• The Journal of the Korea Contents Association
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• v.21 no.9
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• pp.184-197
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• 2021

Prior to the establishment of 'Employment-Related Big Data Center (tentative name)' to support the development of customized employment services. This Paper examines the current status and limitation of employment-related data in korea. Then, the implications were derived through foreign employment-related big data construction cases. Through the above analysis, I proposed measures to build and utilize employment-related big data at the individual level, focusing on the Transitional Labour Markets theory that emphasizes the implementation of individual labor force states. Finally, we presented future challenges such as massive maintenance of employment-related DB, increased representation of big data to be built around employment insurance DB, and increased reliability of DB presented.

• Journal of the Korean Society of Safety
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• v.36 no.4
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• pp.80-87
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• 2021

Risk assessment techniques are processes used to evaluate hazardous risk factors in construction sites, facilities, raw materials, machinery, and equipment, and to estimate the size of risk that could lead to injury or disease, and establish countermeasures. The most important thing in assessing risk is calculating the size of the risk. If the size of the risk cannot be calculated objectively and quantitatively, all members who participated in the evaluation would passively engage in establishing and implementing appropriate measures. Therefore, this study focused on predicting accidents that are expected to occur in the future based on past occupational accident statistics, and quantifying the size of the risk in an overview. The technique employed in this study differs from other risk assessment techniques in that the subjective elements of evaluators were excluded as much as possible by utilizing past occupational accident statistics. This study aims to calculate the size of the risk, regardless of evaluators, such as a manager, supervisor, safety manager, or employee. The size of the risk is the combination of the likelihood and severity of an accident. In this study, the likelihood of an accident was evaluated using the theory of Bud Accident Chainability, and the severity of an accident was calculated using the occupational accident statistics over the past five years according to the accident classification by the International Labor Organization.

• The Journal of the Korea Contents Association
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• v.22 no.10
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• pp.460-474
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• 2022

The purpose of this study was to explore the perception of the extension of the retirement age perceived by corporation top leaders who are the main agents of employment. As a result of analyzing the interview data by qualitative content analysis, companies centered on manufacturing and construction preferred the elderly to foreign workers and leaders of social service organizations suggested that healthy and capable elderly people should be able to continue to work. However several opinions were also presented against the extension of the retirement age uniformly without considering the circumstances of the company. The passion for work of older workers with higher salary decreased, which concerns that the absence of a retirement system would reduce the vitality of the organization and increase the burden of labor costs. As an alternative to this, there is the opinion that employment can be extended even after the retirement age with the contract and in the form of a commissioned job according to an agreement with the company. Furthermore, it was also suggested that it would be easier not only to maintain employment but also to create jobs for the elderly given the employment flexibility.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.9
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• pp.1259-1265
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• 2022

Recently, AI, big data, and IoT technologies are being used in various solutions such as fire detection and gas or dangerous substance detection for safety accident prevention. According to the status of occupational accidents published by the Ministry of Employment and Labor in 2021, the accident rate, the number of injured, and the number of deaths have increased compared to 2020. In this paper, referring to the dataset construction guidelines provided by the National Intelligence Service Agency(NIA), the dataset is directly collected from the field and learned with YOLOv4 to propose a collision risk object detection system through object detection. The accuracy of the dangerous situation rule violation was 88% indoors and 92% outdoors. Through this system, it is thought that it will be possible to analyze safety accidents that occur in industrial sites in advance and use them to intelligent platforms research.

• Korean Journal of Occupational Health Nursing
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• v.30 no.4
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• pp.186-195
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• 2021

Purpose: The current status and rationale of industrial accidents needs to be examined to develop scientific and systemic preventive measures. Methods: The aim of this study is to analyze the current data on industrial accidents provided by the Ministry of Employment and Labor and categorize work-related deaths by types of industries and annual report. Results: First, the highest number of deaths occurred in industries that had less than 50 people. Second, in the manufacturing industry, the highest death rate was found in workers in the age group 50-59 years. In the construction industry, workers aged 50 and above had the highest number of deaths. In other industries, workers aged 60 and above had the highest number of deaths. Third, the highest number of deaths occurred in workers with less than one year of experience in any industry Fourth, in most industries, the highest work-related deaths occurred during weekdays (Monday~Friday). In 2015, the warehouse delivery industry had 33% higher work-related deaths on the weekends (Saturday and Sunday) as compared to other industries. Fifth, in most industries, the highest work-related deaths occurred from 8 AM to 6 PM. The warehouse delivery industry had higher work-related deaths from 10 PM to 8 AM as compared to other industries. Conclusion: In order to increase the efficacy of industrial accident prevention, it is necessary to establish an effective health management system and apply strict safety management activities.

• Computers and Concrete
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• v.31 no.3
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• pp.185-195
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• 2023

Antalya is located south part of minor Asia, one of the biggest cities in Türkiye. As a result of population growth and vast migration to Antalya, many parts of the city that were not suitable for construction due to its geological conditions have become urban areas, and most of these urban areas are full of poorly engineered buildings. Poor engineering has been combined with unplanned urbanization, that causes utter vulnerability to disasters in Antalya. When an earthquake-prone city, Antalya faces with an earthquake risk, fear arises in society. To overcome this problem, it has become necessary to investigate the building stock, expressed in hundreds of thousands, in a fast and reliable way and then perform an urban transformation to create the perception of structural safety. However, the excessive building stock, labor, and economic problems made the implementation stage challenging and revealed the necessity of finding alternative solutions in the field. The present study presents a novel approach for assessment and model based on a rapid visual inspection method to transform areas under earthquake risk in Türkiye. The approach aimed to rank the interventions for decision-making mechanisms by making comparisons in the scale hierarchy. In the present study, to investigate the proposed approach, over 26,000 buildings were examined in Antalya, which is the fifth largest city in Türkiye that has a population of over 2.5 Million. In the results of the study, the risk classification was defined in the framework of building, block, street, neighborhood, and district scales.

• Korean Journal of Agricultural Science
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• v.49 no.2
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• pp.269-284
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• 2022

The development of radish collectors has the potential to increase radish yields while decreasing the time and dependence on human labor in a variety of field activities. Stress and fatigue analyses are essential to ensure the optimal design and machine life of any agricultural machinery. The objectives of this research were to analyze the stress and fatigue of major components of a tractor-mounted radish collector under dynamic load conditions in an effort to increase the design dependability and dimensions of the materials. An experiment was conducted to measure the shaft torque of stem-cutting and transferring conveyor motors using rotary torque sensors at different tractor ground speeds with and without a load. The Smith-Watson-Topper mean stress equation and the rain-flow counting technique were utilized to determine the required shear stress with the distribution of the fatigue life cycle. The severity of the operation was assessed using Miner's theory. All running conditions produced more than 10⁷ of high cycle fatigue strength. Furthermore, the highest severity levels for motor shafts used for stem cutting and transferring and for transportation joints and cutting blades were 2.20, 4.24, 2.07, and 1.07, and 1.97, 3.81, 1.73, and 1.07, respectively, with and without a load condition, except for 5.24 for a winch motor shaft under a load. The stress and fatigue analysis presented in this study can aid in the selection of the most appropriate design parameters and material sizes for the successful construction of a tractor-mounted radish collector, which is currently under development.

• Journal of Drive and Control
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• v.20 no.3
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• pp.35-41
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• 2023

Radish and Chinese cabbage are the most produced and consumed vegetables in Korea. The mechanization of harvesting operations is necessary to minimize the need for manual labor. This study to develop and evaluate the performance of a multi-purpose driving platform that can apply modular Radish and Chinese cabbage harvesting devices. The multi-purpose driving platform consisted of driving, device control, engine, hydraulic, harvesting, conveying, and loading part. Radish and Chinese cabbage harvesting conducted using the multi-purpose driving platform each harvesting module. The performance of the multi-purpose driving platform was evaluated the field efficiency and loss rate. The total Radish harvesting operation time 34.3 min., including 28.8 min., of harvesting time, 1.9 min., of turning time, and 3.6 min., of replacement time of bulk bag. During Radish harvesting, the field efficiency and average loss rate of the multi-purpose driving platform were 2.0 hr/10a and 3.1 %. Chinese cabbage harvesting operation 49.3 min., including 26.6 min., of harvesting time, 4.6 min., of turning time, and 18.1 min., of replacement time of bulk bag. During Chinese cabbage harvesting, the field efficiency and average loss rate of the multi-purpose driving platform 2.1 hr/10a and 0.1 %. Performance evaluation of the multi-purpose driving platform that harvesting work was possible by installing Radish and Chinese cabbage harvest modules. Performance analysis through harvest performance evaluation in various Radish and Chinese cabbage cultivation environments is necessary.

• Journal of People, Plants, and Environment
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• v.22 no.5
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• pp.435-444
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• 2019

This study is based on the premise that a garden space is a place that not only requires physical labor but also encourages conversation in the gardening group. We suggest the use of urban gardens as a place to revitalize local communities by promoting people to participate in various event programs. Through the theoretical study, we set the requirements that can be applied to "urban garden events". We developed measurement items and scales to be used as variables of each construction concept. Our survey was conducted on adults aged 19 and above who visited the 8th Korean Urban Agriculture Expo. Out of total 310 copies of the distributed questionnaire, only 298 effective samples were used in the empirical analysis. We can assume that people want to revitalize local communities based on the fact that 71 (23.8%) participants said they thought the purpose of the event is to achieve unity among residents. Throughout analysis, 15 of the necessary items were confirmed and classified into two factors: image of event (Factor 1) and evaluation item (Factor 2). As a result of verifying the relationship between educational level for Factor 1, age was significant in five items and education level was significant in six items. For Factor 2, four items were effective in relation to education level, while significant results were not found in relation to age. These results are expected to be significant if the intellectual curiosity of the residents is satisfied and the demand base of the urban garden events according to the characteristics of city people is expanded. Based on this study, it is necessary to conduct research on the use of urban gardens as an event with social functions as well as various programs that can be carried out in gardens to build and revitalize the community.

• Journal of the Korea Society of Computer and Information
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• v.28 no.5
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• pp.17-28
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• 2023

Potholes that occur on paved roads can have fatal consequences for vehicles traveling at high speeds and may even lead to fatalities. While manual detection of potholes using human labor is commonly used to prevent pothole-related accidents, it is economically and temporally inefficient due to the exposure of workers on the road and the difficulty in predicting potholes in certain categories. Therefore, completely preventing potholes is nearly impossible, and even preventing their formation is limited due to the influence of ground conditions closely related to road environments. Additionally, labeling work guided by experts is required for dataset construction. Thus, in this paper, we utilized the Mean Teacher technique, one of the semi-supervised learning-based knowledge distillation methods, to achieve robust performance in pothole image classification even with limited labeled data. We demonstrated this using performance metrics and GradCAM, showing that when using semi-supervised learning, 15 pre-trained CNN models achieved an average accuracy of 90.41%, with a minimum of 2% and a maximum of 9% performance difference compared to supervised learning.