• Korean Institute of Interior Design Journal
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• v.19 no.6
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• pp.20-29
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• 2010

Art historians and critics have defined the style as common features appeared in a class of objects. Abstract common features from a set of objects have been used as a bench mark for date and location of original works. Commonalities in shapes are identified by relationships as well as physical properties from shape descriptions. This paper will focus on how the computer and human can recognize common shape properties from a class of shape objects to learn design knowledge. Shape representation using schema theory has been explored and possible inductive generalization from shape descriptions has been investigated. Also learned shape knowledge can be used. for new design process as design concept. Several design process such as parametric design, replacement design, analogy design etc. are used for these design processes. Works of Mario Botta and Louis Kahn are analyzed for explicitly clarifying the process from conceptual ideas to final designs. In this paper, theories of computer science, artificial intelligence, cognitive science and linguistics are employed as important bases.

• Archives of design research
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• v.15 no.4
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• pp.337-346
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• 2002

Among many design processes such as learning, storing, retrieving and applying, the process that learns design knowledge is very important for producing creative results that solve design purposes in design computations. The computer should have the ability similar to human in learning design knowledge. It should recognize not only physical properties but also high level design knowledge constructed from the first level physical properties. The high level design knowledge are recognised in terms of isometric translation relationships. This paper explains properties of isometric translation and methods how the computer can recognize high level shape design knowledge using shape pattern representation.

• Knowledge Management Research
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• v.18 no.2
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• pp.85-102
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• 2017

With rapid development of information and communication technologies, open collaboration can be eased through the Internet. Open source software, as a representative area of open collaboration, is developed and adopted to various fields. In this research, based on organizational learning theory, we examine the impacts of exploration and exploitation on innovation performance in open source software development projects. We define knowledge exploration as a number of developers from outside organization and knowledge exploitation as the ratio of member of an organization who participated in an open source software project managed by the organization. For analysis, we collect data of 4794 projects from github which is a representative open source software development platform using Web crawler developed by Python. As a result, we find that excessive exploration has curvilinear (invers U-shape) relationship on project performance. On the other hand, exploitation with enough external developers will positively impact on project performance.

• Journal of Industrial Convergence
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• v.18 no.1
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• pp.17-23
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• 2020

This study developed augmented reality contents for assembly of automobile engine parts for blended learning and confirmed the usefulness of educational effects through questionnaire.The curriculum for automobile engine assembly was designed and the shape, location, and assembly order of parts to be assembled according to each curriculum were developed as augmented reality contents. The AR simulations are combined with learner-centered collaborative activities so that students are actively involved in knowledge acquisition. The teachers' role, therefore, shifts. Rather than delivering direct instruction, they take on the role of facilitator, allowing them to personalize learning according to student performance, learning preferences and learning goals. As the responsibility of knowledge acquisition shifts to the students, higher level skills such as complex problem solving, social skills, process skills, systems skills and cognitive abilities are deepened and reinforced.

• Journal of Korean Biological Nursing Science
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• v.11 no.1
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• pp.51-58
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• 2009

Purpose: It is to verify learning effect of the instructional media on anatomy classes at a nursing college and to develop an alternative instructional media instead of cadaver. Method: Four groups pretest-posttest experimental design were used. One hundred twenty students who attended an Anatomy lecture in September, 2009 were selected After attending the anatomy lecture, the subjects were divided into four group (30 for each group) conveniently. The heart anatomy knowledge level were measured by a self evaluation questionnaire and quiz before and after a different instructional media being applied for each group including making heart shape using colored clay, taking picture of a real heart, sketching the heart model with color pencil and drawing heart presented in the anatomy textbook. Data was analyzed by t-test, ANNOVA test using the SPSS/PC WIN 12 version. Result: A statistically significant differences in the level of heart anatomy knowledge acquirement was noted after four different instructional media being applied, and four different instructional media was effective to the anatomy practice education. However, no difference in statistical post test results was noted among the four groups. Conclusion: It is recommended that further comparative studies on the learning effect between human cadaver practice and different instructional media is necessary.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.3
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• pp.52-63
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• 1995

A neuro-fuzzy algorithm is presented for nuclear reactor power control in a pressurized water reactor. Automatic reacotr power control is complicated by the use of control rods because of highly nonlinear dynamics in the axial power shape. Thus, manual shaped controls are usually employed even for the limited capability during the power maneuvers. In an attempt to achieve automatic shape control, a neuro-fuzzy approach is considered because fuzzy algorithms are good at various aspects of operator's knowledge representation while neural networks are efficinet structures capable of learning from experience and adaptation to a changing nuclear core state. In the proposed neuro-fuzzy control scheme, the rule base is formulated based ona multi-input multi-output system and the dynamic back-propagation is used for learning. The neuro-fuzzy powere control algorithm has been tested using simulation fesponses of a Korean standard pressurized water reactor. The results illustrate that the proposed control algorithm would be a parctical strategy for automatic nuclear reactor power control.

• Journal of the Korean School Mathematics Society
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• v.16 no.2
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• pp.409-434
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• 2013

The mathematical ability is an essential element for achieving professional competencies and for enhancing application ability in a vocational world and exploring its experiences. In this aspect, for vocational high school students, it is an important and urgent issue to develop remedial learning programs for developing mathematical basic and application ability. In particular, the program is developed based on the individual achievement level, focused on a mathematical basic ability to be applied efficiently in a vocational world. Because of this reason, in this study, the program is comprised of two phases; one is diagnosis test and the other is remedial teaching and learning materials. Then, diagnosis test includes three test; I) level testing evaluation for selecting the subject of remedial learning, ii) pre-test for deciding on which area and level of the materials when students begin to study, and iii) post-test for confirming the learning status is satisfied and the possibility of next step(level) or the other area of the materials. To accomplish this, this study tried to devise an efficient remedial learning system. Based on the system, this study developed remedial learning programs on the four areas of number and quantity, change and relation, uncertain thing, and figure and shape in the middle school level. In particular, this program is comprised of two types of knowledge. One is K-knowledge which is an essential knowledge to achieve a basic mathematical ability. The other is C-knowledge which is the advanced knowledge required to apply efficiently in a vocational world. This paper deals with the content mentioned above, but examples of the materials is shown focused on the area of change and relation.

• Smart Structures and Systems
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• v.31 no.5
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• pp.485-500
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• 2023

Machine learning-based structural health monitoring (ML-based SHM) methods are researched extensively in the recent decade due to the availability of advanced information and sensing technology. ML methods are well-known for their pattern recognition capability for complex problems. However, the main obstacle of ML-based SHM is that it often requires pre-collected historical data for model training. In most actual scenarios, damage presence can be detected using the unsupervised learning method through anomaly detection, but to further identify the damage types would require prior knowledge or historical events as references. This creates the cold-start problem, especially for new and unobserved structures. Modal-based methods identify damages based on the changes in the structural global properties but often require dense measurements for accurate results. Therefore, a two-stage hybrid modal-machine learning damage detection scheme is proposed. The first stage detects damage presence using Principal Component Analysis-Frequency Response Function (PCA-FRF) in an unsupervised manner, whereas the second stage further identifies the damage. To solve the cold-start problem, mode shape assessment using the first mode is initiated when no trained model is available yet in the second stage. The damage identified by the modal-based method would be stored for future training. This work highlights the performance of the scheme in alleviating the cold-start issue as it transitions through different phases, starting from zero damage sample available. Results showed that single and multiple damages can be identified at an acceptable accuracy level even when training samples are limited.

• Journal of Information Processing Systems
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• v.15 no.4
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• pp.717-723
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• 2019

Smart systems and services aim to facilitate growing urban populations and their prospects of virtual-real social behaviors, gig economies, factory automation, knowledge-based workforce, integrated societies, modern living, among many more. To satisfy these objectives, smart systems and services must comprises of a complex set of features such as security, ease of use and user friendliness, manageability, scalability, adaptivity, intelligent behavior, and personalization. Recently, artificial intelligence (AI) is realized as a data-driven technology to provide an efficient knowledge representation, semantic modeling, and can support a cognitive behavior aspect of the system. In this paper, an integration of AI with the smart systems and services is presented to mitigate the existing challenges. Several novel researches work in terms of frameworks, architectures, paradigms, and algorithms are discussed to provide possible solutions against the existing challenges in the AI-based smart systems and services. Such novel research works involve efficient shape image retrieval, speech signal processing, dynamic thermal rating, advanced persistent threat tactics, user authentication, and so on.

• Journal of the Korean Society of Earth Science Education
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• v.7 no.2
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• pp.276-285
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• 2014

The purpose of this study is to investigate the pattern and characteristics of elementary school teaching and learning processes in science based classes. The study participants' class was recorded in video and instructional conversation transcription. The pattern of the observed class was analyzed using the classification frame suggested by Mogan &Saxton(2006). In result, the questioning for elicit information was most frequent and questioning for shape understanding and the questioning for press for reflection in its priority. In result, the presence of elicited questioning for the attainment of knowledge and understanding is more prominent in science-based classrooms. It was revealed that the participating teachers used the questioning sentence pattern more frequently and the self-sustained inquiry that accelerates creative thinking of the student was lacking. It was discovered that teaching elicited questioning, which accelerates creative thinking, as well as fact confirmation pattern is a necessary element of training for teachers.