• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.563-566
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• 2006

In this paper, we studied about AGVs modeling and material handling automation simulation using a virtual AGV. The proposed virtual AGV model that operates independently each other is based on a real AGV. Continuous straight-line and workstation model using vector drawing method that could easily, rapidly work system modeling are suggested. Centralized traffic control, which could collision avoidance in intersection and should not stop AGV as possible, and algorithm for detour routing which performs when another AGV is working in pre-routed path are proposed. The traffic control and the algorithm have been proved efficiently by simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2337-2341
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• 2005

This paper presents the target detection method using Support Vector Machines(SVMs) and the navigation system using behavior-based fuzzy controller. SVM is a machine-learning method based on the principle of structural risk minimization, which performs well when applied to data outside the training set. We formulate detection of target objects as a supervised-learning problem and apply SVM to detect at each location in the image whether a target object is present or not. The behavior-based fuzzy controller is implemented as an individual priority behavior: the highest level behavior is target-seeking, the middle level behavior is obstacle-avoidance, the lowest level is an emergency behavior. We have implemented and tested the proposed method in our mobile robot "Pioneer2-AT". Comparing with a neural-network based detection method, a SVM illustrate the excellence of the proposed method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.11
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• pp.1917-1924
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• 2003

This paper proposes a roughing path generation method fer machining impeller with 5-axis machining center. Traditional researches are focus on finishing for machining impeller. To achieve efficient machining, roughing method must be studied. The proposed method consists two steps : One is to select optimal tool size and tool attitude by dividing cutting area into two regions to reduce cutting time. The regions are automatically divided by character point on the geometry of impeller blade. After dividing, the tool of the optimal size is selected for each divided region. The other is avoidance of tool interference. Tool interference in cutting areas is avoided by checking the distance between tool axis vector and ruling line on blade surface or approximated plan between ruling line. Using this method, the cutting time is reduced efficiently.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.3010-3012
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• 2000

In this paper. we suggest a vector fitness strategy for obstacle avoidance of autonomous mobile robot with genetic algorithm. Ordinary genetic algorithms provide not such a viable solution for autonomous running in a variant environment. because of the difficulty in fitness evaluation in real time. We show that the suggested method is efficient for the problem of autonomous mobile robot. Its control function evolves to adapt the varying environment. The experiment is done using the real mobile robot 'Khepera' with which we use a tournament genetic algorithm model with the Vectored Fitness Genetic Strategy.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.1079-1081
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• 2011

컨테이너터미널 장치장 내 교차로에서 무인 YT(Yard Tractor)간 충돌방지를 위하여 RFID(Radio Frequency Identification) 태그와 ad-hoc 네트워크를 이용한 교차로 충돌방지 알고리즘을 제안한다. 또한 ad-hoc 네트워크 라우팅 프로토콜은 장치장 교차로에서 충돌방지를 위한 YT 간 통신성능을 결정하는 중요한 요소로써, 장치장 교차로 환경과 YT의 이동성을 고려하여 프로토콜을 결정해야 한다. 따라서 RFID 태그를 이용한 YT 위치정보와 AODV(Ad hoc On demand Distance Vector) 방식의 Hello 메시지를 이용해서 충돌방지를 위한 ad-hoc 네트워크 라우팅 프로토콜을 제안한다.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.4
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• pp.8-15
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• 2011

This paper proposes a real-time navigation algorithm which integrates the artificial potential field (APF) for an unmanned vehicle in the unknown environment. This approach uses repulsive potential function around the obstacles to force the vehicle away and an attractive potential function around the goal to attract the vehicle. In this research, laser range finder is used as range sensor. An obstacle detected by the sensor creates repulsive vector. Differential global positioning system (DGPS) and digital compass are used to measure the current vehicle position and orientation. The measured vehicle position is also used to create attractive vector. This paper proposes a new concept of potential field based navigation which controls unmanned vehicle's speed and steering. The magnitude of repulsive force based on the proposed algorithm is designed not to be over the magnitude of attractive force while the magnitude is increased linearly as being closer to obstacle. Consequently, the vehicle experiences a generalized force toward the negative gradient of the total potential. This force drives the vehicle downhill towards its goal configuration until the vehicle reaches minimum potential and it stops. The effectiveness of the proposed APF for unmanned vehicle is verified through simulation and experiment.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.4
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• pp.629-635
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• 2022

Cyber threats are also increasing with recent social changes and the development of ICT technology. Malicious codes used in cyber threats are becoming more advanced and intelligent, such as analysis environment avoidance technology, concealment, and fileless distribution, to make analysis difficult. Machine learning technology is being used to effectively analyze these malicious codes, but a lot of effort is needed to increase the accuracy of classification. In this paper, we propose a malicious code detection technology based on API call interval characteristics to improve the classification performance of machine learning. The proposed technology uses API call characteristics for each section and entropy of binary to separate characteristic factors into sections based on the extraction malicious code and API call order of normal binary. It was verified that malicious code can be well analyzed using the support vector machine (SVM) algorithm for the extracted characteristic factors.

• Korean Journal of Veterinary Research
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• v.46 no.1
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• pp.13-19
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• 2006

Generally known psittacosis or ornithosis is a disease of birds caused by the bacterium Chlamydia psittaci. Humans are accidential hosts and are most commonly infected from avian sources. It raises hepatitis or neurosis. As major outer membrane protein (MOMP) of Chlamydia psittaci has been known to play a role in the avoidance of host immune defenses, research on developing a Chlamydia vaccine has focused on the MOMP. In this study, the gene encoding the major outer membrane protein (MOMP) of the Chlamydia psittaci strain 6BC was cloned and expressed in Escherichia coli strain M-15. The recombinant DNA was cloned by fusion prokaryotic expression vector pQE30-GFPII. Expression of the recombinant protein was performed in E. coli and was induced by IPTG. The size of expressed recombinant protein is 74.220 kDa (MOMP, 43.260 kDa; GFP expression region, 30 kDa; $6{\times}His$ tag, 960Da). This protein was purified by using his-tagging-inclusion body. Recombinant protein was reconfirmed through ELISA test and western blot with antibody against pQE30-GFPII. It will be useful antibody development.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2360-2362
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• 1998

This paper presents a new collison-free trajectory problem for SCARA robot manipulator. we use artificial potential field for collison detection and avoidance. The potential function is typically defined as the sum of attractive potential pulling the robot toward the goal configuration and a repulsive potential pushing the robot away from the obstacles. In here, end-effector of manipulator is represented as a particle in configuration space and moving obstacles is simply represented, too. we consider not fixed obstacle but moving obstacle in random. So, we propose new distance function of artificial potential field with moving obstacle for SCARA robot. At every sampling time, the artificial potential field is update and the force driving manipulator is derived from the gradient vector of artificial potential field. To real-time path planning, we apply very simple modeling to obstacle. Some simulation results show the effectiveness of the proposed approach.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.12
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• pp.981-988
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• 2021

This paper presents a decentralized guidance algorithm for swarm flight of fixed-wing UAVs (Unmanned Aerial Vehicles). Considering swarm flight missions, we assume four representative swarm tasks: gathering, loitering, waypoint/path following, and individual task. Those tasks require several distinct maneuvers such as path following, flocking, and collision avoidance. In order to deal with the required maneuvers, this paper proposes an integrated guidance algorithm based on vector field, augmented Cucker-Smale model, and potential field methods. Integrated guidance command is synthesized with heuristic weights designed for each guidance method. The proposed algorithm is verified through flight tests using up to 19 small fixed-wing UAVs.