• Trans-
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• v.12
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• pp.173-222
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• 2022

This thesis examines the 'universe' acceptance phenomenon, currently used as a content strategy in the K-pop field, from the perspective of K-pop audiences, and then attempts to identify their experience of acceptance and the meaning of the universe. For this, tweets related to the universe acceptance experience of Aespa, the group utilizing the universe as a content strategy the most actively, were collected, and this data was analyzed according to a phenomenological approach, an approach to explore the structure of personal experience and the essence of a phenomenon. As a result of analyzing using Moustakas' method, the semantic structure of the universe acceptance phenomenon of K-pop audiences was derived based on 21 thematic units. It was found that current K-pop audiences are experiencing active cultural consumption rather than unilateral or passive through acceptance of the universe. This means that K-pop audiences have the characteristics of active audiences that produce meaning, interact with other fans, and exert influence on outside of community. At the same time, these characteristics affect acceptance of the universe. Simultaneously, through active acceptance experience, it is found that K-pop audiences give a new meaning in the K-pop universe, as "marketing assets", "fandom community assets", and "K-pop industry expansion assets." Among them, the recognition of 'marketing assets' was reaffirmed as a basis for supporting related previous studies. In addition, it derived the new values of the universe in the K-pop field by discovering the meaning of "fandom's specific assets" and "assets of the K-pop industry for expansion". These meanings had not been found that previous studies from the producers' point of view. And then, for the purpose of expanding the value of the universe in the future, it was discussed the direction of the new meaning of the universe. Finally, this study is meaningful in that it revealed the semantic structure of the universe acceptance phenomenon and discovered a new meaning of the universe in the K-pop field. Additionally, it was intended to contribute to expanding the field of research by suggesting various follow-up studies from various perspectives.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.4
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• pp.67-71
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• 2016

The purpose of this study was to explore olfactory sensitivity of odors from injection molding processing. To do this, the experiment was carried out in an injection molding factory, and participants were exposed to the environment where odor-substances (Formaldehyde, Benzene, Toluene, Ethylbenzene, Xylene, Styrene) exist. In addition, we used the subjective scale using semantic adjectives as an olfactory sensitivity. As a result, the assessment structure of olfactory sensitivity was composed of eight factors (irritant, thermal, tense, unique, like-dislike, active, stable, masculine), and the main factor which was irritant characteristics explained 20% of the total olfactory sensibility. These results suggested that odors from injection molding processing would cause more negative emotional responses than the flavor which is mainly used in olfactory sensitivity. This study, as a basic study of the improvement in a factory environment for the efficiency of work, has limits in that it was conducted to the extent of identifying the olfactory sensitivity structure of those who were at a laboratory and who were exposed to the environment of odor substance induced in the injection molding processing. Therefore, for the method of removing malodorous substance, the effect of materials which can neutralize it, and the comparison of a direct performance in the environment where negative sensitivity structure exists, a series of studies which aim to improve the environment of injection molding factories, such as performance assessment in the environment of a factory and an office need to be conducted. It is expected that when these studies are put together, the improvement guidelines will be provided as a type that can maximize the effectiveness of work in the factory environment where injection molding processing is done.

• Journal of the Korea Society of Computer and Information
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• v.20 no.2
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• pp.121-129
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• 2015

With the explosive growth of information about books, there is a growing number of customers who find it difficult to pick a book. Against the backdrop, the importance of a book recommendation system becomes greater, through which appropriate information about books could be offered then to encourage customers to buy a book in the end. However, existing recommendation systems based on the bibliographical information or user data reveal the reliability issue found in their recommendation results. This is why it is necessary to reflect semantic information extracted from the texts of a book's main body in a recommendation system. Accordingly, this paper suggests a method for extracting keywords from the main body of novels, as a preceding research, by using TF-IDF method as well as the text structure. To this end, the texts of 100 novels have been collected then to divide them into four structural elements of preface, dialogue, non-dialogue and closing. Then, the TF-IDF weight of each keyword has been calculated. The calculation results show that the extraction accuracy of keywords improves by 42.1% in performance when more weight is given to dialogue while including preface and closing instead of using just the main body.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.4
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• pp.253-263
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• 2021

Concrete structures are damaged by aging and external environmental factors. This type of damage is to appear in the form of cracks, to proceed in the form of spalling. Such concrete damage can act as the main cause of reducing the original design bearing capacity of the structure, and negatively affect the stability of the structure. If such damage continues, it may lead to a safety accident in the future, thus proper repair and reinforcement are required. To this end, an accurate and objective condition inspection of the structure must be performed, and for this inspection, a sensor technology capable of detecting damage area is required. For this reason, we propose a deep learning-based image processing algorithm that can detect spalling. To develop this, 298 spalling images were obtained, of which 253 images were used for training, and the remaining 45 images were used for testing. In addition, an improved loss function and data augmentation technique were applied to improve the detection performance. As a result, the detection performance of concrete spalling showed a mean intersection over union of 80.19%. In conclusion, we developed an algorithm to detect concrete spalling through a deep learning-based image processing technique, with an improved loss function and data augmentation technique. This technology is expected to be utilized for accurate inspection and diagnosis of structures in the future.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.149-162
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• 2014

Course guidance is a mentoring process which is performed before students register for coming classes. The course guidance plays a very important role to students in checking degree audits of students and mentoring classes which will be taken in coming semester. Also, it is intimately involved with a graduation assessment or a completion of ABEEK certification. Currently, course guidance is manually performed by some advisers at most of universities in Korea because they have no electronic systems for the course guidance. By the lack of the systems, the advisers should analyze each degree audit of students and curriculum information of their own departments. This process often causes the human error during the course guidance process due to the complexity of the process. The electronic system thus is essential to avoid the human error for the course guidance. If the relation data model-based system is applied to the mentoring process, then the problems in manual way can be solved. However, the relational data model-based systems have some limitations. Curriculums of a department and certification systems can be changed depending on a new policy of a university or surrounding environments. If the curriculums and the systems are changed, a scheme of the existing system should be changed in accordance with the variations. It is also not sufficient to provide semantic search due to the difficulty of extracting semantic relationships between subjects. In this paper, we model a course mentoring ontology based on the analysis of a curriculum of computer science department, a structure of degree audit, and ABEEK certification. Ontology-based course guidance system is also proposed to overcome the limitation of the existing methods and to provide the effectiveness of course mentoring process for both of advisors and students. In the proposed system, all data of the system consists of ontology instances. To create ontology instances, ontology population module is developed by using JENA framework which is for building semantic web and linked data applications. In the ontology population module, the mapping rules to connect parts of degree audit to certain parts of course mentoring ontology are designed. All ontology instances are generated based on degree audits of students who participate in course mentoring test. The generated instances are saved to JENA TDB as a triple repository after an inference process using JENA inference engine. A user interface for course guidance is implemented by using Java and JENA framework. Once a advisor or a student input student's information such as student name and student number at an information request form in user interface, the proposed system provides mentoring results based on a degree audit of current student and rules to check scores for each part of a curriculum such as special cultural subject, major subject, and MSC subject containing math and basic science. Recall and precision are used to evaluate the performance of the proposed system. The recall is used to check that the proposed system retrieves all relevant subjects. The precision is used to check whether the retrieved subjects are relevant to the mentoring results. An officer of computer science department attends the verification on the results derived from the proposed system. Experimental results using real data of the participating students show that the proposed course guidance system based on course mentoring ontology provides correct course mentoring results to students at all times. Advisors can also reduce their time cost to analyze a degree audit of corresponding student and to calculate each score for the each part. As a result, the proposed system based on ontology techniques solves the difficulty of mentoring methods in manual way and the proposed system derive correct mentoring results as human conduct.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.39-58
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• 2014

As the importance of big data and related technologies continues to grow in the industry, it has become highlighted to visualize results of processing and analyzing big data. Visualization of data delivers people effectiveness and clarity for understanding the result of analyzing. By the way, visualization has a role as the GUI (Graphical User Interface) that supports communications between people and analysis systems. Usually to make development and maintenance easier, these GUI parts should be loosely coupled from the parts of processing and analyzing data. And also to implement a loosely coupled architecture, it is necessary to adopt design patterns such as MVC (Model-View-Controller) which is designed for minimizing coupling between UI part and data processing part. On the other hand, big data can be classified as structured data and unstructured data. The visualization of structured data is relatively easy to unstructured data. For all that, as it has been spread out that the people utilize and analyze unstructured data, they usually develop the visualization system only for each project to overcome the limitation traditional visualization system for structured data. Furthermore, for text data which covers a huge part of unstructured data, visualization of data is more difficult. It results from the complexity of technology for analyzing text data as like linguistic analysis, text mining, social network analysis, and so on. And also those technologies are not standardized. This situation makes it more difficult to reuse the visualization system of a project to other projects. We assume that the reason is lack of commonality design of visualization system considering to expanse it to other system. In our research, we suggest a common information model for visualizing text data and propose a comprehensive and reusable framework, TexVizu, for visualizing text data. At first, we survey representative researches in text visualization era. And also we identify common elements for text visualization and common patterns among various cases of its. And then we review and analyze elements and patterns with three different viewpoints as structural viewpoint, interactive viewpoint, and semantic viewpoint. And then we design an integrated model of text data which represent elements for visualization. The structural viewpoint is for identifying structural element from various text documents as like title, author, body, and so on. The interactive viewpoint is for identifying the types of relations and interactions between text documents as like post, comment, reply and so on. The semantic viewpoint is for identifying semantic elements which extracted from analyzing text data linguistically and are represented as tags for classifying types of entity as like people, place or location, time, event and so on. After then we extract and choose common requirements for visualizing text data. The requirements are categorized as four types which are structure information, content information, relation information, trend information. Each type of requirements comprised with required visualization techniques, data and goal (what to know). These requirements are common and key requirement for design a framework which keep that a visualization system are loosely coupled from data processing or analyzing system. Finally we designed a common text visualization framework, TexVizu which is reusable and expansible for various visualization projects by collaborating with various Text Data Loader and Analytical Text Data Visualizer via common interfaces as like ITextDataLoader and IATDProvider. And also TexVisu is comprised with Analytical Text Data Model, Analytical Text Data Storage and Analytical Text Data Controller. In this framework, external components are the specifications of required interfaces for collaborating with this framework. As an experiment, we also adopt this framework into two text visualization systems as like a social opinion mining system and an online news analysis system.

• The Journal of the Korea Contents Association
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• v.8 no.10
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• pp.151-157
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• 2008

This study aims to construct the aged portal sites based on multimedia DB on the basis of request for systematic collection and management of the aged-related specific information which are spreading and construct Multimedia Information System for the Aged by developing digital contents to offer the aged-related information. It also tries to construct ontology based information repository for the aged that includes on/off-line. It extracts semantic relationship of each information by analysing the aged information, knows the hierarchical structure of each vocabulary, and designs and constructs an ontology based repository by designing function of each agent through that. It has also developed a variety of information and digital contents, constructed a systematic multimedia DB for the aged welfare homes, developed web framework which makes automatic registration of the aged welfare homes possible, and designed in order to support the use state of enterprises/homes and statistics state.

• Journal of The Korean Association of Information Education
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• v.10 no.2
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• pp.219-226
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• 2006

For the accurate creation of annotation information in a free-form annotation environment, the ambiguity that arises in the analysis stage between the geometric information and annotations needs to be resolved. Therefore, this This paper identifies, analyzes, and proposes presents solutions methods for the ambiguity that can occur between free-form marking and various contexts in XML-based annotation environment. The proposed method is based on context which includes various textual and structure information between free-form marking and annotated part. The proposed method show that the annotated portions areas included in the free-form marking information are more accurate, achieving more accurate exchange results amongst multiple users in a heterogeneous document environment. This study can be effectively applied to eLearning, Cyber-Class, and IETM

• Journal of KIISE:Software and Applications
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• v.31 no.9
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• pp.1180-1195
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• 2004

Due to the exponential increase of information, search and access for the Web information or service takes much time. Web information is represented through several web pages using hyperlinks and each web page is contains several topics. However. most existing web tools don't reflect such web authoring tendencies and treat it as an independent information unit. This inconsistency yields inherent problems in web browsing and searching. In this paper, we propose a web surfing assistant called LinkBroker that provides collodion pages. They are composed of relevant information extracted from several web pages that have table and frame structure in order to improve accessibility to web information. Especially, the system extracts a set of web pages that are logically connected and groups those pages using table and frame tags. Then, essential information blocks in each page of a group are extracted to construct an integrated summary page. It Provides a comprehensive view to user and one cut way to access distributed information. Experimental results show the effectiveness and usefulness of LinkBroker system.

• Journal of KIISE
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• v.42 no.3
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• pp.413-418
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• 2015

In this paper, we design new video metadata schema for searching video segments to create UEC (User Edited Contents). The proposed video metadata schema employs hierarchically structured units of 'Title-Event-Place(Scene)-Shot', and defines the fields of the semantic information as structured form in each segment unit. Since this video metadata schema is defined by analyzing the structure of existing UECs and by experimenting the tagging and searching the video segment units for creating the UECs, it helps the users to search useful video segments for UEC easily than MPEG-7 MDS (Multimedia Description Scheme) which is a general purpose international standard for video metadata schema.