• Journal of the Korean Society of School Health
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• v.35 no.3
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• pp.104-112
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• 2022

Purpose: The study aimed to examine the effects of disaster nursing simulation training on attitudes toward disaster management, disaster preparedness, learning self-efficacy and nursing practice satisfaction in nursing college students. Methods: The study is based on a one-group pretest-posttest design. A total of 95 nursing students were recruited from a nursing college. Disaster nursing simulation training for fire and earthquake situations were provided for 8 hours in one day. Results: There were significant differences in nursing students' attitudes toward disaster management (t=2.20, p=.030), disaster preparedness (t=7.88, p<.001), learning self-efficacy (t=3.69, p<.001), and nursing practice satisfaction (t=5.28, p<.001). Conclusion: Based on our findings, it is necessary to implement disaster nursing simulation training to improve disaster nursing competency of college students.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.47-52
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• 2023

With the growing data size and the increased computing load in machine learning, energy-efficient resource planning in IoT systems is becoming increasingly important. In this paper, we suggest a new resource planning policy for real-time workloads that can be fluctuated over time in IoT systems. To handle such situations, we categorize real-time tasks into fixed tasks and variable tasks, and optimize the resource planning for various workload conditions. Based on this, we initiate the IoT system with the configuration for the fixed tasks, and when variable tasks are activated, we update the resource planning promptly for the situation. Simulation experiments show that the proposed policy saves the processor and memory energy significantly.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.589-591
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• 2023

현재 수치예보 시스템은 항공기, 위성 등 다양한 센서에서 얻은 다종 관측 데이터를 동화하여 대기 상태를 추정하고 있지만, 관측변수 또는 물리량이 서로 다른 관측들을 처리하기 위한 계산 복잡도가 매우 높다. 본 연구에서 기존 시스템의 계산 효율성을 개선하여 관측을 평가하거나 전처리하는 데에 효율적으로 활용하기 위해, 각 관측의 특성을 고려한 자기 지도학습 방법을 통해 멀티모달 기상관측으로부터 실제 대기 상태를 추정하는 방법론을 제안하고자 한다. 비균질적으로 수집되는 멀티모달 기상관측 데이터를 융합하기 위해, (i) 기상관측의 heterogeneous network를 구축하여 개별 관측의 위상정보를 표현하고, (ii) pretext task 기반의 self-supervised learning을 바탕으로 개별 관측의 특성을 표현한다. (iii) Graph neural network 기반의 예측 모델을 통해 실제에 가까운 대기 상태를 추정한다. 제안하는 모델은 대규모 수치 시뮬레이션 시스템으로 수행되는 기존 기술의 한계점을 개선함으로써, 이상 관측 탐지, 관측의 편차 보정, 관측영향 평가 등 관측 전처리 기술로 활용할 수 있다.

• The Journal of the Acoustical Society of Korea
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• v.25 no.1
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• pp.14-20
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• 2006

In this paper. a novel technique to set up the initial weights in BSS of delayed mixtures is proposed. After analyzing Eigendecomposition for the correlation matrix of mixing data. the initial weights are set from the Eigenvectors ith delay information. The Proposed setting of initial weighting method for conventional FDICA technique improved the separation Performance. The computer simulation shows that the Proposed method achieves the improved SIR and faster convergence speed of learning curve.

• Journal of the Semiconductor & Display Technology
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• v.23 no.2
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• pp.107-113
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• 2024

Scheduling of semiconductor test facilities has been crucial since effective scheduling contributes to the profits of semiconductor enterprises and enhances the quality of semiconductor products. This study aims to solve the scheduling problems for the wafer burn-in test facilities of the semiconductor back-end process by utilizing simulation and deep reinforcement learning-based methods. To solve the scheduling problem considered in this study. we propose novel state, action, and reward designs based on the Markov decision process. Furthermore, a neural network is trained by employing the recent RL-based method, named proximal policy optimization. Experimental results showed that the proposed method outperformed traditional heuristic-based scheduling techniques, achieving a higher due date compliance rate of jobs in terms of total job completion time.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.2
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• pp.116-123
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• 2024

In the manufacturing industry, dispatching systems play a crucial role in enhancing production efficiency and optimizing production volume. However, in dynamic production environments, conventional static dispatching methods struggle to adapt to various environmental conditions and constraints, leading to problems such as reduced production volume, delays, and resource wastage. Therefore, there is a need for dynamic dispatching methods that can quickly adapt to changes in the environment. In this study, we aim to develop an agent-based model that considers dynamic situations through interaction between agents. Additionally, we intend to utilize the Q-learning algorithm, which possesses the characteristics of temporal difference (TD) learning, to automatically update and adapt to dynamic situations. This means that Q-learning can effectively consider dynamic environments by sensitively responding to changes in the state space and selecting optimal dispatching rules accordingly. The state space includes information such as inventory and work-in-process levels, order fulfilment status, and machine status, which are used to select the optimal dispatching rules. Furthermore, we aim to minimize total tardiness and the number of setup changes using reinforcement learning. Finally, we will develop a dynamic dispatching system using Q-learning and compare its performance with conventional static dispatching methods.

• Journal of the Institute of Convergence Signal Processing
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• v.14 no.3
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• pp.147-153
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• 2013

Functional game, which is the combination of play and learning and a futuristic tool, can minimize the dysfunction and maximize the proper functions, and furthermore, has taken root as a new alternative that can change the game industry and game culture. Recently, the focus of game and education markets is shifting to the development of more advanced learning contents, rather than emphasizing the self-control and motivation of users. Along with that, the game market has excluded the socially dysfunctional elements, such as the addiction and learning disabilities, and has witnessed a diversification into the human-friendly entertainment business that emphasizes the mental and physical health and pursues scientific educational effects. In addition, functional games are expanding its reach from the professional sectors - such as medical aide/medical learning, military simulation, health, auxiliary tools, special education and learning tools - to the realm of routine education, mental health, etc., and has seen a steady growth. However, most functional games, which are being currently planned and developed to cope with the special characteristics of the market, have not undergone accurate scientific assessment of their functions and have not proven their effectiveness. An overwhelming proportion of the functional games are being developed based on the intuition and experience of game developers. Moreover, the type of games, which involve the repetition of simple tasks or take the form of simple puzzles, cannot effectively combine the practically interesting factors and the learning effects. Most games incorporate unscientific methods leading to the vague anticipation of improvement in functions, rather than the assessment of human functions. In this paper, a study was conducted to present the measures that could maximize the effects of functional games in relation to the changes in the visual and auditory stimulations in order to maximize the effects of functional games, i,e., the immersion and concentration. To compare the degree of effects arising from the visual stimulation, the functional game contents made in the form of 2D and 3D were utilized. In addition. ultra sound and 3-dimensional functional game contents were utilized to compare the degree of effects resulting from the changes in the auditory stimulation. The brainwave of the users were measured while conducting the experiments related to the response to the changes in visual and auditory stimulations in 3 steps, and the results of the analysis were compared.

• Journal of Internet Computing and Services
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• v.17 no.4
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• pp.115-125
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• 2016

Recently, many attentions have been paid to conducting convergence research across diverse disciplines. Along with this convergence era, an IT-based multi-disciplinary convergence project, called EDISON (EDucation-research Integrated Simulation On the Net), has been launched to support the studies of researchers engaged in several computational science and engineering (CSE) fields and to boost learning motivations of CSE students. Since 2011, we have been successfully carrying out the EDISON project. EDISON as a cyber-learning platform enables CSE researchers to share their own high-performance computing (HPC) simulation softwares developed to solve their research problems accompanying large-scale computation and I/O and users to run the softwares with little constraints on the web. Also, the EDISON platform has been utilized as lecture material by many universities in Korea. This article introduces the construction and service statistics of this EDISON platform. Specifically, we explicate several distinctions between EDISON and existing other HPC service platforms and discuss a three-layered technical architecture of the EDISON platform. We then present the up-to-date service statistics of EDISON over the past four years. Finally, we conclude this article and describe future plans.

• The Journal of Korean Institute for Practical Engineering Education
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• v.3 no.2
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• pp.18-26
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• 2011

Computational chemistry is one of the chemistry fields that deals with the theoretical chemistry problem using computer calculations and can be described as the chemistry lab moved on computer space. In line with recent enhancement of processing capability of computers, utilization of high performance computer cannot be overemphasized in the field of computational chemistry in performing complex calculation of huge molecular structure and simulation. While they have to use commands and consoles for high performance computer to execute complex calculation of huge molecular structure and simulation, most of students in natural science and engineering, who are not experts in computer technically, are likely to be unaware of UNIX. Under the circumstances, web-based educational support system for computational chemistry is needed to enable them to practice computational chemistry, even not knowing UNIX command. In this study, e-Chem, one of such educational support systems, is developed by using Liferay portal platform, which is a Java open source more oriented to standard and outstanding in its content management and collaboration function than other web portals. By using this system, even students who are not familiar with computer, are expected to take part in lab classes and save time learning Unix command and also enhance the learning efficiency by using familiar interface.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.3
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• pp.1178-1185
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• 2012

The 4th year medical students were randomly divided and designated as group HF and LF, representing high and low fidelity simulations respectfully. Both groups performed OSCE on 2 topics(adult intubation and IV cannulation) with each composed of the same scenario. Each scenario was developed by a faculty in charge of clinical skill education with supervision from 2 other faculty members. High fidelity simulations were designed as in-situ simulations in real OR. Low fidelity simulations had the same scenarios but the environment was simulated only with a simple task trainer in the classroom. All students participated in series of survey using a Likert scale before and after the simulations. The provided data was anlayzed with paired T-test and Mann-Whiteney test(p<0.05). The post simulations self evaluation score for group HF was lower than pre-simulation self confidence score for both topics of adult intubation and IV cannulation where as for group LF, it was lower only for adult intubation(p<0.05). In group HF, the needs for clinical training on both topics increased after the simulation. In group LF, there was no significant change of needs for clinical training between pre and post simulation survey. This suggest that fidelity may be a helpful factor to improve the motivation of the students and further study on economical aspect should be addressed.