• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.321-330
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• 2021

By reviewing domestic and international papers, this study examines various fields in which drones are used, and based on the results, fields are suggested in which drones can be used for the work of firefighters. Overall, the research results show that drones are most commonly used for search (51%), disaster and fire monitoring (35%), and delivery (14%). Specifically, in the search field, using a drone is more efficient in terms of manpower, equipment, time, and cost than using people, which is the current practice. Secondly, in disaster and fire monitoring, drones can analyze and identify disasters and fire sites in real time. Therefore, it was confirmed that the use of drones is helpful in securing the safety of firefighters and identifying a disaster site. Third, research in logistics shows that drones can secure the so-called golden time in emergency situations by delivering rescue and relief supplies, emergency medicine, and blood in short order. In a rapidly changing disaster environment, and considering aging in firefighters, this study is meaningful in that it promotes drone utilization in the firefighting field by investigating basic data on drone utilization plans.

• Journal of Trauma and Injury
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• v.32 no.1
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• pp.1-7
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• 2019

Purpose: The present study aimed to evaluate the influence of how the trauma care system applied on the management of trauma patient within the region. Methods: We divided the patients in a pre-trauma system group and a post-trauma system group according to the time when we began to apply the trauma care system in the Halla Hospital after designation of a trauma center. We compared annual general characteristics, injury severity score, the average numbers of the major trauma patients, clinical outcomes of the emergency department, and mortality rates between the two groups. Results: No significant differences were found in the annual patients' average age ($54.1{\pm}20.0$ vs. $52.8{\pm}18.2$, p=0.201), transportation pathways (p=0.462), injury mechanism (p=0.486), injury severity score (22.93 vs. 23.96, p=0.877), emergency room (ER) stay in minutes (199.17 vs. 194.29, p=0.935), time to operation or procedure in minutes (154.07 vs. 142.1, p=0.767), time interval to intensive care unit (ICU) in minutes (219.54 vs. 237.13, p=0.662). The W score and Z score indicated better outcomes in post-trauma system group than in pre-trauma system group (W scores, 2.186 vs. 2.027; Z scores, 2.189 vs. 1.928). However, when analyzing survival rates for each department, in the neurosurgery department, in comparison with W score and Z score, both W score were positive and Z core was higher than +1.96. (pre-trauma group: 3.426, 2.335 vs. post-trauma group: 4.17, 1.967). In other than the neurosurgery department, W score was positive after selection, but Z score was less than +1.96, which is not a meaningful outcome of treatment (pre-trauma group: -0.358, -0.271 vs. post-trauma group: 1.071, 0.958). Conclusions: There were significant increases in patient numbers and improvement in survival rate after the introduction of the trauma system. However, there were no remarkable change in ER stay, time to ICU admission, time interval to emergent procedure or operation, and survival rates except neurosurgery. To achieve meaningful survival rates and the result of the rise of the trauma index, we will need to secure sufficient manpower, including specialists in various surgical area as well as rapid establishment of the trauma center.

• 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.

• The Journal of the Korea Contents Association
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• v.18 no.11
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• pp.643-654
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• 2018

In order to understand and manage traffic flows in urban areas in the past, a variety of traffic engineering theoretical indicators such as intersection lag and highway speed have been applied. However, these theories and indicators have been developed under the constraints of traffic engineering research before the construction of intelligent transportation system. Since the ATIS system currently exists, it is necessary to introduce a separate traffic engineering technology that utilizes the data. In this paper, it is aimed to confirm whether it is applicable to intermittent flow (approach road, intersection, control group, main road axis) by using 'congestion intensity' which is already used in traffic engineering field. The results of this study are as follows: (1) The traffic signal improvement effect of urban road access road, intersection road, control group, Two verification studies were performed to verify the derived congestion intensity index. (1) verification of congestion intensity threshold value analysis and (2) crossing improvement using the congestion intensity. Through verification, it was confirmed that it is possible to apply the congestion intensity in the inter - city intermittent flow using the 5 - minute unit speed data so as to be able to escape from the existing traffic signal operation management which is past passive and manpower limit.

• Journal of The Korean Association For Science Education
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• v.38 no.6
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• pp.781-792
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• 2018

In modern society, as technology develops and industry diversifies, students can choose from a variety of career paths. Since science, technology, engineering, and mathematics require a longer education and experience than other fields, it is important to design science education policies based on the competencies required for science, technology, engineering, and mathematics (STEM) occupations. This study explores the definition of science and technology manpower and STEM occupations and identifies core competencies of STEM occupations using standard job information operated and maintained by the US Department of Labor ($O^*NET$). We specially analyzed ratings of the importance of skills (35 ratings), knowledge (33 ratings), and work activities (41 ratings) conducting descriptive analysis and principal component analysis (PCA). As a result, core competencies of STEM occupations consist of STEM problem-solving competency, Management competency, Technical competency, Social service competency, Teaching competency, Design competency, Bio-chemistry competency, and Public service competency, which accounts for 70% of the total variance. This study can be a reference for setting the curriculum and educational goals in secondary and college education by showing the diversity of science and technology occupations and the competencies required for STEM occupations.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.142-149
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• 2019

In the early 2000s, the Korean government first attempted to acquire nuclear-powered submarines as strategic assets. Acquisition of nuclear-powered submarines must overcome the challenges of the initial costs and operating costs of trillions of US dollars per ship, must be agreed to by the international community (including neighboring countries) and in a national consensus, and must have an established technical infrastructure (including manpower). The US navy has been working with governments that want to acquire nuclear propulsion warships since the 1950s, and in 1982, they enacted an executive order called the United States Naval Nuclear Propulsion Program to consolidate efforts and prepare for the future, which sets out the organizational structure, authority, and responsibilities of US governmental management, and integrates national efforts. This paper is to gain valuable wisdom from the U.S. Naval Nuclear Propulsion Program by analyzing all of its histories and contributions, thereby providing valuable lessons for a future program in Korea. It might not be possible to follow the U.S.A. one-on-one because of the scale of national and military forces, but at least we can avoid time and effort spent on trial and error.

• The Korean Journal of Archival Studies
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• no.34
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• pp.29-56
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• 2012

Since 2011, 148 public institutions (including the central administrative agencies) have been moving to the provinces. First of all, the Prime Minister's Office began to be relocated to Sejong City on 14 Sep, 2012, followed by 6 central administrative agencies and their cooperative agencies are planned to move there. With regard to public institutions' relocation, the issue of record centers' relocation should be also considered. In respect that there is lack of facilities, manpower, and equipment in most record centers, it is doubtable whether the relocation of record centers will end successfully. The purpose of this study is to investigate the current state of record centers and to grasp their issues when they are relocated. The targets are the central administrative agencies which will move in 2012. The data was collected by request of information disclosure and personal contact with record centers. After analyzing collected data, both the issues caused by relocation and the cases of environment improvement were assured. In addition, the improvement of record centers' limitation (ex. The lack of exclusively responsible workers, the shortage of facilities, space and budget etc.) was suggested.

• The Journal of Bigdata
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• v.3 no.2
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• pp.19-33
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• 2018

Owing to the increase of FTA, food trade, and versatile preferences of consumers, food import has increased at tremendous rate every year. While the inspection check of imported food accounts for about 20% of the total food import, the budget and manpower necessary for the government's import inspection control is reaching its limit. The sudden import food accidents can cause enormous social and economic losses. Therefore, predictive system to forecast the compliance of food import with its preemptive measures will greatly improve the efficiency and effectiveness of import safety control management. There has already been a huge data accumulated from the past. The processed foods account for 75% of the total food import in the import food sector. The analysis of big data and the application of analytical techniques are also used to extract meaningful information from a large amount of data. Unfortunately, not many studies have been done regarding analyzing the import food and its implication with understanding the big data of food import. In this context, this study applied a variety of classification algorithms in the field of machine learning and suggested a data preprocessing method through the generation of new derivative variables to improve the accuracy of the model. In addition, the present study compared the performance of the predictive classification algorithms with the general base classifier. The Gaussian Naïve Bayes prediction model among various base classifiers showed the best performance to detect and predict the nonconformity of imported food. In the future, it is expected that the application of the abnormality detection model using the Gaussian Naïve Bayes. The predictive model will reduce the burdens of the inspection of import food and increase the non-conformity rate, which will have a great effect on the efficiency of the food import safety control and the speed of import customs clearance.

• 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 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.