05{\pm}0.57$ which are considered as the optical properties of pollution were found. In contrast with this, the higher particle depolarization ratio values of $0.21{\pm}0.09$, lower lidar ratio of $48{\pm}5sr$ and $46{\pm}4sr$ at 355 nm and 532 nm, respectively, and lower ${\AA}ngstr\ddot{o}m$ exponent of $0.57{\pm}0.24$ which are considered as the optical properties of dust were found. We found that the degree of mixing of anthropogenic pollutant aerosols in mixed Asian dust govern the variation of optical properties of Asian dust and it depends on their altitude when it passed over the polluted regions over China.

• Journal of Life Science
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• v.17 no.12
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• pp.1660-1668
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• 2007

The non-ionic surfactant (NIS) Tween 80 was evaluated for its ability to influence invitro cumulative gas production, dry matter digestibility, cellulolytic enzyme activities, anaerobic microbial growth rates, and adhesion to substrates by mixed rumen microorganisms on rice straw, alfalfa hay, cellulose filter paper and tall fescue hay. The addition of NIS Tween 80 at a level of 0.05% increased significantly (P<0.05) in vitro DM digestibility, cumulative gas production, microbial growth rate and cellulolytic enzyme activity from all of substrates used in this study. In vitro cumulative gas production from the NIS-treated substrates; rice straw, alfalfa hay, filter paper and tall fescue hay was significantly (P<0.05) improved by 274.8, 235.2, 231.1 and 719.5% compared with the control, when substrates were incubated for 48 hr in vitro. The addition of 0.05% NIS Tween 80 to cultures growing on alfalfa hay resulted in a significant increase in CMCase (38.1%), xylanase (121.4%), Avicelase (not changed) and amylase (38.2%) activities after 36 h incubation. These results indicated that the addition of 0.05% Tween 80 could greatly stimulate the release of some kinds of cellulolytic enzymes without decreasing cell growth rate in contrast to trends reported with aerobic microorganism. Our SEM observation showed that NIS Tween. 80 did not influence the microbial adhesion to substrates used in the study. Present data clearly show that improved gas production, DM digestibility and cellulolytic enzyme activity by Tween 80 is not due to increased bacterial adhesion on the substrates.