• International Commerce and Information Review
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• v.17 no.1
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• pp.265-285
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• 2015

After the establishment of WTO for strengthening of GATT in 1995, the world economy has gradually been integrating toward economic globalisation. Even though this multilateral agreement may be beneficial to many countries but it also interferes domestic policies of member countries and threatens the role of local government and policy independence. For these reasons, FTA between countries or regions has been increasing. According to this trend, Korea and China has reached a substantial agreement of Korea-China FTA for mutual benefits. In general, the Korean automobile industry will benefit from Korea-China FTA due to its competitiveness in the global market and improvement of market access. However in the provisional schedule of concessions and commitment reported by press, the automobile seems to be excluded in this schedule of concessions. Hence, Korean automobile industry can not use the price competitiveness from tariff elimination. Therefore, Korean automobile industry needs aggressive marketing strategies for enhancement of brand equity as well as development of environment-friendly cars for following environment policies of Chinese government. Furthermore, they should make efforts to create the efficient investment environment by the removal of non-tariff barriers.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.11
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• pp.7957-7963
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• 2015

R&D trend for Auxiliary Power Supply(APU) of electric vehicle can be well understood by analyzing patents at home and abroad. Based on this trend analysis, domestic technology development direction is proposed. To get technique trend, patents of Korea, Japan, Europe and America published until February of 2014 are analyzed by WIPS DB. First, power converter and transformer two big category are classified. Power converter can be classified into resonant DC to DC converter and resonant Half bridge inverter; transformer can be classified into high frequency transformer, ferrite transformer and matching transformer. By analyzing R&D trend of different counties, companies and years, specific technology needed to be developed and trend of technology can be accurately grasped.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.10 no.4
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• pp.78-84
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• 1996

In this study, 3-D object recognition and restoration independent of the object translation for automotive kind recognition in parking administration system using an ultrasonic sensor array, neural networks and invariant moments are presented. Using invariant moment vectors of the acquired data 16$\times$8 pixels, 3-D objects could be classified by SCL (Simple Competitive Learning) neural networks. Modified SCL neural networks using the 16$\times$8 low resolution image was used for object restoration of 32$\times$32 high resolution image. Invariant moment vectors kept constant independent of the object translation. The recognition rates for the training and the testing data were 98[%] and 95[%], respectively. The experimental results have shown that ultrasonic sensor array with the neural networks could be applied for the detection of the automobiles and classification of the automotive kind.

• Journal of Intelligence and Information Systems
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• v.11 no.2
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• pp.81-103
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• 2005

The Neuron structure in a nervous system consists of inhibitory neurons and excitory neurons. Both neurons are activated by agonistic neurons and inactivated by antagonist neurons. In this paper, we proposed a physiological fuzzy neural network by analyzing the physiological neuron structure in the nervous system. The proposed structure selectively activates the neurons which go through a state of excitement caused by agonistic neurons and also transmit the signal of these neurons to the output layers. The proposed physiological fuzzy neural networks based on the nervous system consists of a input player, and the hidden layer which classifies features of learning data, and output layer. The proposed fuzzy neural network is applied to recognize bronchial squamous cell carcinoma images and car plate images. The result of the experiments shows that the learning time, the convergence, and the recognition rate of the proposed physiological fuzzy neural networks outperform the conventional neural networks.

• Fire Science and Engineering
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• v.26 no.4
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• pp.10-17
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• 2012

This study classifies the fire suppression measures implemented by wooden temples into four types according to availability of the pump trucks (water tanks) at the fire sites. And this study outlines the strategies and methods based on each type of fire suppression measure. The results show that the fire suppression strategy applied in general buildings is also employed in temples where pump trucks (water tanks) and fire-fighting water are available. For temples where trucks and water are not available, the helicopter, water bag, fire suppression strategy focused on water supply link, automatic transmission system of a fire engine's level by using radio communication network, and water bladder are used. In addition, general four-wheel-drive vehicles equipped with fire fighting tools such as motor pump, hose, nozzle, and water bladder should be deployed in fire stations around the temples. A fire suppression strategy using A-type ladders is also required.

• Proceedings of the KWS Conference
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• 2009.11a
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• pp.8-8
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• 2009

알루미늄 합금 Al 6082-T6는 최근에 개발되어 북유럽 등의 선진국에서는 그 뛰어난 해양 내식성과 우수한 강도로 인하여 해양구조물의 헬리데크(Helideck), 타워 갱웨이(Tower gangway), 알루미늄 피팅류(Aluminium fitting)등의 해양구조물과 플랫폼(Flatform), 알루미늄 래더(Aluminium ladder)등의 선박부품, 차량, 기계부품 분야에서 전 세계적으로 널리 사용되기 시작하였다. 그러나 전통적으로 용접금속의 기공은 결함으로 분류 되고, Rakesh Kumar 등의 논문에 따르면 용접 시 용접금속 내에 발생되어진 미세기공이 기계적 성질에 악영향을 미치는 것으로 보고되어졌다. 따라서 용접금속내의 발생하는 기공을 방지하는 용접공정의 개발이 반드시 필요하다. 본 연구의 목적은 Al 6082-T6 고속 MIG용접에서 기공방지를 위한 용접공정을 개발하는 것이다. Al 6082-T6의 7t 플레이트에 Al 5356의 와이어를 사용하여 아크길이 변경 및 용접속도를 60cpm과 120cpm으로 변경하여 실험하였고, 용접속도 120cpm의 고속 MIG용접에서 토치 진행각을 변경하여 실험을 진행하였다. 용접공정 파라메터 변경에 따른 기공율 측정은 이미지 분석 소프트웨어를 사용하여 정량적으로 분석하였다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.5
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• pp.183-196
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• 2022

Public transportation accessibility has been evaluated through minimum level of service for public transportation. However it is evaluated based operators rather than users. This study analyzed the users' accessibility(first-mile, last-mile) to public transportation using altteul transport card data. As a result of user's accessibility of public transportation, rural areas was lower than that in the urban areas. This study calssified type 1 and 2 based average approach time, and average approach time of Type 1 and 2 were more than average approach time of total area. We propsed an efficient introduction of autonomous public transportation on-demand service using delphi survey. As a result of delphi survey, experts agreed on 9 items regarding function, service item, route operation, approach distance, route mileage, punctuality.

• Journal of the Korea Society of Computer and Information
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• v.28 no.5
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• pp.17-28
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• 2023

Potholes that occur on paved roads can have fatal consequences for vehicles traveling at high speeds and may even lead to fatalities. While manual detection of potholes using human labor is commonly used to prevent pothole-related accidents, it is economically and temporally inefficient due to the exposure of workers on the road and the difficulty in predicting potholes in certain categories. Therefore, completely preventing potholes is nearly impossible, and even preventing their formation is limited due to the influence of ground conditions closely related to road environments. Additionally, labeling work guided by experts is required for dataset construction. Thus, in this paper, we utilized the Mean Teacher technique, one of the semi-supervised learning-based knowledge distillation methods, to achieve robust performance in pothole image classification even with limited labeled data. We demonstrated this using performance metrics and GradCAM, showing that when using semi-supervised learning, 15 pre-trained CNN models achieved an average accuracy of 90.41%, with a minimum of 2% and a maximum of 9% performance difference compared to supervised learning.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.2
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• pp.72-81
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• 2023

This research proposes a novel approach to tackle the challenge of categorizing unstructured customer complaints in the automotive industry. The goal is to identify potential vehicle defects based on the findings of our algorithm, which can assist automakers in mitigating significant losses and reputational damage caused by mass claims. To achieve this goal, our model uses the Word2Vec method to analyze large volumes of unstructured customer complaint data from the National Highway Traffic Safety Administration (NHTSA). By developing a score dictionary for eight pre-selected criteria, our algorithm can efficiently categorize complaints and detect potential vehicle defects. By calculating the score of each complaint, our algorithm can identify patterns and correlations that can indicate potential defects in the vehicle. One of the key benefits of this approach is its ability to handle a large volume of unstructured data, which can be challenging for traditional methods. By using machine learning techniques, we can extract meaningful insights from customer complaints, which can help automakers prioritize and address potential defects before they become widespread issues. In conclusion, this research provides a promising approach to categorize unstructured customer complaints in the automotive industry and identify potential vehicle defects. By leveraging the power of machine learning, we can help automakers improve the quality of their products and enhance customer satisfaction. Further studies can build upon this approach to explore other potential applications and expand its scope to other industries.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.593-599
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• 2023

There is risk of derailment due to various factors such as vehicle-track load imbalance in curved parts, so urban railways install and operate derailing prevent guard rails. The angle-type derailing prevent guard rail is composed of various parts including the guard angle. Even if derailment does not occur, various damages occur in the components, so continuous maintenance is required. Through the damage status analysis, the components of the angle-type derailing prevent guard rail with high damage frequency were classified, and conditions for the occurrence of various damages were investigated. In addition, a numerical analysis using a precise 3D numerical model was performed to analyze the cause of the damage analytically. In order to analytically simulate the derailment situation, the static ultimate load condition was applied, and the actual drawing of the angle-type derailing prevent guard rails, rails, and wheels was used for modeling. By analyzing the results of the damage status investigation and finite element analysis, we tried to investigate the damage of the components.