• The Journal of Korean Institute for Practical Engineering Education
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• v.3 no.2
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• pp.114-120
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• 2011

This paper proposed a model of Creative Problem Solving education, using CREAX software based on TRIZ. Learners can get the motivation about development of creative thinking through the theory of TRIZ. Furthermore, they can have good command of creative problem-solving process from the software practice course. As a result of the study, the learners could realize the importance of the creativity and adaptability which are demanded from the knowledge-based society. We planned a three major course for development about adaptability of creative problem solving process and we proposed a guideline about each step of the software utilized CREAX. So, we established the courses about leaners can get the creative problem-solving skill more efficiently.

• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.2031-2042
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• 2017

In this paper, a novel traffic flow control method based-on ramp metering and speed regulation using an adaptive sliding mode control (ASMC) method along with a deadzoned parameter adaptation law is proposed at a stochastic macroscopic level traffic environment, where the influence of the density and speed disturbances is accounted for in the traffic dynamic equations. The goal of this paper is to design a local traffic flow controller using both ramp metering and speed regulation based on ASMC, in order to achieve the desired density and speed for the maintenance of the maximum mainline throughput against disturbances in practice. The proposed method is advantageous in that it can improve the traffic flow performance compared to the traditional methods using only ramp metering, even in the presence of ramp storage limitation and disturbances. Moreover, a prior knowledge of disturbance magnitude is not required in the process of designing the controller unlike the conventional sliding mode controller. A stability analysis is presented to show that the traffic system under the proposed traffic flow control method is guaranteed to be uniformly bounded and its ultimate bound can be adjusted to be sufficiently small in terms of deadzone. The validity of the proposed method is demonstrated under different traffic situations (i.e., different initial traffic status), in the sense that the proposed control method is capable of stabilizing traffic flow better than the previously well-known Asservissement Lineaire d'Entree Autoroutiere (ALINEA) strategy and also feedback linearization control (FLC) method.

• Journal of the Korea Society of Computer and Information
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• v.19 no.12
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• pp.369-384
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• 2014

Since the start of gifted education in 2002, educational support system has now been established, and sufficient growth in quantitative aspects has been achieved in Korea. On the other hand, they report that there are insufficient points in terms of education quality. In other words, most of the gifted education simply expands knowledge by prior-learning. In order to improve the quality of gifted education, they should enhance critical-thinking and creativity able to apply interdisciplinary principles or phenomena for solving problems. In this study, we designed and developed a convergent teaching-learning materials based on the concept of integrated education, which explore the process that basic logic operations such as AND, OR, XOR do the role of computer cells. A survey result showed that student satisfaction(usefulness, understanding, interest) of the materials is significantly higher than that of other traditional learning topics, and the design intent was met.

• The Journal of Korean Association of Computer Education
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• v.19 no.6
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• pp.45-54
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• 2016

The purpose of this study is to investigate the effects of Android application programming education to control Arduino using App Inventor on industrial high school students' creative and integrative thinking ability. We developed an instructional content based on integrative learning and creative problem-solving model and taught a class on it. The result of this study showed that there was a significant improvement in divergent thinking and motivation items among the sub elements of creative problem solving. In addition, students' survey on the integrated thinking has shown that many students think that they could design an IoT system applied to everyday life based on the knowledge they have learned in this class. Therefore, it can be confirmed that physical computing education using App Inventor and Arduino has a positive effect on students' creative and integrative thinking ability.

• Korean Journal of Remote Sensing
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• v.36 no.1
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• pp.15-27
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• 2020

Accurate knowledge of land use/land cover (LULC) features and their relative changes over upon the time are essential for sustainable urban management. Urban sprawl growth has been always also a worldwide concern that needs to carefully monitor particularly in a developing country where unplanned building constriction has been expanding at a high rate. Recently, remotely sensed imageries with a very high spatial/spectral resolution and state of the art machine learning approaches sent the urban classification and growth monitoring to a higher level. In this research, we classified the Quickbird satellite imagery by object-based image analysis of Dempster-Shafer (OBIA-DS) for the years of 2002 and 2015 at Karbala-Iraq. The real LULC changes including, residential sprawl expansion, amongst these years, were identified via change detection procedure. In accordance with extracted features of LULC and detected trend of urban pattern, the future LULC dynamic was simulated by using land transformation model (LTM) in geospatial information system (GIS) platform. Both classification and prediction stages were successfully validated using ground control points (GCPs) through accuracy assessment metric of Kappa coefficient that indicated 0.87 and 0.91 for 2002 and 2015 classification as well as 0.79 for prediction part. Detail results revealed a substantial growth in building over fifteen years that mostly replaced by agriculture and orchard field. The prediction scenario of LULC sprawl development for 2030 revealed a substantial decline in green and agriculture land as well as an extensive increment in build-up area especially at the countryside of the city without following the residential pattern standard. The proposed method helps urban decision-makers to identify the detail temporal-spatial growth pattern of highly populated cities like Karbala. Additionally, the results of this study can be considered as a probable future map in order to design enough future social services and amenities for the local inhabitants.

• Journal of Digital Contents Society
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• v.10 no.1
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• pp.1-10
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• 2009

One important issue to generalize the ubiquitous paradigm is the development of user-centralized and intelligent ubiquitous computing systems. Sharing knowledge and correct communication between users and devices are needed to be aware of continuous changed context information and infer services for which users are suited. The goal of this paper is to describe and manage effectively the meaning of services or data which each device offers for interaction between users and devices based on semantic relationships and reasoning. In this paper, we represent semantic data using OWL and design a ubiquitous based intelligent system. We propose some index structures and strategies to process queries classified by each subsystem and adopt labeling schemes to identify classes and resources in the semantic data. We can find devices which satisfies various user's requests exactly and quickly using the proposed strategies.

• Steel and Composite Structures
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• v.18 no.5
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• pp.1305-1330
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• 2015

The successful application of the component-based approach - widely used to model structural joints - requires knowledge of the mechanical properties of the constitutive joint components, including an appropriate assembly procedure to derive the joint properties. This paper presents a component-method model for a structural joint component that is located in the tension zone of blind-bolted connections to concrete-filled tubular steel profiles. The model relates to the response of blind-bolts with headed anchors under monotonic loading, and the blind-bolt is termed the "Extended Hollo-bolt". Experimental data is used to develop the model, with the data being collected in a manner such that constitutive models were characterised for the principal elements which contribute to the global deformability of the connector. The model, based on a system of spring elements, incorporates pre-load and deformation from various parts of the blind-bolt: (i) the internal bolt elongation; (ii) the connector's expanding sleeves element; and (iii) the connector's mechanical anchorage element. The characteristics of these elements are determined on the basis of piecewise functions, accounting for basic geometrical and mechanical properties such as the strength of the concrete applied to the tube, the connection clamping length, and the size and class of the blind-bolt's internal bolt. An assembly process is then detailed to establish the model for the elastic and inelastic behaviour of the component. Comparisons of model predictions with experimental data show that the proposed model can predict with sufficient accuracy the response of the component. The model furthers the development of a full and detailed design method for an original connection technology.

• Journal of the Korea Convergence Society
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• v.11 no.3
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• pp.67-75
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• 2020

The 'level of difficulty' is one of the major factors for learners when selecting learning contents. However, the criteria for the difficulty level is mostly defined by the contents providers. This approach does not support the personalized education which should consider the abilities and environments of various learners. In this research, the knowledge of the learners and contents were formalized and generalized to resolve the issue, and object models, including a metric for personalized difficulty level, were designed in order to be applied for experiments. And then, based on 100 contents for music education and 20 learners, we performed simulations with an implemented tool to validate our approach. The experimental results showed that our method can calculate the personalized difficulty levels considering the similarities between the knowledges from the learning state and the contents. Our approach can be effectively applied to the on-line learning management system which contains easy access to the learning state and contents data.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.05a
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• pp.408-411
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• 2009

In this paper, conventional PI, fuzzy neural network(FNN) and adaptive teaming mechanism(ALM)-FNN for rotor field oriented controlled(RFOC) induction motor are studied comparatively. The widely used control theory based design of PI family controllers fails to perform satisfactorily under parameter variation nonlinear or load disturbance. In high performance applications, it is useful to automatically extract the complex relation that represent the drive behaviour. The use of learning through example algorithms can be a powerful tool for automatic modelling variable speed drives. They can automatically extract a functional relationship representative of the drive behavior. These methods present some advantages over the classical ones since they do not rely on the precise knowledge of mathematical models and parameters. Comparative study of PI, FNN and ALM-FNN are carried out from various aspects which is dynamic performance, steady-state accuracy, parameter robustness and complementation etc. To have a clear view of the three techniques, a RFOC system based on a three level neutral point clamped inverter-fed induction motor drive is established in this paper. Each of the three control technique: PI, FNN and ALM-FNN, are used in the outer loops for rotor speed. The merit and drawbacks of each method are summarized in the conclusion part, which may a guideline for industry application.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.79-82
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• 2019

This study aims to design and implement automated SEO tools that has applied the artificial intelligence techniques for search engine optimization (SEO; Search Engine Optimization). Traditional Search Engine Optimization (SEO) on-page optimization show limitations that rely only on knowledge of webpage administrators. Thereby, this paper proposes the metadata generation system. It introduces three approaches for recommending metadata; i) Downloading the metadata which is the top of webpage ii) Generating terms which is high relevance by using bi-directional Long Short Term Memory (LSTM) based on attention; iii) Learning through the Generative Adversarial Network (GAN) to enhance overall performance. It is expected to be useful as an optimizing tool that can be evaluated and improve the online marketing processes.