• Journal of the Korea Society for Simulation
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• v.29 no.2
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• pp.11-20
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• 2020

As the manufacturing environment becomes more complex, traditional simulation models alone are having a lot of difficulties in reflecting real-time manufacturing situations. Although the Digital Twin concept is actively discussed as an alternative to overcome theses issues, many studies are being carried out only in the product design phase. This research presents a Digital Twin-based manufacturing environment framework for applying the Digital Twin concept to the manufacturing process. Twin model that is operated in virtual space, physical system and databases describing the actual manufacturing environment, are proposed as detailed components that make up the framework. To check the applicability of proposed framework, a simple Digital Twin-based manufacturing system was simulated in a conveyor system using Arena software and Excel VBA. Experiment results have shown that the twin model is transmitted real time data from the physical system via DB and were operating in the same time unit. The Excel VBA fitted parameters defined by cycle time based on historical data that real-time and training data are being accumulated together. This study proposes operating method of digital twin model through the simple experiment examples. The results lead to the applicability of Digital twin model.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.3
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• pp.33-45
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• 2014

The Government of South Korea is actively promoting entrepreneurship policies to help solve an age old problem of unemployment; however, the unemployment rate of youth entrepreneurship remains at a low. Primarily due to the government fragmented policies that are unable to solve the daily difficulties young entrepreneurs undergo. Therefore, this study aims at deriving a modern solution to an age old problem that exists through the use of co-creation by first interviewing young entrepreneurs to help derive a paradigm model. The model was developed through a grounded theory approach to help strengthen the young venture entrepreneurs. The results revealed that majority of the young entrepreneurship revitalization policies had exclusive participation structure, allowing only a selected few: complex policies of various government departments, short-term funding, one-size-fits-all training and support, lack of follow-up support policies after start-up, excessive administrative requirements, and performance-oriented fragmented support. Concluding that the policies were unrealistic and ineffective for the entrepreneurs. Accordingly, the result suggests that Co-creation entrepreneurship revitalization policy, based on the experiences of entrepreneurs, will need to be established to formulate an effective policy that provides practical assistance to the entrepreneurs in the field.

• Korean Business Review
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• v.13
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• pp.1-30
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• 2000

The corporate make an effort to improve organizational committment and the degree of employees' satisfaction(internal customer satisfaction). And If it's possible, it enhance competitive advantage of organization for external customer satisfaction. But in fact, the external customer satisfaction and competitive power is made by the complex function between leader support and organizational support in organization. Those hypotheses has been supported by the study of many scholars. Nevertheless the reliability in the results is not to be enough for certain conclusion. Therefore this study investigated the influence of organizational support and leader support(as a independent variable) on commitment(as a mediating variable) and citizenship(as a dependent variable). The result indicated that employees who perceive a high degree of organization and leader support show a high committment to organization in affection and positive OCB. Also the result showed that high committment to organization in affection enhance the relation between organizational support, leader's support and OCB(organization citizenship behavior) Implications for managers in organizations are suggested.

• Journal of Digital Convergence
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• v.11 no.1
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• pp.431-439
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• 2013

This thesis is to research the before and after changes of physical configurations, blood components and physical strength for normal and geriatric diseased senior citizens at the end of 24 week of combined exercises constructed of aerobic and muscular strength training to create most suitable and effective complex exercise program for geriatric diseased patients. For this experiment 20 normal and 20 geriatric diseased patients in the age of 65 residing in "K" city were selected to carry out the 24 weeks of combined exercises in regularly. The result of the research showed that geriatric patients increased significantly in everything, but normal group showed significant change in only WHR. There was a slight improvement in the blood components for the average participants but it only differed slightly from the diseased participants so there were no major changes reflecting the outcomes from both before and after. After concluding the program both groups displayed positive improvements in stamina but no significant alterations in physical strength., agility, muscle endurance and balance. The positive factors for each groups could be that the norms were able to maintain their health and enhancement in stamina and diseased were able to prevent their condition from worsening. Additionally, over 50 percent of all senior citizens have one or more geriatric diseases but the participation of any physical activity is in the decrease. Henceforth, this is a field that still needs a lot of work and combined exercise programs should be created and followed through so it may enhance in the improvement of health and quality of life as well.

• Journal of Digital Convergence
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• v.15 no.2
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• pp.173-181
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• 2017

In this paper, we have studied tracking as a training stage of considering the position and the scale of a person given its previous position, scale, as well as next and forward image fraction. Unlike other learning methods, CNN is thereby learning combines both time and spatial features from the image for the two consecutive frames. We introduce multiple path ways in CNN to better fuse local and global information. A creative shift-variant CNN architecture is designed so as to alleviate the drift problem when the distracting objects are similar to the target in cluttered environment. Furthermore, we employ CNNs to estimate the scale through the accurate localization of some key points. These techniques are object-independent so that the proposed method can be applied to track other types of object. The capability of the tracker of handling complex situations is demonstrated in many testing sequences. The accuracy of the SVM classifier using the features learnt by the CNN is equivalent to the accuracy of the CNN. This fact confirms the importance of automatically optimized features. However, the computation time for the classification of a person using the convolutional neural network classifier is less than approximately 1/40 of the SVM computation time, regardless of the type of the used features.

• Journal of the Korean Society of Marine Environment & Safety
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• v.19 no.5
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• pp.476-482
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• 2013

This study aims to enhance the effectivity of VTS(Vessel Traffic Service) control by investigating the minimum safe distance between vessel and vessel, vessel and land(obstacle) for the vessel's safe navigation within the VTS control area. In addition, to suggest basic data for the safe navigation, this study has done survey and analysis to each VTS center, and individual on the minimum safe distance to VTS operators of each ports of korea. Through ocean voyage by training ship, Singapore and Malacca strait's congested vessel traffic zone's control distance was compared and investigated the difference on safe distance by the different VTS operators. As a result, there was huge difference of minimum safe distance between the VTS operators belong to the same center. Over all, the port with gentle coastline, like donghae, the safe distance was wider than the other port. On the other hand, port with complex coastline and frequent entry and departure of the vessel, like mokpo, the safe distance was the shortest of all. Therefore, development of module suitable to port's natural conditions and traffic volume's necessity is required, for the operators affiliated to the same VTS center control according to formal method. Lastly, the full discussion by the expert group about establishment of standard control procedure in the future should be considered as well.

• Journal of the Society of Naval Architects of Korea
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• v.34 no.1
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• pp.122-129
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• 1997

Thermo-elastic-plastic analyses used in solving plate forming process are often computationally expensive. To obtain an optimal process of line heating typically requires numerous iterations between the simulation and a finite element analysis. This process often becomes prohibitive due to the amount of computer time required for numerical simulation of line heating process. Therefore, a new techniques that could significantly reduce the computer time required to solve a complex analysis problem would be beneficial. In this paper, we considered factors that influence the bending effect by line heating and developed inference engine by using the concept of artificial neural network. To verify the validity of the neural network, we used results obtained from numerical analysis. We trained the neural network with the data made from numerical analysis and experiments varying the structure of neural network, in other words varying the number of hidden layers and the number of neurons in each hidden layers. From that we concluded that if the number of neurons in each hidden layers is large enough neural network having two hidden layers can be trained easily and errors between exact value and results obtained from trained network are not so large. Consequently, if there are enough number of training pairs, artificial neural network can infer similar results. Based on the numerical results, we applied the artificial neural network technique to deal with mechanical behavior of line heating at simulation stage effectively.

• Journal of the Society of Disaster Information
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• v.14 no.3
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• pp.360-366
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• 2018

Purpose: This study operation of Joint inter-agency Chemical Emergency Preparedness Center and contribute to the reduction of chemical accidents that occur continuously. Method: The Joint inter-agency Chemical Emergency Preparedness Center functions and Chemical accident statistics data of the ('13~'17) were utilized. Results: The number of chemical accidents is decreasing from 113 in '15, 78 in '16, 87 in '17(latest five years 469 chemical accidents). The Joint inter-agency Chemical Emergency Preparedness Center is located in the industrial complex that handling a large amount of chemical, and performs functions such as prompt response, probation & investigation, accident prevention training, safety patrol. It is believed that it contributes to the decreasing of chemical accident by local control accident prevention function. Conclusion: Decreasing the safety management according to the Chemicals control act('15.1.1). The Joint inter-agency Chemical Emergency Preparedness Center('14.1 set up manage organization), which is operated as a mission to prepare respond to chemical accidents, plays a role.

• KEPCO Journal on Electric Power and Energy
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• v.6 no.4
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• pp.413-418
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• 2020

It is necessary to manage the prediction accuracy of the machine learning model to prevent the decrease in the performance of the grid network condition prediction model due to overfitting of the initial training data and to continuously utilize the prediction model in the field by maintaining the prediction accuracy. In this paper, we propose an automation technique for maintaining the performance of the model, which increases the accuracy and reliability of the prediction model by considering the characteristics of the power grid state data that constantly changes due to various factors, and enables quality maintenance at a level applicable to the field. The proposed technique modeled a series of tasks for maintaining the performance of the power grid condition prediction model through the application of the workflow management technology in the form of a workflow, and then automated it to make the work more efficient. In addition, the reliability of the performance result is secured by evaluating the performance of the prediction model taking into account both the degree of change in the statistical characteristics of the data and the level of generalization of the prediction, which has not been attempted in the existing technology. Through this, the accuracy of the prediction model is maintained at a certain level, and further new development of predictive models with excellent performance is possible. As a result, the proposed technique not only solves the problem of performance degradation of the predictive model, but also improves the field utilization of the condition prediction model in a complex power grid system.

• Journal of the Korea institute for structural maintenance and inspection
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• v.25 no.6
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• pp.111-120
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• 2021

When a fire occurs in a commercial building, the evacuation route is complicated and the direction of smoke and flame is similar to that of the egress route of occupants, resulting in many casualties. Performance-based evacuation design for buildings is essential to minimize human casualties. In order to apply the performance-based evacuation design to buildings, it requires a complex fire simulation for each building, demanding a large amount of time and manpower. In order to supplement this, it would be very useful to develop an Available Safe Egress Time (ASET) prediction model that can rationally derive the ASET without performing a fire simulation. In this study, the correlations between fire temperature with visibility and toxic gas concentration were investigated through a fire simulation on a commercial building, from which databases for the training of artificial neural networks (ANN) were created. Based on this, an ANN model that can predict the available safe egress time was developed. In order to examine whether the proposed ANN model can be applied to other commercial buildings, it was applied to another commercial building, and the proposed model was found to estimate the available safe egress time of the commercial building very accurately.