• Journal of The Korean Association For Science Education
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• v.12 no.3
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• pp.61-76
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• 1992

The purpose of this study was to develop the instructional model and teaching material to change the middle school students'conceptions of electric current into the scientific ones and to investigate the effects of the model in actual classrooms. We identified the students' ideas and their misunderstanding about the concept of eIectic current through reviewing the literatures and our in this study. Based on the above results, we developed the instructional model and designed the teaching sequence and prepare the learning materials about the unit of the electric current in middle school Our instructional model was based on 'learning cycle' developed by Lawson, but the new stage called "exploration through qualitative questions" to elicit the students' own conceptions was inserted to it. To investigate the effects or the new teaching model, the pre- and post-test using the POE type were administered to experimental group(52 students) taught with learning cycles and control group(52 students) taught with traditional styles. The results are as follows; 1) The rates of correct. predictions was varying according to the kinds of problems. And the rates of the correct. reasons of their predictions were lower than those of the predictions. 2) The mean scores of the post-test of both groups were significantly higher than those of the pre-test. We could not find statistically significant difference in theme an score between experimental group and control group after implementation of the model. But the experimental group gained higher scores than those of the control group on two problem. Therefore, although we cannot show the prominent effects of our teaching model based on learning cycles, there are some effects of our model on changing the middle school students' conceptions of electric current.

• Journal of the Korean Society for Library and Information Science
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• v.40 no.3
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• pp.53-71
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• 2006

The purpose of this study is to investigate how the different types of reading instruction programs and reading methods influenced the creative ability and the self-directed learning ability, They were divided into two groups. Class A was taught to use 'The Author-Reader-Inquirer Cycle'. which concentrated on the writing-centered reading program model. Class B was taught to use 'The Literature Circles'. which concentrated on the speaking and listening-centered reading program model. After reading instruction. the creative ability and the self-directed learning ability increased. The writing-centered reading instruction was more effective than the speaking and listening-centered reading instruction. The reading instruction during the long-period was more effective than that during the short-period. The 'intensive reading' among the reading methods had a significant influence on the creative ability and the self-directed learning ability.

• Journal of Korean Elementary Science Education
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• v.35 no.1
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• pp.54-64
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• 2016

The purpose of this study is to develop instructional strategy which utilizes thinking maps focused on drawing as a measure to enhance science learning motivation, self-directed learning activity and science academic achievement of learners, and to examine the effects of its application. The target unit for this study is 'life cycle of plants' in the fourth grade of elementary school. Two classes of 4th grades of elementary school were selected and divided into two groups. The learners of experimental group have completed thinking map by drawing a picture to express the results to be observed and measured, and used it to arrange the learning contents. The result of this study is as follows. First, it is proven that using thinking maps focused on drawing actually helped improving the motivation of learners to study science. Second, it is proven that this strategy was effective to change their self-directed learning ability in positive ways. Third, it contributed to the improvement of learners' science academic achievement. We found out that the application of this strategy enabled them to enjoy the mapping using drawing, to be immersed in learning, to better recognize the scientific concepts and the structure of learning contents, and to have a positive awareness of the usefulness of thinking maps focused on drawing.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.428-439
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• 2020

The continuous development of information and communication technologies has resulted in an exponential increase in data. Consequently, technologies related to data analysis are growing in importance. The shipbuilding industry has high production uncertainty and variability, which has created an urgent need for data analysis techniques, such as machine learning. In particular, the industry cannot effectively respond to changes in the production-related standard time information systems, such as the basic cycle time and lead time. Improvement measures are necessary to enable the industry to respond swiftly to changes in the production environment. In this study, the lead times for fabrication, assembly of ship block, spool fabrication and painting were predicted using machine learning technology to propose a new management method for the process lead time using a master data system for the time element in the production data. Data preprocessing was performed in various ways using R and Python, which are open source programming languages, and process variables were selected considering their relationships with the lead time through correlation analysis and analysis of variables. Various machine learning, deep learning, and ensemble learning algorithms were applied to create the lead time prediction models. In addition, the applicability of the proposed machine learning methodology to standard work hour prediction was verified by evaluating the prediction models using the evaluation criteria, such as the Mean Absolute Percentage Error (MAPE) and Root Mean Squared Logarithmic Error (RMSLE).

• Journal of Korea Multimedia Society
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• v.6 no.4
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• pp.685-697
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• 2003

The Web based multimedia programmes/courses are becoming widely available in recent years. Most of these courses focus on Behaviorist way of learning, which does not promote deep learning in any way. For Adults this approach further incapacitated, as it does not satisfy Andragogical needs. The search for Constructivist way of learning through the web applied to Indian conditions led to need for developing a curriculum development approach that would promote construction of knowledge through web based collaboration. This paper attempts to reengineer existing curriculum development processes and lays out a framework of‘Problem Based Online Learning (PBOL)’curriculum design. In this context, entire curriculum development life cycle is evolved and explained. This is a part of doctoral work (Ph.D), which is in progress and being undertaken by K.James Mathai, and guided of Dr.D.S.Karaulia.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.135-138
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• 2008

최근 인간을 모방하는 휴머노이드 로봇(Humanoid robot)에 대한 관심이 증가함에 따라, 기계공학, 생체공학, 제어이론 등 여러 분야에서 관련 연구가 활발히 진행되고 있다. 이에 본 논문에서는 액츄에이터(Actuator)가 없이 경사진 지면을 걸을 수 있는 두 발을 가진 패시브 로봇(Passive robot)을 대상으로 강화학습과 메니폴드(Manifold control) 기법을 사용하여 안정적으로 걸을 수 있도록 제어기(Controller)를 설계하는 방안을 고려한다.

• The Mathematical Education
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• v.39 no.2
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• pp.151-166
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• 2000

The purpose of this study is to understand what two models of SOLO taxonomy and van Hiele theory suggest and find out what relation there is between the category system of the SOLO taxonomy and the thinking level of the van Hiele theory. The van Hiele theory describes in line of ranking level so that it may increase the teaching effects by putting together a class, which takes into consideration the students thoughts. The SOLO taxonomy focused on the response mode of the students rather than the thinking level or the developmental stage of them to pursuit the method that can describe the students understanding in depth quality-wise. Although the SOLO taxonomy and the van Hiele model seem to have different form and character from outside in terms of their goals, a closer examination reveals that the two stances have much in common and that the models are complementary. Although the van Hiele placed more focus on the thoughts, because the conclusion was based on the students responses, the van Hiele theory can be interpreted within the structure identified in the SOLO model. In this study, we have tried to understand how the response structure form the SOLO taxonomy and the thinking level of the van Hiele theory are related, based on the studies of Pegg and Davery1998). If you briefly look at them, there are following corresponding relation between the SOLO taxonomy and the van Hiele theory. a) The relational level(R) in iconic moe is van Hiele level 1. b) The multisturctural level(M$_2$) in the second cycle of concrete-symbolic mode is van Hiel level 2. c) The relation level(R$_2$) in the second cycle of concrete-symbolic mode is van Hiele level 3. d) The unistructural level(U$_2$) in the second cycle of formal mode is van Hiele level 4. e) The postformal mode is van Hiele levle 5. Though it would be difficult to conclude that these correspondences were perfectly done, if you look at their relation, you can see that the learning process of the students were not carried out uniformly. Therefore, by studying the students response structure, using the SOLO taxonomy, and identifying the learning cycle and understand the geometrical concept more in depth.

• Journal of Information Processing Systems
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• v.19 no.1
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• pp.67-79
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• 2023

In the image field, data augmentation refers to increasing the amount of data through an editing method such as rotating or cropping a photo. In this study, a generative adversarial network (GAN) image was created using CycleGAN, and various colors of dogs were reflected through data augmentation. In particular, dog data from the Stanford Dogs Dataset and Oxford-IIIT Pet Dataset were used, and 10 breeds of dog, corresponding to 300 images each, were selected. Subsequently, a GAN image was generated using CycleGAN, and four learning groups were established: 2,000 original photos (group I); 2,000 original photos + 1,000 GAN images (group II); 3,000 original photos (group III); and 3,000 original photos + 1,000 GAN images (group IV). The amount of data in each learning group was augmented using existing data augmentation methods such as rotating, cropping, erasing, and distorting. The augmented photo data were used to train the MobileNet_v3_Large, ResNet-152, InceptionResNet_v2, and NASNet_Large frameworks to evaluate the classification accuracy and loss. The top-3 accuracy for each deep neural network model was as follows: MobileNet_v3_Large of 86.4% (group I), 85.4% (group II), 90.4% (group III), and 89.2% (group IV); ResNet-152 of 82.4% (group I), 83.7% (group II), 84.7% (group III), and 84.9% (group IV); InceptionResNet_v2 of 90.7% (group I), 88.4% (group II), 93.3% (group III), and 93.1% (group IV); and NASNet_Large of 85% (group I), 88.1% (group II), 91.8% (group III), and 92% (group IV). The InceptionResNet_v2 model exhibited the highest image classification accuracy, and the NASNet_Large model exhibited the highest increase in the accuracy owing to data augmentation.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.7
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• pp.144-150
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• 1999

n active control for the swing of crane systems is very important for increasing the productivity. This article introduces the control for the position and the swing of a crane using the fuzzy learning method. Because the crane is a multi-variable system, learning is done to control both position and swing of the crane. Also the fuzzy control rules are separately acquired with the loading and unloading situation of the crane for more accurate control. The result of simulations shows that the crane is just controlled for a very large swing angle of 1 radian within nearly one cycle.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.3
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• pp.176-183
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• 2010

The benefits of information technology cannot be obtained unless potential users utilize it for their work. This led to a lot of research works on computer system acceptance. But most of the works address the early stage of system introduction, leaving the learning effect on system acceptance unexplored. In this longitudinal study, two groups of novice and experienced users have been empirically investigated and compared for their acceptance of computer system and for the learning effect of actual usage. A research model based on the technology acceptance theory has been proposed and applied to the two groups. The result shows that the factor job relevance gets more important and the effect of user training on system acceptance diminishes as time passes. This finding may help introducing computer systems which can be easily accepted by users over the whole life cycle period of computer systems.