• Journal of information and communication convergence engineering
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• v.2 no.1
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• pp.26-31
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• 2004

In the last few years, The Semantic Web has increased the interest in ontologies. Ontology is an essential component of the semantic web. Ontologies continue to change and evolve. We consider the management of versions in ontology. We study a set of changes based on domain changes, changes in conceptualization, metadata changes, and temporal dimension. In many cases, we want to be able to search in historical versions, query changes in versions, retrieve versions on the temporal dimension. In order to support an ontology query language that supports temporal operations, we consider temporal dimension includes transaction time and valid time. Ontology versioning brings about massive amount of versions to be stored and maintained. We present the storage policies that are storing all the versions, all the sequence of changed element, all the change sets, the aggregation of change sets periodically, and the aggregation of change sets using a criterion. We conduct a set of experiments to compare the performance of each storage policies. We present the experimental results for evaluating the performance of different storage policies from scheme 1 to scheme 5.

• Korean Linguistics
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• v.48
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• pp.333-354
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• 2010

When defining the word related to passive and causative in Korean dictionary, the meaning of headword can be explained by linking them to other related words. The link could be expressed into two forms; the one is 'passive verb causative verb of A' and the other is 'passive form causative form of A.' Whichever the dictionary takes, the important thing is that the content to which it refer should be correct. However the format of 'passive verb causative verb of A' and 'passive form causative form of A' is problematic because the definition of headword does not contain semantic information but syntactic or morphological information. Generic concept 'passive form causative form' and 'passive verb causative verb' refers to respectively morphological and syntactic level but specific concept 'A' refers to semantic level. These morphological, syntactic and semantic level can not be a same dimension so the size of their denotation can not be compared. The way of transform syntactic dimension 'passive verb causative verb' and morphological dimension 'passive form causative form' into semantic dimension is removing 'verb' and 'form' from 'passive verb causative verb' and 'passive form causative form' respectively. Therefore the expression 'passive verb causative verb of A' or 'passive form causative form of A' ought be changed into 'passive causative of A.'

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.10
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• pp.2643-2657
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• 2023

Scene graphs are structured representations that can clearly convey objects and the relationships between them, but are often heavily biased due to the highly skewed, long-tailed relational labeling in the dataset. Indeed, the visual world itself and its descriptions are biased. Therefore, Unbiased Scene Graph Generation (USGG) prefers to train models to eliminate long-tail effects as much as possible, rather than altering the dataset directly. To this end, we propose Geometric and Semantic Improvement (GSI) for USGG to mitigate this issue. First, to fully exploit the feature information in the images, geometric dimension and semantic dimension enhancement modules are designed. The geometric module is designed from the perspective that the position information between neighboring object pairs will affect each other, which can improve the recall rate of the overall relationship in the dataset. The semantic module further processes the embedded word vector, which can enhance the acquisition of semantic information. Then, to improve the recall rate of the tail data, the Class Balanced Seesaw Loss (CBSLoss) is designed for the tail data. The recall rate of the prediction is improved by penalizing the body or tail relations that are judged incorrectly in the dataset. The experimental findings demonstrate that the GSI method performs better than mainstream models in terms of the mean Recall@K (mR@K) metric in three tasks. The long-tailed imbalance in the Visual Genome 150 (VG150) dataset is addressed better using the GSI method than by most of the existing methods.

• Journal of the Korean Society of Clothing and Textiles
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• v.29 no.6
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• pp.793-804
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• 2005

The new paradigm of the 21st century demand an openly different world of formative ideologies in respect to art and design. The purpose of this study is focused on trying to comprehend aesthetic essence of clothing as an, with the investigation of artistic theories manifested by art philosophers. Art to Wear was categorized into style to understand its artistic meaning as well as to analyze its character. Upon the foundation of semiotics theory, the feature of Art to Wear and its analysis category were argued in the context of Charles Morris three dimension of semiotics analysis. The conclusion to the research is like so. The feature and analysis category of Art to Wear upon a semiotics perspective was divided into syntactic dimension, semantic dimension and pragmatic dimension. The analytical categorization upon the perspective of syntactic dimension fell into the category of topology, shape and color. The semantic dimension of Art to Wear was divided into categories of denotation and connotation. In addition, the pragmatic dimension of Art to Wear analytical categorization was divided into a delivering function and common function.

• Journal of the Korean Society of Clothing and Textiles
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• v.22 no.5
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• pp.597-606
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• 1998

The purposes of the study were 1) to evaluate the visual image of colored Korean traditional dress for woman 2) to analyze the colors and, color combinations effect on the image perception using gestalt theory. The research method was a quasi-experimental with a between subjects design. The experimental materials developed for the study were a set of stimuli and a response scale. The stimuli was consisted of 17 drawings of females wearing Korean tradinational dress, by using CAD simulation. A response scale consisted of semantic differential scales. The subjects were 1138 undergraduate students of Taejon city, Chungnam province and Chungbuk province. Their responses to the semantic differential scales were analyzed using factor analysis, one-way ANOVA, Duncan's multiple range test, 1-test. Results were as follows; 1) The image of the stimulus was consisted of the 4 different dimensions.(sociability, evaluation, visibility, attractiveness) 2) Clothing colors had significant effects on image perception of the evaluation dimension, visibility dimension and attractiveness dimension in the mono-color set. The blue showed the most positive image on the evaluation dimension, and the yellow and the gray showed negative image on the same dimension. The yellow showed the most salient image and the gray showed the least salient image on the visibility dimension. The red showed the most attractive image and the green showed the least attractive image on the attractiveness dimension. 3) In hi-color set stimulus, the perceived image was influenced by color combinations. The yellow blouse-the red skirt set showed the most sociable image on the sociability dimension. The blue blouse-the green skirt set showed the most positive image on the evaluation dimension. The yellow blouse-the red skirt set showed the most salient image and the blue blouse-the green skirt set showed the least salient image on the visibility dimension. And the red blouse-the yellow skirt set showed the most attractive image on the attractiveness dimension. On conclusion the visual image of Korean traditional dress wearer was affected by dress colors and color combinations.

• Asia pacific journal of information systems
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• v.19 no.1
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• pp.1-31
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• 2009

This paper empirically examines factors that potentially influence the success of a Web-based semantic search engine. A research model has been proposed that shows the impact of quality-related factors upon the effectiveness of a semantic search engine, based on DeLone and McLean's(2003) information systems success model. An empirical study has been conducted to test hypotheses formulated around the research model, and statistical methods were applied to analyze gathered data and draw conclusions. Implications for academics and practitioners are offered based on the findings of the study. The proposed model includes three quality dimensions of a Web-based semantic search engine-namely, information quality, system quality and service quality. These three dimensions each have measures designed to collectively assess the respective dimension. The model is intended to examine the relationship between measures of these quality dimensions and measures of two dependent constructs, including individuals' net benefit and user satisfaction. Individuals' net benefit was measured by the extent to which the user's information needs were adequately met, whereas user satisfaction was measured by a combination of the perceived satisfaction with search results and the perceived satisfaction with the overall system. A total of 23 hypotheses have been formulated around the model, and a questionnaire survey has been conducted using a functional semantic search website created by KT and Hakia, so as to collect data to validate the model. Copies of a questionnaire form were handed out in person to 160 research associates and employees working in the area of designing and developing semantic search engines. Those who received the form, 148 respondents returned valid responses. The survey form asked respondents to use the given website to answer questions concerning the system. The results of the empirical study have indicated that, of the three quality dimensions, information quality was found to have the strongest association with the effectiveness of a Web-based semantic search engine. This finding is consistent with the observation in the literature that the aspects of the information quality should serve as a basis for evaluating the search outcomes from a semantic search engine. Measures under the information quality dimension that have a positive effect on informational gratification and user satisfaction were found to be recall and currency. Under the system quality dimension, response time and interactivity, were positively related to informational gratification. On the other hand, only one measure under the service quality dimension, reliability was found to have a positive relationship with user satisfaction. The results were based on the seven hypotheses that have been accepted. One may wonder why 15 out of the 23 hypotheses have been rejected and question the theoretical soundness of the model. However, the correlations between independent variables and dependent variables came out to be fairly high. This suggests that the structural equation model yielded results inconsistent with those of coefficient analysis, because the structural equation model intends to examine the relationship among independent variables as well as the relationship between independent variables and dependent variables. The findings offer some useful implications for owners of a semantic search engine, as far as the design and maintenance of the website is concerned. First, the system should be designed to respond to the user's query as fast as possible. Also it should be designed to support the search process by recommending, revising, and choosing a search query, so as to maximize users' interactions with the system. Second, the system should present search results with maximum recall and currency to effectively meet the users' expectations. Third, it should be capable of providing online services in a reliable and trustworthy manner. Finally, effective increase in user satisfaction requires the improvement of quality factors associated with a semantic search engine, which would in turn help increase the informational gratification for users. The proposed model can serve as a useful framework for measuring the success of a Web-based semantic search engine. Applying the search engine success framework to the measurement of search engine effectiveness has the potential to provide an outline of what areas of a semantic search engine needs improvement, in order to better meet information needs of users. Further research will be needed to make this idea a reality.

• Journal of Information Technology Applications and Management
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• v.12 no.3
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• pp.27-39
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• 2005

The Semantic Web has increased the interest in ontologies recently Ontology is an essential component of the semantic web and continues to change and evolve. We consider versions management schemes in ontology. We study a set of changes based on domain changes, changes in conceptualization, metadata changes, and temporal dimension. Our change specification is represented by a set of changes. A set of changes consists of instance data change, structural change, and identifier change. In order to support a query in ontology versions, we consider temporal dimension includes valid time. Ontology versioning brings about massive amount of versions to be stored and maintained. We present the ontology versions management schemes that are 1) storing all the change sets, 2) storing the aggregation of change sets periodically, and 3) storing the aggregation of change sets using an adaptive criterion. We conduct a set of experiments to compare the performance of each versions management schemes. We present the experimental results for evaluating the performance of the three version management schemes from scheme 1 to scheme 3. Scheme 1 has the least storage usage. The average response time in Scheme 1 is extremely large, those of Scheme 3 is smaller than Scheme 2. Scheme 3 shows a good performance relatively.

• Journal of Gifted/Talented Education
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• v.27 no.1
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• pp.17-35
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• 2017

The purpose of this study is to analyze the learning objectives characteristics of educational programs of centers for the university affiliated science-gifted education using semantic network analysis, we examined the applicability of semantic network analysis in analyzing learning objectives by comparing the results of analysis with Bloom's revised taxonomy. For this purpose, 702 learning objectives presented in 169 science subjects were selected as subjects to be analyzed. After classifying and coding the learning objectives according to Bloom's revised taxonomy, we conducted a semantic network analysis to investigate the relationship between learning objectives. The results of the analysis are as follows. First, we looked at the number of learning objectives used for each subject, and about 3 elementary school levels and about 6 middle school levels were used. Second, the knowledge dimension such as 'factual and conceptual knowledge' and cognitive process dimension such as 'remember', 'understand', and 'create' was high regardless of the research method and school level. Third, the results of analysis based on the weighting through the semantic network analysis method, the elementary school level emphasize activities th be applied to the actual experimental process through learning about scientific facts, while the middle school level emphasize the understanding of scientific facts and concepts themselves. As a result, it can be seen that the semantic network analysis can analyze characteristics of various learning objectives rather than the conventional simple statistical analysis.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.363-365
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• 2004

Ontology is an essential component of the semantic web and it continue to change and evolve. We study a set of changes based on domain changes, changes in conceptualization, metadata changes, and time dimension. Ontology versioning brings about massive amount of versions to be stored and maintained. We present several storage policies and conduct a set of experiments to compare the performance of each storage policies.

• Korean Journal of Computational Design and Engineering
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• v.7 no.3
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• pp.157-169
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• 2002

In the initial stages of ship design, designers represent geometry, arrangement, and dimension of hull structures with 2D geometric primitives such as points, lines, arcs, and drawing symbols. However, these design information(‘2D geometric primitives’) defined in the drawing sheet require more intelligent translation processes by the designers in the next design stages. Thus, the loss of design semantics could be occurred and following design processes could be delayed. In the initial design stages, it is not easy to adopt commercial 3D CAD systems, which have been developed f3r being used in detail and production design stages, because the 3D CAD systems require detailed input for geometry definition. In this study, a semantic product model data structure was proposed, and an initial structural CAD system was developed based on the proposed data structure. Contents(‘product model data and design knowledges’) of the proposed data structure are filled with minimal input of the designers, and then 3D solid model and production material information can be automatically generated as occasion demands. Finally, the applicability of the proposed semantic product model data structure and the developed initial structural CAD system was verified through application to deadweight 300,000ton VLCC(Very Large Crude oil Carrier) product modeling procedure.