• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.37 no.1
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• pp.68-75
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• 2019

This study aims to look at the application methods of landscape architecture in response to the 4th Industrial Revolution. The results of the analysis of trends in the 4th Industrial Revolution and the subsequent search for application methods to the field of landscape architecture are as follows. First, the 4th Industrial Revolution means innovative change based on digital technology and seeks to create value based on intelligent information technology, and continuous growth is being made through innovation. This requires expertise to collect large amounts of information and creatively rework it, and a strategy to flexibly cope with changes in the times. Second, the status of technological use in response to the 4th Industrial Revolution in the field of landscape architecture is generalizing the establishment of precise analysis results such as survey technology and global mapping using drones, three-dimensional design simulation, and VR. In the field of traditional landscape architecture, efforts are made to obtain accurate fact-finding data on landscape site components. Third, the application methods in the field of landscape science according to the 4th Industrial Revolution in the future are required to supply precision technology and supply programs in the technology sector, and to provide a shared platform. In addition, a systemically standardized process will need to be established for this. In addition, educational efforts should be continued to professional manpower training and provide economic support for the development of technologies.

• Journal of Digital Convergence
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• v.17 no.5
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• pp.117-125
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• 2019

This study measured inefficiencies of Korean banks with weighted Russell directional distance function, WRDDM, for the years of 2004-2013. Checking contributions of inputs and outputs to these inefficiencies, we found that non-performing loan as undesirable output was the most influential factor. The annual average of inefficiencies of Korean banks was 0.3912, and it consisted of non-performing loan 0.1883, output factors 0.098 except non-performing loan, input factors 0.098. The annual average inefficiency went sharply up from 0.2995 to 0.4829 mainly due to the sharp increase of inefficiency of non-performing loan from 0.1088 to 0.2678 before and after 2007-2008 Global financial crisis. We empirically showed the non-performing loan needed to be considered since it was the most important factor among the influential factors of technical inefficiency such as manpower, total deposit, securities, and non-performing loan. This study had some limitation since we did not control financial environment factor in WRDDM.

• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.93-103
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• 2021

Despite the efforts of financial authorities in conducting the direct management and supervision of collection agents and bond-collecting guideline, the illegal and unfair collection of debts still exist. To effectively prevent such illegal and unfair debt collection activities, we need a method for strengthening the monitoring of illegal collection activities even with little manpower using technologies such as unstructured data machine learning. In this study, we propose a classification model for illegal debt collection that combine machine learning such as Support Vector Machine (SVM) with a rule-based technique that obtains the collection transcript of loan companies and converts them into text data to identify illegal activities. Moreover, the study also compares how accurate identification was made in accordance with the machine learning algorithm. The study shows that a case of using the combination of the rule-based illegal rules and machine learning for classification has higher accuracy than the classification model of the previous study that applied only machine learning. This study is the first attempt to classify illegalities by combining rule-based illegal detection rules with machine learning. If further research will be conducted to improve the model's completeness, it will greatly contribute in preventing consumer damage from illegal debt collection activities.

• Journal of Korean Society of Forest Science
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• v.110 no.2
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• pp.210-216
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• 2021

Musculoskeletal disorders affect workers' safety in most industries, and forest operations are classified as a musculoskeletal burden according to the Occupational Safety and Health Act in South Korea. In particular, felling and delimbing operations are mainly conducted by manpower, and then, it is necessary to evaluate ergonomic risk assessment for safety of felling and delimbing workers. Three ergonomic risk assessment methods, such as Ovako Working posture Analysis System (OWAS), Rapid Upper Limb Assessment (RULA), and Rapid Entire Body Assessment (REBA), are available for assessing exposure to risk factors associated with timber harvesting operations. Here, three ergonomic risk assessment methods were applied to examine ergonomic risk assessments in chainsaw felling and delimbing operations. Additionally, exposure to risk factors in each method was analyzed to propose an optimal working posture in felling and delimbing operations. The risk levels of these operations were evaluated to be highest in the RULA method, followed by the OWAS and REBA methods, and most of the exposed working postures were examined with a low-risk level of two and three without requiring any immediate working posture changes. However, two significant working postures, including the bending posture of the waist and leg in felling operation and standing posture on the fallen trees in delimbing operation, were assessed as the high-risk level and needed immediate working posture changes. Low-risk work levels were examined in the squatting posture for felling operation and the straightened posture of the waist and leg for delimbing operation. Moreover, the slope in felling operation and the tree height in delimbing operation significantly affected risk level assessment of working posture. Therefore, our study supports that felling and delimbing workers must operate with low-risk working postures for safety.

• Journal of the Korea Society of Computer and Information
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• v.24 no.10
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• pp.149-157
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• 2019

Recent research has been actively carried out on systems that want to optimize resource utilization by analyzing the intended behavior and pattern of behavior of objects (users, consumers). A service system that applies information about an object's location or behavior must include a location trigger processing system for tracking an object's real-time location. In this paper, we analyze design problems for the implementation of a context-awareness based location trigger system, and present system models based on analysis details. For this purpose, this paper introduces the concept of location trigger for intelligent location tracking techniques about moving situations of objects, and suggests a mobile agent system with active rules that can perform monitoring and appropriate actions based on sensing information and location context information, and uses them to design and implement the location trigger system for context-awareness based location services. The proposed system is verified by implementing location trigger processing scenarios and trigger service and action service protocols. In addition, through experiments on mobile agents with active rules, it is suggested that the proposed system can optimize the role and function of the application system by using rules appropriate to the service characteristics and that it is scalable and effective for location-based service systems. This paper is a preliminary study for the establishment of an optimization system for utilizing resources (equipment, power, manpower, etc.) through the active characteristics of systems such as real-time remote autonomous control and exception handling over consumption patterns and behavior changes of power users. The proposed system can be used in system configurations that induce optimization of resource utilization through intelligent warning and action based on location of objects, and can be effectively applied to the development of various location service systems.

• Economic and Environmental Geology
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• v.54 no.1
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• pp.127-136
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• 2021

This study was carried out to understand China's earthquake governance and role-sharing, and to strategically use it for research cooperation in related fields with China. The characteristics of China's national earthquake governance and role-sharing are detailed in this study. First, unlike Korea, China's geoscience and earthquake research fields are separate, and are clearly distinguished from other fields of science and technology. They hold a higher status compared to other fields in China. Second, China's provincial earthquake agencies simultaneously carry out related tasks under the dual supervisory management system of the central and provincial governments. Third, the China Earthquake Administration (CEA) has the authority to do research and development, manpower training, and degree conferment, which are centered on directly affiliated institutions. Fourth, China carries out similar functions in directly affiliated institutions of the CEA and the China Geological Survey (CGS), and affiliated institutions of the Chinese Academy of Sciences (CAS), respectively. Fifth, the CEA is continuously expanding the seismic observation network that connects the vast land of the country. Sixth, China is considered to have detailed structures of earthquake-related laws and regulations. Given China's earthquake governance and role-sharing, it is considered that the possibility of success in research cooperation is high if Korea first determines whether it is under the jurisdiction of the CGS, CEA, and CAS, depending on the specific field.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.85-91
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• 2020

Recently, video-taping equipment such as CCTV have been seeing more use for crime prevention and general safety concerns. Since these video-taping equipment operates all throughout the day, the need for security personnel is lessened, and naturally costs incurred from managing such manpower should also decrease. However, technology currently used predominantly lacks self-sufficiency when given the task of searching for a specific object in the recorded video such as a person, and has to be done manually; current security-based video equipment is insufficient in an environment where real-time information retrieval is required. In this paper, we propose a technology that uses the latest deep-learning technology and OpenCV library to quickly search for a specific person in a video; the search is based on the clothing information that is inputted by the user and transmits the result in real time. We implemented our system to automatically recognize specific human objects in real time by using the YOLO library, whilst deep learning technology is used to classify human clothes into top/bottom clothes. Colors are also detected through the OpenCV library which are then all combined to identify the requested object. The system presented in this paper not only accurately and quickly recognizes a person object with a specific clothing, but also has a potential extensibility that can be used for other types of object recognition in a video surveillance system for various purposes.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.77-83
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• 2020

The heat treatment facility is in a situation where the scope of application of the remote IOT system is expanding due to the harsh environment caused by high heat and long working hours among the root industries. In this heat treatment process environment, the IOT middleware is required to play a pivotal role in interpreting, managing and controlling data information of IoT devices (sensors, etc.). Until now, the system controlled by the heat treatment remotely was operated with the command of the operator's batch system without overall monitoring of the site situation. However, for the safety and precise control of the heat treatment facility, it is necessary to control various sensors and recognize the surrounding work environment. As a solution to this, the heat treatment safety support system presented in this paper proposes a support system that can detect the access of the work manpower to the heat treatment furnace through thermal image detection and operate safely when ordering work from a remote location. In addition, an OPEN CV-based deterioration analysis system using DNN deep learning network was constructed for faster and more accurate recognition than general fixed hot spot monitoring-based thermal image analysis. Through this, we would like to propose a system that can be used universally in the heat treatment environment and support the safety management specialized in the heat treatment industry.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.199-211
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• 2021

This study suggests an alternative for solving quality-of-life problems of an aging workforce by seeking ways to utilize an aging workforce in corporations and society. This research empirically analyzed data from the 6th panel data of aging. Study results are as follows. First, it was confirmed that job satisfaction of aging manpower plays a mediating role in the relationship between quality of life and the job characteristics of an aging workforce. Second, it was found that the wage level of regular workers had a significant effect on job satisfaction and quality of life, and the job satisfaction of regular workers was mediated between wage level and quality of life. On the other hand, the wage level of non-regular workers did not have any effect on job satisfaction and quality of life. The results of this study suggest the necessity for companies to recognize the use of an aging workforce to improve social value. Furthermore, our results provide implications for domestic firms and government policymakers on how to use a domestic aging workforce and how to utilize regular and non-regular workers.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.231-239
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• 2021

The purpose of this study was to understand how a dental hygienist is viewed by students in terms of both image and job /employment perception using structural equations. This together with the incorporation of available online information would help in collating the necessary data for ensuring adequate manpower of dental hygienists' in the future. The collected data were analyzed using SPSS Statistics 24.0 and AMOS Graphics 21.0 statistics packages. It was found that students who perceive employment positively have a positive image of a dental hygienist even if a new infectious disease were to occur. They appreciate that a negative image of a dental hygienist's job during an epidemic could cause a negative perception of employment as a dental hygienist. Those who think negatively of the internet as a source of information believe that the internet has a lot of false information, is harmful, promotes anxiety, and has been shown to promote negative perceptions about employment as a dental hygienist. Those who think positively of internet information think that dental hygienists are susceptible to infection and can transmit infection, which has been shown to negatively affect their perception of employment. In conclusion, it is important to form an image of a dental hygienist through the recognition of the correct internet information in the period of new infectious diseases.