• Journal of The Korean Association For Science Education
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• v.33 no.7
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• pp.1418-1430
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• 2013

In this study, we investigated the writing process components and the writing strategies that appeared in the process of argumentative writing through students' think-alouds and semi-structured interviews. The subjects were 18 eighth graders. During argumentative writing, students were asked to decide whether they agreed with the given argument or not on the basis of information provided in the writing task. We categorized the writing process components and the writing strategies by analyzing the protocols of students' think-alouds and interviews, and evaluated the level of their written compositions. The analyses of the results indicated that the writing process components of argumentative writing showed different characteristics from those of problem solving writing in several components such as setting goals, organizing an outline, and evaluating content. In addition, the writing process component 'coordinating information' was newly discovered in argumentative writing. The writing strategies were categorized into four groups by the types of decision making (reflective/intuitive) and the existence of outline organization: Reflective decision making and outline organization, reflective decision making and no outline organization, intuitive decision making and outline organization, and intuitive decision making and no outline organization. Students with the reflective decision making and outline organization strategy were found to get the highest scores in written composition in terms of the relationship between the argument and its grounds, the rebuttal of the opposing argument, and the structure of the writing. Educational implications are discussed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.834-841
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• 2022

Recently, applying artificial intelligence technologies in various fields of production has drawn an upsurge of research interest due to the increase for smart factory and artificial intelligence technologies. A great deal of effort is being made to introduce artificial intelligence algorithms into the defect detection task. Particularly, detection of defects on the surface of metal has a higher level of research interest compared to other materials (wood, plastics, fibers, etc.). In this paper, we compare and analyze the speed and performance of defect classification by combining machine learning techniques (Support Vector Machine, Softmax Regression, Decision Tree) with dimensionality reduction algorithms (Principal Component Analysis, AutoEncoders) and two convolutional neural networks (proposed method, ResNet). To validate and compare the performance and speed of the algorithms, we have adopted two datasets ((i) public dataset, (ii) actual dataset), and on the basis of the results, the most efficient algorithm is determined.

• Journal of The Korean Association For Science Education
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• v.42 no.2
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• pp.239-252
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• 2022

This study aims to develop performance criteria based on characteristics observed in science inquiry tasks for elementary school students. First, the performance characteristics by observing 70 fifth-grade elementary school students' science inquiry activity report are listed. Second, the checklist-type scoring criteria in connection with the theoretical framework of scientific inquiry process and relevant competencies are developed. Third, with the developed scoring criteria, 11 raters participate in scoring 350 students' reports. The main findings are as follow: first, the scoring data are well-fitted for the many-faceted Rasch model, and 22 scoring criteria are reasonably-well differentiated for various levels of proficiency. Second, at low performance level, observable characteristics are to answer questions explicitly required by the task or to observe objects or phenomena using pre-learned scientific concepts, while at high performance level, to explore additional data other than given data or to reflect on one's experimental process. Based on the results, the usefulness of analyzing students' performance characteristics for developing the scoring criteria, and further research directions are discussed.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.2
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• pp.196-206
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• 2012

AESA radar is able to instantaneously and adaptively position and control the beam, and such adaptive beam pointing of AESA radar enables to remarkably improve the multi-mission capability, compared with mechanically scanned array radar. AESA radar brings a new challenges, radar resource management(RRM), which is a technique efficiently allocating finite resources, such as energy and time to each task in an optimal and intelligent way. Especially radar beam scheduling is the most critical component for the success of RRM. In this paper, we proposed stochastic radar beam scheduling algorithm using simulated annealing(SA), and evaluated the performance on the multi-function radar scenario. As a result, we showed that our proposed algorithm is superior to previous dispatching rule based scheduling algorithm from the viewpoint of beam processing latency and the number of scheduled beams, with real time capability.

• Korean Journal of Computational Design and Engineering
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• v.17 no.6
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• pp.417-425
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• 2012

In recent years, great attention has been paid to using simple physical objects as tangible objects to improve user interaction in augmented reality (AR) environments. In this paper, we address AR-based user interaction using tangible objects, which has been used as a key component for virtual design evaluation of engineered products including digital handheld products. We herein consider the use of two types (product-type and pointer-type) of tangible objects. The user creates input events by touching specified parts of the product-type object with the pointer-type object, and the virtual product reacts to the events by rendering its visual and auditory contents on the output devices. The product-type object is used to reflect the geometric shape of a product of interest and to determine its position and orientation in the AR environment. The pointer-type object is used to recognize the reference position of the pointer (or finger) in the same environment. The rapid prototype of the product is employed as a good alternative to the product-type object, but various alternatives to the pointer-type object can be considered according to fabrication process and touching mechanism. In this paper, we present four alternatives to the pointer-type object and investigate their strong and weak points by performing experimental comparison of their various aspects including interaction accuracy, task performance, and qualitative user experience.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.51 no.5
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• pp.242-248
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• 2002

It is important to develop new effective technologies to increase the interruption capacity and to reduce the size of a UB(Gas Circuit Breakers). Major design parameters such as nozzle geometries and interrupting chamber dimensions affect the cooling of the arc and the breaking performance. But it is not easy to test real GCB model in practice as in theory. Therefore, a simulation tool based on a computational fluid dynamics(CFD) algorithm has been developed to facilitate an optimization of the interrupter. Special attention has been paid to the supersonic flow phenomena between contacts and the observation of hat-gas flow for estimating the breaking performance. However, there are many difficult problems in calculating the flow characteristics in a GCB such as shock wave and complex geometries, which may be either static or in relative motion. Although a number of mesh generation techniques are now available, the generation of meshes around complicated, multi-component geometries like a GCB is still a tedious and difficult task for the computational fluid dynamics. This paper presents the CFD program using CFB-CAD integration technique based on Cartesian cut-cell method, which could reduce researcher's efforts to generate the mesh and achieve the accurate representation of the geometry designed by a CAD tools.

• Journal of Power System Engineering
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• v.20 no.4
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• pp.32-37
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• 2016

This paper proposes two measurement methods for injured rate of fish surface using color image segmentation method based on K-means clustering algorithm and Otsu's threshold algorithm. To do this task, the following steps are done. Firstly, an RGB color image of the fish is obtained by the CCD color camera and then converted from RGB to HSI. Secondly, the S channel is extracted from HSI color space. Thirdly, by applying the K-means clustering algorithm to the HSI color space and applying the Otsu's threshold algorithm to the S channel of HSI color space, the binary images are obtained. Fourthly, morphological processes such as dilation and erosion, etc. are applied to the binary image. Fifthly, to count the number of pixels, the connected-component labeling is adopted and the defined injured rate is gotten by calculating the pixels on the labeled images. Finally, to compare the performances of the proposed two measurement methods based on the K-means clustering algorithm and the Otsu's threshold algorithm, the edge detection of the final binary image after morphological processing is done and matched with the gray image of the original RGB image obtained by CCD camera. The results show that the detected edge of injured part by the K-means clustering algorithm is more close to real injured edge than that by the Otsu' threshold algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.12
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• pp.1113-1119
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• 2000

To operate a process plant safely and economically, process monitoring is very important. Process monitoring is the task to identify the state of the system from sensor data. Process monitoring includes data acquisition, regulatory control, data reconciliation, fault detection, etc. This research focuses on the data recon-ciliation using scale-space filtering and fault detection using functional-link associative neural networks. Scale-space filtering is a multi-resolution signal analysis method. Scale-space filtering can extract highest frequency factors(noise) effectively. But scale-space filtering has too large calculation costs and end effect problems. This research reduces the calculation cost of scale-space filtering by applying the minimum limit to the gaussian kernel. And the end-effect that occurs at the end of the signal of the scale-space filtering is overcome by using extrapolation related with the clustering change detection method. Nonlinear principal component analysis methods using neural network have been reviewed and the separately expanded functional-link associative neural network is proposed for chemical process monitoring. The separately expanded functional-link associative neural network has better learning capabilities, generalization abilities and short learning time than the exiting-neural networks. Separately expanded functional-link associative neural network can express a statistical model similar to real process by expanding the input data separately. Combining the proposed methods-modified scale-space filtering and fault detection method using the separately expanded functional-link associative neural network-a process monitoring system is proposed in this research. the usefulness of the proposed method is proven by its application a boiler water supply unit.

• Journal of the Korean Institute of Gas
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• v.7 no.3 s.20
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• pp.24-31
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• 2003

To operate process plant safely and economically, process monitoring is very important. There are a great number of data acquired through distributed control system and process information system. Fault monitoring is the task with difficulties owing to not only the huge amount of data, but also nonlinearity of chemical processes. In this research, the program, REFA, based on PCA and functional link associative neural network has developed. REFA has better learning capabilities, generalization abilities, and shorter learning time than existing neural network programs. In this work its usefulness has proven by application to Tennessee Eastman process.

• School Mathematics
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• v.9 no.4
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• pp.487-506
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• 2007

The aims of this study is figure out the characteristics of justification patterns and mathematical representation which are derived from 14 mathematically gifted middle school students in the process of solving the spatial tasks on Archimedean solid. This study shows that mathematically gifted students apply different types of justification such as empirical, or deductive justification and partial or whole justification. It would be necessary to pay attention to the value of informal justification, by comparing the response of student who understood the entire transformation process and provided a reasonable explanation considering all component factors although presenting informal justification and that of student who showed formalization process based on partial analysis. Visual representation plays an valuable role in finding out the Idea of solving the problem and grasping the entire structure of the problem. We found that gifted students tried to create elaborated symbols by consolidating mathematical concepts into symbolic re-presentations and modifying them while gradually developing symbolic representations. This study on justification patterns and mathematical representation of mathematically gifted students dealing with spatial geometry tasks provided an opportunity for understanding their the characteristics of spacial geometrical thinking and expending their thinking.