• The Journal of the Convergence on Culture Technology
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• v.9 no.2
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• pp.171-179
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• 2023

Due to man-made climate change, global abnormal weather phenomena have occurred, increasing disasters. Major developed countries(military) are preparing for disasters caused by extreme weather appearances. However, currently, disaster prevention plans and facilities have been implemented based on the frequency and intensity method based on statistical data, it is not enough to prepare for disasters caused by frequent extreme weather based on probability basis. The U.S. and British forces have been the fastest to take research and policy approaches related to climate change and the threat of disaster change, and are considering both climate change mitigation and adaptation. The South Korean military regards the perception of disasters to be storm and flood damage, and there is a lack of discussion on extreme weather and disasters due to climate change. In this study, the process of establishing disaster management systems in developed countries(the United States and the United Kingdom) was examined, and the response policies of each country(military) were analyzed using literature analysis techniques. In order to maintain tight security, our military should establish a response policy focusing on sustainability and resilience, and the following three policy approaches are needed. First, it is necessary to analyze the future operational environment of the Korean Peninsula in preparation for the environment that will change due to climate change. Second, it is necessary to discuss climate change 'adaptation policy' for sustainability. Third, it is necessary to prepare for future disasters that may occur due to climate change.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.1
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• pp.85-93
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• 2024

The monitoring of environmental information (e.g. noise, dust, vibration, temperature, humidity) is crucial to the safe and sustainable operation of a construction site. However, commercial sensors exhibit certain drawbacks when applied on-site. First, the installation cost is prohibitively high. Second, these sensors have been engineered without considering the rugged and harsh conditions of a construction site, resulting in error-prone sensing. Third, construction sites are compelled to allocate additional resources in terms of manpower, expenses, and physical spaces to accommodate individual sensors. This research developed an integrated sensing module to measure the environmental information in construction site. The sensing module slashes the installation cost to 3.3%, is robust enough to harsh and outdoor sites, and consolidates multiple sensors into a single unit. The sensing module also supports GPS, LTE, and real-time sensing. The evaluation showed remarkable results including 97.5% accuracy and 99.9% precision in noise measurement, an 89.7% accuracy in dust measurement, and a 93.5% reliability in data transmission. This research empowers the collection of substantial volumes and high-quality environmental data from construction sites, providing invaluable support to decision-making process. These encompass objective regulatory compliance checking, simulations of environmental data dispersion, and the development of environmental mitigation strategies.

• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.6
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• pp.555-567
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• 2023

The cracks in the tunnel are currently determined through visual inspections conducted by inspectors based on images acquired using tunnel imaging acquisition systems. This labor-intensive approach, relying on inspectors, has inherent limitations as it is subject to their subjective judgments. Recently research efforts have actively explored the use of deep learning to automatically detect tunnel cracks. However, most studies utilize public datasets or lack sufficient objectivity in the analysis process, making it challenging to apply them effectively in practical operations. In this study, we selected test datasets consisting of images in the same format as those obtained from the actual inspection system to perform an objective evaluation of deep learning models. Additionally, we introduced ensemble techniques to complement the strengths and weaknesses of the deep learning models, thereby improving the accuracy of crack detection. As a result, we achieved high recall rates of 80%, 88%, and 89% for cracks with sizes of 0.2 mm, 0.3 mm, and 0.5 mm, respectively, in the test images. In addition, the crack detection result of deep learning included numerous cracks that the inspector could not find. if cracks are detected with sufficient accuracy in a more objective evaluation by selecting images from other tunnels that were not used in this study, it is judged that deep learning will be able to be introduced to facility safety inspection.

• Tunnel and Underground Space
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• v.34 no.3
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• pp.231-247
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• 2024

In the field of high-level radioactive waste disposal targeting deep rock environments, hydraulic characteristic information serves as the most important key factor in selecting relevant disposal sites, detailed design of disposal facilities, derivation of optimal construction plans, and safety evaluation during operation. Since various rock types are mixed and distributed in a small area in Korea, it is important to conduct preliminary work to analyze the hydrogeological characteristics of rock aquifers for various rock types and compile the resulting data into a database. In this paper, we obtained hydraulic conductivity data, which is the most representative field hydraulic characteristic of a high-depth volcanic bedrock aquifer, and also analyzed and evaluated the field data. To acquire field data, we used a high-performance hydraulic testing system developed in-house and applied standardized test methods and investigation procedures. In the process of hydraulic characteristic data analysis, hydraulic conductivity values were obtained for each depth, and the pattern of groundwater flow through permeable rock joints located in the test section was also evaluated. It is expected that the series of data acquisition methods, procedures, and analysis results proposed in this report can be used to build a database of hydraulic characteristics data for high-depth rock aquifers in Korea. In addition, it is expected that it will play a role in improving technical know-how to be applied to research on hydraulic characteristic according to various bedrock types in the future.

• Convergence Security Journal
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• v.24 no.2
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• pp.89-104
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• 2024

This study is an empirical study to examine the factors that influence the intention to use artificial intelligence (AI) technology for SW engineering-related tasks, and the purpose of the study is to understand the key factors that influence the use in terms of AI augmentation characteristics and interactive UI/UX characteristics. For this purpose, a survey was conducted among information and communication workers who have experience in using AI-related technologies and the collected data was analyzed. The results of the empirical analysis showed that perceived usefulness was positively influenced by the factors of expertise, interestingness, realism, aesthetics, efficiency, and flexibility, and perceived ease of use was positively influenced by the factors of expertise, interestingness, realism, aesthetics, and flexibility. Variety had no effect on both perceived ease of use and perceived usefulness. Perceived ease of use had a significant effect on perceived immersion, which positively influenced intention to use. These findings are significant in that they provide an academic understanding of the factors that influence the use of AI-enhanced tools in SW engineering-related tasks such as application design, development, testing, and process automation, as well as practical directions for the creators of tools that provide AI-enhanced development services to develop user acquisition strategies.

• Smart Media Journal
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• v.12 no.11
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• pp.154-164
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• 2023

The Construction Technology Information System collects, processes, and provides the public with free of charge 16 types of construction technology-related texts or index information, such as construction standards, construction practices, and construction reports, required at construction sites to enhance domestic construction technology. This study judged that user satisfaction could be increased if the budget was allocated first to the most effective construction technology information DB establishment. For each type of construction technology information, the level of satisfaction felt by the population for the quantity provided and the value of use according to the acquisition and utilization of information were investigated. Reliability between independent variables and dependent variables through a multiple regression analysis process to identify how the demographic characteristics of the population affect user satisfaction and the factors that affect the use value of information for each type of construction technology information. and the correlation was analyzed. The correlation between the demographic characteristics of respondents and users' satisfaction with the provided quantity was generally low, but construction experience, age, etc. were found to have an effect on satisfaction with the provided quantity. In particular, among the demographic measurement items of respondents, the more construction experience they had, the higher their satisfaction level with the quantity provided of low-level technical standards, and it was analyzed that older age had an impact on satisfaction with the quantity provided for small and medium-sized business support information.

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.729-736
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• 2024

In connection with the OECD's core competency proposal, we would like to consider an attempt to realize this in liberal arts education at Korean universities and examine what kind of education plan it is desirable to present to learners. Universities are expanding competency-based education into human and social fields by reconsidering new talent awards and the direction of education. In this way, each university selects and organizes core competencies and incorporates the core competencies that the university pursues into educational goals. Under the supervision of the Ministry of Education, education centered on core competencies is exploring its potential in liberal arts courses at universities above all else. We want to explore a methodology that can achieve learner-centered teaching and learning effects in the process of incorporating and accepting this. Language acquisition along with cross-cultural understanding is above all else a part that can promote learners' competencies in terms of diversity and mutual understanding. Therefore, we reflect this in French liberal arts education and explore teaching and learning processes by incorporating respect for diversity and mutual cultural understanding competency education related to learners' motivation into lectures. We aim to supplement this through collaboration and mutual cultural understanding processes as presentation tasks in order to overcome the existing competency-based evaluation while deriving acceptance results from learners. Therefore, they recognize that the direction of core competency education naturally shifts to value-centered education.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.2
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• pp.67-80
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• 2020

This study has been conducted at a time when Korean government continues to extend support for youth startups as part of its policy to create jobs and the focus moves from career and employment to youth startups with a growing interest in the field of youth startups. Against this background, this study aims to identify difficulty factors of youth startups in areas besides the Seoul Metropolitan Area, seek ways to overcome difficulty factors, and propose policy implications. To this end, this study set five criteria and 25 sub-criteria to evaluate the difficulties of youth startups by reviewing previous studies and conducting literature review, and performing brainstorming method. The empirical analysis of the evaluation criteria was performed, using the analytic hierarchy process (AHP) method, on youths aged 19 to 39 in Gunsan area. The analysis results showed that the largest difficulty factors facing local youths include business model establishment, business administration and management, and startup funding in the criteria. As for sub-criteria, the largest difficulty factors are market information acquisition, technology commercialization, project feasibility, technology development, and new market pioneering in descending order. Local youths have much difficulty about the process of turning a business item into a product and commercializing it. According to a comparative analysis by gender, men were a relatively high difficulty in commercializing business models than women. men were a relatively high difficulty in commercializing business models than women. On the other hand, women were higher than men in all factors (management management, entrepreneurship, improvement of entrepreneurship system, and improvement of entrepreneurship awareness) except for factors affecting business model. In addition, the factors of entrepreneurship were found to be relatively different among young people (college students, prospective entrepreneurs, entrepreneurs). In conclusion, it was suggested that in order to revitalize youth entrepreneurship in the region, it is necessary to actively resolve the difficulties of business model commercialization rather than entrepreneurship funds. In addition, it is necessary to strategically support customized entrepreneurship support and situational administrative services because gender and hierarchical difficulties are different than general solutions. This study presented practical priorities and derivation methods for the entrepreneurship difficulties faced by local youth, and suggested measures and improvements for vitalizing local youth entrepreneurship in the future.

• Management & Information Systems Review
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• v.36 no.5
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• pp.1-26
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• 2017

In the meantime, research on corporate informatization focuses on the completeness of information technology itself and its financial effects, so there is insufficient research on whether information technology can support business strategy. It is necessary to verify whether the management strategy implementation of the company can be led through the informatization of the enterprise and the relation between the main mechanism factors and the informatization performance. In this study, what a mechanism factor is applied in the process of result creation of informatization from three mechanism perspectives such as selecting mechanism, learning mechanism and coordinating mechanism with cases of representative domestic IT company and what an importance mechanism factors have been ascertained. This study results in 8 propositions. For a main agent of companies, securement of information capability of organizations has been selected to realize informatization results and investment of informatization has been selected to solve organizational decentralization problems as the most important factor. Additionally, as competition in the industry gets fierce, investment on informatization has been changed to a utility way of implementation of strategies and decision on investment has been made through the official process and information technology. Differentiated company capability has been made based on acquisition of technical knowledge and company information has been expanded to its whole employees through the information system. Also, informatization change management and outside subcontractor management have been acknowledged as an important adjustment factor of company. The first implication of this study is that since case studies on mechanism factors that preceding studies on informatization results did not empirically cover have directly been dealt with based on experiences of executives in charge of business and in charge of informatization, this study can provide practical views about factors that should be mainly managed for informatization results of IT companies. Secondly, since ser-M framework has been applied for IT companies for the first time, this study can academically contribute to companies in other fields about main mechanism factors for result creation of informatization based on deeper understanding and empirical cases.

• Journal of IKEEE
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• v.25 no.3
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• pp.493-500
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• 2021

In this paper, we propose the development of deep learning structure to improve quality of polygonal containers. The deep learning structure consists of a convolution layer, a bottleneck layer, a fully connect layer, and a softmax layer. The convolution layer is a layer that obtains a feature image by performing a convolution 3x3 operation on the input image or the feature image of the previous layer with several feature filters. The bottleneck layer selects only the optimal features among the features on the feature image extracted through the convolution layer, reduces the channel to a convolution 1x1 ReLU, and performs a convolution 3x3 ReLU. The global average pooling operation performed after going through the bottleneck layer reduces the size of the feature image by selecting only the optimal features among the features of the feature image extracted through the convolution layer. The fully connect layer outputs the output data through 6 fully connect layers. The softmax layer multiplies and multiplies the value between the value of the input layer node and the target node to be calculated, and converts it into a value between 0 and 1 through an activation function. After the learning is completed, the recognition process classifies non-circular glass bottles by performing image acquisition using a camera, measuring position detection, and non-circular glass bottle classification using deep learning as in the learning process. In order to evaluate the performance of the deep learning structure to improve quality of polygonal containers, as a result of an experiment at an authorized testing institute, it was calculated to be at the same level as the world's highest level with 99% good/defective discrimination accuracy. Inspection time averaged 1.7 seconds, which was calculated within the operating time standards of production processes using non-circular machine vision systems. Therefore, the effectiveness of the performance of the deep learning structure to improve quality of polygonal containers proposed in this paper was proven.