• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.7
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• pp.817-822
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• 2005

Recently tile study that exploits visual information for tile services of robot in indoor environments is active. Conventional image processing approaches are based on the pre-defined geometric models, so their performances are likely to decrease when they are applied to the uncertain and dynamic environments. For this, diverse researches to manage the uncertainty based on the knowledge for improving image recognition performance have been doing. In this paper we propose a Bayesian network modeling method for predicting the existence of target objects when they are occluded by other ones for improving the object detection performance of the service robots. The proposed method makes object relationship, so that it allows to predict the target object through observed ones. For this, we define the design method for small size Bayesian networks (primitive Bayesian netqork), and allow to integrate them following to the situations. The experiments are performed for verifying the performance of constructed model, and they shows $82.8\%$ of accuracy in 5 places.

• Journal of KIISE:Software and Applications
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• v.34 no.6
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• pp.549-561
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• 2007

Vision-based scene understanding is to infer and interpret the context of a scene based on the evidences by analyzing the images. A probabilistic approach using Bayesian networks is actively researched, which is favorable for modeling and inferencing cause-and-effects. However, it is difficult to gather meaningful evidences sufficiently and design the model by human because the real situations are dynamic and uncertain. In this paper, we propose a learning method of Bayesian network that reduces the computational complexity and enhances the accuracy by searching an efficient BN structure in spite of insufficient evidences and training data. This method represents the domain knowledge as ontology and builds an efficient hierarchical BN structure under constraint rules that come from the ontology. To evaluate the proposed method, we have collected 90 images in nine types of circumstances. The result of experiments indicates that the proposed method shows good performance in the uncertain environment in spite of few evidences and it takes less time to learn.

• Journal of Digital Convergence
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• v.14 no.4
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• pp.1-10
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• 2016

Society is operating with software and a new digital era through the Internet of Things started. A variety of fields are being in conjunction with each other based on computing. As problems in real life become more complicated and communication based on various knowledge and problem solving skills are emphasized, these changes are reflected in the curriculum. These changes started from overseas in advance then Korea includes SW education in elementary and secondary education through curriculum revision of 2015. On the other hand, SW education for university students just started after the curriculum revision of elementary and secondary education. The new SW education highlights and develops Computational Thinking beyond programming and it will be a key for the future. Therefore, this study analyzed trends of Computational Thinking and examples of CT courses in Universities. Suggestions and ideas for instructional model to develop Computational Thinking were discussed.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.1
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• pp.1-8
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• 2016

In this paper, several problems functioning as the obstacles against software reuse were summarized. Among them, the issues dealt with in this paper include the effective method for constructing the library, the proper structure of the library, and the efficient retrieval technique. The knowledge-based approach and the information retrieval approach were integrated to construct and manage the library. The former is on the object- oriented model. Basically the object-oriented library is based on the classes and organized by inheritance. Because inheritance hierarchy is based on syntactical information, it dose not present the relationship of functionality. Using the information retrieval approach, the index file which characterizes the component and similarity among the components can be analyzed. Especially, we focused on the reusable library for the object-oriented programming environments.

• The KIPS Transactions:PartA
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• v.12A no.6 s.96
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• pp.547-556
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• 2005

Online collaborative teaming, which has emerged as a new type of education in knowledge-based society, is being discussed actively in the areas of action learning at companies and project-based learning and inquiry-based learning at schools. It regards as an effective method for improving learners practical and highly advanced problem solving abilities, and for stimulating their absorption into learning through pursuing common goals of learning together. Different from individual learning, however, collaborative learning involves complicated processes such as organizing teams, setting common goals, performing tasks and evaluating the outcome of team activities .Thus, it is difficult for a teacher to promote and evaluate the whole process of collaborative learning, and it is necessary to develop systems to support collaborative learning. Therefore, in order to monitor and promote interaction among learners in the process of collaborative learning, the present study developed an extensible collaborative teaming supporting agent (ECOLA) in online learning environments.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.33-41
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• 2022

Infrastructure procurement has been a major engagement route between China and Africa. This contributes immensely to the gradual infrastructure development seen on the continent. However, maturing discourse purports that these infrastructure collaborations lack intentionality in the continuous development of strategic guidelines and policies for effective implementation despite their uniqueness and criticality. This study proposes that an efficient approach to policy recommendations is through the political and economic analysis (PEA) of these partnerships using public-private partnership (PPP) optics. Unquestionably, these partnerships are representative of the concept of diplomatic transnational public-private partnership (DT-PPP) where infrastructure is procured through the collaboration of public (African governments) and private sector (Chinese state-owned corporations) who provide the managerial, financial, and technical resources for the project implementation. Given the quest for sustainable win-win, this study identifies strategies towards the realization of win-win in the implementation (i.e enablers of win-win) such that fairness and co-benefit, as well as interests, will be achieved. Thus, based on the PEA framework, case scenarios from Ghana and Nigeria using expert interviews identify the criticalities and best practices for the realization of these enablers at the development phase. Findings indicate more effort is required of the public sector (African host countries) in terms of people, structure/institutions, and the implementation processes. Recommendations include improvement of environmental management structures, contract administration procedures, external stakeholders/local community engagement mechanisms, knowledge and technology transfer procedures, and sector-based project operation and maintenance culture and systems. Additionally, actors must have emotional intelligence, good problem-solving abilities, and overall ensure cordial relationships for continued bilateral cooperation.

• Structural Engineering and Mechanics
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• v.86 no.6
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• pp.715-730
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• 2023

Broad studies have addressed the issue of structural element damage identification, however, rubber bearing, as a key component of load transmission between the superstructure and substructure, is essential to the operational safety of a bridge, which should be paid more attention to its health condition. However, regarding the limitations of the traditional bearing damage detection methods as well as few studies have been conducted on this topic, in this paper, inspired by the model updating-based structural damage identification, a two-stage bearing damage identification method has been proposed. In the first stage, we deduce a novel bearing damage localization indicator, called element relative MSE, to accurately determine the bearing damage location. In the second one, the prior knowledge of bearing damage localization is combined with sailfish optimization (SFO) to perform the bearing damage estimation. In order to validate the feasibility, a numerical example of a 5-span continuous beam is introduced, also the noise robustness has been investigated. Meanwhile, the effectiveness and engineering applicability are further verified based on an experimental simply supported beam and actual engineering of the I-40 Bridge. The obtained results are good, which indicate that the proposed method is not only suitable for simple structures but also can accurately locate the bearing damage site and identify its severity for complex structure. To summarize, the proposed method provides a good guideline for the issue of bridge bearing detection, which could be used to reduce the difficulty of the traditional bearing failure detection approach, further saving labor costs and economic expenses.

• Advances in concrete construction
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• v.14 no.3
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• pp.153-167
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• 2022

The interaction between blast load and structures, as well as the interaction among structural members may well affect the structural response and damages. Therefore, it is necessary to analyse more realistic reinforced concrete structures in order to gain an extensive knowledge on the possible structural response under blast load effect. Among all the civilian structures, columns are considered to be the most vulnerable to terrorist threat and hence detailed investigation in the dynamic response of these structures is essential. Therefore, current research examines the effect of blast loads on the reinforced concrete columns via development of Pressure- Impulse (P-I) diagrams. In the finite element analysis, the level of damage on each of the aforementioned RC column will be assessed and the response of the RC columns when subjected to explosive loads will also be identified. Numerical models carried out using LS-DYNA were compared with experimental results. It was shown that the model yields a reliable prediction of damage on all RC columns. Validation study is conducted based on the experimental test to investigate the accuracy of finite element models to represent the behaviour of the models. The blast load application in the current research is determined based on the Lagrangian approach. To develop the designated P-I curves, damage assessment criteria are used based on the residual capacity of column. Intensive investigations are implemented to assess the effect of column dimension, concrete and steel properties and reinforcement ratio on the P-I diagram of RC columns. The produced P-I models can be applied by designers to predict the damage of new columns and to assess existing columns subjected to different blast load conditions.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.135-146
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• 2023

An effective educational program warrants the inclusion of an innovative construction which enhances the higher education efficacy in such a way that accelerates the achievement of desired results and reduces the risk of failures. Educational Decision Support System (EDSS) has currently been a hot topic in educational systems, facilitating the pupil result monitoring and evaluation to be performed during their development. Insufficient information systems encounter trouble and hurdles in making the sufficient advantage from EDSS owing to the deficit of accuracy, incorrect analysis study of the characteristic, and inadequate database. DMTs (Data Mining Techniques) provide helpful tools in finding the models or forms of data and are extremely useful in the decision-making process. Several researchers have participated in the research involving distributed data mining with multi-agent technology. The rapid growth of network technology and IT use has led to the widespread use of distributed databases. This article explains the available data mining technology and the distributed data mining system framework. Distributed Data Mining approach is utilized for this work so that a classifier capable of predicting the success of students in the economic domain can be constructed. This research also discusses the Intelligent Knowledge Base Distributed Data Mining framework to assess the performance of the students through a mid-term exam and final-term exam employing Multi-agent system-based educational mining techniques. Using single and ensemble-based classifiers, this study intends to investigate the factors that influence student performance in higher education and construct a classification model that can predict academic achievement. We also discussed the importance of multi-agent systems and comparative machine learning approaches in EDSS development.

• Journal of Korean Academy of Nursing
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• v.15 no.1
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• pp.30-43
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• 1985

Liver cirrhosis is the common cause of death in Korea today. But, if liver cirrhosis Patients were treated in the early stage of the disease Process, they can have a chance to carry their daily lives with prescribed medical and nursing regimens. Each patient has different health beliefs that there is a different Sick Role Behavior in the process of treatment. In order to increase and control the desired patient's Sick Role Behavior, it is important for nurses to understand the health beliefs influencing Sick Role Behavior. The purpose of this study was to determine factors influencing Sick Role Behavior and provide objective and scientific data to health education, treatment and nursing care. The subjects for this study were 80 Liver Cirrhosis patients selected from in and out patients of the medical department of four University Hospitals in Seoul, Won Joo and Mok Po city. Data was collected from Sep. 18, to Oct. 15, 1984. The measurement tool was the questionaire that developed by the investigator from the literature review based on Health Belief Model. The data Collection was done by interview. Analysis of data was done by use Mean, S.D., ANOVA, Pearson Correlation Coefficient and Stepwise Multiple Regression. The result of study were as follows: 1. The significant influencing variables on the Liver Cirrhosis Patient's Sick Role Behavior in general characteristics were Sex, Marital Status, Educational levels, Family's income and Duration after diagnosis. 2. Between the Sick Role Behavior and Health Belief Model, a) The first hypothesis that the stronger degree of Health Motivation, the higher degree of Liver Cirrhosis Patient's Sick Hole Behavior was supported (r=0.7892, p=0.0000). b) The second hypothesis that the higher degree of perceived susceptibility, the higher degree of Liver Cirrhosis Patients' Sick Role Behavior was supported (r=0.6383, p=0.0000) c) The third hypothesis that the higher degree of perceived severity, the higher degree of Liver Cirrhosis Patients' Sick Role Behavior was supported (r=0.5869, p=0.0000). d) The fourth hypothesis that the higher degree of perceived benefit, the higher degree of Liver Cirrhosis patient's Sick Role Behavior was supported (r=0.7535, p=0.0000). e) The fifth hypothesis that the lower degree of perceived barrier, the higher degree of Liver Cirrhosis Patient's Sick Role Behavior was supported(r=-9.7709, p=0.0000) f) The sixth hypothesis that the higher degree of knowledge in Disease, the higher degree of Liver Cirrhosis patients'lck Role Behavior was supported (r=0.7538, p=0.0000), g) In the correlation among variables, it was found positive correlation except that perceived barrier was negatively correlated. In the Stepwise Multiple Regression and Independent Variables, the factor“Health Motivation”could account for Sick Role Behavior in 62.28% of the Sample (F=128. 786, p<0.01). When the factor“perceived barrier”is added to this, it account for 70.38% of Sick Role Behavior (F=93.479, p <0.01) and the factor“knowledge in disease”is also included, it account for 74.78% of Sick Role Behavior (F=75.131, p <0.01). Finally, when the factor“perceived susceptibility”is included, it account for 75.03% of Sick Role Behavior (F=56.329, p <0.01).