• Journal of the Korea Convergence Society
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• v.12 no.6
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• pp.233-239
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• 2021

Recently, the COVID-19 virus has caused people to stay indoors longer without going out. As a result of this, people's activity decreased sharply, and their weight gained. So people became more interested in health. Home training can be an alternative method to solve this problem. Accordingly, To find out the trends of home training, we collected articles from December 1, 2019, to November 30, 2020, using the news provided by BIG KINDS, a news analysis system. We analyzed frequency analysis, relational analysis according to weighting, and related word analysis with the program using the algorithm developed by BIG KINDS. In conclusion, first, it was found that home training is led by technology and the emergence of artificial intelligence. Second, it can be assumed that people mainly do home training using content and video services related to mobile carriers. Third, people had a high preference for Pilates in the sports category. It can be seen that the number of patent applications increased as the demand for exercise products related to Pilates increased. In the next study, we expect that this study will be used as primary data for various big data studies by supplementing the research methodology and conducting various analyses.

• Journal of Digital Convergence
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• v.19 no.7
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• pp.217-226
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• 2021

The use of personal mobility(PM) is increasing because of preading shared mobility, but, it causes risk of accidents and fear to pedestrians because of lack of sound. The purpose of this study is to find out the effects of the alert sound in PM and driving direction on risk perception of pedestrians, awareness on PM driver, and allowance for driving on each road. The 8 videos were produced from a pedestrian perspective, depending on the alert sound type(silent, vess, bell, voice) and direction of driving(front, back). After watching each video, participants completed surveys. There was a non-effect on the driving direction. Regardless of the alert sound type, all of the sounds reduced the risk perception. Also, the awareness of PM drivers and allowance for driving on each road were positive. This study found that PM needed an alert sound for pedestrian safety. We expect the results of the study to help improve awareness of PM and make policies and regulations.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.705-712
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• 2021

The purpose of this study is to propose the features of autonomous DRT UX design based on level 5 autonomous vehicle applicable in 2027. As the scope of the study, the system focused on the interaction between the elderly and the in/outside of the vehicle, and the level 5 autonomous vehicle was the subject of the study. As of 2021, the targets for application were set from 60s to 90s. This study is different from previous studies in that it is a study on the features of autonomous DRT UX design that derives practical insights through direct communication with the elderly. As a research method, autonomous vehicle and DRT were theoretically considered through literature research, and based on this, cases of autonomous vehicle and DRT were analyzed. As a case study, generalization was conducted through interviews with the elderly, test-drive of autonomous vehicle, video production, survey, and VR test-drive of autonomous vehicle for the elderly. Ten features of autonomous DRT UX design were derived through focus group interview(FGI), and the derived features were classified into reservation, get on, input, driving, emergency, and get off. Through this study, I hope that it will contribute to improving mobility of the elderly and further accelerate the practical use of autonomous DRT.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.32 no.4
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• pp.5-24
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• 2021

The purpose of this study was to investigate and analyze the operating conditions of lecture contents in contactless online classes for University students. First, as a result of analyzing the responses of 93 respondents, 93.3% of the respondents took real-time online lectures (47.7%) or recorded video lectures (45.6%). Second, as a result of analyzing the contents used as textbooks, it was found that e-books (materials) and paper books (materials) were used together (36.6%), or e-books or electronic materials (36.6% and 37.6% respectively) were used in both liberal arts (47.3%) and major subjects (39.8%). In addition to textbooks, both major subjects and liberal arts highly used web materials (47.6% and 40.5% respectively) and YouTube materials (33.3% and 48.0% respectively) as external materials. Third, both liberal arts and major subjects used 'electronic files in the form of PPT or text organized and written by instructors' (62.9% and 58.1% respectively), 'internet materials' (16.7% and 19% respectively) and 'paper book or materials' (10.4% and 12.3% respectively) to share lecture contents. For the screen displayed lecture contents, 93.5% of the respondents satisfied in major subjects, and 90.2% of the respondents satisfied in liberal arts. These results suggest developing multimedia-based lecture contents and an evaluation solution capable of real-time exam supervision, developing a task management system capable of AI-based plagiarism search, task guidance, and task evaluation, and institutionalizing a solution to copyright problems for electronicizing lecture materials so that lectures can be given in the ubiquitous environment.

• Korean Association of Arts Management
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• no.53
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• pp.101-125
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• 2020

This paper presents the problems and improvement methods in estimating demand and benefit, which have been controversial in the feasibility study of building cultural facilities. Although there are justifications for supplying cultural facilities by expanding leisure time and increasing income, the economic burden from the insolvent operation after construction is high. Feasibility studies can prevent these problems in advance. In order to estimate the demand for cultural facilities, similar facilities were selected and the gravity model was used to estimate the demand. In the future, it is necessary to prepare the criteria for setting the reference facility to increase the accuracy of the demand estimation. In addition, in the case of cultural facilities constructed through feasibility study, it is necessary to induce and enforce the disclosure of operational data and information, and to establish a database so that it can be used as a reference facility for demand estimation in future feasibility study on cultural facility. Accurate benefit estimation requires multiple CVM surveys. In addition to the current CVM survey, this paper suggest that supplementary online non-face-to-face surveys is considered. Furthermore, this research suggests that the use of video media for explanation of alternative materials for cultural facilities to be constructed because the WTP may be excessive due to lack of alternatives for survey respondents in the current CVM survey.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.223-231
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• 2022

Covid-19, which has made a huge difference in our daily lives, has also brought major changes to our college education. As the class was changed from the traditional face-to-face class to a non face-to-face class, both teachers and students had difficulties in adapting, and problems such as the occurrence of academic achievement gaps due to non face-to-face classes were also raised. Therefore, this study aims to find out what attitudes students have toward non-face-to-face classes at universities caused by Covid-19. Accordingly, this study tried to identify the types of subjective perceptions college students have toward non-face-to-face classes by applying the Q methodology, and to suggest points for reference in the development and improvement of non-face-to-face classes in the future. Five types were found as a result of analysis using 30 P samples and 34 Q samples. First, learning efficiency-oriented type, second, class participation and communication-oriented type, third, non-face-to-face class active acceptance and utilization type, fourth, dissatisfaction type due to remote system and equipment operation errors, fifth, passive response type according to the situation to be. From the results of this study, it seems that it is necessary to develop an educational method for effective non-face-to-face class considering the characteristics of each type, and the merits of non-face-to-face classes, especially recorded lectures, in terms of learning efficiency, are evident. Therefore, even if face-to-face classes are conducted entirely at universities, it is believed that providing video-recorded lectures in class will be of great help to students' learning.

• Journal of the Society of Disaster Information
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• v.19 no.3
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• pp.498-509
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• 2023

Purpose: This paper proposes a method detecting the falling of a maintenance worker in the underground utility tunnel, by applying deep learning techniques using CCTV video, and evaluates the applicability of the proposed method to the worker monitoring of the utility tunnel. Method: Each rule was designed to detect the falling of a maintenance worker by using the inference results from pre-trained YOLOv5 and OpenPose models, respectively. The rules were then integrally applied to detect worker falls within the utility tunnel. Result: Although the worker presence and falling were detected by the proposed model, the inference results were dependent on both the distance between the worker and CCTV and the falling direction of the worker. Additionally, the falling detection system using YOLOv5 shows superior performance, due to its lower dependence on distance and fall direction, compared to the OpenPose-based. Consequently, results from the fall detection using the integrated dual deep learning model were dependent on the YOLOv5 detection performance. Conclusion: The proposed hybrid model shows detecting an abnormal worker in the utility tunnel but the improvement of the model was meaningless compared to the single model based YOLOv5 due to severe differences in detection performance between each deep learning model

• International Journal of Computer Science & Network Security
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• v.23 no.1
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• pp.112-119
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• 2023

Traditionally used for networking computers and communications, the Internet has been evolving from the beginning. Internet is the backbone for many things on the web including social media. The concept of social networking which started in the early 1990s has also been growing with the internet. Social Networking Sites (SNSs) sprung and stayed back to an important element of internet usage mainly due to the services or provisions they allow on the web. Twitter and Facebook have become the primary means by which most individuals keep in touch with others and carry on substantive conversations. These sites allow the posting of photos, videos and support audio and video storage on the sites which can be shared amongst users. Although an attractive option, these provisions have also culminated in issues for these sites like posting offensive material. Though not always, users of SNSs have their share in promoting hate by their words or speeches which is difficult to be curtailed after being uploaded in the media. Hence, this article outlines a process for extracting user reviews from the Twitter corpus in order to identify instances of hate speech. Through the use of MPCA (Modified Principal Component Analysis) and ECNN, we are able to identify instances of hate speech in the text (Enhanced Convolutional Neural Network). With the use of NLP, a fully autonomous system for assessing syntax and meaning can be established (NLP). There is a strong emphasis on pre-processing, feature extraction, and classification. Cleansing the text by removing extra spaces, punctuation, and stop words is what normalization is all about. In the process of extracting features, these features that have already been processed are used. During the feature extraction process, the MPCA algorithm is used. It takes a set of related features and pulls out the ones that tell us the most about the dataset we give itThe proposed categorization method is then put forth as a means of detecting instances of hate speech or abusive language. It is argued that ECNN is superior to other methods for identifying hateful content online. It can take in massive amounts of data and quickly return accurate results, especially for larger datasets. As a result, the proposed MPCA+ECNN algorithm improves not only the F-measure values, but also the accuracy, precision, and recall.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.6
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• pp.897-906
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• 2017

Projection Mapping, also known as Spatial Augmented Reality(SAR) has attracted much attention recently and used for many division, which can augment physical objects with projected various virtual replications. However, conventional approaches towards projection mapping have faced some limitations. Target objects' geometric transformation property does not considered, and movements of flexible objects-like paper are hard to handle, such as folding and bending as natural interaction. Also, precise registration and tracking has been a cumbersome process in the past. While there have been many researches on Projection Mapping on static objects, dynamic projection mapping that can keep tracking of a moving flexible target and aligning the projection at interactive level is still a challenge. Therefore, this paper propose a new method using Unity3D and ARToolkit for high-speed robust tracking and dynamic projection mapping onto non-rigid deforming objects rapidly and interactively. The method consists of four stages, forming cubic bezier surface, process of rendering transformation values, multiple marker recognition and tracking, and webcam real time-lapse imaging. Users can fold, curve, bend and twist to make interaction. This method can achieve three high-quality results. First, the system can detect the strong deformation of objects. Second, it reduces the occlusion error which reduces the misalignment between the target object and the projected video. Lastly, the accuracy and the robustness of this method can make result values to be projected exactly onto the target object in real-time with high-speed and precise transformation tracking.

• Journal of the Korea Knowledge Information Technology Society
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• v.13 no.3
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• pp.305-317
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• 2018

This study is about the elderly people's use and experience of Virtual Reality (VR) in order to enhance their quality of life. Leisure is main activity of the elderly. As a result, the quality and diversity of leisure affects the quality of the elderly people's life. VR services including video contents could provide them with advanced and interesting experiences. Across the world, population aging becomes one of the most important problems in each society. The social and economic burden of aging is serious challenge to sustainability welfare of the world, including S. Korea. The authors used virtual reality devices to conduct experiments on 99 aged 50 to 90 (men's average age : 75 and women's average age : 70.8). Through the survey, major variants were measured such as system quality, present sense, enjoyment, intent to reuse, and awareness of advanced technology. Multiple regression analyses with the presence as a dependent variable resulted in a sense of closeness (t = 5.381, p <. 01) and a sense of clarity (t = 4.494, p <. 01). The presence of an independent variant had significant effects on pleasure (t = 4.312, p <. 01) and significant effects on the intent to reuse (t = 3.323,).Therefore, it can be interpreted that the higher the sense of existence, the more pleasure and the intent to reuse it. As a result, the possibility of using VR devices and content to enjoy leisure activities can be found in this study even if the elderly group is unfamiliar with IT devices.