• Journal of the Korea Society for Simulation
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• v.31 no.1
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• pp.11-18
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• 2022

Recently, research to classify human activity using imagery has been actively conducted for the purpose of crime prevention and facility safety in public places and facilities. In order to improve the performance of human activity classification, most studies have applied deep learning based-transfer learning. However, despite the increase in the number of backbone network models that are the basis of deep learning as well as the diversification of architectures, research on finding a backbone network model suitable for the purpose of operation is insufficient due to the atmosphere of using a certain model. Thus, this study applies the transfer learning into recently developed deep learning backborn network models to build an intelligent system that classifies human activity using imagery. For this, 12 types of active and high-contact human activities based on sports, not basic human behaviors, were determined and 7,200 images were collected. After 20 epochs of transfer learning were equally applied to five backbone network models, we quantitatively analyzed them to find the best backbone network model for human activity classification in terms of learning process and resultant performance. As a result, XceptionNet model demonstrated 0.99 and 0.91 in training and validation accuracy, 0.96 and 0.91 in Top 2 accuracy and average precision, 1,566 sec in train process time and 260.4MB in model memory size. It was confirmed that the performance of XceptionNet was higher than that of other models.

• Korean Journal of Construction Engineering and Management
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• v.23 no.1
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• pp.46-53
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• 2022

The railway platform is an important facility closely related to the safety of passengers, trains, and images of railway facilities, and requires thorough facility management. However, the problem that the finishing material (plastering mortar) for the joint finishing of dissimilar materials (concrete+granite) falls off in the direction of the track at the platform podium is occurring multiple times across the country. Since these problems threaten the safety of train operation and the safety of passengers, immediate and continuous management is required. This study tried to derive improvement plans through the analysis of the drop-off problem of finishing materials occurring at the platform podium. The status of missing finishing materials for the platform podiums of about 200 railway stations and the related design and construction standards of the Korea National Railway were investigated. After that, the cause of the drop-off of the finishing material was analyzed, and as a result, it was found that the main cause was the boundary between the roadbed and the architectural process that occurred during construction. Subsequently, in connection with the derived causes and design, construction standards, (1) improvement of finishing materials or construction methods, (2) design of finishing materials that are easy to adjust height, (3) design of separate finishing methods, (4) improvement methods and durability were suggested.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.991-1005
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• 2022

Satellite imaging is an effective supplementary data source for detecting and verifying nuclear activity. It is also highly beneficial in regions with limited access and information, such as nuclear installations. Time series analysis, in particular, can identify the process of preparing for the conduction of a nuclear experiment, such as relocating equipment or changing facilities. Differences in the semantic segmentation findings of time series photos were employed in this work to detect changes in meaningful items connected to nuclear activity. Building, road, and small object datasets made of KOMPSAT 3/3A photos given by AIHub were used to train deep learning models such as U-Net, PSPNet, and Attention U-Net. To pick relevant models for targets, many model parameters were adjusted. The final change detection was carried out by including object information into the first change detection, which was obtained as the difference in semantic segmentation findings. The experiment findings demonstrated that the suggested approach could effectively identify altered pixels. Although the suggested approach is dependent on the accuracy of semantic segmentation findings, it is envisaged that as the dataset for the region of interest grows in the future, so will the relevant scope of the proposed method.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.6
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• pp.549-558
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• 2021

In order to keep infrastructures such as tunnels and underground facilities safe, cracks of concrete lining in tunnel should be detected by regular inspections. Since regular inspections are accomplished through manual efforts using maintenance lift vehicles, it brings about traffic jam, exposes works to dangerous circumstances, and deteriorates consistency of crack inspection data. This study aims to provide methodology to automatically extract cracks from tunnel concrete lining images generated by the existing tunnel image acquisition system. Specifically, we train a deep learning based semantic segmentation model with open dataset, and evaluate its performance with the dataset from the existing tunnel image acquisition system. In particular, we compare the model performance in case of using all of a public dataset, subset of the public dataset which are related to tunnel surfaces, and the tunnel-related subset with negative examples. As a result, the model trained using the tunnel-related subset with negative examples reached the best performance. In the future, we expect that this research can be used for planning efficient model training strategy for crack detection.

• Journal of Venture Innovation
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• v.6 no.1
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• pp.59-73
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• 2023

In the era of the 4th Industrial Revolution, manufacturing is the implementation of smart factories through digital transformation, and refers to consumer-centered intelligent factories that combine next-generation digital new technologies and manufacturing technologies beyond the existing factory automation level. In order to successfully settle such a smart factory, it is necessary to train professionals. However, education for smart factories is difficult to have actual field mechanical facilities or overall production processes. Therefore, there is a need for a system that can visualize and control the flow and process of logistics at the actual production site. In this paper, the logistics flow of the actual site was implemented as a small FMS, a physical system, and the production process was implemented as a digital system. In real-time synchronization of the physical system and the digital system, the location of AGV and materials, and the process state can be monitored to see the flow of logistics and process processes at the actual manufacturing site. The developed digital twin system can be used as an effective educational system for training manpower in smart factories.

• Journal of the Korean Society of Food Science and Nutrition
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• v.44 no.12
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• pp.1881-1894
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• 2015

The objective of this study was to provide information on difficulty of performing tasks, degree of task satisfaction, job satisfaction, organizational commitment, and turnover intention as well as investigate correlations among these factors. Data were collected on employees working at Centers for Children's Foodservice Management, which had been operating for over 6 months until December 2013. The recruitment period was from December 16, 2013 to January 30, 2014. A total of 228 employees (79.7%) participated in the study, and 227 completed questionnaires were analyzed. Statistical analyses were performed on the data utilizing the SPSS V20.0 and AMOS V21.0 programs. The main results of this study were as follows: task satisfaction of employees in charge of 'visiting-teaching' for children was highest (4.24 points), whereas that of employees in charge of financial management was lowest (2.92 points). In terms of evaluation of job satisfaction factors, the score of 'co-worker' was highest (3.99 points) while that of 'payment' was lowest (2.45 points). Average scores of general job satisfaction, organizational commitment, and turnover intention were 3.56 points, 3.54 points, and 3.07 points, respectively. Job achievement was the most significant influencing factor on general job satisfaction, organizational commitment, and turnover intention. According to the path analysis results, the degree of task satisfaction affected job satisfaction. Organizational commitment had a more significant effect on turnover intention than job satisfaction and mediate both job satisfaction and turnover intention. Although employees of CCFSMs endeavor to improve the quality of child-care facility foodservice, some facilities do not. Controlling turnover intention of employees is especially critical for CCFSMs since it is important for each employees to form strong bonds with child-care facilities as well as to shorten the time required to train new employees. Thus, job satisfaction, which is related to organizational commitment and turnover intention, can be improved by considering poorly scored job satisfaction factors such as wage or workload.

• Journal of Korea Entertainment Industry Association
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• v.14 no.7
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• pp.141-160
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• 2020

The purpose of this study was to devise a specific plan for activating sports to promote health in old age against the prolonged COVID-19 pandemic. Through literature review, it also analyzed the association between health status and COVID-19 in old age, suggested health promotion policies and projects for elderly people, and presented a plan for activating sport to promote health in old age against COVID-19 era. First, it is necessary to revise the relevant laws, including the Sport Promotion Act and the Elderly Welfare Act, partially or entirely, make developmental and convergent legislations for elderly health and sports, and establish an institutional device as needed. Second, it is necessary to build an integrated digital platform for the elderly and make a supporting system that links facilities, programs, information, and job creation as part of a New Deal program in the field of sports on the basis of the Korean New Deal. Third, it is necessary to train elderly welfare professionals. Efforts should be made to establish more departments related to elderly sports in universities and make it compulsory to place elderly sports instructors at elderly leisure and welfare facilities. Fourth, it is necessary to develop contents related to health in old age. This means performing diverse movements by manipulating them through a virtual reality (VR) simulation. Fifth, it is necessary to make a greater investment in research and development related to elderly sports and relevant fields. This means the need to conduct constant research on healthy and active aging in a systematic and practical way through multidisciplinary cooperation. Sixth, it is necessary to establish and operate an elderly management agency (elderly health agency) under the influence of the Office of the Prime Minister. This means the need to secure independence in implementing the functions related to health promotion in old age and make comprehensive operation, which involves all the issues of health promotion in old age, daily function maintenance and rehabilitation, social adjustment, and long-term care, by establishing an elderly management agency in an effort to give lifelong health management to the elderly and cope with the untact, New Normal age.