• Journal of the Korean Institute of Landscape Architecture
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• v.44 no.1
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• pp.51-65
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• 2016

A syllabus can be considered to be a masterplan for good educational results. This study tries to diagnose the current status of landscape architectural design education and suggest improvement strategies for better landscape design courses through the analysis of the syllabi of mid-level landscape design studio classes collected from the four-year undergraduate programs. The findings and suggestions are as follows. First, it is necessary to take advantage of a syllabus as a contract as well as a plan and a learning tool. Second, it is crucial to make more detailed statement from the perspectives of learners. Third, more customized components for design courses should be developed; the syllabus should give the structure of a design class as an integration and synthesis of other courses. Fourth, it is necessary to increase the interrelationship and relevance among the components, especially between course objectives and evaluation criteria, and course activities and references. Fifth, a syllabus needs to function as a communication tool in a flexible manner. Sixth, a syllabus needs to give a comprehensive information about the site and the design project. Finally, instructors need to introduce a set of detailed evaluation rubrics or criteria acceptable to students in order to increase the fairness and transparency of the evaluation.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.6
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• pp.517-523
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• 2002

In this paper, we propose system that apply VIBL method to add speech recognition to LIBL method based on human s studying method to use natural language to steering system of ship, MERCS and winch appliances and use VIBL method to alternate process that linguistic instruction such as officer s steering instruction is achieved via ableman and control steering gear, MERCS and winch appliances. By specific method of study, ableman s suitable steering manufacturing model embodies intelligent steering gear controlling system that embody and language direction base studying method to present proper meaning element and evaluation rule to steering system of ship apply and respond more efficiently on voice instruction of commander using fuzzy inference rule. Also we embody system that recognize voice direction of commander and control MERCS and winch appliances. We embodied steering manufacturing model based on ableman s experience and presented rudder angle for intelligent steering system, compass bearing arrival time, evaluation rule to propose meaning element of stationary state and correct steerman manufacturing model rule using technique to recognize voice instruction of commander and change to text and fuzzy inference. Also we apply VIBL method to speech recognition ship control simulator and confirmed the effectiveness.

• Korean journal of communication and information
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• v.52
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• pp.48-68
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• 2010

In covering the controversies surrounding the so-called cyber defamation laws, the Korean press offered competitive frames in terms of values (security vs. freedom of speech) and attributional patterns (episodic vs. thematic attribution). By attending to core values and attributional patterns as two essential components of news frames, this study explored the cognitive and affective processes of value and attributional framing and their effects on issue opinion. According to a 3-group online experiment, first, it was found that core values increased the perceived importance of relevant beliefs, which further affected individuals' attitudes toward the laws. The affective effects of core values were also found marginally significant. The value of security increased the intensity of anger toward deviant netizens (so-called defamatory repliers), and it further increased individuals' support for the laws. It was not substantiated, however, that individualistic attribution, than social attribution, would provoke stronger anger toward defamatory repliers. Instead, episodic frames appeared to be more effective in driving issue opinion as indicated by the value frame.

• Journal of Intelligence and Information Systems
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• v.11 no.1
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• pp.123-151
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• 2005

In the world of Web pages, there are oceans of documents in natural language texts and tables. To extract rules from Web pages and maintain consistency between them, we have developed the framework of XRML(extensible Rule Markup Language). XRML allows the identification of rules on Web pages and generates the identified rules automatically. For this purpose, we have designed the Rule Identification Markup Language (RIML) that is similar to the formal Rule Structure Markup Language (RSML), both as pares of XRML. RIML is designed to identify rules not only from texts, but also from tables on Web pages, and to transform to the formal rules in RSは syntax automatically. While designing RIML, we considered the features of sharing variables and values, omitted terms, and synonyms. Using these features, rules can be identified or changed once, automatically generating their corresponding RSML rules. We have conducted an experiment to evaluate the effect of the RIML approach with real world Web pages of Amazon.com, BamesandNoble.com, and Powells.com We found that $97.7\%$ of the rules can be detected on the Web pages, and the completeness of generated rule components is $88.5\%$. This is good proof that XRML can facilitate the extraction and maintenance of rules from Web pages while building expert systems in the Semantic Web environment.

• Journal of KIISE:Software and Applications
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• v.35 no.10
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• pp.608-615
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• 2008

In Knowledge Q&A services where information is created by unspecified users, document quality is an important factor of user satisfaction with search results. Previous work on quality prediction of Knowledge Q&A documents evaluate the quality of documents by using non-textual information, such as click counts and recommendation counts, and focus on enhancing retrieval performance by incorporating the quality measure into retrieval model. Although the non-textual information used in previous work was proven to be useful by experiments, data sparseness problem may occur when predicting the quality of newly created documents with such information. To solve data sparseness problem of non-textual features, this paper proposes new features for document quality prediction, namely text-confidence features, which indicate how trustworthy the content of a document is. The proposed features, extracted directly from the document content, are stable against data sparseness problem, compared to non-textual features that indirectly require participation of service users in order to be collected. Experiments conducted on real world Knowledge Q&A documents suggests that text-confidence features show performance comparable to the non-textual features. We believe the proposed features can be utilized as effective features for document quality prediction and improve the performance of Knowledge Q&A services in the future.

• Science of Emotion and Sensibility
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• v.16 no.2
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• pp.195-206
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• 2013

The main causes of traffic accidents while driving a car is of the driver's visual distraction. In this study, the color sensitivity of the information projected on the windshield were evaluated for HUD (Head Up Display) system which helps the driver's eyes on the road while driving. The driving Information were projected $9^{\circ}$ downward from front sight $0^{\circ}$ under lab's fluorescent lights, LED floorlights and the TV had having 25 [lux] illumination when driving at night environment and 100,000 [lux] of daylight environment. Munsell color hue of the basic five colors (R, Y, G, B, P) and the color of traffic lights YR, W were the color of the seven characters, each character were outlined by White, Gray except for W. Total of 19 experimental stimuli was shown in the environment of day and night driving for asking visibility information of color, fatigue, preferences, and evaluate the degree of interference. The results came out that the bright Y and G color is visibility significantly for daylight. Second, with the outline of the text, the color of the outline works as a background for luminance contrast effects and affects visibility. Third, without the outline, the glass in front of the vehicle acts as the background and the luminance contrast of characters achieve greater brightness and visibility. The luminance contrast between the stimuli and background should be considered for increasing color visibility for driving information which is an important factor for HUD commercialization.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.3
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• pp.319-327
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• 2016

Korea faces a wide range of problems in areas such as safety, environment, and traffic due to the rapid economic development and urbanization process. Despite the local governments’ efforts to deal with electronic civil complaints and solve urban problems, civil complaints have been on the increase year by year. In this study, we collected civil complaint data over the last six years from a small and medium-sized city, Jinju-si. In order to conduct a spatial distribution pattern analysis, we indicated the location data on the area through Geocoding after classifying the reasons for civil complaints and then extracted the location data of the civil complaint occurrence spots in order to analyze the correlation between electronic civil complaints and land use. Results demonstrated that electronic civil complaints in Jinju-si were clustered in residential, central commercial, and residential-industrial mixed-use areas—areas where land development had been completed within the city center. After analyzing the civil complaints according to the land use, results revealed that complaints about illegal parking were the highest. Regarding the analysis results of facility distribution within a 50m radius from the civil complaint areas, civil complaints occurred a lot in detached housing areas located within the commercial and residential-industrial mixed-use areas. In the case of residential areas(old downtown), civil complaints were condensed in the areas with many ordinary restaurants. This research explored civil complaints in terms of the urban space and can be expected to be effectively utilized in finding solutions to the civil complaints

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.5
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• pp.640-649
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• 2018

This study analyzed the consumer awareness of cycling wear using web mining, one of the big data analysis methods. For this, the texts of postings and comments related to cycling wear from 2006 to 2017 at Naver cafe, 'people who commute by bicycle' were collected and analyzed using R packages. A total of 15,321 documents were used for data analysis. The keywords of cycling wear were extracted using a Korean morphological analyzer (KoNLP) and converted to TDM (Term Document Matrix) and co-occurrence matrix to calculate the frequency of the keywords. The most frequent keyword in cycling wear was 'tights', including the opinion that they feel embarrassed because they are too tight. When they purchase cycling wear, they appeared to consider 'price', 'size', and 'brand'. Recently 'low price' and 'cost effectiveness' have become more frequent since 2016 than before, which indicates that consumers tend to prefer practical products. Moreover, the findings showed that it is necessary to improve not only the design and wearability, but also the material functionality, such as sweat-absorbance and quick drying, and the function of pad. These showed similar results to previous studies using a questionnaire. Therefore, it is expected to be used as an objective indicator that can be reflected in product development by real-time analysis of the opinions and requirements of consumers using web mining.

• Journal of the Korean Society for information Management
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• v.23 no.2
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• pp.265-285
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• 2006

In text categorization a certain level of correctness of labels assigned to training documents is assumed without solid knowledge on that of real-world collections. Our research attempts to explore the quality of pre-assigned subject categories in a real-world collection, and to identify the relationship between the quality of category assignment in training set and text categorization performance. Particularly, we are interested in to what extent the performance can be improved by enhancing the quality (i.e., correctness) of category assignment in training documents. A collection of 1,150 abstracts in computer science is re-classified by an expert group, and divided into 907 training documents and 227 test documents (15 duplicates are removed). The performances of before and after re-classification groups, called Initial set and Recat-1/Recat-2 sets respectively, are compared using a kNN classifier. The average correctness of subject categories in the Initial set is 16%, and the categorization performance with the Initial set shows 17% in $F_1$ value. On the other hand, the Recat-1 set scores $F_1$ value of 61%, which is 3.6 times higher than that of the Initial set.

• Journal of the Korean Society for information Management
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• v.25 no.1
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• pp.211-233
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• 2008

This study examines various weighting methods for improving the performance of automatic classification based on Rocchio algorithm on two collections(LISA, Reuters-21578). First, three factors for weighting are identified as document factor, document factor, category factor for each weighting schemes, the performance of each was investigated. Second, the performance of combined weighting methods between the single schemes were examined. As a result, for the single schemes based on each factor, category-factor-based schemes showed the best performance, document set-factor-based schemes the second, and document-factor-based schemes the worst. For the combined weighting schemes, the schemes(idf*cat) which combine document set factor with category factor show better performance than the combined schemes(tf*cat or ltf*cat) which combine document factor with category factor as well as the common schemes (tfidf or ltfidf) that combining document factor with document set factor. However, according to the results of comparing the single weighting schemes with combined weighting schemes in the view of the collections, while category-factor-based schemes(cat only) perform best on LISA, the combined schemes(idf*cat) which combine document set factor with category factor showed best performance on the Reuters-21578. Therefore for the practical application of the weighting methods, it needs careful consideration of the categories in a collection for automatic classification.