• ETRI Journal
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• v.20 no.2
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• pp.192-213
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• 1998

The current approaches in Object-Oriented Analysis have limitations on modeling complex real world systems because they require priori knowledge about objects and their interactions before applying them. This may be practical in small systems and systems with clear domain knowledge, but not in large real world systems with unclear domain knowledge. Our approach uses a stepwise refinement technique in a top-down manner to the Object-Oriented Analysis stage with the application of use cases. This approach is especially good for new areas where we do not know all the information in advance. We present the approach with an example of its application to the B-ISDN service modeling and distributed systems.

• 한국디지털정책학회:학술대회논문집
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• 2005.11a
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• pp.383-389
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• 2005

The purpose of this paper is to develop the metadata on the information of research result in Science and technology and to design the domain knowledge structure using semantic web technology for further implementation. In this paper, we first analyze the existing theories and techniques related to the metadata in such fields as R&D research result, international standard, and semantic web. Then, we extract and group the relevant factors from Dublin Core, CERIF, and the research results for building the integrated metadata framework. Based on our proposed metadata, we design a domain knowledge structure which employs RDF/RDFS as knowledge representation tool. Therefore, we can implement the ontology which produce the 'intelligent' information service and improve the interoperability between the research institutions. Also, the metadata can be used as the basis for developing National R&D Performance Information, and in terms of research institutions, can be used as tools for managing the their own research results information systematically and consistently.

• Journal of Ship and Ocean Technology
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• v.5 no.3
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• pp.27-35
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• 2001

In this research, hybrid method with case-based reasoning and rule-based reasoning is applied. Using case-based reasoning, design experts'experience and know-how are effectively represented in order to obtain a proper configuration of midship section in the initial ship design stage. Since there is not sufficient domain knowledge available to us, traditional case-adaptation algorithms cannot be applied to our problem, i.e., creating the configuration of midship section. Thus, new case-adaptation algorithms not requiring any domain knowledge are developed antral applied to our problem. Using the knowledge representation of DnV rules, rule-based reasoning can perform deductive inference in order to obtain the scantling of midship section efficiently. The results from the case-based reasoning and the rule-based reasoning are examined by comparing the results with various conventional methods. And the reasonability of our results is verified by comparing the results wish actual values from parent ship.

• Proceedings of the Korean Society of Computer Information Conference
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• 2012.07a
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• pp.97-100
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• 2012

본 논문은 변환영역 기반의 방법 중 DCT 변환영역 워터마크를 이용한 이미지 무결성 검증 시스템을 제안하였다. DCT 변환영역에 워터마크를 삽입하는 것이 공간영역에 삽입하는 것보다 잡음과 일반적인 신호처리나 영상편집, 선형/비선형 필터링, 압축 등의 영상처리에 강하다. 추출된 워터마크가 원본 워터마크와의 유사도 평가에서 임계값보다 크면 이미지에 변형이 없었다고 판단한다. 만약 이미지에 변형이 있을 경우 워터마크가 훼손되어 정확한 정보를 추출하기 어려울 수 있다. 이때 추출기에서 이미지 왜곡을 역변환 시켜 워터마크를 온전하거나 최소화된 훼손으로 추출한다.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.58-65
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• 2023

Bankruptcy is a significant risk for start-up companies, but with the help of cutting-edge artificial intelligence technology, we can now predict bankruptcy with detailed explanations. In this paper, we implemented the Category Boosting algorithm following data cleaning and editing using OpenRefine. We further explained our model using the Shapash library, incorporating domain knowledge. By leveraging the 5C's credit domain knowledge, financial analysts in banks or investors can utilize the detailed results provided by our model to enhance their decision-making processes, even without extensive knowledge about AI. This empowers investors to identify potential bankruptcy risks in their business models, enabling them to make necessary improvements or reconsider their ventures before proceeding. As a result, our model serves as a "glass-box" model, allowing end-users to understand which specific financial indicators contribute to the prediction of bankruptcy. This transparency enhances trust and provides valuable insights for decision-makers in mitigating bankruptcy risks.

• Iberoamérica
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• v.13 no.1
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• pp.351-388
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• 2011

Many global business failures have been ascribed to a lack of intercultural competence, especially to a lack of an adequate conceptualization and definition of intercultural competence, focusing instead on the knowledge, skills, and attributes that appear to be its antecedents. Intercultural competence should be perceived as multifaceted important components of global management capabilities. Depending on the related concepts of intercultural competence, such as global mindset, intercultural sensitivity, and cultural intelligence, dynamic aspects of intercultural competence as learning process are suggested. Also, the domain of intercultural competence in the context of global management or business comprised three dimensions - perception management, relationship management, and self management. Each dimension is characterized by facets that further delineate aspects of intercultural competence. With respect to the domain of intercultural competence, appropriateintercultural training methods should be designed. In practice, human resource managers may benefit from gaining knowledge about which measures to use for identifying employee's weakness in intercultural competence in order to create appropriate training programs.

• Knowledge Management Research
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• v.19 no.3
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• pp.1-29
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• 2018

This study focuses on the mediating role of creativity on the knowledge management process. To confirm focal hypotheses, we conducted survey on 538 employees of foreign subsidiaries of global enterprises. Main findings are: first, creativity turned out to positively mediate the effect of knowledge transfer on the firm's performance; second, the mediating role of creativity differs depending on the domain of acquiring knowledge such as exploitation and exploration. This research found that the influence of exploitative knowledge on knowledge creation and innovative performance was stronger. As such, among tension view and foundational view, which are two competing views on the relationship between knowledge and creativity, the latter is more soundly supported.

• Journal of Information Technology Applications and Management
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• v.13 no.2
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• pp.1-15
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• 2006

This paper classifies the critical knowledge/skill set required to IS practitioners according to content or domain of knowledge : IS technology knowledge/skills, organizational and societal knowledge/skills, interpersonal knowledge/skills, and personal traits knowledge/skills. The survey reveals that Korean IS practitioners rate interpersonal knowledge/skills and personal traits knowledge/skills the most important, and organizational and societal knowledge/skills the least important. Specifically, they rate creative thinking, critical thinking, interpersonal communication skills, team working skills, personal motivation, operating systems, programming languages, DB/data warehouse, IS technological trend, networkicommunicationisecurity especially important. The survey also shows that Koran IS practitioners feel knowledge deficiency in almost all knowledge/skills areas. The results confirm that the curriculum of universities, the training and education programs of industries, and IS/IT education policy of the government should be revised as soon as possible.

• Journal of Korean Academy of Nursing
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• v.26 no.1
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• pp.73-93
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• 1996

This study aimed to analyse the test contents of the national examination for the registered nurses (NERN) over 3 years from 1991 to 1993 in Korea. In recent years in Korea, the MCQ(multiple choice question) has been showing to be a highly recognized method for assessing the qualification of registered nurses. Unfortunately, nursing faculties have found NERN had some bad MCQs through having evaluation workshop for Some MCQs often provide so many unwriting clues which become a bias of the results, and some items fell into the category of the lower level of educational taxonomy such as isolated recall a fact or data. Frequently the stems of the questions are ambigous, unclear, disputable, esoterical or trivial. Considering those fallacies of the national examination, it is very critical to review the test items to see whether it is of high quality, is more fair, reliable and objective in depth. Therefore, this study was done to provide data for the improvement of the test contents as well as the teachers's assessment skill. For this study, the ad hoc committee was composed of 16 members, including 5 education board members of Korean Academic Nurses Association and 11 nursing faculty members. This committee had one day panel discussion and filled the checklist for this study. The process of analysing data was held over 10 times during 1992-1994. The analysis focussed on educational taxonomy such as cognitive domain(knowledge), psychmotor domain (skill), affective domain(attitude) and the level of learning such as recall, understanding, problems solving, and learning area of theory and practice, and the learning content categorised by nursing process and disease process. The test analysed using difficulty index and the structure of the test items was analysed. The conclusions and suggestion as follows : 1. In learning area, the average ratio of the theory and practice was 1 : 1.1 which was less than 1 : 2 suggested by Korean National Health Institute, and the ratio was different by the 8 leaning subjects of nursing. 2. In category of the educational taxonomy, the knowledge domain was emphasized mostly（79. 7％）, the skill domain was 14.9％, and the attitude domain was 5.4％ only. 3. In the level of learning, generally, the test items of the level of recall（45.5％） and the understanding（46.3％） were covered almost and the problem solving was 8.1％. 4. In the learning contents, generally, the test items related to nursing process was 67.2％ and that of disease process was 32.8％. However, this proportion was different by the 8 leaning subjects. Even though the nursing diagnosis has been emphasized in nursing curricula recently, the test items of this was identified very few. 5. In the structure of the test item, some were not clear, incorrect grammar, unclear description and some have clues to answer. 6. In the item analysis, the non-acceptable level of the difficulty index (means too easy) was 65.7％, and the acceptable level was 33.9％. Considering the results we would like to suggest the followings, 1. Since the test items of knowledge domain was dominant, the test items of the practice domain and attitude domain should be emphasized more. 2. The regular review and analysis of NERN should be arranged in order to improve the quality of the test items which will give influence to the nursing education positively.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.3
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• pp.141-148
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• 2022

Recently, reinforcement learning combined with deep neural network technology has achieved remarkable success in various fields such as board games such as Go and chess, computer games such as Atari and StartCraft, and robot object manipulation tasks. However, such deep reinforcement learning describes states, actions, and policies in vector representation. Therefore, the existing deep reinforcement learning has some limitations in generality and interpretability of the learned policy, and it is difficult to effectively incorporate domain knowledge into policy learning. On the other hand, dNL-RRL, a new relational reinforcement learning framework proposed to solve these problems, uses a kind of vector representation for sensor input data and lower-level motion control as in the existing deep reinforcement learning. However, for states, actions, and learned policies, It uses a relational representation with logic predicates and rules. In this paper, we present dNL-RRL-based policy learning for transportation mobile robots in a manufacturing environment. In particular, this study proposes a effective method to utilize the prior domain knowledge of human experts to improve the efficiency of relational reinforcement learning. Through various experiments, we demonstrate the performance improvement of the relational reinforcement learning by using domain knowledge as proposed in this paper.