• Journal of Practical Engineering Education
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• v.14 no.3
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• pp.479-489
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• 2022

In order to understand how to increase the use of virtual training content at K University's online lifelong education institute, this study examined the use experience, content recognition, field practice replacement, and requirements, focusing on the examples of operating institutions. To this end, 12 institutions that operated virtual training contents distributed by the K University Online Lifelong Education Center in 2020 were selected for in-depth interviews and qualitative analysis was conducted on the interviews of 11 institutions. As a result of the analysis, first, the experience of using the contents of the virtual training operating institution was aimed at changing the educational environment, supplementing theoretical learning, and improving the sense of practice. Second, according to a survey on the recognition of virtual training content, if the importance and utilization of the content are high, it can be replaced by on-site practice in non-face-to-face classes, such as experiences of facilities and equipment, attracting interest and attention. Third, in many cases, the perception of replacement for field practice is not unreasonable to use as a pre-training material for field practice, but it is difficult to replace field practice. Fourth, content quality improvements can be summarized as content quality improvement, content access and manipulation improvement, dedicated device development, training for instructors, and curriculum systematization. Fifth, institutional requirements include improving the quality of virtual training content itself, equipment support, curriculum systemization and characterization, systematic curriculum and detailed content sharing, detailed guidance on using virtual training content, introducing how to use content, and recruiting instructors. This study is meaningful in that it sought ways to improve the utilization of virtual training content based on the perception of virtual training content operating institutions.

• Journal of Naturopathy
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• v.13 no.2
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• pp.112-117
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• 2024

Background: Breathing, which can be voluntarily controlled, is understood to improve autonomic nervous system dysfunction caused by irregular lifestyle habits and stress. Purpose: This study aims to design a musical instrument for breathing excise and to present preliminary cases demonstrating the effectiveness of the breathing exercise with the instrument. Method: Based on a palm flute, a musical instrument was designed to produce the intended sound when exhaling softly, evenly, and for a long duration using the diaphragm. The instrument was applied to 4 individuals with symptoms of autonomic nervous system imbalance, and its effects were evaluated. Results: Case A (62 years old, male); After 1 hour of daily breathing excise for 2 weeks, the subject was able to discontinue the use of sleep-inducing medication, which had been taken for 5 years, and showed improvement in symptoms of overactive bladder. Case B (35 years old, male); After 30 minutes of breathing excise daily for 2 months, the subject's sleep patterns improved, and insomnia symptoms were alleviated. Case C (57 years old, female); After 30 minutes of breathing excise, 3 times per week for 4 weeks, the time required to fall asleep was significantly reduced, and sleep quality was enhanced. Case D (67 years old, male); After 1 hour of daily breathing excise for 1 week, the subject's insomnia improved. Conclusion: The proposed breathing excise instrument which efficiently trains exhalation is understood to positively influences the parasympathetic nervous system. The instrument is expected to hold potential for effective use in natural healing programs, aimed at restoring and maintaining autonomic nervous system balance.

• Journal of Practical Engineering Education
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• v.16 no.5_spc
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• pp.709-724
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• 2024

The purpose of this study is to come up with a plan enhancing the effectiveness of vocational competency development projects based on Edutech, which was accelerated by the era of COVID-19 and the expansion of the Internet industry which was established by the fourth industrial revolution. For this purpose, we conducted literature review on existing remote training and carried out a survey to analyze the pros and cons, effectiveness, necessary functions, and improvements of diginal twin training equipment on employees of large and small enterprises as well as unemployed people including students. Through this, it is confirmed that digital twin training equipment has limitations in replacing real equipment at the current level, but if it is improved in the future, it can be used for various purposes as training equipment. In addition, through consultation with human resources personnel and educational expert, we suggested utilization plans on mixed training, national/private technical qualification, training for foreign workers, and military personnel social adaptation training as plans to exploiting digital twin training equipment in the field of vocational ability development.

• Korean Security Journal
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• no.13
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• pp.529-550
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• 2007

In proportion to the increase of public security demand, the private companies advanced continuously every year. However the size of the industry expanded in its quantity, the quality remains the same as before. So it's important to training of the security officers. This study suggest the improvements of training system through the analysis and the review of problems of training and education security officers. To develop our private security industry, we suggest as follows. First, In spite of the training is important, the recognition against security officers training is low, so the improvement is demanded. Second, When selecting the educational institution, it does not reflect the demand and situation of education enough. So there is necessary that selecting the educational institution again, after finishing a demonstration duration. Third, The education contents is general, so there is a necessity of the education which is professionalized. Fourth, In order to improve the ability of the lecturer, we must strengthen the qualification of the lecturer. Fifth, For the development of securities industry, we must found the professional training institution.

• Journal of Korea Entertainment Industry Association
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• v.14 no.3
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• pp.383-392
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• 2020

This study was to compare the effects of joint mobilization, treadmill with insole, and joint mobilization and treadmill with insole on pain, pelvic angle, and foot pressure in patients with sacroiliac joint pain. 24 patients randomly assigned to joint mobilization group(n=8), treadmill with insole group(n=8), or joint mobilization and treadmill with insole group(n=8). Each groups were conducted 30 minutes a day, two days a week for four weeks. Pain was evaluated using visual analogue scale and pelvic angle was measured using palpation meter and foot pressure(fore/rear ratio) was measured using Gateview AFA-50 before intervention and after 4 weeks. All groups were significant differences pain in intragroup(p<.01). In pelvic angle, the joint mobilization group was statistically significant in the anterior tilt only, the joint mobilization and treadmill with insole group showed statistically significant improvement in both anterior and posterior tilt(p<.01), and the treadmill with insole group did not show any statistically significant change(p>.05). Also the joint mobilization and treadmill with insole group were significant differences in foot pressure(p<.01). All the interventions reduce sacroiliac joint pain and joint mobilization and treadmill with insole training are most effective changes in pelvic angle and foot pressure. This study can be used as a basic data for prevention of injury, posture correction and gait training in patients with sacroiliac joint pain, as well as chronic low back pain and plantar pressure problem.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.08a
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• pp.74-77
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• 1998

우리는 C++를 이용하여 음성인식기를 구현하여 기존의 C를 이용한 경우에 비하여 30% 수준의 소스로 표현하였고 인식기의 공동개발, 확장 및 개선, 기술 전수 등이 용이하게 되었으며 이를 음성인식 엔진 및 음성인식 연구를 위한 툴로 사용할 수 있게 되었다. 이 인식기의 특징으로는 연속 음성 및 대화체 음성을 인식할 수 있으며 trigram 언어 모델을 사용하였고 문맥 종속 음소 모델링에서는 기존의 triphone 보다 넓은 문맥을 고려한 n-phone context modeling을 사용하였으며 모델의 선정에는 음성학적 지식을 기반으로 한 질문을 사용한 decision tree를 사용하여 훈련에 나타나지 않은 단어나 문맥인 경우라도 가장 가까운 모델을 선정할 수 있게 하였다. 또, tree lexicon을 사용하여 속도를 개선하였으며 state 단위의 모델 공유를 통해 제한된 데이터를 이용하여 더 많은 모델을 훈련할 수 있어 성능을 개선하였다. 상용화를 염두에 두고 pc에서 구현하였다.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2022.10a
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• pp.205-206
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• 2022

이번 연구에서는 재난관리 교육프로그램 개선을 위해 민방위재난안전교육연구원의 교육과정에 중점을 둔 전문가들을 대상으로 AHP분석을 실시하여 교육과정 개혁의 우선순위를 분석하였다. 분석 결과 재난현장지휘시스템에 대한 이해가 가장 중요한 분야로 인식되고 있으며, 재난관리 교육훈련 과정에서 대응현장에 적용되는 표준조치절차(SOP)에 대한 이해와 획득이 중요한 분야로 인식되고 있다. 따라서 재난관리 교육 프로그램 개선을 위한 현장지향적 재난대응역량 제고를 위한 교육 프로그램 부문 강화가 필요하다. 특히 재난현장에 참여하는 다양한 정부기관과 중앙정부 및 지방자치단체 관계자들의 현장 이해도 제고를 위한 교육이 이뤄져야 한다.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.2
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• pp.80-98
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• 2023

This study explores the effectiveness of various data preprocessing algorithms for improving subseasonal to seasonal (S2S) climate predictions from six climate forecast models and their Multi-Model Ensemble (MME) using a deep learning-based postprocessing model. A pipeline of data transformation algorithms was constructed to convert raw S2S prediction data into the training data processed with several statistical distribution. A dimensionality reduction algorithm for selecting features through rankings of correlation coefficients between the observed and the input data. The training model in the study was designed with TimeDistributed wrapper applied to all convolutional layers of U-Net: The TimeDistributed wrapper allows a U-Net convolutional layer to be directly applied to 5-dimensional time series data while maintaining the time axis of data, but every input should be at least 3D in U-Net. We found that Robust and Standard transformation algorithms are most suitable for improving S2S predictions. The dimensionality reduction based on feature selections did not significantly improve predictions of daily precipitation for six climate models and even worsened predictions of daily maximum and minimum temperatures. While deep learning-based postprocessing was also improved MME S2S precipitation predictions, it did not have a significant effect on temperature predictions, particularly for the lead time of weeks 1 and 2. Further research is needed to develop an optimal deep learning model for improving S2S temperature predictions by testing various models and parameters.

• Journal of Korean Society of Forest Science
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• v.103 no.4
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• pp.574-582
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• 2014

In order to prevent occupational injury in forestry operations, several laws and regulations related to forestry have been enacted. Forestry education and training is overseen by the Forest Training Institute under the Korea Forest Service and three training centers under the National Forestry Cooperative Federation. The latter are managing both common and specialized courses, with safety education and training as an important focus. Improvements to reduce the accident rate are as follows: (1) strengthening of qualifications (via aptitude test) and selection standards of forestry workers (such as age limits); (2) raise of the number of training days and the rate of certified essential forces that compose Units of Forest Craft Workers; (3) revision of regulations to select forestry management engineers (second grade certified engineer); (4) introduction of a qualification renewal system; (5) improvement of working conditions at forestry scenes and systemization of safety education; (6) revision of regulations of individual protection equipment; (7) enforcement of wearing individual protection equipment; (8) supplementation of disaster response for increasing safety perception.

• Journal of the Korea Society of Computer and Information
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• v.16 no.6
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• pp.71-77
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• 2011

In this paper, we propose a learning based super resolution algorithm using local block for image enhancement of vehicle license plate. Local block is defined as the minimum measure of block size containing the associative information in the image. Proposed method essentially generates appropriate local block sets suitable for various imaging conditions. In particular, local block training set is first constructed as ordered pair between high resolution local block and low resolution local block. We then generate low resolution local block training set of various size and blur conditions for matching to all possible blur condition of vehicle license plates. Finally, we perform association and merging of information to reconstruct into enhanced form of image from training local block sets. Representative experiments demonstrate the effectiveness of the proposed algorithm.