• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.147-153
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• 2022

The uncertainty of start-ups are factors that weaken the entrepreneurial intentions of college students and prospective founders, and are also the cause of the low rate of entrepreneurship among art college students. This study tried to identify the effect of subjective norms entrepreneurial efficacy on start-up intentions. Studies have shown that entrepreneurial efficacy and subjective norms have a significant impact on start-up intentions. In addition, start-up education support has been shown to control the impact of subjective norms on start-up intentions, and start-up activity support has been shown to control the impact of subjective norms on start-up intentions, while start-up commercialization support does not control the impact of start-up efficacy or subjective norms on start-up intentions. In order to revitalize the start-up and effectively guide the start-up of art college students, it is necessary to show the social support of the people around them for the start-up and to enhance the efficacy of the start-up by supporting the prototyping activities.

• Journal of Industrial Convergence
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• v.21 no.1
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• pp.55-65
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• 2023

The purpose of this study is to explore the teaching experience of first-time youth soccer leaders. To this end, four leaders registered in the U-12 team were selected from those with more than 10 years of player experience, less than 5 years of coaching experience, and a level C or higher of the Korea Football Association leader's license. Accordingly, the analysis categories and analysis units were categorized according to the research problem, and data analysis was conducted through an inductive method. As a result of the study, youth soccer leaders were starting their coaching with the mindset of "I shouldn't" and "I can do it" based on their past experiences. They who concerned their uncertainty about the future in the teaching field were struggling with how to communicate with student and were less professional in teaching and learning ability. but they were trying to gain expertise while feeling rewarded in teaching. Accordingly, it was discussed to improve the treatment of youth soccer leaders and improve the program that is the leader training system.

• Journal of the Earthquake Engineering Society of Korea
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• v.27 no.5
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• pp.213-220
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• 2023

Seismic fragility curves play a crucial role in assessing potential seismic losses and predicting structural damage caused by earthquakes. This study compares non-sampling-based methods of seismic fragility curve derivation, particularly the probabilistic seismic demand model (PSDM) and finite element reliability analysis (FERA), both of which require employing sophisticated finite element analysis to evaluate and predict structural damage caused by earthquakes. In this study, a three-dimensional finite element model of API 5L X65, a buried gas pipeline widely used in Korea, is constructed to derive seismic fragility curves. Its seismic vulnerability is assessed using nonlinear time-history analysis. PSDM and a FERA are employed to derive seismic fragility curves for comparison purposes, and the results are verified through a comparison with those from the Monte Carlo Simulation (MCS). It is observed that the fragility curves obtained from PSDM are relatively conservative, which is attributed to the assumption introduced to consider the uncertainty factors. In addition, this study provides a comprehensive comparison of seismic fragility curve derivation methods based on sophisticated finite element analysis, which may contribute to developing more accurate and efficient seismic fragility analysis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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• pp.216-238
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• 2023

In intelligent transportation systems, traffic management is an important task. The accurate forecasting of traffic characteristics like flow, congestion, and density is still active research because of the non-linear nature and uncertainty of the spatiotemporal data. Inclement weather, such as rain and snow, and other special events such as holidays, accidents, and road closures have a significant impact on driving and the average speed of vehicles on the road, which lowers traffic capacity and causes congestion in a widespread manner. This work designs a model for multivariate short-term traffic congestion prediction using SLSTM_AE-BiLSTM. The proposed design consists of a Bidirectional Long Short Term Memory(BiLSTM) network to predict traffic flow value and a Convolutional Neural network (CNN) model for detecting the congestion status. This model uses spatial static temporal dynamic data. The stacked Long Short Term Memory Autoencoder (SLSTM AE) is used to encode the weather features into a reduced and more informative feature space. BiLSTM model is used to capture the features from the past and present traffic data simultaneously and also to identify the long-term dependencies. It uses the traffic data and encoded weather data to perform the traffic flow prediction. The CNN model is used to predict the recurring congestion status based on the predicted traffic flow value at a particular urban traffic network. In this work, a publicly available Caltrans PEMS dataset with traffic parameters is used. The proposed model generates the congestion prediction with an accuracy rate of 92.74% which is slightly better when compared with other deep learning models for congestion prediction.

• Convergence Security Journal
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• v.23 no.1
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• pp.109-115
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• 2023

The future outlook for defense faces various and challenging environments such as the acceleration of uncertainty in the global security landscape and limitations in domestic social and economic conditions. In response, the Ministry of National Defense seeks to address the problems and threats through defense innovation based on scientific and technological advancements such as artificial intelligence, drones, and robots. To introduce advanced AI-based technology, it is essential to integrate and utilize data on IT environments such as cloud and 5G. However, existing traditional security policies face difficulties in data sharing and utilization due to mainly system-oriented security policies and uniform security measures. This study proposes a paradigm shift to a data value-based security policy based on theoretical background on data valuation and life-cycle management. Through this, it is expected to facilitate the implementation of scientific and technological innovations for national defense based on data-based task activation and new technology introduction.

• Journal of the Korea Institute of Building Construction
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• v.23 no.3
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• pp.285-293
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• 2023

In this research, we embarked on a meticulous analysis of the challenges inherent in real-world scenarios relating to the durability design standards of engineered concrete structures and the assessment of carbonation durability in concrete guidelines. Our investigation brought to light substantial issues concerning constructability and quality assurance. The genesis of these problems is the exclusive application of prescribed strength to exterior walls, neglecting other elements to facilitate smoother licensing procedures. While this methodology aims to mitigate financial constraints in alignment with enhanced standards, it invariably invites complications. Furthermore, it is imperative to resolve the uncertainty surrounding durability evaluations by establishing a clear and definitive objective. Alongside this, actionable steps must be formulated to forestall the emergence of fissures between the floors of residential buildings, particularly apartment complexes. It is equally essential to tackle issues connected to application by devising a comprehensive management strategy for potential cracking during the phase of maintenance.

• Smart Structures and Systems
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• v.29 no.5
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• pp.661-675
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• 2022

In this paper, an electric vehicle drives with efficient control and low cost hardware using four quadrant DC converter with Permanent Magnet Direct Current (PMDC) motor fed by DC boost converter is presented. The main idea of this work is to improve the energy efficiency of the conversion chain of an electric vehicle by inserting a boost converter between the battery and the four quadrant-DC motor chopper assembly. Consequently, this method makes it possible to maintain the amplification gain of the 4 quadrant chopper constant regardless of the battery voltage drop and even in the presence of a fault in the battery. One of the most important control problems is control under heavy uncertainty conditions. The higher order sliding mode control technique is introduced for the adjustment of DC bus voltage and mechanical motor speed. To implement the proposed approach in the automotive field, experimental tests were carried out. The performances obtained show the usefulness of this system for a better energy management of an electric vehicle and an ideal control under different operating conditions and constraints, mostly at nominal operation, in the presence of a load torque, when reversing the direction of rotation of the motor speed and even in case of battery chamber failure. The whole system has been tested experimentally and its performance has been analyzed.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.152-152
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• 2021

The importance of groundwater has long been recognized, but the ground water potential to become contaminated as a result of human activities has only been recognized in recently. Before 1980 it was thought that soils served as filters, preventing harmful substances deposited at the surface from migrating into groundwater. Today it is known that soils have a finite capacity to protect groundwater. It can be contaminated from divers sources. Therefore, Assessment of aquifer vulnerability to pollution is essential for the protection and management of groundwater and land use planning. In this study, we used DRASTIC and AVI for groundwater vulnerability to contamination assessment. the different methods were applied to the southern coastal sedimentary basin of Benin and DRASTIC method was modified in two different steps. First, we modified DRASTIC by adding land use parameter to include the actual pollution sources (DRASTIC_LcLu) and second, classic DRASTIC weights was modified using Shannon's entropy (Entropy weight DRASTIC). The reliability of the applied approaches was verified using nitrate (NO3^-) concentration and by comparing the overall vulnerability maps to the previous researches in the study area and in the world. The results from validation showed that the addition of landcover/land use parameter to the classic DRASTIC helps to improve the method for better definition of the vulnerable areas in the basin and also, the weight modification using entropy improved better the method because Entropy weight DRASTIC_LcLu showed the highest correlation with nitrate concentration in the study basin. In summary the weight modification using entropy approach reduced the uncertainty of the human subjectivity in assigning weights and ratings in the standard DRASTIC.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.99-99
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• 2022

Jeju island has a humid subtropical climate and this climate zone is expected to migrate northward toward the main land, Korea Peninsula, as temperature increases are accelerated. Vegetation type has been inevitably shifted along with the climatic change, having more subtropical species native in southeast Asia or even in Africa. With the forest composition shift, it becomes more important than ever to analyze the water balance of the forest wihth the ongoing as well as upcoming climate change. Here, we implemented the Ecosystem Demography Biosphere Model (ED2) by initializing the key variables using forest inventory data (diameter at breast height in 2012). Out of 10,000 parameter sets randomly generated from prior distribution distributions of each parameter (i.e., Monte-Carlo Method), we selected four behavioral parameter sets using remote-sensing data (LAI-MOD15A2H, GPP-MOD17A2H, and ET-MOD16A2, 8-days at 500-m during 2001-2005), and evaluated the performances using eddy-covariance carbon flux data (2012 Mar.-Sep. 30-min) and remote sensing data between 2006-2020. We simulated each of the four RCP scenarios (2.6, 4.5, 6.0, and 8.5) from four climate forcings (GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, and MIROC5 from ISIMIP2b). Based on those 64 simulation sets, we estimate the changes in water balance resulting from the forest composition shift, and also uncertainty in the estimates and the sensitivity of the estimates to the parameters, climate forcings, and RCP scenarios.

• Korea Trade Review
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• v.46 no.4
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• pp.189-204
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• 2021

The fourth industrial revolution is affecting the industry as a whole, and the current logistics industry is coexisting with crises and opportunities. As part of overcoming this situation, the online platformization of the logistics market has recently been rapidly taking place, and the growth of e-commerce around developed countries has emerged as a demand for flexible freight services that can send and receive cargo anywhere and anytime at appropriate cost. However, the logistics industry has not been able to change rapidly in line with the demands of the market as it is immersed in traditional transportation transactions. Thus, the digital transformation of the freight market has become urgent to address problems such as uncertainty over traditionally closed and conservative freight market transaction processes and the lack of reliability caused by information asymmetry. Therefore, innovative domestic and foreign companies are attempting to establish a new way of transporting cargo, especially a marketplace way of connecting suppliers and consumers. Current status analysis and case studies were conducted through existing literature surveys, and prior research on freight market place selection factors was previewed, and the selection factors were stratified into five upper and 19 lower factors. Through this study, it is expected that improvements for sustainable growth of freight marketplace companies will be derived and that it will be a basic study of establishing management strategies through marketplace operation and quality control. In addition, it is deemed that the priority of customer requirements can be actively accepted, providing an opportunity to actively respond and strengthen corporate competitiveness.