• Journal of the Korean Society of Industry Convergence
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• v.24 no.6_2
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• pp.849-860
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• 2021

Recently, it is easy to find cases of 3D printing product, equipment, and materials in the architecture field. However, there is a lack of distribution environment where 3D printing products can be traded on an online platform or to access on-demand services in the architecture field. Therefore, in this study, a distribution platform development plan was proposed in consideration of the maturity level of the 3D printing distribution market in the domestic architecture field. For this purpose, the research was carried out as follows. First, by analyzing the case of the 3D printing distribution platform, the development stage of the distribution platform was set as three stages from the perspective of market maturity, platform development level, and sales/purchase experience level of suppliers and consumers. Second, the market maturity of the current domestic architecture field was evaluated as the first stage, and a distribution platform that could be implemented in the first stage was presented as a pilot. Third, we presented the first stage pilot, collected practical opinions on future construction plans through in-depth interviews, and presented detailed implementation plans for each stage necessary to achieve the second and third stage market maturity goals. Based on the roadmap derived from this study, it is expected that the domestic distribution platform market will grow step by step in the future and be utilized for business model development.

• Journal of Korea Trade
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• v.24 no.8
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• pp.189-206
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• 2020

Purpose - This paper attempted to verify the process by which a multinational corporation (MNC)'s subsidiary practices entrepreneurship to create effective knowledge (KC) in the local market. We have looked at whether subsidiary entrepreneurship (SENT) has a moderation effect in creating knowledge for the local market when a subsidiary has been given autonomy (AUT) from the headquarters (HQ). We also argue that when a subsidiary creates meaningful knowledge, the effect of the increased status by the HQ within the MNC network position (NP) has an indirect effect on whether knowledge is transferred to other overseas subsidiaries (KTO). Design/methodology - This paper used a structural equation model (SEM) of 282 effective foreign companies invested in Korea. To test the hypothesis about the process of SENT on KTO, descriptive statistics, confirmatory factor analysis, reliability, convergent and discriminant validities, and common method bias were analyzed using STATA. In addition, the moderation effect was verified along with SEM. The moderation effect of AUT on SENT and KC was presented graphically by confirming \mathrm{\pm1} standard deviation of AUT for the main effect. Findings - Our findings are as follows. First, while the hypothesis about the direct effect of SENT and KC on KTO was not supported, all other hypotheses were supported. Second, both the AUT and moderating effect and the indirect effect of NP were significant. In the conclusion, these findings are discussed in relation to its various theoretical and practical implications. Originality/value - This study attempted to contribute to the knowledge creation theory of MNC by contemplating how subsidiaries can move away from HQ and grow in the local market. Although there is still a shortage of foreign investment in the Korean market, our practical implications offer guidance for how current subsidiaries can develop more than other overseas subsidiaries.

• Smart Structures and Systems
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• v.30 no.1
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• pp.49-62
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• 2022

Experimental and discrete element methods were used to investigate the effects of triple joints lengths and triple joint angle on the failure behavior of rock mass under uniaxial compressive test. Concrete samples with dimension of 20 cm × 20 cm × 5 cm were prepared. Within the specimen, three imbedded joint were provided. The joint lengths were 2 cm, 4cm and 6 cm. In constant joint lengths, the angle between middle joint and other joints were 30°, 60°, 90°, 120° and 150°. Totally 15 different models were tested under compression test. The axial load rate on the model was 0.05 mm/min. Concurrent with experimental tests, the models containing triple joints, length and joint angle are similar to the experiments, were numerical by Particle flow code in two dimensions (PFC2D). Loading rate in numerical modelling was 0.05 mm/min. Tensile strength of material was 1 MPa. The results show that the failure behaviors of rock samples containing triple joints were governed by both of the angle and the length of the triple joints. The uniaxial compressive strengths (UCS) of the specimens were related to the fracture pattern and failure mechanism of the discontinuities. Furthermore, it was shown that the compressive behavior of discontinuities is related to the number of the induced tensile cracks which are increased by decreasing the joint length. Along with the damage failure of the samples, the acoustic emission (AE) activities are excited. There were only a few AE hits in the initial stage of loading, then AE hits rapidly grow before the applied stress reached its peak. In addition, every stress drop was accompanied by a large number of AE hits. Finally, the failure pattern and failure strength are similar in both methods i.e., the experimental testing and the numerical simulation methods.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.27-38
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• 2023

In this paper, we propose a conversational AI agent based on continual learning that can continuously learn and grow with new data over time. A continual learning-based conversational AI agent consists of three main components: Task manager, User attribute extraction, and Auto-growing knowledge graph. When a task manager finds new data during a conversation with a user, it creates a new task with previously learned knowledge. The user attribute extraction model extracts the user's characteristics from the new task, and the auto-growing knowledge graph continuously learns the new external knowledge. Unlike the existing conversational AI agents that learned based on a limited dataset, our proposed method enables conversations based on continuous user attribute learning and knowledge learning. A conversational AI agent with continual learning technology can respond personally as conversations with users accumulate. And it can respond to new knowledge continuously. This paper validate the possibility of our proposed method through experiments on performance changes in dialogue generation models over time.

• Asian Journal for Public Opinion Research
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• v.11 no.3
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• pp.257-273
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• 2023

Conducting face-to-face surveys is difficult and cost prohibitive, necessitating a new attempt to build a probability-based panel in South Korea. Since 99.9% of adult Koreans own a mobile phone, mobile phone numbers provide a viable sampling frame. Random digit dialing (RDD) surveys were conducted August-December 2021. Of the 288,056 valid phone numbers dialed, 13,655 respondents between the ages of 19 and 69 completed a phone survey. These respondents were later invited by text message to join a panel; 3,202 of these (23.4% or 1.2% based on the number initially contacted) joined the panel. When compared to official government statistics like resident registration data, the census, or the Social Survey, this new probability-based panel can be said to be representative of the Korean population on the basis of age, gender, location, marital status, and household size after weighting is applied. However, even after weighting, panel members are more educated than the general population, white-collar workers and self-employed people are overrepresented, and blue-collar workers are underrepresented. As of February 2023, this panel has grown to 10,471 participants with plans to continue to invite more panel members in the same way. Based on the comparisons in this paper, we can regard this panel as a cost-effective, probability-based panel that may be used for various kinds of public opinion research, by researchers both within and outside of Korea. As we continue to refine and grow this panel, we hope it will become more widely used by researchers as well as provide a model for those building similar panels in other countries.

• Transactions of the Korean hydrogen and new energy society
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• v.34 no.4
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• pp.358-368
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• 2023

The fuel cell market is expected to grow rapidly. Therefore, it is necessary to scale up fuel cells for buildings, power generation, and ships. A multi-stack system can be an effective way to expand the capacity of a fuel cell. Multi-stack fuel cell systems are better than single-stack systems in terms of efficiency, reliability, durability and maintenance. In this research, we developed a residential fuel cell stack and system model that generates electricity using the fuel cell-photovoltaic hybrid system. The efficiency and hydrogen consumption of the fuel cell system were calculated according to the three proposed power distribution methods (equivalent, Daisy-chain, and optimal method). As a result, the optimal power distribution method increases the efficiency of the fuel cell system and reduces hydrogen consumption. The more frequently the multi-stack fuel cell system is exposed to lower power levels, the greater the effectiveness of the optimal power distribution method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.5
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• pp.1310-1338
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• 2023

As Internet of Things (IoT) applications and devices rapidly grow, cyber-attacks on IoT networks/systems also have an increasing trend, thus increasing the threat to security and privacy. Botnet is one of the threats that dominate the attacks as it can easily compromise devices attached to an IoT networks/systems. The compromised devices will behave like the normal ones, thus it is difficult to recognize them. Several intelligent approaches have been introduced to improve the detection accuracy of this type of cyber-attack, including deep learning and machine learning techniques. Moreover, dimensionality reduction methods are implemented during the preprocessing stage. This research work proposes deep Autoencoder dimensionality reduction method combined with Artificial Neural Network (ANN) classifier as botnet detection system for IoT networks/systems. Experiments were carried out using 3- layer, 4-layer and 5-layer pre-processing data from the MedBIoT dataset. Experimental results show that using a 5-layer Autoencoder has better results, with details of accuracy value of 99.72%, Precision of 99.82%, Sensitivity of 99.82%, Specificity of 99.31%, and F1-score value of 99.82%. On the other hand, the 5-layer Autoencoder model succeeded in reducing the dataset size from 152 MB to 12.6 MB (equivalent to a reduction of 91.2%). Besides that, experiments on the N_BaIoT dataset also have a very high level of accuracy, up to 99.99%.

• Journal of People, Plants, and Environment
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• v.22 no.4
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• pp.341-354
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• 2019

Urban agriculture, which promotes communication in vulnerable classes and the formation of social networks has been gaining attention with an emphasis on healthy city, elderly-friendly city, safe city and happy city as future keywords about urban life. There is a growing interest in public awareness in many areas such as health, society, economy, and ecology. As an attempt to improve the diversity of urban gardens, this study begins with collecting suitable crops for urban gardens from "Imwongyeongjeji (林園經濟志)," an encyclopedia written by Yoo-Ku Seo, a scholar in the 18-19th century. Out of those recorded in "Gwanhyuji (灌畦志)," 128 kinds of crops with linkage of the historical achievements of the realists who gave their priority to public welfare were selected and 53 crops which had traditionality, historicality, health functionality and popularity were finally selected. The properties (cold, warm, clam) of the selected crops were evenly distributed, and there was no crop that was hot and cool. In addition, the number of crops that have a sweet taste was the highest, followed by spicy and bitter, but there was no salty vegetable, which can be attributed to the fact that 12 namuls (wild vegetables) that grow in seas were excluded in this study since they were not suitable for urban gardens. Urban gardens can be transformed from those that focus on primary production and secondary consumption activities into a new resource that offers educational and traditional values by applying humanities to urban agriculture as a content resource in the era of cultural consilience and convergence. It is expected to satisfy urban residents' intellectual and participatory needs and to enhance the diversity and utility of urban gardens by applying traditional knowledge to a new model of urban agriculture. We hope that further research will be conducted to develop new types and models of urban agriculture going forward.

• Journal of Information Technology Applications and Management
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• v.30 no.6
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• pp.31-52
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• 2023

The government's various support policies have helped Korea's SMEs and startups to grow from the beginning to the end, from domestic companies to exporters. In particular, direct business support policies such as financial support, R&D projects, and export support have been effective in helping a large number of entrepreneurs and startup companies to establish themselves in the market and have achieved tangible results every year since the establishment of the Ministry of SMEs and Startups. As such, the government is making significant efforts to create and promote various types of support policies and to help companies utilize them in their business. However, this study aims to analyze the factors that affect the satisfaction of government policies and the achievement of managerial performance from the companies' perspective and to suggest the purpose of government support policies and the direction companies should take. Specifically, this study categorizes entrepreneurial self-efficacy into marketing, innovation, management, risk-taking, and financial management, using the relationship model of self-efficacy and collective efficacy to ultimately lead to practical results for SMEs and startups support policies. It uses perceived firm efficacy as a variable to reveal the influence relationship. In addition, the direct and mediating effects of entrepreneurial self-efficacy and policy satisfaction on managerial performance were analyzed to determine what SMEs and startups support policies should do. The results showed that, first, among the five components of entrepreneurial self-efficacy, innovation, and risk-taking efficacy positively affected perceived firm efficacy. Second, the specific components of entrepreneurial self-efficacy, marketing, and financial management efficacy positively influenced policy satisfaction. Third, we found that perceived firm efficacy positively influenced policy satisfaction and managerial performance, which are factors of SMEs and startups' policy performance. Specifically, perceived firm efficacy positively influenced policy satisfaction managerial performance. Fourth, we found that policy satisfaction positively influenced managerial performance.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.26 no.5
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• pp.33-46
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• 2023

In this study, carbon storage in the aboveground biomass, litter layer, and soil layer was calculated for abandoned mining restoration areas to determine the level of carbon storage after the restoration project through comparison with the ecological reference. Five survey sites were selected for each abandoned mining restoration area in Boryeong-si, Chungcheongnam-do, and the ecological reference that can be a goal and model for the restoration project. The carbon storage in the restoration area was 0~21.3Mg C ha^-1, the deciduous layer 3.3~6.0Mg C ha^-1, and the soil layer(0-30cm) 8.3~35.1Mg C ha^-1, showing a significant difference in carbon storage by target site. The total carbon storage was between 6.1 and 35.3% of the ecological reference, with restoration area ranging from 14.0 to 62.4 Mg C ha^-1. The total carbon storage in the restoration area and the ecological reference differed the most in the aboveground biomass and was less than 12%. Based on these results, forest restoration area need to improve the carbon storage of forests through continuous management and monitoring so trees can grow and restore productivity in the early stages of the restoration project. The results of this study can be used as primary data for preparing future forest restoration indicators by identifying the storage of abandoned mining restoration areas.