• Journal of Auto-vehicle Safety Association
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• v.4 no.2
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• pp.32-36
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• 2012

The Automatic unmanned target object carrying system (AUTOCS) is developed for testing road vehicle radar and vision sensor. It is important for the target to reflect the realistic target characteristics when developing ASV or ADAS products. The AUTOCS is developed to move the pedestrian or motorcycle target for desired speed and position. The AUTOCS is designed that only payload target which is a manikin or a motorcycle is detected by the sensor not the AUTOCS itself. In order for the AUTOCS to have low exposure to radar, the AUTOCS is stealthy shaped to have low RCS(Radar Cross Section). For deceiving vision sensor, the AUTOCS has a specially designed pattern on outside skin which resembles the asphalt pattern. The AUTOCS has three driving modes which are remote control, path following and replay. The AUTOCS V.1 is tested to verify the radar detect characteristics, and the AUTOCS successfully demonstrated that it is not detected by a car radar. The result is presented in this paper.

• Journal of the Korean Society of Industry Convergence
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• v.19 no.1
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• pp.42-49
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• 2016

This study proposes a non-contact inspective technology based robot vision system for Faulty Inspection of welding States and Parts Shape. The maine focus is real time implementation of the machining parts' automatic inspection by the robotic moving. For this purpose, the automatic test instrument inspects the precision components designator the vision system. pattern Recognition Technologies and Precision Components for vision inspection technology and precision machining of precision parts including the status and appearance distinguish between good and bad. To perform a realization of a real-time automation integration system for the precision parts of manufacturing process, it is designed a robot vision system for the integrated system controller and verified the reliability through experiments. The main contents of this paper, the robot vision technology for noncontact inspection of precision components and machinery parts is useful technology for FA.

• Journal of the Korean Institute of Gas
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• v.2 no.1
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• pp.53-58
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• 1998

By knowledge-based approach, the SDG(Signed Directed Graph) is automatically synthesized, which is commonly used to represent the causal effects between process variables. Automatic synthesis of SDG is progressed by two steps : (1)inference step uses knowledge base and (2)verification step uses Loop-Verifier. First, Topology and Knowledge Base are constructed by using the information on equipment. And then, Primary-SDG is synthesized by Character Pattern Matching between Variable-Relation-Representation generated by using Topology and Variable-Tendency-Data contained in Knowledge Base. Finally, a modified SDG is made after the Primary-SDG is verified by Loop-Verifier.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4310-4330
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• 2020

With the continuous emergence of new applications and cyberattacks and their frequent updates, the need for automatic protocol reverse engineering is gaining recognition. Although several methods for automatic protocol reverse engineering have been proposed, each method still faces major limitations in extracting clear specifications and in its universal application. In order to overcome such limitations, we propose an automatic protocol reverse engineering method using a two-pathway model based on a contiguous sequential pattern (CSP) algorithm. By using this model, the method can infer both command-oriented protocols and non-command-oriented protocols clearly and in detail. The proposed method infers all the key elements of the protocol, which are syntax, semantics, and finite state machine (FSM), and extracts clear syntax by defining fine-grained field types and three types of format: field format, message format, and flow format. We evaluated the efficacy of the proposed method over two non-command-oriented protocols and three command-oriented protocols: the former are HTTP and DNS, and the latter are FTP, SMTP, and POP3. The experimental results show that this method can reverse engineer with high coverage and correctness rates, more than 98.5% and 99.1% respectively, and be general for both command-oriented and non-command-oriented protocols.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.04a
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• pp.381-386
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• 2002

In this paper, we have proposed a new approach to the design of robot vision system to develop the technology for the automatic test and assembling of precision mechanical and electronic parts for the factory automation. In order to perform real time implementation of the automatic assembling tasks in the complex processes, we have developed an intelligent control algorithm based-on neural networks control theory to enhance the precise motion control. Implementing of the automatic test tasks has been performed by the real-time vision algorithm based-on TMS320C31 DSPs. It distinguishes correctly the difference between the acceptable and unacceptable defective item through pattern recognition of parts by the developed vision algorithm. Finally, the performance of proposed robot vision system has been illustrated by experiment for the similar model of fifth cell among the twelve cell for automatic test and assembling in S company.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.78-80
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• 2005

The pattern recognition of automobile and parking line for the automatic car parking system was processed based on statistical method for reducing the processing time. The command of driving for parking at the vacant parking lot was transmitted from processor to motor driven actuator using direct sequence spread spectrum communication, which enables the multiple transmission in CAN(controller area network). The test-bed which has CCD camera, processor, radio transceiver and FPGA was implemented and demonstrated to be operated well.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.04a
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• pp.217-222
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• 2001

In this paper, we have proposed a new approach to the design of robot vision system to develop the technology for the automatic test and assembling of precision mechanical and electronic parts for the factory automation. In order to perform real time implementation of the automatic assembling tasks in the complex processes, we have developed an intelligent control algorithm based-on neural networks control theory to enhance the precise motion control. Implementing of the automatic test tasks has been performed by the real-time vision algorithm based-on TMS320C31 DSPs. It distinguishes correctly the difference between the acceptable and unacceptable defective item through pattern recognition of parts by the developed vision algorithm. Finally, the performance of proposed robot vision system has been illustrated by experiment for the similar model of fifth cell among the twelve cell for automatic test and assembling in S company.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.8
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• pp.1787-1798
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• 1995

Monitoring and diagnosis of the operating machine mean evaluating the condition of a machine such as the detection of the defects and the prediction of the time to failure in the machine elements, while it is running. In this study, a technique of automatic diagnosis using probability concept is studied and the analyses of the pattern comparison are introduced. An expert system, which is able to analyze the automatic identification of the multiple defects in the ball bearings, is also developed. Finally, to confirm the effectiveness of the programmed algorithms, some tests were made with specimens of the ball bearings involving the multiple defects. The proposed system reasonably predicts the defects.

• Journal of Power System Engineering
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• v.5 no.2
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• pp.93-99
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• 2001

This paper presents the automatic recognition system for car number plate. In our country, two types of number plate pattern is used. The one is old type of number plate, the other is new type of number plate. To recognize both new and old type number plates, the system must have flexibility. Therefore, in this paper, automatic recognition system is developed by use of the neural network for good adaptation, good generalization, and modulation. And because the number plate is made of three codes, the multi neural network consists of three networks. Neural network is teamed by GDR(Generalized Delta learning Rule) and it is verified the effectiveness of the method through experimental results.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.182-187
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• 2000

In this paper, we have proposed a new approach to the design of robot vision system to develop the technology for the automatic test and assembling of precision mechanical and electronic parts for the factory automation. In order to perform real time implementation of the automatic assembling tasks in the complex processes, we have developed an intelligent control algorithm based-on neural networks control theory to enhance the precise motion control. Implementing of the automatic test tasks has been performed by the real-time vision algorithm based-on TMS320C31 DSPs. It distinguishes correctly the difference between the acceptable and unacceptable defective item through pattern recognition of parts by the developed vision algorithm. Finally, the performance of proposed robot vision system has been illustrated by experiment for the similar model of fifth cell among the twelve cell for similar model of fifth cell among the twelve cell for automatic test and assemblig in S company.