• Environmental and Resource Economics Review
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• v.9 no.4
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• pp.747-771
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• 2000

This paper reports the results of a study to elicit willingness to pay (WTP) for changes in health risks from exposure to As, Pb, THM in tap water using experimental market method. The experimental market method, compared with other non-market valuation methods, allows us to use incentive compatible demand revealing scheme, to acquire market-like experience through repetitive auctions, and to incorporate learning process by providing new information during the session. Participants seemed to utilize the objective risk information in a 'rational' manner, and to change their WTP bids accordingly. Moreover they were able to reduce the 'ambiguity' in risk perception processes when objective risk probabilities provided are quite different from their subjective perceptions. Nonetheless, anchoring effects appeared to be still persistent in spite of market-like experience and learning opportunity. And implicit values entailed by WTP bid/risk tradeoffs indicate a wide variation in values across alternative risk reductions and overrated responses to very small risk reductions.

• Korean Journal of English Language and Linguistics
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• v.2 no.1
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• pp.123-147
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• 2002

As far as the recent ELT research concerned, it seems to have been no hot ‘theoretical’ issues, but ‘practical’ ones in general: e.g., learners and learning, components of proficiency, correlates of L2 learning, etc. This paper focuses on the theme given above, with a special reference to the sub-title: specifically, 1) World English, world Englishes and world's lingua franca; 2) ENL, ESL and EFL; 3) Grammars, style manuals, dictionaries and media; 4) Pronunciation models: RP, BBC model and General American, Network Standard; 5) Lexical, grammatical variations and discourse grammars; 6) Beliefs and subjective theories in foreign language research; 7) Dilemma among radical, canonical and eclectic views. In conclusion, the author offers a modest proposal: we need to appeal to our own experience, intention, feeling and purpose, that is, our identity to express “our own selves” in our contexts toward the world anywhere, if not sounding authentic enough, but producing it plausibly well. It is time for us (with our ethno-cultural autonomy) to need to be complementary to and parallel with its native speakers' linguistic-cultural authenticity in terms of the broadest mutual understanding.

• Journal of Korea Multimedia Society
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• v.22 no.10
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• pp.1149-1159
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• 2019

We present a novel deep learning architecture for obtaining a latent image from a single blurry image, which contains dynamic motion blurs through object/camera movements. The proposed architecture consists of two sub-modules: blur image restoration and optical flow estimation. The tasks are highly related in that object/camera movements make cause blurry artifacts, whereas they are estimated through optical flow. The ablation study demonstrates that training multi-task architecture simultaneously improves both tasks compared to handling them separately. Objective and subjective evaluations show that our method outperforms the state-of-the-arts deep learning based techniques.

• Journal of Korea Multimedia Society
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• v.22 no.6
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• pp.646-654
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• 2019

Image denoising is considered as a key factor for capturing high-quality photos in digital cameras. Thus far, several image denoising methods have been proposed in the past decade. In addition, previous studies either relied on deep learning-based approaches or used the hand-crafted filters. Unfortunately, the previous method mostly emphasized on image denoising regardless of preserving or recovering the detail information in result images. This study proposes an detail extraction network to estimate detail information from a noisy input image. Moreover, the extracted detail information is utilized to enhance the final denoised image. Experimental results demonstrate that the proposed method can outperform the existing works by a subjective measurement.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1405-1419
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• 2018

An image fusion method is proposed on the basis of depth model segmentation to overcome the shortcomings of noise interference and artifacts caused by infrared and visible image fusion. Firstly, the deep Boltzmann machine is used to perform the priori learning of infrared and visible target and background contour, and the depth segmentation model of the contour is constructed. The Split Bregman iterative algorithm is employed to gain the optimal energy segmentation of infrared and visible image contours. Then, the nonsubsampled contourlet transform (NSCT) transform is taken to decompose the source image, and the corresponding rules are used to integrate the coefficients in the light of the segmented background contour. Finally, the NSCT inverse transform is used to reconstruct the fused image. The simulation results of MATLAB indicates that the proposed algorithm can obtain the fusion result of both target and background contours effectively, with a high contrast and noise suppression in subjective evaluation as well as great merits in objective quantitative indicators.

• Smart Structures and Systems
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• v.26 no.6
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• pp.797-807
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• 2020

Due to the influence of nonlinearity and time-variation, it is difficult to establish an accurate model of concrete frame structures that adopt active controllers. Fuzzy theory is a relatively appropriate method but susceptible to human subjective experience to decrease the performance. This paper proposes a novel artificial intelligence based EBA (Evolved Bat Algorithm) controller with machine learning matched membership functions in the complex nonlinear system. The proposed affine transformed membership functions are adopted and stabilization and performance criterion of the closed-loop fuzzy systems are obtained through a new parametrized linear matrix inequality which is rearranged by machine learning affine matched membership functions. The trajectory of the closed-loop dithered system and that of the closed-loop fuzzy relaxed system can be made as close as desired. This enables us to get a rigorous prediction of stability of the closed-loop dithered system by establishing that of the closed-loop fuzzy relaxed system.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.4_2
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• pp.573-586
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• 2022

Corrosion can cause dangerous and expensive damage and failures of ship hulls and equipment. Therefore, it is necessary to maintain the vessel by periodic corrosion inspections. During visual inspection, many corrosion locations are inaccessible for many reasons, especially safety's point of view. Including subjective decisions of inspectors is one of the issues of visual inspection. Automation of visual inspection is tried by many pieces of research. In this study, we propose image preprocessing methods by image patch segmentation and thresholding. YOLOv5 was used as an object detection model after the image preprocessing. Finally, it was evaluated that corrosion detection performance using the proposed method was improved in terms of mean average precision.

• The Journal of Korean Academic Society of Nursing Education
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• v.9 no.1
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• pp.81-93
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• 2003

Purpose: The purpose of this study was to develop a PBL module in maternity nursing based on the clinical cases. A PBL module applied to maternity nursing class to test the effects on improving the learning ability of students. And it would be used for developing further PBL module even more perfectly. Method: We selected the concept of the PBL module which is based on the purpose of the contents of maternity nursing class and national test held by Korean Nursing Association. The module scenario was composed up of the cases of clinical practices and was also checked by clinical practice professionals as well as the nursing professionals in other colleges. We used this PBL module for the 20 second grade student nurses in K college for 6 weeks. Besides, we checked self-analyses on the PBL class, assessments done by students on the PBL class itself and on the academic adviser and analyzed the students' subjective statements on the PBL class . Results: The achievements of the experimental students given a PBL class, are better than those of the control group statistically. And the experimental group do their almost all learning planned actively for themselves and show their positive responses on the PBL class being helpful in practicing clinical cases. Conclusion: PBL class could be considered the method to fortify student nurses' abilities on adjusting themselves to clinical real situations through the learning planned by themselves. Afterwards it is necessary to activate PBL class in nurse education. Most of all, it is more important that nurse educators should recognize the values of this PBL class and try to apply it in reality.

• KIEAE Journal
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• v.17 no.5
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• pp.95-100
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• 2017

Purpose: The purpose of this study is to investigate the prior art based on deep learning to objectively calculate the metabolic rate which is the subjective factor for the PMV optimum control and to make a plan for future research based on this study. Methods: For this purpose, the theoretical and technical review and applicability analysis were conducted through various documents and data both in domestic and foreign. Results: As a result of the prior art research, the machine learning model of artificial neural network and deep learning has been used in various fields such as speech recognition, scene recognition, and image restoration. As a representative case, OpenCV Background Subtraction is a technique to separate backgrounds from objects or people. PASCAL VOC and ILSVRC are surveyed as representative technologies that can recognize people, objects, and backgrounds. Based on the results of previous researches on deep learning based on metabolic rate for occupational metabolic rate, it was found out that basic technology applicable to occupational metabolic rate calculation technology to be developed in future researches. It is considered that the study on the development of the activity quantity calculation model with high accuracy will be done.

• Philosophy of Education
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• no.39
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• pp.191-221
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• 2009

The aim of this study is to analyse of elements and structure of consciousness theory in the 1887 Psychology written by John Dewey, and to research its educational implications. Conclusions are as follows: Firstly, consciousness theory articulated in first edition of Dewey's Psychology was influenced by neo-Hegelian G. S. Hall, and then characteristics of its theory was metaphysical and idealistic. But after of researching the work of William James, his approach to consciousness changed surprisingly from idealistic to experimental. His experimental approach and scientific attitude to it influenced the formation and development of advanced theories in his epistemology, axiology and pedagogy. Secondly, the structure of consciousness expressed by Dewey has three forms such as knowledge, feeling and will(or volition). This forms are too dynamic and unitary. Dewey considered cognition, feeling, will to be integral functions of each self. The tripartite functions of self, moreover, are unified in will. In other word, will combines subjective feeling and objective knowledge as one self. Will regulates impulse because it powers some stimulus into activity of self. In this view point, his theory of consciousness differs from traditional theories about consciousness for emphasizing dynamic relations and functions. Thirdly, Dewey's theory of consciousness will give some important implications to educational field. It is necessary to fundamental arguments about conscious conditions of learners as a human. For it is impossible to establish some aim of learning, to organize meaningful contents of learning, and also to create some effective methods of learning without consideration of this conditions. And it is important to construct and organize the contents and methods of learning for widening and deepening of educational experiences. Then consciousness and experiences of learners interact each other, so then they will produce some meaningful results of learning in this process.