• Proceedings of the Membrane Society of Korea Conference
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• 1999.07a
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• pp.39-42
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• 1999

Perfluoropolymers represent the ultimate resistance to hostile chemical environments and high service temperature, attributed to the presence of fluorine in the polymer backbone, i.e. to the high bond energy of C-F and C-C bonds of fluorocarbons. Copolymers of Tetrafluoroethylene (TEE) and 2, 2, 4Trifluoro-5Trifluorometoxy- 1, 3Dioxole (TTD), commercially known as HYFLON AD, are amorphous perfluoropolymers with glass transition temperature (Tg)higher than room temperature, showing a thermal decomposition temperature exceeding 40$0^{\circ}C$. These polymer systems are highly soluble in fluorinated solvents, with low solution viscosities. This property allows the preparation of self-supported and composite membranes with desired membrane thickness. Symmetric and asymmetric perfluoropolymer membranes, made with HYFLON AD, have been prepared and evaluated. Porous and not porous symmetric membranes have been obtained by solvent evaporation with various processing conditions. Asymmetric membranes have been prepared by th wet phase inversion method. Measure of contact angle to distilled water have been carried out. Figure 1 compares experimental results with those of other commercial membranes. Contact angles of about 120$^{\circ}$for our amorphous perfluoropolymer membranes demonstrate that they posses a high hydrophobic character. Measure of contact angles to hexandecane have been also carried out to evaluate the organophobic character. Rsults are reported in Figure 2. The observed strong organophobicity leads to excellent fouling resistance and inertness. Porous membranes with pore size between 30 and 80 nanometers have shown no permeation to water at pressures as high as 10 bars. However high permeation to gases, such as O2, N2 and CO2, and no selectivities were observed. Considering the porous structure of the membrane, this behavior was expected. In consideration of the above properties, possible useful uses in th field of gas- liquid separations are envisaged for these membranes. A particularly promising application is in the field of membrane contactors, equipments in which membranes are used to improve mass transfer coefficients in respect to traditional extraction and absorption processes. Gas permeation properties have been evaluated for asymmetric membranes and composite symmetric ones. Experimental permselectivity values, obtained at different pressure differences, to various single gases are reported in Tab. 1, 2 and 3. Experimental data have been compared with literature data obtained with membranes made with different amorphous perfluoropolymer systems, such as copolymers of Perfluoro2, 2dimethyl dioxole (PDD) and Tetrafluorethylene, commercialized by the Du Pont Company with the trade name of Teflon AF. An interesting linear relationship between permeability and the glass transition temperature of the polymer constituting the membrane has been observed. Results are descussed in terms of polymer chain structure, which affects the presence of voids at molecular scale and their size distribution. Molecular Dyanmics studies are in progress in order to support the understanding of these results. A modified Theodoru- Suter method provided by the Amorphous Cell module of InsightII/Discover was used to determine the chain packing. A completely amorphous polymer box of about 3.5 nm was considered. Last but not least the use of amorphous perfluoropolymer membranes appears to be ideal when separation processes have to be performed in hostile environments, i.e. high temperatures and aggressive non-aqueous media, such as chemicals and solvents. In these cases Hyflon AD membranes can exploit the outstanding resistance of perfluoropolymers.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.77-92
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• 2014

Recently, numerous documents including unstructured data and text have been created due to the rapid increase in the usage of social media and the Internet. Each document is usually provided with a specific category for the convenience of the users. In the past, the categorization was performed manually. However, in the case of manual categorization, not only can the accuracy of the categorization be not guaranteed but the categorization also requires a large amount of time and huge costs. Many studies have been conducted towards the automatic creation of categories to solve the limitations of manual categorization. Unfortunately, most of these methods cannot be applied to categorizing complex documents with multiple topics because the methods work by assuming that one document can be categorized into one category only. In order to overcome this limitation, some studies have attempted to categorize each document into multiple categories. However, they are also limited in that their learning process involves training using a multi-categorized document set. These methods therefore cannot be applied to multi-categorization of most documents unless multi-categorized training sets are provided. To overcome the limitation of the requirement of a multi-categorized training set by traditional multi-categorization algorithms, we propose a new methodology that can extend a category of a single-categorized document to multiple categorizes by analyzing relationships among categories, topics, and documents. First, we attempt to find the relationship between documents and topics by using the result of topic analysis for single-categorized documents. Second, we construct a correspondence table between topics and categories by investigating the relationship between them. Finally, we calculate the matching scores for each document to multiple categories. The results imply that a document can be classified into a certain category if and only if the matching score is higher than the predefined threshold. For example, we can classify a certain document into three categories that have larger matching scores than the predefined threshold. The main contribution of our study is that our methodology can improve the applicability of traditional multi-category classifiers by generating multi-categorized documents from single-categorized documents. Additionally, we propose a module for verifying the accuracy of the proposed methodology. For performance evaluation, we performed intensive experiments with news articles. News articles are clearly categorized based on the theme, whereas the use of vulgar language and slang is smaller than other usual text document. We collected news articles from July 2012 to June 2013. The articles exhibit large variations in terms of the number of types of categories. This is because readers have different levels of interest in each category. Additionally, the result is also attributed to the differences in the frequency of the events in each category. In order to minimize the distortion of the result from the number of articles in different categories, we extracted 3,000 articles equally from each of the eight categories. Therefore, the total number of articles used in our experiments was 24,000. The eight categories were "IT Science," "Economy," "Society," "Life and Culture," "World," "Sports," "Entertainment," and "Politics." By using the news articles that we collected, we calculated the document/category correspondence scores by utilizing topic/category and document/topics correspondence scores. The document/category correspondence score can be said to indicate the degree of correspondence of each document to a certain category. As a result, we could present two additional categories for each of the 23,089 documents. Precision, recall, and F-score were revealed to be 0.605, 0.629, and 0.617 respectively when only the top 1 predicted category was evaluated, whereas they were revealed to be 0.838, 0.290, and 0.431 when the top 1 - 3 predicted categories were considered. It was very interesting to find a large variation between the scores of the eight categories on precision, recall, and F-score.

• Journal of the Korean Institute of Landscape Architecture
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• v.43 no.1
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• pp.29-39
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• 2015

This study has attempted to determine the micro-discourse from blogs as personal media that reflect citizens' actual opinions of the Seoul Forest without intervention of experts. Furthermore, a qualitative research method discourse analysis was selected to analyze the micro-discourse regarding the Seoul Forest in a time series. The extracted samples of blogs by year were intended to identify the comment section of the process of change and the discursive structure. The results are as follows; first, from the beginning of the development of the Seoul Forest to the present, it is divided into four chronological periods along with individuals' micro-discourse with social changes. During the beginning of the development of the Seoul Forest, the social discourse was formed, and in the next period, the micro-discourse was developed with a more emotional and complex discourse. In the formative period, four or five years later, the discourse reflected the civic consciousness of development more than ever, showing the diversity of participation in the program at the Seoul Forest. In the growth period, as the users' experiences had been accumulated, the users started writing about the role of the Seoul Forest in their own words. This can also be called place discourse. From the individuals' micro-discourse, this study shows the discourse structure of how individuals think about the Seoul Forest in each period. Unlike the experts, the micro-discourse contains specific daily interactions, experiences, and the stories of individuals who actually use the parks. It also shows how users reproduce and understand the space. In this respect, this is the most significant finding of this study. Based on this research, this study has demonstrated that the emotional description of a place that actually functions as a discourse about city parks, and confirms that blogs could be used as a space to form discourse and as a research tool to read the trends. In accordance with these results, this study has described not only the discourse of experts, but also how the discourse of individuals' comments can be an important part of the discourse of modern urban parks.

• Cartoon and Animation Studies
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• s.36
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• pp.147-165
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• 2014

Around the turn of 21st century, there has been a major technological shift in the animation industry. With development of reality-based computer graphics, major American animation studios replaced hand-drawn method with the new 3D computer graphics. Traditional animation was known for its simplified shapes such as circles and triangle that makes characters' movements distinctive from non-animated feature films. Computer-generated animation has largely replaced it, but is under continuous criticism that automated movements and reality-like graphics devaluate the aesthetics of animation. Although hand-drawn animation is still produced, 3D computer graphics have taken commercial lead and there has been many changes to acting of animated characters, which calls for detailed investigation. Firstly, the changes in acting of 3D characters can be traced from looking at human-like rigging method that mimics humanistic moving mechanism. Also, if hair and clothing was part of hand-drawn characters' acting, it has now been hidden inside mathematical simulation of 3D graphics, leaving only the body to be used in acting. Secondly, looking at "Stretch and Squash" method, which represents the distinctive movements of animation, through the lens of media, a paradox arises. Hand-drawn animation are produced frame-by-frame, and a subtle change would make animated frames shiver. This slight shivering acts as an aesthetic distinction of animated feature films, but can also require exaggerated movements to hide the shivering. On the contrary, acting of 3D animation make use of calculated movements that may seem exaggerated compared to human acting, but seem much more moderate and static compared to hand-drawn acting. Moreover, 3D computer graphics add the third dimension that allows more intuitive movements - maybe animators no longer need fine drawing skills; what they now need is directing skills to animate characters in 3D space intuitively. On the assumption that technological advancement and change of artistic expressionism are inseparable, this paper compares acting of 3D animation studio Pixar and classical drawing studio Disney to investigate character acting style and movements.

• 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.18 no.1
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• pp.109-123
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• 2012

Many kinds of the education systems are provided to students. Many kinds of the contents like School subjects, license, job training education and so on are provided through many kinds of the media like text, image, video and so on. Students will apply the knowledge they learnt and will use it when they learn other things. In the existing education system, there have been many situations that the education system isn't really helpful to the students because too hard contents are transferred to them or because too easy contents are transferred to them and they learn the contents they already know again. To solve this phenomenon, a method that transfers the most proper lecture contents to the students is suggested in the thesis. Because the difficulty is relative, the contents A can be easier than the contents B to a group of the students and the contents B can be easier than the contents A to another group of the students. Therefore, it is not easy to measure the difficulty of the lecture contents. A method considering this phenomenon to transfer the proper lecture contents is suggested in the thesis. The whole lecture contents are divided into many lecture modules. The students solve the pattern recognition questions, a kind of the prior test questions, before studying the lecture contents and the system selects and provides the most proper lecture module among many lecture modules to the students according to the score about the questions. When the system selects the lecture module and transfer it to the student, the students' answer and the difficulty of the lecture modules are considered. In the existing education system, 1 kind of the content is transferred to various students. If the same lecture contents is transferred to various students, the contents will not be transferred efficiently. The system selects the proper contents using the students' pattern recognition answers. The pattern recognition question is a kind of the prior test question that is developed on the basis of the lecture module and used to recognize whether the student knows the contents of the lecture module. Because the difficulty of the lecture module reflects the all scores of the students' answers, whenever a student submits the answer, the difficulty is changed. The suggested system measures the relative knowledge of the students using the answers and designates the difficulty. The improvement of the suggested method is only applied when the order of the lecture contents has nothing to do with the progress of the lecture. If the contents of the unit 1 should be studied before studying the contents of the unit 2, the suggested method is not applied. The suggested method is introduced on the basis of the subject "English grammar", subjects that the order is not important, in the thesis. If the suggested method is applied properly to the education environment, the students who don't know enough basic knowledge will learn the basic contents well and prepare the basis to learn the harder lecture contents. The students who already know the lecture contents will not study those again and save more time to learn more various lecture contents. Many improvement effects like these and so on will be provided to the education environment. If the suggested method that is introduced on the basis of the subject "English grammar" is applied to the various education systems like primary education, secondary education, job education and so on, more improvement effects will be provided. The direction to realize these things is suggested in the thesis. The suggested method is realized with the MySQL database and Java, JSP program. It will be very good if the suggested method is researched developmentally and become helpful to the development of the Korea education.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.6
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• pp.1407-1415
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• 2006

Japan started to colonize Korea in 1910. It's when It forced and made Chosun sign on the Treaty of Protectorate. The Chosun faithfully practiced Japan's colonial policy over Korea. Futhermore, it stopped many Koreans from an anti-Japanese movement and tried to make Koreans have a positive attitude towards Japan. For this, Japan advertised the policy called Nae-sun-il-che which meant Korea and Japan were a community together from the same root. Ultimately, it targeted on absorbing Korea within their territory. With this goal, Japan kept on practicing the policy to acculturize and brainwash Koreans, totally depending on force and pressure from 1910 to 1919. However, this policy had changed by the overall anti-Japanese movement happening on March 1st 1919. Saito, the third governor-general who was appointed laster on, made an effort to win over He favor of Koreans in a less forceful way of the cultural politics. The change of policy had been specified in diverse actions such as permitting civil mass-media bodies forming the observation groups and opening conferences. In the case of daily newspapers, Japan had permitted only the ones by the Government-General of Chosun such as Maeil-shinbo, Kyunsung-ilbo, and Seoul Press before, but then other civil newspapers In Korean stated to be released. Along His Japan formed both Korean and Japanese observation groups to promote the mutual understanding and showed off Japan's goods in the propaganda films by implementing a film department. It's because Japan totally recognized and understood the impact of films. Therefore, Japan distincitively established a film agency for the production of propaganda movies while it banned the civil film production after 1937 when Japan started the war against China and USA in row. So, only one film agency, ruled by the Government-General of Chosun, produced movies from 1942 to 1945.

• Journal of the Mineralogical Society of Korea
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• v.20 no.4
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• pp.357-366
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• 2007

Microorganisms participate in a variety of geochemical processes such as weathering and formation of minerals, leaching of precious metals from minerals, and cycling of organic matter The objective of this study was to investigate biogeochemical processes of iron leaching from magnetite ore by iron-reducing bacteria isolated from intertidal flat sediments, southwestern part of Korea. Microbial iron leaching experiments were performed using magnetite ore, Shinyemi magnetite ore, in well-defined media with and without bacteria at room temperature for a month. Water soluble Fe and Mn during the leaching experiments were determined by ICP analysis of bioleached samples, and the resulting precipitated solids were characterized by X-ray diffraction (XRD) and scanning electron microscopy (SEM). The extent of iron leaching from magnetite in the aerobic conditions (Fe = 15 mg/L and Mn = 3.41 mg/L) was lower than that in the anaerobic environments (Fe = 32.8 mg/L and Mn = 5.23 mg/L). The medium pH typically decreased from 8.3 to 7.2 during a month incubation. The Eh of the initial medium decreased from +144.9 mV to -331.7 mV in aerobic environments and from -2.3 mV to -494.6 mV in anaerobic environments upon incubation with the metal reducing microorganisms. The decrease in pH is due to glucose fermentation producing organic acids and $CO_2$. The ability of bacteria to leach soluble iron from crystalline magnetite could have significant implications for biogeochemical processes in sediments where Fe(III) in magnetite represents the largest pool of electron acceptor as well as to use as a novel biotechnology for leaching precious and heavy metals from raw materials.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.33-56
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• 2016

Many researchers have focused on developing bankruptcy prediction models using modeling techniques, such as statistical methods including multiple discriminant analysis (MDA) and logit analysis or artificial intelligence techniques containing artificial neural networks (ANN), decision trees, and support vector machines (SVM), to secure enhanced performance. Most of the bankruptcy prediction models in academic studies have used financial ratios as main input variables. The bankruptcy of firms is associated with firm's financial states and the external economic situation. However, the inclusion of qualitative information, such as the economic atmosphere, has not been actively discussed despite the fact that exploiting only financial ratios has some drawbacks. Accounting information, such as financial ratios, is based on past data, and it is usually determined one year before bankruptcy. Thus, a time lag exists between the point of closing financial statements and the point of credit evaluation. In addition, financial ratios do not contain environmental factors, such as external economic situations. Therefore, using only financial ratios may be insufficient in constructing a bankruptcy prediction model, because they essentially reflect past corporate internal accounting information while neglecting recent information. Thus, qualitative information must be added to the conventional bankruptcy prediction model to supplement accounting information. Due to the lack of an analytic mechanism for obtaining and processing qualitative information from various information sources, previous studies have only used qualitative information. However, recently, big data analytics, such as text mining techniques, have been drawing much attention in academia and industry, with an increasing amount of unstructured text data available on the web. A few previous studies have sought to adopt big data analytics in business prediction modeling. Nevertheless, the use of qualitative information on the web for business prediction modeling is still deemed to be in the primary stage, restricted to limited applications, such as stock prediction and movie revenue prediction applications. Thus, it is necessary to apply big data analytics techniques, such as text mining, to various business prediction problems, including credit risk evaluation. Analytic methods are required for processing qualitative information represented in unstructured text form due to the complexity of managing and processing unstructured text data. This study proposes a bankruptcy prediction model for Korean small- and medium-sized construction firms using both quantitative information, such as financial ratios, and qualitative information acquired from economic news articles. The performance of the proposed method depends on how well information types are transformed from qualitative into quantitative information that is suitable for incorporating into the bankruptcy prediction model. We employ big data analytics techniques, especially text mining, as a mechanism for processing qualitative information. The sentiment index is provided at the industry level by extracting from a large amount of text data to quantify the external economic atmosphere represented in the media. The proposed method involves keyword-based sentiment analysis using a domain-specific sentiment lexicon to extract sentiment from economic news articles. The generated sentiment lexicon is designed to represent sentiment for the construction business by considering the relationship between the occurring term and the actual situation with respect to the economic condition of the industry rather than the inherent semantics of the term. The experimental results proved that incorporating qualitative information based on big data analytics into the traditional bankruptcy prediction model based on accounting information is effective for enhancing the predictive performance. The sentiment variable extracted from economic news articles had an impact on corporate bankruptcy. In particular, a negative sentiment variable improved the accuracy of corporate bankruptcy prediction because the corporate bankruptcy of construction firms is sensitive to poor economic conditions. The bankruptcy prediction model using qualitative information based on big data analytics contributes to the field, in that it reflects not only relatively recent information but also environmental factors, such as external economic conditions.

• The Korean Journal of Blood Transfusion
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• v.23 no.2
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• pp.115-126
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• 2012

Background: Umbilical cord (UC) is a promising source of mesenchymal stromal cells (MSCs). We compared the characteristics of MSCs from cryopreserved UC with those from fresh tissues, and demonstrated the possibility of UC cryopreservation for acquisition of MSCs from cryopreserved UC. Methods: Each UC was sliced into two types ($1{\sim}2mm^3$ vs. 0.5 cm), and cryopreserved in liquid nitrogen using different media (autologous cord blood plasma, aCBP vs. RPMI 1640). A fresh aliquot of $1{\sim}2mm^3$-sized UC was used as control tissue. After one week, the cryopreserved tissues were thawed and cultured. For the 0.5 cm UC, a slicing step into $1{\sim}2mm^3$ was needed. Cell count, viability, proliferative activity, and surface antigens were determined from harvested MSCs. Several growth factors (EGF, IGF-1, PDGF, TGF-${\beta}$, bFGF, and VEGF), were measured from the culture supernatant. Results: Eleven UC were enrolled in the study. Efficiencies of obtaining MSCs were higher in cryopreserved UC using RPMI 1640, compared with use of aCBP; the same result was observed for 0.5 cm sized UC, compared with $1{\sim}2mm^3$ sized UC. No difference in proliferative activity was observed between MSCs from fresh and cryopreserved UC. The amount of growth factors in culture supernatant using RPMI 1640 was larger than that of fresh tissues. Conclusion: We obtained growth factors from the supernatant as well as MSCs from cryopreserved UC. As with a cord blood bank, in the future, cryopreservation of UC for acquisition of both MSCs and growth factors would be possible in a time of need.