• Journal of information and communication convergence engineering
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• v.9 no.3
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• pp.287-294
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• 2011

This paper proposes a search system using the topic maps that it extends XMDR into Knowledge based XMDR for solving of the problems of the heterogeneity of distributed data on a network and integrate data by an efficient way. The proposed system combined Topic Maps and the extended metadata registry effectively. The Topic Maps represent related knowledge and reasoning relationship by associations of topic. And the extended metadata registry standards and manages the metadata of the local systems through registration and certification on the distributed environment. We also proposed a meta layer, include the meta topic and meta association to achieve semantic classification grouping of topics and to define relationship between Topic Maps and extended metadata registry.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1309-1314
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• 2003

If an agent has a learning ability using previous knowledge, then it is expected that the agent can speed up learning by interacting with environment. In this paper, we present an improved reinforcement learning algorithm using domain knowledge which can be represented by problem-independent features and their classifiers. Here, neural networks are employed as knowledge classifiers. To show the validity of our proposed algorithm, computer simulations are illustrated, where navigation problem of a mobile robot and a micro aerial vehicle(MAV) are considered.

• Journal of the Korea Society of Computer and Information
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• v.24 no.6
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• pp.37-43
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• 2019

This study focused on the design and development of contents using Unplugged CS method to learn computer science knowledge. With the strengthening of software education, all universities students including elementary and junior high school students are demanding knowledge of computer science centered on the computational thinking. We have developed educational contents using unplugged computing method as a way to effectively learn the concept of computer science. First, we analyze the related research of Unplugged CS theory and investigate the educational method accordingly. And we divided the areas of computer science and selected learning concepts in each area. The contents of learning were divided into basic and intermediate classes considering the level of the learner. The subject of learning contents was selected evenly in the area of computer science and it consisted of 16 basic subjects and 16 intermediate subjects based on concepts that are important in each field. In order to confirm the validity of the Unplugged CS learning topic and the development contents for computer science, we conducted expert reviews and content validity tests. As a result of the validity test, the validity of the learning topic and area selection was found to be more than .92 for the CVI value and the validity of the 32 subject learning contents was over .935 in basic level and .925 in intermediate level for the CVI values. Based on the design contents, we developed digital contents for online learning and put them in the system. We expect that this study will contribute to the understanding of computer science for all, including elementary and junior-high school students as well as students at software - oriented universities, and contribute to the spread of software education.

• The Journal of Korean Association of Computer Education
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• v.4 no.2
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• pp.135-143
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• 2001

Teachers' cognitive understanding of subject matter content have direct impact on the quality of students learning. In order to understand this, we need to investigate the relationships between the teachers' level of knowledge about the content and the instruction teacher provide for students. Professional development programs for computer education teachers include courses in computer science, curriculum studies, and the application of computers in the classroom. Effective teachers, however, have expertise in the subject matter content, know curriculum, and understand contextual knowledge for teaching computers in the classrooms. Although computer education have evolved for last 20 years, we have not yet made significant progress on researching "what" is the professional knowledge of computer teachers, and "how" they could be trained. Teacher's knowledge includes pedagogical and contextual knowledge of teaching the specific subject. The purpose of this paper is to understand the professional knowledge of computer teachers, and the adoption of PCK (pedagogical content knowledge). As a result of this paper, I hope to initiate further discussions and researches on PCK and its' implication for computer teachers and teacher preparation programs in Korea.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1165-1168
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• 2002

Knowledge acquisition is the process that extracts the required knowledge from available sources, such as experts, textbooks and databases, for incorporation into a knowledge-based system. Knowledge acquisition is described as the first step in building expert systems and a major bottleneck in the efficient development and application of effective knowledge based expert systems. One cause of the problem is that the process of human reasoning we need to understand for knowledge-based system development is not available for direct observation. Moreover, the expertise of interest is typically not reportable due to the compilation of knowledge which results from extensive practice in a domain of problem solving activity. This is also a problem of modeling knowledge, which has been described as not a problem of accessing and translating what is known, but the familiar scientific and engineering problem of formalizing models for the first time. And this formalization process is especially difficult for knowledge engineers who are often faced with the difficult task of creating a knowledge model of a domain unfamiliar to them. In this paper, we propose an automated knowledge acquisition tool which is based on an implementation of the Inferential Modeling Technique. The Inferential Modeling Technique is derived from the Inferential Model which is a domain-independent categorization of knowledge types and inferences ［Chan 1992］. The model can serve as a template of the types of knowledge in a knowledge model of any domain.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.12
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• pp.3416-3435
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• 2023

Task offloading in vehicular networks is hot topic in the development of autonomous driving. In these scenarios, due to the role of vehicles and pedestrians, task characteristics are changing constantly. The classical deep learning algorithm always uses a pre-trained neural network to optimize task offloading, which leads to system performance degradation. Therefore, this paper proposes a neural network fine-tuning task offloading algorithm, combining with location prediction for pedestrians and vehicles by the Payne model of fluid dynamics and the car-following model, respectively. After the locations are predicted, characteristics of tasks can be obtained and the neural network will be fine-tuned. Finally, the proposed algorithm continuously predicts task characteristics and fine-tunes a neural network to maintain high system performance and meet low delay requirements. From the simulation results, compared with other algorithms, the proposed algorithm still guarantees a lower task offloading delay, especially when congestion occurs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.2
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• pp.461-484
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• 2021

Compressed sensing in image reconstruction has attracted attention and many studies are proposed. As we know, adding prior knowledge about the distribution of the support on the original signal to CS can improve the quality of reconstruction. However, it is still difficult for a recovery framework adjusts its strategy for exploiting the prior knowledge efficiently according to the current estimated signals in serial iterations. With the theory of information geometry, we propose an adaptive strategy based on the current estimated signal in each iteration of the recovery. We also improve the performance of existing algorithms through the adaptive strategy for exploiting the prior knowledge according to the current estimated signal. Simulations are presented to validate the results. In the end, we also show the application of the model in the image.

• The Journal of Korean Association of Computer Education
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• v.9 no.3
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• pp.29-45
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• 2006

The IT(Information Technology) is very important growth power in the knowledge information based society. But there is nothing an educational program or system for putting the computer science education in the primary and secondary school into practice. We can talk this problem because of the national curriculum. This existing state brings to a conclusion not only to the political and administrative support but also to the national curriculum. These internal problems are two. First problem is the content in the computer textbook. And second problem is the connection between the computer science education curriculum of university and that of primary and secondary school. This study analyzed the relation about it. And this study suggested the ideal method for connecting those of them. Finally, the results of this study are two. First result is the necessary to reconstruct the domain knowledge of the computer based on the computer science for getting the identity. And second result is necessary to connect between the domain knowledge of the computer based on the computer science identity of university and that of primary and secondary school.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.327-341
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• 2021

The knowledge management was considered as the inevitable result of the rule of knowledge in this era, and its importance became clear in being the main source for achieving success, the need to consider and manage knowledge as an independent field that must be addressed with a clear scientific methodology has become intangible - they are very valuable and a strategic asset. On the other hand, the innovation process relates to all parts of the organization, and helps to improve the behavioral patterns of individuals and their attitudes towards adopting modern and innovative ideas, it is a purposeful process adopted by the senior management and works to provide the capabilities and requirements for embodying the innovative behavior in it. In the field of dealing with the market, it is a product of the organization's innovative approach, which aims at advancement, change, and intended and organized renewal. The main objective of this article is to determine the most appropriate ways to integrate knowledge management mechanisms to employ innovation factors within universities based on the role of universities in supporting innovation. This was achieved through reviewing many relevant research and listing the most prominent concepts of knowledge management, its importance, objectives, and processes determining the stages of knowledge management application, the requirements for applying knowledge management, and the obstacles that impede its application; Then the statement "Innovation in universities, through which it addressed the concept of innovation, its importance, stages, and requirements for its application, as well as identifying the most prominent models of innovation, and obstacles to innovation, in addition to that the role of universities in supporting innovation will be identified. From the surveyed study done in this article, we concluded that the relationship among organizational culture, knowledge management and innovation capability can provide useful insights for managers regarding developing a strong culture, promote knowledge management practices effectively and eventually enhance the whole organization's innovation capability. Also, we found that different components of Knowledge Management as Knowledge activities, Knowledge types, transformation of knowledge and technology have a significant positive effect in bringing innovation through transformation of knowledge into knowledge assets in universities.

• Journal of the Korea Society of Computer and Information
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• v.28 no.11
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• pp.227-234
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• 2023

The evaluation of students' computational thinking begins with the evaluation of knowledge about the concepts and principles of computing. In this study, we analyzed the differences in teachers' perceptions depending on the description method of the bebras challenge questions to evaluate computer science knowledge. First, we classified the questions into two types depending on whether computer science terms were included or not. Also we made a computational thinking questionnaire with two types of questions and surveyed 72 major teachers. As a result, teachers expressed the opinion that the evaluation questions that revealed computer science terms were appropriate as evaluation questions for information subjects. They also perceived it as more helpful in assessing computational thinking and coding skills. Through the results of this study, we suggested that the way the questions are worded is important in the process of assessing students' understanding of computer science concepts and computational thinking skills.