• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.6
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• pp.583-598
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• 2022

As human-based tunnel inspections are affected by the subjective judgment of the inspector, making continuous history management difficult. There is a lot of deep learning-based automatic crack detection research recently. However, the large public crack datasets used in most studies differ significantly from those in tunnels. Also, additional work is required to build sophisticated crack labels in current tunnel evaluation. Therefore, we present a method to improve crack detection performance by inputting existing datasets into a deep learning model. We evaluate and compare the performance of deep learning models trained by combining existing tunnel datasets, high-quality tunnel datasets, and public crack datasets. As a result, DeepLabv3+ with Cross-Entropy loss function performed best when trained on both public datasets, patchwise classification, and oversampled tunnel datasets. In the future, we expect to contribute to establishing a plan to efficiently utilize the tunnel image acquisition system's data for deep learning model learning.

• Journal of Convergence for Information Technology
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• v.11 no.9
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• pp.17-27
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• 2021

The aim of this research was to identify the issue of the work permit system and consciousness of the people on the system, and to suggest some ideas on the government policies on it. To achieve the aim of research, this research used text mining based on social data. This research collected 1,453,272 texts from 6,217 units of online documents which contained 'work permit system' from January to December, 2020 using Textom, and did text-mining and social network analysis. This research extracted 100 key words frequently mentioned from the analyses of data top-level key word frequency, and degree centrality analysis, and constituted job problem, importance of policy process, competitiveness in the respect of industries, and improvement of living conditions of foreign workers as major key words. In addition, through semantic network analysis, this research figured out major awareness like 'employment policy', and various kinds of ambient awareness like 'international cooperation', 'workers' human rights', 'law', 'recruitment of foreigners', 'corporate competitiveness', 'immigrant culture' and 'foreign workforce management'. Finally, this research suggested some ideas worth considering in establishing government policies on the work permit system and doing related researches.

• Korean Journal of Remote Sensing
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• v.37 no.5_3
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• pp.1425-1434
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• 2021

Continuous and periodic data acquisition must be preceded to maintain and manage the river facilities effectively. Adapting the existing general facilities methods, which include river surveying methods such as terrestrial laser scanners, total stations, and Global Navigation Satellite System (GNSS), has limitation in terms of its costs, manpower, and times to acquire spatial information since the river facilities are distributed across the wide and long area. On the other hand, the Mobile Mapping System (MMS) has comparative advantage in acquiring the data of river facilities since it constructs three-dimensional spatial information while moving. By using the MMS, 184,646,009 points could be attained for Anyang stream with a length of 4 kilometers only in 20 minutes. Levee points were divided at intervals of 10 meters so that about 378 levee cross sections were generated. In addition, the waterside maximum and average slope could be automatically calculated by separating slope plane form levee point cloud, and the accuracy of RMSE was confirmed by comparing with manually calculated slope. The reference slope was calculated manually by plotting point cloud of levee slope plane and selecting two points that use location information when calculating the slope. Also, as a result of comparing the water side slope with slope standard in basic river plan for Anyang stream, it is confirmed that inspecting the river facilities with the MMS point cloud is highly recommended than the existing river survey.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.4
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• pp.211-221
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• 2021

The Rabbit grass(Trifolium Repens, call it 'Clover') is a representative harmful plant of lawn, and it starts growing earlier than lawn, forming a water pipe on top of the lawn and hindering the photosynthesis and growth of the lawn. As a result, in competition between lawn and clover, clover territory spreads, but lawn is damaged and dried up. Damage to the affected lawn area will accelerate during the rainy season as well as during the plant's rear stage, spreading the area where soil is exposed. Therefore, the restoration of damaged lawn is causing psychological stress and a lot of economic burden. The purpose of this study is to distinguish clover which is a representative harmful plant on lawn, to identify the distribution of damaged areas due to the spread of clover, and to review of changes in vegetation before and after the eradication of clover. For this purpose, a time series analysis of three vegetation indices calculated based on images of convergence Drone with RGB(Red Green Blue) and BG-NIR(Near Infra Red)sensors was reviewed to identify the separation between lawn and clover for selective eradication, and the distribution of damaged lawn for recovery plan. In particular, examined timeseries changes in the ecology of clover before and after the weed-whacking by manual and brush cutter. And also, the method of distinguishing lawn from clover was explored during the mid-year period of growth of the two plants. This study shows that the time series analysis of the MGRVI(Modified Green-Red Vegetation Index), NDVI(Normalized Difference Vegetation Index), and MSAVI(Modified Soil Adjusted Vegetation Index) indices of drone-based RGB and BG-NIR images according to the growth characteristics between lawn and clover can confirm the availability of change trends after lawn damage and clover eradication.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.9
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• pp.359-366
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• 2021

A number of construction companies in Korea invest considerable human and financial resources to construct a system for managing apartment defect data and for categorizing repair tasks. Thus, this study proposes machine learning models to automatically classify defect complaint text-data into one of the sub categories of 'finishing work' (i.e., one of the defect repair tasks). In the proposed models, we employed two word representation methods (Bag-of-words, Term Frequency-Inverse Document Frequency (TF-IDF)) and two machine learning classifiers (Support Vector Machine, Random Forest). In particular, we conducted both binary- and multi- classification tasks to classify 9 sub categories of finishing work: home appliance installation work, paperwork, painting work, plastering work, interior masonry work, plaster finishing work, indoor furniture installation work, kitchen facility installation work, and tiling work. The machine learning classifiers using the TF-IDF representation method and Random Forest classification achieved more than 90% accuracy, precision, recall, and F1 score. We shed light on the possibility of constructing automated defect classification systems based on the proposed machine learning models.

• 한국노년학
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• v.38 no.2
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• pp.271-290
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• 2018

The study aims to analyze the effects of socio-economic deprivation on suicidal ideation. The analysis data were used as a guide for Korea Welfare Panel Study 9. the frequency analysis, mean difference analysis, correlation analysis, and logistic regression were performed by SPSS programs. The results of analysis are as follows. First, The results of frequency analysis by deprivation type showed a high frequency of deprivation in the following order. Experience of not receiving a public pension, experience of being able to work but unemployed, experience of not being able to eat a balanced diet due to financial difficulties, and experience where you had nothing to eat but no more money to buy. Second, the average difference analysis shows that when a person does not have a spouse, the lower the academic background and the income level, the higher the likelihood of suicide. Third, regression analysis shows that the following deprivation patterns have a statistically significant effect on older adults' thoughts of suicide. Experience in which the respondents or their family could not go to hospital because they had no money, experience that move house because is back rent more than 2 months or can not pay rent, experience that they could not afford to buy food and eat well-balanced meals, experience of failing to pay your bills on time, experience of being able to work but not having a job, and experience in which financial difficulties left them short of food and no money to live. Based on such research results, some policy measures, such as the expanding management of medical care benefits cases, the improvement of elderly housing, residential conditions and the diet survey for the elderly, and the expansion of measures to support elderly people's tax rates, were proposed.

• Journal of vocational education research
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• v.30 no.4
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• pp.1-22
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• 2011

Paradoxically, leadership has not only positive effects but also negative effects. The purpose of this study is to examine supervisors' dysfunctional leadership behaviors, antecedents and results in order to draw HRD implications for protecting organizations and employees from dysfunctional leaders and provide implications for leadership development. A qualitative research method based on semi-organized interviews with 28 employees from S-group was used. The results of this study show that the dysfunctional leadership behaviors were associated with ten behavioral categories: belittling and insulting the subordinates, authoritative and arbitrary behaviors, self-aggrandizement, biased preference for certain personnel, arrogance, micro-managing, inability to change and adapt, discordance between words and actions, over-dependance on supervisor, lack of ethics and values. Dysfunctional leadership behaviors were casually attributed to 'personal traits & experience', 'task characteristics', and 'internal & external environments of the organization'. Finally, the results of supervisor's dysfunctional leadership behaviors on employees and the organizational effects were 'increased turnover rate', 'declining work efficiency', 'collapsing morale', 'retraining innovative thinking', 'passive working culture', 'discouraging organizational vitality', 'discouraging organizational synergy', 'losing loyalty' and 'declining trust on supervisor'.

• Journal of vocational education research
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• v.35 no.6
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• pp.113-141
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• 2016

The apprenticeship training is given as a solution of the youth unemployment problem. The apprenticeship is a system that companies hire and instruct trainees and is implemented in various countries. In Korea, there is a Korean work-learning dual system which is managed by the government rather than the company itself. This Study analyzed Germany, Switzerland and Austria's apprenticeship training system and compared common factors of apprenticeship system, a trainer in company and cost-benefit analysis. The result of the study can be shown as follows. First, Germany operates practical training, meanwhile Switzerland and Austria provide a pre-education course before students enter the upper-secondary VET course. Second, Germany and Switzerland give a single type apprenticeship training, whereas Austria runs a modularization system, which enables students to specify their skills and improves clarity. Third, social partners as well as the government, states, companies/schools actively participate in apprenticeship. Fourth, there is a suitable trainer's qualification system in all countries. Finally, Germany and Austria's companies cause larger cost than benefit in apprenticeship. On the other hand, Switzerland gets larger net-benefit than cost. We can give implications to the Korean work-learning dual system based on this study.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.407-416
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• 2019

This study is about a Customized Nursery School where working women can support work - life balance and a reduction in retirement or turnover. The research method is to identify the current status of Customized Nursery services and to recognize the recognition and need of the operation of Customized Nursery School. The importance of securing skilled nurses and preventing them from changing their jobs for the health and safety of people cannot be emphasized enough. A Customized Nursery School must be opened to reduce the retirement or change of jobs of working women nurses and to provide care for continuous work in three shifts from 365days to support the balance between the working mother and family. It is considered that nurses will put their children in relief when using retired nurses who have the ability to work 24hour rotation in a Customized Nursery School and when a Customized Nursery School be ran suited for the condition and demand of working women nurses, it is expected to reduce retirement and the change of jobs, also to give positive effect on marrige and family planning which would make improvement in low birthrate. To activate the Customized Nursery School, Creating a secure learning environment and qualification of educators great effort should be put. A program curriculum based on 'basic life and habits' should be the center of education. Continuous management and effort will need to be placed in continuous development of educators.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.4
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• pp.75-89
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• 2019

In the case of SMEs, entrepreneurship that organizes only core functions with the minimum number of people is increasing, and a responsibility management system focusing on core functions is emphasized, so that the interest in innovation behavior and survival strategy of enterprises is getting bigger. However, in the case of SMEs, it is not easy to pursue continuous innovation due to lack of capital and lack of professional manpower. The purpose of this study is to investigate the effect of SME on innovation behavior by selecting exploratory study and literature study for SMEs. The data for this study were 545 out of the total 600 copies distributed to employees in SMEs. The data were analyzed using SPSS 21.0 and amos18.0. First, product diversification, strategy formulation, and R & D have a significant effect on innovation behavior, and market diversification has no effect on innovation behavior. Second, working variables such as product diversification, market diversification, strategy formulation, and R & D do not control the influence of innovative behavior on innovation behavior. Third, the rank variable, which is the controlling variable, controls the magnitude of the effect of product diversification, market diversification, strategy formulation, and R & D on innovation behavior. As a result, corporate managers should lead the organization in order to promote product diversification, market diversification strategy, R & D and innovation activities. After discussing the conclusions and implications of this study, this study presented the direction of the research for the follow-up study.