• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.347-358
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• 2003

VSField-associated term is a single or compound word whose terms occur in any document, and which makes it possible to recognize a field of text by using common knowledge of human. For example, human recognizes the field of document such as or , a field name of text, when she encounters a word 'Pitcher' or 'election', respectively We Proposes an efficient construction method of field-associated terms (FTs) for specializing field to decide a field of text. We could fix document classification scheme from well-classified document database or corpus. Considering focus field we discuss levels and stability ranks of field-associated terms. To construct a balanced FT collection, we construct a single FTs. From the collections we could automatically construct FT's levels, and stability ranks. We propose a new extraction algorithms of FT's for document classification by using FT's concentration rate, its occurrence frequencies.

• The KIPS Transactions:PartB
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• v.13B no.2 s.105
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• pp.139-148
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• 2006

In the collaborative product design environment, the communication between designers is important to capture design intents and to share a common view among the different but semantically similar terms. The Semantic Web supports integrated and uniform access to information sources and services as well as intelligent applications by the explicit representation of the semantics buried in ontology. Ontologies provide a source of shared and precisely defined terms that can be used to describe web resources and improve their accessibility to automated processes. Therefore, employing ontologies on assembly modeling makes assembly knowledge accurate and machine interpretable. In this paper, we propose a framework of semantic assembly modeling using ontologies to share design information. An assembly modeling ontology plays as a formal, explicit specification of a shared conceptualization of assembly design modeling. In this paper, implicit assembly constraints are explicitly represented using OWL (Web Ontology Language) and SWRL (Semantic Web Rule Language). The assembly ontology also captures design rationale including joint intent and spatial relationships.

• Journal of The Korean Association of Information Education
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• v.25 no.3
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• pp.501-510
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• 2021

This paper was described to assess the possibility of field application of the developed textbooks by developing a textbook using action learning to conduct ICT electromagnetic waves training education for elementary and middle school teachers and applying it on a pilot basis. To this end, it was organized to be used in conjunction with classes in several subjects and provided various teaching materials to facilitate teachers' convenience to use the textbook. Also, the textbook was composed of a content structure of 10 sessions. As for the proposed textbook, the overall understanding of ICT electromagnetic waves was improved through pilot application in teacher training, and problem-solving ability, cooperative learning ability, democratic citizenship, and knowledge information processing ability were improved through action learning. It can be said that it contributed to improving the understanding of ICT electromagnetic waves and teachers' competencies.

• Journal of the Korea Society of Computer and Information
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• v.14 no.10
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• pp.73-82
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• 2009

This paper proposes a variance recovery method for character strokes that can be missed in applying the previously proposed color variance approach in text detection of natural scene images. The previous method has a shortcoming of missing the color variance due to the fixed length of horizontal and vertical windows of variance detection when the character strokes are thick or long. Thus, this paper proposes a variance recovery method by using geometric information of bounding boxes of connected components and heuristic knowledge. We have tested the proposed method using various kinds of document-style and natural scene images such as billboards, signboards, etc captured by digital cameras and mobile-phone cameras. And we showed the improved text detection accuracy even in the images of containing large characters.

• Journal of the Korea Society of Computer and Information
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• v.29 no.2
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• pp.67-78
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• 2024

Amidst the onset of the Fourth Industrial Revolution and the prominence of artificial intelligence, societal structures are undergoing significant changes. There is a heightened global interest in AI education for nurturing future talents. Consequently, this research aims to develop an AI-integrated Korean language curriculum for first-year high school students, utilizing the ADDIE model for instructional program development. To assess the program's effectiveness, pre-post assessments were conducted on future core competencies (Collaboration, Communication, Critical Thinking, Creativity) and knowledge information processing skills. The curriculum, spanning nine sessions and incorporating four small projects, sought to provide students with a new experience of AI-integrated Korean language education. As a result, students who participated in the program demonstrated improvement in future core competencies across all areas, and positive outcomes were observed in satisfaction levels and qualitative analysis. Through these findings, it is suggested that this program successfully integrates artificial intelligence into high school Korean language education, potentially contributing to the cultivation of future talents among students.

• Journal of vocational education research
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• v.35 no.4
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• pp.131-153
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• 2016

The purpose of this study was to derive evaluator's role and capability for institution accreditation evaluation of NCS-based vocational competency development training. This study attempted to explore in various ways evaluator's minute roles using Delphi method, and to derive knowledge, skill, attitude and integrity needed to verify the validity. To the end, this study conducted the Delphi research for over three rounds by selecting education training professionals and review evaluation professions as professional panels. From the results, roles of evaluators were defined as the total eight items including operator, moderator-mediator, cooperator, analyzer, verifier, institution evaluator, institution consultant, and learner, and the derived capabilities with respect to each role were 25 items in total. The area of knowledge included four items of capabilities such as HRD knowledge, NCS knowledge, knowledge of vocational competency development training, and knowledge of training institution accreditation evaluation, and the area of skill comprised fourteen items of capabilities such as conflict management ability, interpersonal relation ability, word processing ability, problem-solving ability, analysis ability, pre-preparation ability, time management ability, decision making ability, information comprehension and utilization ability, comprehensive thinking ability, understanding ability of vocational competency development training institutions, communication ability, feedback ability, and core understanding ability. The area of attitude was summarized with the seven items in total including subjectivity and fairness, service mind, sense of calling, ethics, self-development, responsibility, and teamwork. The knowledge, skill and attitude derived from the results of this study may be utilized to design and provide education programs conducive to qualitative and systematic accreditation and assessment to evaluators equipped with essential prerequisites. It is finally expected that this study will be helpful for designing module education programs by ability and for managing evaluator's quality in order to perform pre-service education and in-service education according to evaluator's experience and role.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.768-770
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• 2015

We performed integration and standardization of the omics data related agriculture. To do this, we requires progressed computational methods and bioinformatics infrastructures for integration, standardization, mining, and analysis. It makes easier biological knowledge to find. we potentialize registration a row and processed data in NABIC (National Agricultural Biotechnology Information Center) and its processed analysis results were offered related researchers. And we also provided various analysis pipelines, NGS analysis (Reference assembly, RNA-seq), GWAS, Microbial community analysis. In addition, the our system was carried out based on the design and build the quality assurance in management omics information system and constructed the infrastructure for utilization of omics analyze system. We carried out major improvement quality of omics information system. First is Improvement quality of registration category for omics based information. Second is data processing and development platform for web UI about related omics data. Third is development of proprietary management information for omics registration database. Forth is management and development of the statistics module producers about omics data. Last is Improvement the standard upload/ download module for Large omics Registration information.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.6
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• pp.279-290
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• 2013

In digital forensics log files have been stored as a form of large data for the purpose of tracing users' past behaviors. It is difficult for investigators to manually analysis the large log data without clues. In this paper, we propose a text mining technique for extracting intrusion logs from a large log set to recommend reliable evidences to investigators. In the training stage, the proposed method extracts intrusion association words from a training log set by using Apriori algorithm after preprocessing and the probability of intrusion for association words are computed by combining support and confidence. Robinson's method of computing confidences for filtering spam mails is applied to extracting intrusion logs in the proposed method. As the results, the association word knowledge base is constructed by including the weights of the probability of intrusion for association words to improve the accuracy. In the test stage, the probability of intrusion logs and the probability of normal logs in a test log set are computed by Fisher's inverse chi-square classification algorithm based on the association word knowledge base respectively and intrusion logs are extracted from combining the results. Then, the intrusion logs are recommended to investigators. The proposed method uses a training method of clearly analyzing the meaning of data from an unstructured large log data. As the results, it complements the problem of reduction in accuracy caused by data ambiguity. In addition, the proposed method recommends intrusion logs by using Fisher's inverse chi-square classification algorithm. So, it reduces the rate of false positive(FP) and decreases in laborious effort to extract evidences manually.

• The KIPS Transactions:PartD
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• v.17D no.1
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• pp.1-8
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• 2010

Association rule mining techniques enable us to acquire knowledge concerning sales patterns among individual items from voluminous transactional data. Certainly, one of the major purposes of association rule mining is utilizing the acquired knowledge to provide marketing strategies such as catalogue design, cross-selling and shop allocation. However, this requires too much time and high cost to only extract the actionable and profitable knowledge from tremendous numbers of discovered patterns. In currently available literature, a number of interest measures have been devised to accelerate and systematize the process of pattern evaluation. Unfortunately, most of such measures, including support and confidence, are prone to yielding impractical results because they are calculated only from the sales frequencies of items. For instance, traditional measures cannot differentiate between the purchases in a small basket and those in a large shopping cart. Therefore, some adjustment should be made to the size of market baskets because there is a strong possibility that mutually irrelevant items could appear together in a large shopping cart. Contrary to the previous approaches, we attempted to consider market basket's size in calculating interest measures. Because the devised measure assigns different weights to individual purchases according to their basket sizes, we expect that the measure can minimize distortion of results caused by accidental patterns. Additionally, we performed intensive computer simulations under various environments, and we performed real case analyses to analyze the correctness and consistency of the devised measure.

• The KIPS Transactions:PartD
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• v.18D no.4
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• pp.275-286
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• 2011

The purpose of this study is to find the beneficial plan for business success by the advantage of social media service in the business organization. There is few research for applying social media on a variety of fields in business organization although many companies are trying to find the way for its application. Hence, this study identifies the possibility for the utilization of social media services, and it also finds the plan for their effective application. The social relationship is created by increasing communications between users of social media service. The research model is established on the basis of the hypothesis that the social relationship affects knowledge share, pursuit of ego, social participation, amusement. To maximize the impact of results, the research was conducted on the basis of the target on two groups including the business men and non-business men who use social media services. As results of the research, the business men tend to appeal their impression based on sharing knowledge with anonymous people. Also, it is necessary to make a social participation to a management participation, and to utilize the social media in the organization by including amusement to its function. This research is expected to have significant implication to companies which wants to apply social media services in the future.