• Journal of the Korea Society of Computer and Information
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• v.28 no.7
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• pp.19-27
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• 2023

In the process of collecting social reviews, a number of noise reviews irrelevant to a given search keyword can be included in the search results. To filter out such reviews, machine learning can be used. However, if the number of reviews is insufficient for a target place to be analyzed, filtering accuracy can be degraded due to the lack of training data. To resolve this issue, we propose a supervised learning method to improve accuracy of the noise review filtering for the places with insufficient reviews. In the proposed method, training is not performed by an individual place, but by a group including several places with similar characteristics. The classifier obtained through the training can be used for the noise review filtering of an arbitrary place belonging to the group, so the problem of insufficient training data can be resolved. To verify the proposed method, a noise review filtering model was implemented using LSTM and BERT, and filtering accuracy was checked through experiments using real data collected online. The experimental results show that the accuracy of the proposed method was 92.4% on the average, and it provided 87.5% accuracy when targeting places with less than 100 reviews.

• Korean Journal of Applied Biomechanics
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• v.33 no.2
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• pp.62-72
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• 2023

Objective: Although balance training has been used as an effective ankle injury rehabilitation program to restore neuromuscular deficits in patients with chronic ankle instability, it is not effectively used in terms of motor learning. Attentional focusing can be an effective method for improving ankle kinematics to prevent recurrent ankle injuries. This study aimed to 1) evaluate the effects of attentional focus, including internal and external focus, and 2) determine a more effective focusing method for patients with chronic ankle instability to learn balance tasks. Method: Twenty-four patients with chronic ankle instability were randomly assigned to three groups (external focus, internal focus, and no feedback) and underwent four weeks of progressive balance training. The three-dimensional ankle kinematics of each patient were measured before and after training as the main outcomes. Ensemble curve analysis, discrete point analysis, and post hoc pairwise comparisons were performed to identify interactions between groups and time. Results: The results showed that (1) the external focus group was more dorsiflexed and everted than the internal focus group; (2) the external focus group was more dorsiflexed than the no feedback group; and (3) the no feedback group was more dorsiflexed than the internal focus group. Conclusion: Because dorsiflexion and eversion are ankle motions that oppose the mechanism of lateral ankle sprain, using the external focus method during balance training may be more effective in modifying these motions, thereby reducing the risk of ankle sprain.

• The Journal of the Korea Contents Association
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• v.10 no.9
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• pp.155-175
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• 2010

The purpose of this thesis is to introduce the alternative method of the new training program for film acting and directing. Recently in Korea, acting in movies has become a trend and broadcasting still depicts reality. But men of the theater is usually privileged getting the most acting education offered by the theater training program. They also is hardly teach about acting's directing for film directors. So I thought of establishing a new training program for film acting and acting's directing. I made two short films , that I had practical training program for film acting as practical text. This program applied partially 'Atude' that Stanislavsky devised for theater acting practice, and referred to 'Method Acting System' that Lee Strasberg made for film acting at the Actors Studio. Another main point of this program is camera use. That training program can be attended not only by actors but also by director and film staff. Through this thesis, I wish to prove my new training program for film acting and acting directing. The focus of this training is to target a better execution according to the group you belong to whether amateur group, associate professionals, professional actors.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.4
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• pp.267-275
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• 2015

Those land cover maps have widely been used in various fields, such as environmental studies, military strategies as well as in decision-makings. This study proposes a method to extract training data, automatically and classify the cover using ingle satellite images and national land cover maps, provided by the Ministry of Environment. For this purpose, as the initial training data, those three were used; the unsupervised classification, the ISODATA, and the existing land cover maps. The class was classified and named automatically using the class information in the existing land cover maps to overcome the difficulty in selecting classification by each class and in naming class by the unsupervised classification; so as achieve difficulty in selecting the training data in supervised classification. The extracted initial training data were utilized as the training data of MLC for the land cover classification of target satellite images, which increase the accuracy of unsupervised classification. Finally, the land cover maps could be extracted from updated training data that has been applied by an iterative method. Also, in order to reduce salt and pepper occurring in the pixel classification method, the MRF was applied in each repeated phase to enhance the accuracy of classification. It was verified quantitatively and visually that the proposed method could effectively generate the land cover maps.

• The Journal of Korea Robotics Society
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• v.15 no.2
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• pp.184-189
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• 2020

This paper is a study on data augmentation for small dataset by using deep learning. In case of training a deep learning model for recognition and classification of non-mainstream objects, there is a limit to obtaining a large amount of training data. Therefore, this paper proposes a data augmentation method using perspective transform and image synthesis. In addition, it is necessary to save the object area for all training data to detect the object area. Thus, we devised a way to augment the data and save object regions at the same time. To verify the performance of the augmented data using the proposed method, an experiment was conducted to compare classification accuracy with the augmented data by the traditional method, and transfer learning was used in model learning. As experimental results, the model trained using the proposed method showed higher accuracy than the model trained using the traditional method.

• Journal of Fisheries and Marine Sciences Education
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• v.17 no.2
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• pp.252-259
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• 2005

In this research, as an educational tool in the Refrigeration instruction, a project learning method was applied which enables active hand on practice and encourages a more active participation of students with an increased level of interest in learning. The purpose of this study is to present project learning method as an educational tool that can arouse interest and motivation of students by an active hands-on learning process. This will aid in the enhancement of understanding of educators and students in the project learning method, and assist in development of project learning method that can increase intuitiveness and originality of students. For the purpose of the study, the following questions were asked. First, what is the level of existing knowledge pertaining to Refrigeration Training Program of students? Second, what effect does Refrigeration Training Program conducted via the project approach have on the level of motivation and interest of students? Third, what effect does Refrigeration Training Program conducted via the project approach have on the study habits of students?

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.5
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• pp.493-504
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• 2010

This study proposes a classification method based on an automated training extraction procedure that may be used with very high resolution (VHR) images of non-accessible areas. The proposed method overcomes the problem of scale difference between VHR images and geographic information system (GIS) data through filtering and use of a Landsat image. In order to automate maximum likelihood classification (MLC), GIS data were used as an input to the MLC of a Landsat image, and a binary edge and a normalized difference vegetation index (NDVI) were used to increase the purity of the training samples. We identified the thresholds of an NDVI and binary edge appropriate to obtain pure samples of each class. The proposed method was then applied to QuickBird and SPOT-5 images. In order to validate the method, visual interpretation and quantitative assessment of the results were compared with products of a manual method. The results showed that the proposed method could classify VHR images and efficiently update GIS data.

• The Journal of the Korea Contents Association
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• v.14 no.4
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• pp.160-167
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• 2014

The purpose of this paper was to develop the key performance indicators of regional co-training programs, using analytic hierarchy process method. Firstly, we pooled indicators by reviewing the literatures. The researcher checked the properness and representative of them and then, the training professionals reviewed them again. Finally, we finalized the indicators, depending on the indicator domains such as MOU (Memorandum of Agreement) company (the training participation rate of MOU companies, training participation of employees, and etc.), training performance (the completion of the program, employment rate, and etc.), cost-effectiveness (training cost per capita), satisfaction (satisfaction rate of MOU companies and training participants), and regional co-training enhancement (the operation of the committee, the will for training of the regional municipal government, and etc.). The weight size varied by the regional training needs, satisfaction of MOU companies, and regional committees of human resource development. We also suggested the continuous revision of the key performance indicators for regional co-training.

• Journal of the Society of Disaster Information
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• v.14 no.2
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• pp.211-218
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• 2018

Purpose: The purpose of this study is to find a way to use the disaster drill system that can be used in the training in the required situation in the safety training situation in the safety industry to prepare for the disaster in the energy industry field by utilizing the developed system. Method: In order to accomplish the purpose of the research, I investigated the papers, reports, statistical data, and visited the site to investigate the training situation. Results: Disaster response safety Korean training is not only responding to disasters but also cooperating activities with local governments and related organizations. The contents are complex, diverse, and multifaceted. Conclusion: The disaster training system should be applied to the self training of the organization to prepare for the disaster and the safety training for disaster response in Korea.

• Journal of Internet Computing and Services
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• v.18 no.4
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• pp.19-25
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• 2017

In this paper, we designed and implemented IoT sensors based badminton motion analysis and training system that can be readily used by badminton players with PC. Unlike the traditional badminton training system which uses signals of the flags by coach, the proposed electronic training system used IoT sensors to automatically detect and analysis the motions for badminton players. The proposed badminton motion analysis and training system has the advantage with low power, because it communicates with the program through BLE communication. The badminton motion analysis system automatically measures the training time according to the player's movement, so it is possible to collect objective result data with less errors than the conventional flag signal based method by coach. In this paper, training data of 5 athletes were collected and it provides the feedback function through the visualization of each section of the training results by the players which can enable the effective training. For the weakness section of each player, the coach and the player can selectively and repeatedly perform the training function with the proposed training system. Based on this, it is possible to perform the repeated training on weakness sections and they can improve the response speed for these sections. Continuous research is expected to be able to compare more various players' agility and physical fitness.