• The Journal of Korean Academic Society of Nursing Education
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• v.18 no.1
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• pp.14-24
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• 2012

Purpose: This study was conducted to identify the effect of simulation-based education relevant to the care of patients with acute renal failure (ARF) for third-year nursing students. Methods: This study was a non-equivalent control pre-posttest design. Based on the clinical situation scenarios pertaining to patients with ARF, a simulation-based learning module was developed using Human Patient Simulator version 6 (HPS6) manufactured by Medical Education Technologies Inc. The pretest was conducted so as to evaluate the difference in prior knowledge and clinical competence between two groups. The control group consisted of 91 students during the 2010 academic year and the experimental group consisted of 94 students during the 2011 academic year. Data were analysed using SPSS/win 10.1. Results: In the experimental group, knowledge related to care for ARF patients was not significantly increased; however, clinical competence improved significantly for the experimental group. Conclusion: In conclusion, the simulation-based education program was effective in contributing towards the development of clinical competence. Increased development of clinical competence is vital for today's clinical environment where nursing professionals need the necessary knowledge, thinking, and performance skills to meet the needs of the hospital and their patients.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.15 no.3
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• pp.63-69
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• 2007

Culture is that the system of shared beliefs, values, customs, behaviors, and artifacts that the members of society use to cope with their world and with one another, and that are transmitted from generation to generation through learning. Members of an organization are affected by culture. And dissensions in an organization give negative effects to behavior of the members, especially to satisfaction from organization. This study is on the dissension management by considering of cultural characteristics of pilots. Cultural characteristics of pilots were surveyed and analyzed with the V5M94(values survey module94) which was developed by Hofstede. As results, the cultural indexes of the pilots were different from the national means. The indexes presented that korean pilots' cultural characteristics are low POI, high IDV, low MAS and low UAI as North European cultural characteristics. For managing the pilots group, make expansion of opportunity to take part in decision making, release or share of informations are required. And motivations, delegation, free from unnecessary interventions, understanding and forgiveness rather than disciplinary punishment, thoughtful considerations could be effectiveness. And for developing more effective management methods, management strategies of north european airlines should be studied.

• Journal of Korea Game Society
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• v.1 no.1
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• pp.61-67
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• 2001

This paper describes a program which learns good strategies for two-poison, deterministic, zero-sum board games of perfect information. The program learns by simply playing the game against either a human or computer opponent. The results of the program's teaming of a lot of games are reported. The program consists of search kernel and a move generator module. Only the move generator is modified to reflect the rules of the game to be played. The kernel uses a temporal difference procedure combined with a backpropagation neural network to team good evaluation functions for the game being played. Central to the performance of the program is the search procedure. This is a the capture tree search used in most successful janggi playing programs. It is based on the idea of using search to correct errors in evaluations of positions. This procedure is described, analyzed, tested, and implemented in the game-teaming program. Both the test results and the performance of the program confirm the results of the analysis which indicate that search improves game playing performance for sufficiently accurate evaluation functions.

• Hwankyungkyoyuk
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• v.19 no.3
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• pp.80-92
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• 2006

The purpose of this study was to make valuable suggestions for improving environmental education(EE) teaching materials. For the purpose of this study, we analyzed four secondary school EE textbooks in the perspective of environmental literacy components. The findings of this study are as follows: (1) As a whole, the EE textbooks tend to focus the understanding environmental knowledge much more than environmental activities. (2) In 'main text' domain of EE textbooks, environmental information, including environmental issue knowledge, is much more focused than environmental attitudes and behavior, including socio-political and environmental issue knowledge. (3) In 'graphic data' domain, environmental information about environmental issue knowledge was most prevalent. (4) Most learning activities focus on 'issue skill' component, rather than 'attitude' and 'action' component. (5) The objectives of EE in the 7th national Curriculum were not explicitly embedded in textbooks and too much is inclined toward 'knowledge' and 'skill'. Accordingly, it is necessary to develop 'module-type' EE textbooks to enable integrative EE. Also, it is suggested to develop specific strategies for linking environmental knowledge and attitude/behavior.

• Proceedings of the SAREK Conference
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• 2008.06a
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• pp.282-287
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• 2008

Identification of steady-state is the first step in developing a fault detection and diagnosis (FDD) system. In a complete FDD system, the steady-state detector will be included as a module in a self-learning algorithm which enables the working system's reference model to "tune" itself to its particular installation. In this study, a steady-state detector of a residential air conditioner based on moving windows was designed. Seven representing measurements were selected as key features for steady-state detection. The optimized moving window size and the feature thresholds was suggested through startup transient test and no-fault steady-state test. Performance of the steady-state detector was verified during indoor load change test. From the research, the general methodology to design a moving window steady-state detector was provided for vapor compression applications.

• Perspectives in Nursing Science
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• v.8 no.2
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• pp.86-96
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• 2011

Purpose: This study examined the effects of simulation-based education on knowledge about and self-confidence in maternity nursing care in senior students. Methods: One group, pre-post design, was utilized with 28 students. The simulation-based maternity nursing education that consisted of two sessions each 2 hours long for intrapartum and postpartum care was provided to 4 small groups. An expert panel of 3 maternity clinical instructors developed the module with a high-fidelity maternal simulator. Core items of knowledge about and self-confidence in maternity nursing care were measured with 13 items before and after the sessions. Results: The knowledge score did not increase significantly (z=-1.95, p=.05); however, self-confidence in maternity nursing care showed a significant change in the posttest (z=-2.82, p<.001). The subjective evaluation of the students indicated that the simulation-based education was helpful in preparing for clinical practicum as far as interaction with clients, psychological readiness to practice, and learning efficiencies. Conclusion: The simulation-based nursing education was useful in improving self-confidence in clinical performance for childbirth and postpartum care in nursing students. Along with the application of diverse scenarios in simulations, modules with standard patients and role-plays are also recommended for maternity nursing practicum to empower the competency of the students.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.11
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• pp.585-592
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• 2016

A topic segmentation module is to divide statements or conversations into certain topic units. Until now, topic segmentation has progressed in the direction of finding an optimized set of segments for a whole document, considering it all together. However, some applications need topic segmentation for a part of document which is not finished yet. In this paper, we propose a model to perform topic segmentation during the progress of the statement with a supervised learning model that uses a convolution neural network. In order to show the effectiveness of our model, we perform experiments of topic segmentation both on-line status and off-line status using C99 algorithm. We can see that our model achieves 17.8 and 11.95 of Pk score, respectively.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.72-79
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• 2008

The weak point of the artificial neural network(ANN) is that it is easy to fall in local minima when it learns too much nonlinear data. Accordingly, the classification ratio must be low. To overcome this weakness, the hybrid method has been proposed. That is, the ANN learns data selectively after detecting the defect position by the support vector machine(SVM). First, the SVM has been used for determination of the defect position and then the magnitude of the defect has been measured by the ANN. In off-design condition, the operation region of the engine is wide and the nonlinearity of learning data increases. The module system, dividing the whole operating region into reasonably small-size sections, has been suggested to solve this problem. In this study, the proposed algorithm has diagnosed the defects of triple components as well as single and dual components of the gas turbine engine in off-design condition.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.3942-3961
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• 2019

Recently, the models of deep super-resolution networks can successfully learn the non-linear mapping from the low-resolution inputs to high-resolution outputs. However, for large scaling factors, this approach has difficulties in learning the relation of low-resolution to high-resolution images, which lead to the poor restoration. In this paper, we propose Stage Generative Adversarial Networks (Stage-GAN) with semantic maps for image super-resolution (SR) in large scaling factors. We decompose the task of image super-resolution into a novel semantic map based reconstruction and refinement process. In the initial stage, the semantic maps based on the given low-resolution images can be generated by Stage-0 GAN. In the next stage, the generated semantic maps from Stage-0 and corresponding low-resolution images can be used to yield high-resolution images by Stage-1 GAN. In order to remove the reconstruction artifacts and blurs for high-resolution images, Stage-2 GAN based post-processing module is proposed in the last stage, which can reconstruct high-resolution images with photo-realistic details. Extensive experiments and comparisons with other SR methods demonstrate that our proposed method can restore photo-realistic images with visual improvements. For scale factor ${\times}8$, our method performs favorably against other methods in terms of gradients similarity.

• Journal of Broadcast Engineering
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• v.23 no.6
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• pp.760-767
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• 2018

Advanced driver assistance system(ADAS) is a major technique in the intelligent vehicle field. The techniques for ADAS can be separated in two classes, i.e., methods that directly control the movement of vehicle and that indirectly provide convenience to driver. In this paper, we propose a novel system that gives a visual assistance to driver by translating a night road image to a day road image. We use the black box images capturing the front road view of vehicle as inputs. The black box images are cropped into three parts and simultaneously translated into day images by the proposed image translation module. Then, the translated images are recollected to original size. The experimental result shows that the proposed method generates realistic images and outperforms the conventional algorithms.