• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.3
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• pp.277-288
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• 2021

Building information modeling (BIM) element to industry foundation classes (IFC) entity mappings need to be checked to ensure the semantic integrity of BIM models. Existing studies have demonstrated that machine learning algorithms trained on geometric features are able to classify BIM elements, thereby enabling the checking of these mappings. However, reliance on geometry is limited, especially for elements with similar geometric features. This study investigated the employment of relational data between elements, with the assumption that such additions provide higher classification performance. Neural structured learning, a novel approach for combining structured graph data as features to machine learning input, was used to realize the experiment. Results demonstrated that a significant improvement was attained when trained and tested on eight BIM element types with their relational semantics explicitly represented.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.12
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• pp.485-496
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• 2018

So far, the deep learning, a field of artificial intelligence, has achieved remarkable results in solving problems from unstructured data. However, it is difficult to comprehensively judge situations like humans, and did not reach the level of intelligence that deduced their relations and predicted the next situation. Recently, deep neural networks show that artificial intelligence can possess powerful relational reasoning that is core intellectual ability of human being. In this paper, to analyze and observe the performance of Relation Networks (RN) among the neural networks for relational reasoning, two types of RN-based deep neural network models were constructed and compared with the baseline model. One is a visual question answering RN model using Sort-of-CLEVR and the other is a text-based question answering RN model using bAbI task. In order to maximize the performance of the RN-based model, various performance improvement experiments such as hyper parameters tuning have been proposed and performed. The effectiveness of the proposed performance improvement methods has been verified by applying to the visual QA RN model and the text-based QA RN model, and the new domain model using the dialogue-based LL dataset. As a result of the various experiments, it is found that the initial learning rate is a key factor in determining the performance of the model in both types of RN models. We have observed that the optimal initial learning rate setting found by the proposed random search method can improve the performance of the model up to 99.8%.

• Journal of the Korean School Mathematics Society
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• v.18 no.4
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• pp.353-370
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• 2015

This study was conducted as a qualitative case study that explored how gifted 3rd-grade elementary school children who had learned the primary concepts of division and fraction, when they studied contents about decimal, formed the transformed primary concept and transformed schema of decimal by the learning of accurate primary concepts and connecting the concepts. That is, this study investigated how the subjects attained relational understanding of decimal based on the primary concepts of division and fraction, and how they formed a transformed primary concept based on the primary concept of decimal and carried out vertical mathematizing. According to the findings of this study, transformed primary concepts formed through the learning of accurate primary concepts, and schemas and transformed schemas built through the connection of the concepts played as crucial factors for the children's relational understanding of decimal and their vertical mathematizing.

• Journal of KIBIM
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• v.12 no.2
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• pp.12-25
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• 2022

To increase the usability of Building Information Modeling (BIM) in construction projects, it is critical to ensure the interoperability of data between heterogeneous BIM software. The Industry Foundation Classes (IFC), an international ISO format, has been established for this purpose, but due to its structural complexity, geometric information and properties are not always transmitted correctly. Recently, deep learning approaches have been used to learn the shapes of the BIM elements and thereby verify the mapping between BIM elements and IFC entities. These models performed well for elements with distinct shapes but were limited when their shapes were highly similar. This study proposed a method to improve the performance of the element type classification by using an Ensemble model that leverages not only shapes characteristics but also the relational information between individual BIM elements. The accuracy of the Ensemble model, which merges MVCNN and MLP, was improved 0.03 compared to the existing deep learning model that only learned shape information.

• Communications of Mathematical Education
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• v.28 no.4
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• pp.475-492
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• 2014

This study aimed to explore the affective characteristics of primary and middle school students in mathematics and to analyze the relationship between the affective characteristics and initiative in mathematics learning. For the purpose of this study, a survey was conducted for students in a primary and a middle school in Incheon area. The questionnaires using in this study consisted of five affective domains of interest, self-efficacy, value, self-regulation, and mathematics anxiety. The results of this study showed that the participant students' affective characteristics tended to be decreased by grades. Moreover, the gender differences were increase as the participant students grew older. Students who take the initiative in mathematics learning showed better affective characteristics in general than students who depends on other assistants.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.05a
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• pp.183-186
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• 2018

In this paper, we propose the database design for skill learning service through the internet from the viewpoint of service engineering. This paper we describe the outlines for a design theory for skill learning service, which can lead to the satisfaction of both learner and instructor. Compared to other services, motion control learning takes a considerable amount of time, and this leads to a difficulty for learners to rate the quality of the service as well as for the instructors to provide consistent quality and standard of teaching. To solve these problems, we use a relational database with MongoDB which is an unstructured database allowing to flexibly incorporate the demands of both learner and instructor into the database itself.

• Knowledge Management Research
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• v.13 no.2
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• pp.73-93
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• 2012

Although a wide range of theoretical researches have emphasized on the importance of knowledge management in cooperative R&D network, the empirical researches to synthetically examine the role of organizational learning and open innovation which influence on the performance of technological innovation are not enough to meet academic and practical demands. This study is to investigate the effect of open innovation and organizational learning in venture business on technological competitive advantage and establish the mediating role of organizational learning. For the purpose, the questionnaires, made based on the reviewing previous researches, were collected from 274 Korean venture businesses whose managerial focus is on developing technological innovation. As a result of analysis, the relational dimensions of open innovation - network, intensity and trust shared by a firm with external R&D partners - as well as the internal organizational learning system and competence have positive influence on building technological competitive advantage whose sub-variables are technological excellence, market growth potential and business feasibility. In addition, it is identified that organizational learning has the mediating and moderating effect in the relationship between open innovation and technological competitive advantage. These results imply that open innovation complements and expend the range of limited resources and the scope of innovation in technology-intensive small and medium-sized enterprises. Besides, organizational learning activity reinforces the use of knowledge and resources, obtained from external R&D partners. On the basis of these results, detailed issues and discussion were made in the conclusion.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.3
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• pp.113-121
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• 2022

The study aimed to assess the availability of intellectual capital in Kuwaiti private universities in terms of its three dimensions (human capital, structural capital, and relational capital), as well as its role in crisis management (crisis preparedness, crisis mitigation, confrontation, and response to the crisis, and learning from the crisis) during the COVID-19 pandemic. Members of the boards of trustees, university presidents, their deputies, and deans of the colleges were chosen as respondents to this study from a sample of (8) private universities in Kuwait, with the sampling unit consisting of leaders in these universities. The study revealed that all dimensions of intellectual capital play a statistically significant impact in executing crisis management during the COVID-19 pandemic at Kuwaiti private universities after conducting the data analysis process. The study concluded that universities should pay attention to intellectual capital in all its dimensions (human capital, structural capital, and relational capital) because of its role in improving their ability to implement crisis management strategies and strive to improve their capabilities to face crises by implementing crisis management strategies.

• Knowledge Management Research
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• v.18 no.4
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• pp.31-62
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• 2017

It found that employee silence negatively impacts both organizations and their employees as shown in findings from many studies and recently there has been a growing interest in it. Silence is described as intentionally withholding job-related ideas, information, concerns, and opinions. Employee silence may decrease organizational change and innovation and reduce employee learning motivation and knowledge sharing engagement as well. The purpose of this study is to examine the relationships among silence motivations, perceived silence climate, and employee silence; the relationships among employee silence, learning inertia and knowledge sharing disengagement; the mediating role of employee silence between antecedents of employee silence and consequences additionally. The results that analyzed using data from 225 employees in 42 organizations are as follows. First, the impact of silence motivation and perceived silence climate on employee silence are positively significant. Second, the influence of defensive silence motivation on the acquiescent and relational silence motivation is positively significant. Third, the influence of employee silence on learning inertia and knowledge sharing disengagement is positively significant. Forth, employee silence mediates the relationship between silence motivation and perceived silence climate and learning inertia and knowledge sharing disengagement. These results suggest that employee silence is another strong expression and message for organizations to try to establish a learning organization from the perspective of knowledge management.

• Knowledge Management Research
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• v.9 no.4
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• pp.35-49
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• 2008

The purpose of the study is to develop and validate an instructional design model from the perspective of the knowledge creation. To serve the purpose, the researcher conducted 1) literature review to find causal relationship model among knowledge creation factors and to propose a hypothetical instructional design model, 2) data analysis with 50 senior level e-Learning instructional designers, and 3) testing the fitness of the proposed model and relevant causal-relational hypotheses. Results indicate; 1) the proposed model fit to the empirical evidence, 2) 6 hypotheses among 11 were validated. A typical instructional designer's personal competency was evidenced as the most powerful independent variable that predicted knowledge acquisition, knowledge sharing, and the application of the instructional models. However, the expected effect of instructional design models toward other dependent variable was not be found. In addition, further suggestions for the future research are addressed.