• 정보처리학회논문지C
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• 제16C권2호
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• pp.223-228
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• 2009

무선 애드-혹 네트워크와 유선 네트워크를 연동하는 하이브리드 애드-혹 네트워크에서 효율적인 서비스 검색 기법은 중요하다. 본 논문에서는 무선 애드-혹 네트워크를 인터넷으로 확장한 하이브리드 애드-혹 네트워크를 위해 중복을 허용하는 다중 경로 소스 라우팅 프로토콜을 사용하는 효율적인 크로스-레이어 서비스 검색 기법을 제안한다. 이 기법은 다중 경로 소스 라우팅 프로토콜의 장점뿐만 아니라 크로스-레이어 서비스 검색 기법의 장점을 동시에 갖는 기법이다. 서비스와 경로 검색이 동시에 이루어지는 크로스-레이어 서비스 검색 기법이 서비스 검색 후 해당 경로를 다시 검색하여 서비스를 제공받는 기존 기법보다 적은 오버헤드를 가진다는 것은 직관적으로 이해할 수 있으므로, 본 시뮬레이션을 통해서는 이 기법이 각 노드에서 다중 라우팅 경로를 유지함으로써 경로 단절시 보다 빠른 라우팅 복구가 가능하며, 다중 경로의 수를 제한하고 링크/노드 중복을 허용하는 다중 경로를 유지하도록 함으로써 라우팅 오버헤드를 줄일 수 있음으로 보인다.

• 방송공학회논문지
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• 제13권2호
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• pp.245-250
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• 2008

효율적인 서비스 검색 기법은 무선 애드-혹 네트워크의 유용성을 위해 중요한 특성이다. 무선 애드-혹 네트워크는 어떤 기존의 네트워크 하부구조 또는 중앙 관리 체계의 도움 없이 무선 이동 노드들만으로 구성되는 임시 네트워크이다. 본 논문에서는 무선 애드-혹 네트워크를 위해 중복을 허용하는 다중 경로 라우팅 프로토콜을 사용하는 효율적인 서비스 검색 기법을 제안한다. 이 기법은 다중 경로 소스 라우팅 프로토콜의 장점뿐만 아니라 크로스-레이서 서비스 검색의 장점 역시 갖는다. 시뮬레이션을 통해서 이 기법이 각 노드에서 다중 라우팅 경로를 유지함으로써 경로 단절시 보다 빠른 라우팅 복구가 가능하며, 다중 경로의 수를 제한하고 링크/노드 중복을 허용하는 다중 경로를 유지하도록 함으로써 라우팅 유지 오버헤드를 줄인다는 것을 보인다.

• 자동차안전학회지
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• 제3권2호
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• pp.28-33
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• 2011

This paper presents driving path estimation algorithm for adaptive cruise control system and advanced emergency braking system using multi-sensor fusion. Through data collection, yaw rate filtering based road curvature and vision sensor road curvature characteristics are analyzed. Yaw rate filtering based road curvature and vision sensor road curvature are fused into the one curvature by weighting factor which are considering characteristics of each curvature data. The proposed driving path estimation algorithm has been investigated via simulation performed on a vehicle package Carsim and Matlab/Simulink. It has been shown via simulation that the proposed driving path estimation algorithm improves primary target detection rate.

• Journal of Electrical Engineering and Technology
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• 제12권2호
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• pp.918-925
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• 2017

This paper presents a path planning problem for multi-robot system in the environment with dynamic obstacles. In order to guide the robots move along a collision-free path efficiently and reach the goal position quickly, a navigation method based on fuzzy logic controllers has been developed by using proximity sensors. There are two kinds of fuzzy controllers developed in this work, one is used for obstacle avoidance and the other is used for orientation to the target. Both static and dynamic obstacles are included in the environment and the dynamic obstacles are defined with no type of restriction of direction and velocity. Here, the environment is unknown for all the robots and the robots should detect the surrounding information only by the sensors installed on their bodies. The simulation results show that the proposed method has a positive effectiveness for the path planning problem.

• 한국정밀공학회지
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• 제26권7호
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• pp.73-80
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• 2009

This paper describes a path planning algorithm, which is the minimal turning path based on the shape and size of the cell to clean up the whole area with two cleaning robots. Our method divides the whole cleaning area with each cell by cellular decomposition, and then provides some path plans among of the robots to reduce the rate of energy consumption and cleaning time of it. In addition we suggest how to plan between the robots especially when they are cleaning in the same cell. Finally simulation results demonstrate the effectiveness of the algorithm in an unknown area with multiple robots. And then we compare the performance index of two algorithms such as total of turn, total of time.

• 유체기계공업학회:학술대회논문집
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• 유체기계공업학회 1999년도 유체기계 연구개발 발표회 논문집
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• pp.114-117
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• 1999

Five-path ultrasonic flowmeters (200 and 300 mm diameters) were tested to obtain it's characteristics in a water flow standard system. A five-path ultrasonic flowmeter was installed after various pipe fittings (elbow, valve, tee) or a pump. The distance between flow disturbance source and a flowmeter was main experimental parameter. Without a flow conditioner, a five-path ultrasonic flowmeter shows good characteristics as the distance between flow disturbance source and a flowmeter is longer than 10 diameter of a flowmeter.

• 반도체디스플레이기술학회지
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• 제17권1호
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• pp.88-92
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• 2018

Currently drone industry has become one of the fast growing markets and the technology for unmanned aerial vehicles are expected to continue to develop at a rapid rate. Especially small unmanned aerial vehicle systems have been designed and utilized for the various field with their own specific purposes. In these fields the path planning problem to find the shortest path between two oriented points is important. In this paper we introduce a path planning strategy for an autonomous flight of unmanned aerial vehicles through reinforcement learning with self-positioning technique. We perform Q-learning algorithm, a kind of reinforcement learning algorithm. At the same time, multi sensors of acceleraion sensor, gyro sensor, and magnetic are used to estimate the position. For the functional evaluation, the proposed method was simulated with virtual UAV environment and visualized the results. The flight history was based on a PX4 based drones system equipped with a smartphone.

• 한국통신학회논문지
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• 제29권5B호
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• pp.508-519
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• 2004

이 논문에서는 MPLS를 사용한 인터넷 트래픽 엔지니어링에 사용될 수 있는 다중경로 한계조건 기반 라우팅 알고리즘을 제안한다. 기존에 사용되던 한계조건 기반 최단경로 라우팅 알고리즘은 트래픽 엔지니어링의 중요한 요소 중에 하나인 대역폭 한계조건이 큰 간을 가지는 경우에는 조건을 만족하는 경로를 찾지 못할 확률이 높아진다. 제안된 다중경로 알고리즘은 대역폭 한계조건을 만족하는 하나의 경로를 찾을 수 없는 경우, 대역폭 조건을 여러 개의 작은 값으로 나누어 각각의 작은 대역폭 한계조건에 대해 다중경로를 찾는 알고리즘이다. 시뮬레이션을 통하여 제안한 알고리즘을 사용할 경우 주어진 네트웍 상황과 대역폭 한계 조건에서 더 높은 경로설정 성공확률을 나타내며, 네트웍 자원 이용률도 개선되는 것을 보였다.

• Nuclear Engineering and Technology
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• 제54권10호
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• pp.3604-3613
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• 2022

The Physical Protection System (PPS) plays an important role and must effectively deal with various adversary attacks in nuclear security. In specific single adversary path scenarios, we can calculate the PPS effectiveness by EASI (Estimated Adversary Sequence Interruption) through Probability of Interruption (P_I) calculation. EASI uses a single value of the probability of detection (P_D) and the probability of alarm communications (P_C) in the PPS. In this study, we develop a multi-path analysis code based on EASI to evaluate the effectiveness of PPS. Our quantification method for P_I considers the variability and uncertainty of P_D and P_C value by Monte Carlo simulation. We converted the 2-D scheme of the nuclear facility into an Adversary Sequence Diagram (ASD). We used ASD to find the adversary path with the lowest probability of interruption as the most vulnerable paths (MVP). We examined a hypothetical facility (Hypothetical National Nuclear Research Facility - HNNRF) to confirm our code compared with EASI. The results show that implementing the variability extension can estimate the P_I value and its associated uncertainty. The multi-path analysis code allows the analyst to make it easier to assess PPS with more extensive facilities with more complex adversary paths. However, the variability of the P_D value in each protection element allows a significant decrease in the PI value. The possibility of this decrease needs to be an important concern for PPS designers to determine the P_D value correctly or set a higher standard for PPS performance that remains reliable.

• 품질경영학회지
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• 제47권4호
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• pp.701-711
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• 2019

Purpose: The problem of optimizing redundancy allocation in multi-level systems is considered when each item in a multi-level system has alternative items with the same function. The number of redundancy of multi-level system is allocated to maximize the reliability of the system under path set and cost limitation constraints. Methods: Based on cost limitation and path set constraints, a mathematical model is established to maximize system reliability. Particle swarm optimization is employed for redundant allocation and verified by numerical experiments. Results: Comparing the particle swarm optimization method and the memetic algorithm for the 3 and 4 level systems, the particle swarm optimization method showed better performance for solution quality and search time. Particularly, the particle swarm optimization showed much less than the memetic algorithm for variation of results. Conclusion: The proposed particle swarm optimization considerably shortens the time to search for a feasible solution in MRAP with path set constraints. PS optimization is expected to reduce search time and propose the better solution for various problems related to MRAP.