• The Journal of the Convergence on Culture Technology
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• v.8 no.4
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• pp.435-444
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• 2022

There are three focuses in the paper. Firstly, the study identified what channels were most viewed by YouTube users to watch the 'Daejang-dong scandal,' which was the most powerful agenda to influence the candidate preference among voters during the 20th presidential election. Secondly, the study analyzed whether the political tone of the first videos was in line with that of the subsequent videos. Finally, we compared the sentiment of comments on the first and subsequent videos. The results showed that TBS 'News Factory' and 'TV Chosun News' represented liberal and conservative factions, respectively. Secondly, the political tone of channels that were viewed subsequently was neutral, but the conservative channel users left more negative comments and that was significant statistically. In addition, about 80% of the conservative and liberal channel users shared the same political tendency with the channel they watched first, and more than 90% of the comments left at the subsequent videos in line with that of at the first news. Based on these results, the study concluded that the voters tended to seek political news that was similar with their political ideology, and it was considered a sort of echo chamber phenomenon on the YouTube. The study suggests that the performance of high-quality journalism by traditional news outlet might contribute to decrease the negative influence of political contents on YouTube users.

• Journal of Navigation and Port Research
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• v.46 no.3
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• pp.280-288
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• 2022

This study examined the diagnostics of abnormalities and faults of equipment, whose rotational speed changes even during regular operation. The purpose of this study was to suggest a procedure that can properly apply machine learning to the time series data, comprising non-stationary characteristics as the rotational speed changes. Anomaly and fault diagnosis was performed using machine learning: k-Nearest Neighbor (k-NN), Support Vector Machine (SVM), and Random Forest. To compare the diagnostic accuracy, an autoencoder was used for anomaly detection and a convolution based Conv1D was additionally used for fault diagnosis. Feature vectors comprising statistical and frequency attributes were extracted, and normalization & dimensional reduction were applied to the extracted feature vectors. Changes in the diagnostic accuracy of machine learning according to feature selection, normalization, and dimensional reduction are explained. The hyperparameter optimization process and the layered structure are also described for each algorithm. Finally, results show that machine learning can accurately diagnose the failure of a variable-rotation machine under the appropriate feature treatment, although the convolution algorithms have been widely applied to the considered problem.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.7
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• pp.299-306
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• 2022

In recent, sensors embedded in robots, equipment, and circuits have become common, and research for diagnosing device failures by learning measured sensor data is being actively conducted. This failure diagnosis study is divided into a classification model for predicting failure situations or types and a regression model for numerically predicting failure conditions. In the case of a classification model, it simply checks the presence or absence of a failure or defect (Class), whereas a regression model has a higher learning difficulty because it has to predict one value among countless numbers. So, the reason that regression modeling is more difficult is that there are many irregular situations in which it is difficult to determine one output from a similar input when predicting by matching input and output. Therefore, in this paper, we focus on input and output data with periodicity, analyze the input/output relationship, and secure regularity between input and output data by performing sliding window-based input data patterning. In order to apply the proposed method, in this study, current and temperature data with periodicity were collected from MMC(Modular Multilevel Converter) circuit system and learning was carried out using ANN. As a result of the experiment, it was confirmed that when a window of 2% or more of one cycle was applied, performance of 97% or more of fit could be secured.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.4
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• pp.459-468
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• 2022

Long-term data analyses and bioassay experiments were conducted to assess limiting nutrients in Cheonsu Bay and Taean sea. First, long-term nutrient data (2004-2016) provided by the National Water Quality Monitoring Network were used to assess potential limiting nutrients. Analysis of the long-term data showed that the dissolved inorganic nitrogen/dissolved inorganic phosphate (DIN/DIP) ratio was mostly below 16, with N limitation being dominant. A subsequent analysis using the concentration ratios of N, P, and Si showed that N limitation was dominant during summer and autumn but that Si limitation occasionally occurred during winter and spring in relatively limited areas. However, the dominant limiting nutrient was not determined. The nutrient analysis of the field water collected during the bioassay experiment showed that DIN/DIP revealed P limitation at all stations in March and May, whereas N limitation was dominant in July and October. In the analysis using the concentration ratios of N, P, and Si, P and Si limitation appeared in March and May, but there were points with no dominant limiting nutrient. However, N limitation was dominant in July and October. In the bioassay experiment for assessment of the actual limiting nutrient, the results showed no specific limiting nutrient in March, whereas NH₄⁺ and NO₃^- showed responses in May, July, and October, which confirmed that N was a substantial limiting nutrient directly involved in phytoplankton growth during this period.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.3
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• pp.27-46
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• 2022

Today, public libraries are contributing deeply to our society by strengthening their ability and services to identify and respond to users' needs through various programs. However, it is difficult to find a study that analyzed the research status of public library programs or changes over time. Therefore, for the purpose of systematically grasping research trends in the field of overseas public library programs, an intellectual structure analysis based on keyword profiling was performed. Specifically, subject terms analysis, network analysis and cluster analysis, and analysis by period/year were performed based on the controlled keywords (subject terms) of journal articles papers searched in the LISTA database. As a result, first, it was found that 9 subjects corresponding to all global/hot/local topics are leading the research in the field of overseas public library programs. Second, five research areas in the field of overseas public library programs(cultural programs, outreach programs, activity programs, public services, community) could be visualized and clearly identified. Third, research in the field of overseas public library programs began in earnest in the late 1990s and was active from the mid-2000s to the early 2010s, and after that, it was found to be somewhat stagnant until recently. This study is the result of specifically identifying research trends on programs that recently emerged as a major task of public libraries, and can be used as basic data and prior knowledge to explore the development direction of public library programs in the future.

• Tunnel and Underground Space
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• v.32 no.3
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• pp.194-202
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• 2022

An increased number of cases have occurred in applying ICT technology in the resource development field due to factors such as safety, eco-friendliness, and low cost since the 2000s. In Korea, the 2nd mining master plan specified the significance of converging the full cycle of mining and ICT, while the 3rd mining master plan highlighted ICT and smart mining such as supporting the supply of an ICT mining device and introducing demonstrational smart mining. This study introduces the application of an ICT device and safety system operation in the Jangseong underground mine of Korea Cement Co., Ltd. Currently, Jangseong mine combines two different kinds of 3D equipment including the handheld 3D scanner and multi-station that provides both the measurement and 3D scanning to perform a 3D measurement of the mine. Taken from the 3D measurement of the mine, it is now possible to identify any hazardous areas and abnormalities in different directions and analyze the safety of the crown pillar between two stopes in different level. Besides, the real-time location tracking and communications system have established highly efficient rescue and evacuation plans to effectively deal with any accidents in the mine.

• Journal of IKEEE
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• v.26 no.2
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• pp.160-168
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• 2022

In this paper, we propose a 3D mesh reconstruction method from a single image using deep learning and a sphere shape transformation method. The proposed method has the following originality that is different from the existing method. First, the position of the vertex of the sphere is modified to be very similar to the 3D point cloud of an object through a deep learning network, unlike the existing method of building edges or faces by connecting nearby points. Because 3D point cloud is used, less memory is required and faster operation is possible because only addition operation is performed between offset value at the vertices of the sphere. Second, the 3D mesh is reconstructed by covering the surface information of the sphere on the modified vertices. Even when the distance between the points of the 3D point cloud created by correcting the position of the vertices of the sphere is not constant, it already has the face information of the sphere called face information of the sphere, which indicates whether the points are connected or not, thereby preventing simplification or loss of expression. can do. In order to evaluate the objective reliability of the proposed method, the experiment was conducted in the same way as in the comparative papers using the ShapeNet dataset, which is an open standard dataset. As a result, the IoU value of the method proposed in this paper was 0.581, and the chamfer distance value was It was calculated as 0.212. The higher the IoU value and the lower the chamfer distance value, the better the results. Therefore, the efficiency of the 3D mesh reconstruction was demonstrated compared to the methods published in other papers.

• Journal of Korea Entertainment Industry Association
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• v.15 no.4
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• pp.383-390
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• 2021

Recently, the drone industry is rapidly expanding as it is suggested that it will be used in various fields. As the size of the drone market grows, interest in drone-related certificates is also increasing. However, the current drone-related qualification system and education system are insufficient. Thus this study, analyzed the necessity of drone training, the features of functional games, and the effectiveness of educational training using AR through related technical studies to solve the practical difficulties of drone educational training. Later, drone educational training game contents using AR were divided into practice mode and test mode based on the drone national qualification course practical test, and the result screen was displayed at the end of the curriculum so that players could learn by level and evaluate the results on their own. In addition, constructed a hybrid processing system and network and AR operation system for response rate and response speed, implemented drone training game contents utilizing AR based on the design contents. It is expected that the use of game content using AR presented in this paper for drone training will further alleviate environmental difficulties and improve the sense of immersion in play, which will lead to a more effective drone educational training experience.

• Journal of Korea Entertainment Industry Association
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• v.15 no.4
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• pp.359-367
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• 2021

This study tried to examine the factors that affect the entrepreneurial intentions in the field of culture and tourism industry. Through this, it was attempted to present strategic implications for start-up plans to prospective entrepreneurs in the cultural tourism industry. As a result of the study, the following implications were drawn. First, prospective entrepreneurs in the field of culture and tourism industry need to analyze the start-up items they want to start and systematically design a start-up plan based on market research. Also, by analyzing various start-up cases, it is necessary to secure various prior experiences of failure and success. Second, prospective entrepreneurs in the field of culture and tourism industry will need to increase their interest in starting a business by completing various entrepreneurship education conducted by more diverse institutions and schools than now, and they will have to increase the sense of achievement and willpower that can appear in education. In addition, by making efforts to create human relationships through various entrepreneurship education, efforts should be made to show the utilization of human networks and information sharing when starting a business. Lastly, prospective entrepreneurs in the field of culture and tourism industry should visit startup-related institutions and receive education and advice from experts in order to acquire various information. In addition, efforts should be made to provide more diverse start-up support by obtaining information on start-ups implemented by the state.

• Journal of Korea Entertainment Industry Association
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• v.15 no.2
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• pp.123-135
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• 2021

The data processing of this study is focused on keywords related to 'Corona 19 and professional baseball' and 'Corona 19 and professional baseball no spectators', using text mining and social network analysis of textom program to identify problems and view quality. It was used to set the variable of For quantitative analysis, a questionnaire on viewing quality was constructed, and out of 270 survey respondents, 250 questionnaires were used for the final study. As a tool for securing the validity and reliability of the questionnaire, exploratory factor analysis and reliability analysis were conducted, and IPA analysis (importance-satisfaction) was conducted based on the questionnaire that secured validity and reliability, and the results and strategies were presented. As a result of IPA analysis, factors related to the image (image composition, image coloration, image clarity, image enlargement and composition, high-quality image) were found in the first quadrant, and the second quadrant was the game situation (support team game level, support player game level, star). Player discovery, competition with rival teams), game information (match schedule information, player information check, team performance and player performance, game information), interaction (consensus with the supporting team), and some factors appeared. The factors of commentator (baseball-related knowledge, communication ability, pronunciation and voice, use of standard language, introduction of game-related information) and interaction (real-time communication with the front desk, sympathy with viewers, information exchange such as chatting) appeared.