• Knowledge Management Research
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• v.12 no.4
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• pp.17-40
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• 2011

This study examines the differences of enacting models and influential causes of benefit-sharing practices between Korean automobile networks and the Japanese networks. The case study method is chosen for this research because only small numbers of supply networks adopt benefit-sharing practices. I employ semi-structured interviews with managers from four automobile manufacturers and eight of their suppliers in South Korea and Japan. I find that Japanese automobile networks have adopted a higher level of trust-demanding, with a higher level of value-creating models such as supplier development, joint-new-product development. Whereas, the Korean networks have adopted the lower trust demanding, also less profitable models such as supplier's suggestion and buyer's suggestion. In terms of work-related cultural values, I find that Japanese networks emphasized collectivism. Both buyers and suppliers in the Japanese networks are supposed to have common causes. In contrast, Korean networks emphasized individualism. Both buyers and suppliers of Korea generally do not identify that they are common group members with a common cause. I also find that a slight differences of the enacting models and the causes between foreign-owned networks and domestic-owned networks within each country. Foreign-owned networks have adopted lower trust demanding, also less profitable models. The findings demonstrate that the cultural values have a decisive influence on the adoption of benefit sharing models for the networks in Japan, and South Korea.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.6
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• pp.524-531
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• 2010

The automobile networks consist of the communication bus systems which become independent and heterogeneous each other. Most often, the CAN buses are implemented in a car in order to connect all the electronic control units in various ways. Thus, some gateways are necessary for exchanging the useful information between electronic control units on the buses. The automobile body networks group is divided into two kinds on a large scale, namely the low-speed bus and the high-speed bus. To interchange messages between the two, a CAN signal gateway is designed and implemented in a miniature scale. A network analyzer (called "Vehicle spy") and an oscilloscope monitor network situation to confirm the due operation of CAN signal gateway. The efficiency of the designed gateway is evaluated. The more message thread increased, the more efficiency decreased.

• The International Journal of Costume Culture
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• v.12 no.2
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• pp.129-140
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• 2009

In this study, the effect of innovativeness of external networks on the corporate innovativeness and innovation performance were explored based on web survey data collected from 230 manufacturing companies. Specifically, according to the manufacturers' business categories divided by the technology level, three groups such as advance technology (electronic/IT), mid- to high technology (automobile/machine), and low technology (textile/clothing) companies were investigated to find out which external network influences corporate innovativeness and innovation performance. In the result, textile/clothing companies were not different in company size, history, and innovation effort from advanced technology and mid- to high technology companies. Collectively, the innovativeness of external networks affected corporate innovativeness and innovation performance. In the result by a business category, innovativeness and innovation performance of textile/clothing companies were affected by the innovativeness of competitors, whereas automobile/machine companies in the mid- to high technology group were affected by suppliers. In addition, advanced technology (electronics/IT) were affected by buyers and competitors. These differences suggest that the way to use vertical networks toward upstream (e.g., suppliers) and downstream (e. g., buyers) as well as horizontal networks toward competitors can be different by the business category of manufacturers. The result would provide implications for the academia and the industry.

• Journal of the Economic Geographical Society of Korea
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• v.10 no.1
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• pp.1-18
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• 2007

This study examines the development direction of Ulsan automobile cluster and suggests strategic interventions, based on the possibility of system transformation in the open economic system. The spatial characteristics of global, national and local production and R&D networks were analyzed to investigate the conditions of Ulsan automobile cluster. And the agglomeration process of automobile industry and the capabilities accumulated in Ulsan were analyzed and alternative developmental path and policy suggestions were proposed.

• Journal of Satellite, Information and Communications
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• v.9 no.3
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• pp.33-40
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• 2014

One of the most important requirements for the Ethernet-based automobile is the reliability. In order to achieve this goal, we propose using the High-availability Seamless Redundancy (HSR) protocol (IEC 62439-3 clause 5) in these networks. The HSR protocol provides duplicated frame copies for each sent frame, which means that the destination node will receive at least one copy in case the second copy is lost due to a failure. In other words, there will be no network stoppage even if failure occurs. Moreover, the destination node will receive at least one frame copy with zero-recovery time (seamless) and it will not need to wait to receive the other copy if the first one is lost, which occurs it in the Ethernet standard, as a result of reconfiguration of the network paths. However, the main drawback of the HSR protocol is the unnecessary redundant traffic that is caused by the duplicated frames. Several solutions, including QR, VRing, RURT, and DVP, have already been proposed to improve the traffic performance of the HSR protocol. In this paper, we propose three automobile network topologies. each of which has pros and cons depending on the automobile requirements. Then we applied the HSR protocol with and without the QR and VRing approaches to each scenario. The comparison among these topologies depend on the traffic performance result for each of them. The QR and VRing approaches give a better traffic reduction percentage, ranging from 48% to 75% compared to the standard HSR protocol. Therefore they could limit the redundant traffic in automobile networks when the HSR protocol is used instead of the Ethernet network, which does not provide any seamless recovery if a failure occurs.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.11
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• pp.2119-2125
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• 1992

An air-fuel ratio control method is studied to keep the air-fuel ratio of the exhaust gas in the neighborhood of the stoichiometric air-fuel ratio to maximize the conversion efficiency of the three-way catalytic converter. Estimators, which estimate the air-fuel ratio of the exhaust gas, are proposed using neural networks to overcome the limit of the presently used bang-bang type exhaust gas oxygen sensor. Using these estimators, PI controller for air-fuel ratio control is designed and is experimented for an automobile engine. The proposed controller reduces the variation of air-fuel ratio of the exhaust gas from the stoichiometric air-fuel ratio by 50%-75% when compared to the existing controller.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.1
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• pp.40-48
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• 2018

This paper proposes a license-plate recognition algorithm for automobile black-box image which is obtained from the camera moving with the automobile. The algorithm intends to increase the overall recognition-rate of the license-plate by increasing the Korean character recognition-rate using multi-stage neural network for automobile black-box image where there are many movements of the camera and variations of light intensity. The proposed algorithm separately recognizes the vowel and consonant of Korean characters of automobile license-plate. First, the first-stage neural network recognizes the vowels, and the recognized vowels are classified as vertical-vowels('ㅏ','ㅓ') and horizontal-vowels('ㅗ','ㅜ'). Then the consonant is classified by the second-stage neural networks for each vowel group. The simulation for automobile license-plate recognition is performed for the image obtained by a real black-box system, and the simulation results show the proposed algorithm provides the higher recognition-rate than the existing algorithms using a neural network.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.164-164
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• 2000

This paper proposes a moving window technique that extracts lanes and vehicles using the images captured by a CCD camera equipped inside an automobile in real time. For the purpose, first of all the optimal size of moving window is determined based upon speed of the vehicle, road curvature, and camera parameters. Within the moving windows that are dynamically changing, lanes and vehicles are extracted, and the vehicles within the driving lanes are classified as obstacles. Assuming highway driving, there are two sorts of image-objects within the driving lanes: one is ground mark to show the limit speed or some information for driving, and the other is the vehicle as an obstacle. Using characteristics of three-dimension objects, a neural network can be trained to distinguish the vehicle from ground mark. When it is recognized as an obstacle, the distance from the camera to the front vehicle can be calculated with the aids of database that keeps the models of automobiles on the highway. The correctness of this measurement is verified through the experiments comparing with the radar and laser sensor data.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1107-1109
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• 1996

In this paper, we discuss the automatic recognition system of vehicle types and licence plate numbers using artificial neural networks, which will be used as vehicle identifier. We confine to expose the vehicle licence number for violating bus lane and stolen cars. Therefore, the vehicle height, width and distribution profile are used as the feature parameters of vehicle type. This system is composed of two parts: one is an image preprocessor of vehicle images and the other one is a pattern classifier by neural networks. The experimental results show that our method has good results for the recognition of vehicle types and numbers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3523-3543
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• 2022

Autonomous vehicles are gradually being regarded as the mainstream trend of future development of the automobile industry. Autonomous driving networks generate many intensive and delay-sensitive computing tasks. The storage space, computing power, and battery capacity of autonomous vehicle terminals cannot meet the resource requirements of the tasks. In this paper, we focus on the task scheduling problem of autonomous driving in software-defined edge networks. By analyzing the intensive and delay-sensitive computing tasks of autonomous vehicles, we propose an emotion model that is related to task urgency and changes with execution time and propose an optimal base station (BS) task scheduling (OBSTS) algorithm. Task sentiment is an important factor that changes with the length of time that computing tasks with different urgency levels remain in the queue. The algorithm uses task sentiment as a performance indicator to measure task scheduling. Experimental results show that the OBSTS algorithm can more effectively meet the intensive and delay-sensitive requirements of vehicle terminals for network resources and improve user service experience.