• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 2000년도 THE THIRD INTERNATIONAL CONFERENCE ON AGRICULTURAL MACHINERY ENGINEERING. V.II
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• pp.333-343
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• 2000

An automatic guidance system for combine was designed to harvest paddy rice by following a predetermined path. The automatic guidance system consisted of DGPS to locate position of combine, a gyro sensor system to measure heading angle, ultrasonic sensors to detect obstacles, a hydraulic system, microcomputer as a controller, and I/O interface system. Hydraulic cylinders and valves were installed to control movement of the combine. The heading angle and the position of the combine, and ultrasonic measurements from edge were used as the inputs of the controller. The operating position of hydraulic cylinder was determined as output of the controller. The automatic guidance system was evaluated at the 45-m straight path by changing the posture of the combine. The average RMS errors were 14.0 cm without offset and 15.0 cm with 1-m offset. The DGPS provided accurate position information within the limited error to guide the combine in the field. The results showed that the automatic guidance system could guide the combine autonomously in the paddy field when the posture of the combine was changed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권9호
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• pp.4606-4623
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• 2019

Nowadays modern cities develop in a very rapid speed. Buildings become larger than ever and the interior structures of the buildings are even more complex. This drives a high demand for precise and accurate indoor navigation systems. Although the existing commercially available 2D indoor navigation system can help users quickly find the best path to their destination, it does not intuitively guide users to their destination. In contrast, an indoor navigation system combined with augmented reality technology can efficiently guide the user to the destination in real time. Such practical applications still have various problems like position accuracy, position drift, and calculation delay, which causes errors in the navigation route and result in navigation failure. During the navigation process, the large computation load and frequent correction of the displayed paths can be a huge burden for the terminal device. Therefore, the navigation algorithm and navigation logic need to be improved in the practical applications. This paper proposes an improved navigation algorithm and navigation logic to solve the problems, creating a more accurate and effective augmented reality indoor navigation system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제15권1호
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• pp.12-19
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• 2015

In order to guide the robots move along a collision-free path efficiently and reach the goal position quickly in the unknown multi-obstacle environment, this paper presented the navigation problem of a wheel mobile robot based on proximity sensors by fuzzy logic controller. Then a genetic algorithm was applied to optimize the membership function of input and output variables and the rule base of the fuzzy controller. Here the environment is unknown for the robot and contains various types of obstacles. The robot should detect the surrounding information by its own sensors only. For the special condition of path deadlock problem, a wall following method named angle compensation method was also developed here. The simulation results showed a good performance for navigation problem of mobile robots.

• 한국멀티미디어학회논문지
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• 제20권2호
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• pp.344-351
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• 2017

In this paper, we propose the obstacle database management module for obstacle estimation and clustering. The proposed G-eye manager system can create customized walking route for blind people using the UI manager and verify the coordinates of the path. Especially, G-eye management system designed a regional information module. The regional information module can improve the loading speed of the obstacle data by classifying the local information by clustering the coordinates of the obstacle. In this paper, we evaluate the reliability of the walking route generated from the obstacle map. We obtain the coordinate value of the path avoiding the virtual obstacle from the proposed system and analyze the error rate of the path avoiding the obstacle according to the size of the obstacle. And we analyze the correlation between obstacle size and route by classifying virtual obstacles into sizes.

• 한국정보처리학회논문지
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• 제6권3호
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• pp.633-640
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• 1999

Reinforcement learning performs learning through interacting with trial-and-error in dynamic environment. Therefore, in dynamic environment, reinforcement learning method like Q-learning and TD(Temporal Difference)-learning are faster in learning than the conventional stochastic learning method. However, because many of the proposed reinforcement learning algorithms are given the reinforcement value only when the learning agent has reached its goal state, most of the reinforcement algorithms converge to the optimal solution too slowly. In this paper, we present COMREL(COMpressed REinforcement Learning) algorithm for finding the shortest path fast in a maze environment, select the candidate states that can guide the shortest path in compressed maze environment, and learn only the candidate states to find the shortest path. After comparing COMREL algorithm with the already existing Q-learning and Priortized Sweeping algorithm, we could see that the learning time shortened very much.

• 한국컴퓨터정보학회논문지
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• 제22권12호
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• pp.49-54
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• 2017

Pathfinding for pedestrians provided by various navigation programs is based on a shortest path search algorithm. There is no big difference in their guide results, which makes the path quality more important. Multiple criteria should be included in the search cost to calculate the path quality, which is called a multi-criteria pathfinding. In this paper we propose a user adaptive pathfinding algorithm in which the cost function for a multi-criteria pathfinding is defined as a weighted sum of multiple criteria and the weights are learned automatically by Perceptron learning. Weight learning is implemented in two ways: short-term weight learning that reflects weight changes in real time as the user moves and long-term weight learning that updates the weights by the average value of the entire path after completing the movement. We use the weight update method with momentum for long-term weight learning, so that learning speed is improved and the learned weight can be stabilized. The proposed method is implemented as an app and is applied to various movement situations. The results show that customized pathfinding based on user preference can be obtained.

• 대한교통학회지
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• 제28권6호
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• pp.99-108
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• 2010

최근 들어 기후변화가 국제적으로 최우선 의제로 급부상 하면서 유엔의 최우선 아젠다로 추진하게 되었다. 이에 따라 우리나라에서는 '범지구적 기후변화대응 노력에 동참하고 녹색성장을 통한 저탄소사회 구현, -Low Carbon, Green Growth-' 이란 비전을 국가기본계획으로 발표하였으며, 일환으로 전국 자전거도로 네트워크 구축을 추진하고 있다. 자전거도로 및 인프라 구축을 추진하고 있으나, 길안내를 위한 자전거 도로표지는 고려하고 있지 않은 상황이다. 본 연구에서는 자전거를 위한 안내표지 설치 방안에 대해 연구하였다. 도로표지는 운전자가 이를 인식하고 그 내용을 파악하며 정지 등의 행동을 취하기까지의 거리에 대해 자전거 및 운전자의 자세특성을 고려한 안내표지의 규격 및 설치위치에 대해 이론적 고찰을 하였으며, 그 결과에 따른 실험적 검증을 실시하였다. 자전거 운전자의 전방 시야각에 따른 설치높이를 변경하여 높이에 대해 실험을 실시하였다.

• 한국지능시스템학회논문지
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• 제15권4호
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• pp.425-430
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• 2005

많은 문제가 그래프로 모델링될 수 있고, 그래프 이론에 기반한 방법에 의해서 해결될 수 있다. 이 논문에서는 분산되고 중첩된 대사경로 네트워크들에 대해서 경로를 찾는 방법에 대해서 다룬다. 제안한 방법은 분산된 그래프를 통합하지 않은 채, 다중 에이전트의 협동작업을 통해서 경로를 찾는 방법이다. 각 그래프에는 해당 그래프를 책임지고 있는 에이전트가 하나씩 있어서, 해당 그래프에서 시작되는 경로검색을 주도하고, 다른 에이전트로부터 경로에 대한 정보 요청에 응답하도록 한다. 제안한 방법에서는 우선 전체 분산된 그래프에 대해서 뷰그래프라고 하는 추상화된 그래프를 형성하고, 이를 이용하여 경로를 찾기 위해 에이전트간에 어떤 방법으로 협력을 할지 알 수 있게 한다. 각 에이전트는 해당 그래프에 대한 최단경로 정보를 관리하고 있다. 어떤 에이전트가 해당 그래프의 어떤 노드에서 시작하는 경로를 찾으라는 요구를 받게 되면, 다른 에이전트로부터 정보를 받아서 목적지까지는 가는 경로를 찾게 된다.

• 디지털산업정보학회논문지
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• 제10권2호
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• pp.213-227
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• 2014

The Purpose of this research was to examine the influence of university students' self-leadership and career decision self-efficacy upon career preparation behavior. A total of 342 participants in 1th ~ 3th grades from universities in Seoul. Result from multiple regression analysis indicated the following. First, self-leadership and career decision self-efficacy had an impact on career preparation behavior. Second self-leadership had impact an career decision self-efficacy. Third, career decision self-efficacy had an impact on career preparation behavior. The result showed that there was significant interaction. Finally, the limitations of this study and suggestions for future research on career path preparation behavior were discussed. The implication of this study is that self-leadership and self-efficacy can the university students' career path preparation behavior. This research findings, theoretical and practical implications were suggested. Consequently it mean that the career guide program for university student. Therefore, effective counseling strategies to enhance career preparation behavior.

• Fashion, Industry and Education
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• 제16권2호
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• pp.1-16
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• 2018

This study explored men's choice of fashion as a college major and, subsequently, a non-traditional career path. Such investigation is important to gain a better understanding of the motives and processes of selecting a non-traditional college major and subsequent career path. This research consulted several theoretical frameworks to guide the development of research questions and help interpret the findings of the study. Specifically, our study builds upon Holland's trait theory (1982), Gottfredson's (1981) circumscription theory, Farmer's (1985) model of career motivation, and Simpson's (2005) typology of men's non-traditional career entry. A qualitative method was used to explore men's experiences of selecting fashion as an academic major in college and deciding to pursue a career in the traditionally female-dominated field. Following the analysis of 22 individual interviews with male upperclassmen majoring in fashion, three topical areas emerged and we proposed a model of male students' path to a non-traditional college major. The model explains male students' dynamics of entering a non-traditional college major, the role of personal and social factors in the decision process as well as the role of future career orientation when choosing to study fashion as an academic major.