• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.6
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• pp.719-725
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• 2013

In this paper, we propose a local path planning method based on RANGER algorithm and autonomy manager for autonomous navigation of UGV in urban environment. LPP method is designed to generate the local path in sensing area by using lane and curb of pavement and autonomy manager is designed to make a decision which transit the status of LPP component to a proper status for current navigation environment. A field test is conducted with scenarios in real urban environment in which crossroad, crosswalk and pavement are included and the performance of proposed method is validated.

• Journal of Korea Multimedia Society
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• v.21 no.11
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• pp.1327-1332
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• 2018

An AGV(Automated Guided Vehicle) where is running on production automated system is related efficiency of production system similarly. On previous study proposed a path collision avoidance algorithms using shortest path of AGV. Running time about loading and unloading with shortest path of AGV is important factor to decide the production system efficiency. In this paper, we propose a method of shortest path and shortest time. Also propose the decision making method of collision avoidance position for setup a shortest runway for next command. To do verify the proposed method consist a simulation for AGV. Finally, we compare and analyse the proposed system between the existing system and show that our system can effectively the performance.

• IE interfaces
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• v.3 no.2
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• pp.53-62
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• 1990

본 연구는 컴퓨터에 의한 인쇄체 한글의 인식방법을 제안하고 있다. 일반적인 인식방법에서는 세선화과정 후의 이미지를 처리하고 있으나, 본 연구는 이 과정을 거치지 않고 원 이미지로부터 직업 패턴점들을 찾아내고, 이들을 이용하여 획을 결정하고 자모를 분리하였다. 문자 판별시에는 한글 의사 결정 나무(Decision-Tree)를 이용하여 자소를 분리하고 판별하였다. 본 연구는 자형에 관계없는 인식 방법을 제안 하였으므로 필기체 한글 인식에 기초를 제공하게 된다.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.109-122
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• 2023

As platforms become primary decision making tools, platforms for decision have been introduced to improve quality of decision results. Because, decision platforms applied augmented decision-making process which uses experiences and feedback of users. This process creates a variety of alternatives tailored for users' abilities and characteristics. However, platform users choose alternatives before considering significant quality factors based on securing decision quality. In real world, platform managers use an algorithm that distorts appropriate alternatives for their commercial benefits. For improving quality of decision-making, preceding researches approach trying to increase rational decision -making ability based on experiences and feedback. In order to overcome bounded rationality, users interact with the machine to approach the optional situation. Differentiated from previous studies, our study focused more on characteristics of users while they use decision platforms. This study investigated the impact of quality factors on decision-making using platforms, the dimensions of systematic factors and user characteristics. Systematic factors such as platform reliability, data quality, and user characteristics such as user abilities and biases were selected, and measuring variables which trust, satisfaction, and loyalty of decision platforms were selected. Based on these quality factors, a structural equation research model was created. A survey was conducted with 391 participants using a 7-point Likert scale. The hypothesis that quality factors affect trust was proved to be valid through path analysis of the structural equation model. The key findings indicate that platform reliability, data quality, user abilities, and biases affect the trust, satisfaction and loyalty. Among the quality factors, group bias of users affects significantly trust of decision platforms. We suggest that quality factors of decision platform consist of experience-based and feedback-based decision-making with the platform's network effect. Through this study, the theories of decision-making are empirically tested and the academic scope of platform-based decision-making has been further developed.

• Journal of Information Technology Applications and Management
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• v.14 no.4
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• pp.1-16
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• 2007

In the microcell- or picocell-based system the frequent movements of the mobile bring about excessive traffics into the networks. A mobile location estimation mechanism can facilitate both efficient resource allocation and better QoS provisioning through handoff optimization. Existing location estimation schemes consider only LOS model and have poor performance in presence of multi-path and shadowing. In this paper we study a novel scheme which can increase estimation accuracy by considering NLOS environment and other multiple decision parameters than the received signal strength.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.9
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• pp.891-897
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• 2010

This paper proposes a cooperative control algorithm for a dual-arms robot which is carrying an object to the desired location. When the dual-arms robot is carrying an object from the start to the goal point, the optimal path in terms of safety, energy, and time needs to be selected among the numerous possible paths. In order to quantify the carrying efficiency of dual-arms, DAMM (Dual Arm Manipulability Measure) has been defined and applied for the decision of the optimal path. The DAMM is defined as the intersection of the manipulability ellipsoids of the dual-arms, while the manipulability measure indicates a relationship between the joint velocity and the Cartesian velocity for each arm. The cost function for achieving the optimal path is defined as the summation of the distance to the goal and inverse of this DAMM, which aims to generate the efficient motion to the goal. It is confirmed that the optimal path planning keeps higher manipulability through the short distance path by using computer simulation. To show the effectiveness of this cooperative control algorithm experimentally, a 5-DOF dual-arm robot with distributed controllers for synchronization control has been developed and used for the experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.2805-2826
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• 2021

In most cases, the routing policy of networks shows a preference for a static one-to-one mapping of communication pairs to routing paths, which offers adversaries a great advantage to conduct thorough reconnaissance and organize an effective attack in a stress-free manner. With the evolution of network intelligence, some flexible and adaptive routing policies have already proposed to intensify the network defender to turn the situation. Routing mutation is an effective strategy that can invalidate the unvarying nature of routing information that attackers have collected from exploiting the static configuration of the network. However, three constraints execute press on routing mutation deployment in practical: insufficient route mutation space, expensive control costs, and incompatibility. To enhance the availability of route mutation, we propose an OpenFlow-based route mutation technique called Polymorphic Path Transferring (PPT), which adopts a physical and virtual path segment mixed construction technique to enlarge the routing path space for elevating the security of communication. Based on the Markov Decision Process, with considering flows distribution in the network, the PPT adopts an evolution routing path scheduling algorithm with a segment path update strategy, which relieves the press on the overhead of control and incompatibility. Our analysis demonstrates that PPT can secure data delivery in the worst network environment while countering sophisticated attacks in an evasion-free manner (e.g., advanced persistent threat). Case study and experiment results show its effectiveness in proactively defending against targeted attacks and its advantage compared with previous route mutation methods.

• Journal of Gifted/Talented Education
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• v.20 no.3
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• pp.921-946
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• 2010

The purpose of this study is to devise a model of career decision in the science-gifted by exploring factors of having influence upon career decision in the science-gifted undergraduates of our country, and by examining pattern and path of career decision. By suggesting a model of structure, which synthetically considered factors of parents (parental social support), school (stress of college life, adjustment to college life), and individual characteristics(problem solving ability, career decision-making self-efficacy, conviction for major selection)as for career decision in the science-gifted undergraduates through this study, the aim was to arrange the theoretical frame for career in the science-gifted undergraduates. The research subjects were 93(class of 2007~2009) students who completed education in 2002 and 2003 at the gifted education center affiliated with University, and 264 scholarship students(class of 2005-2008) by the President at home and abroad, who are receiving scholarship by being selected as a science scholarship student by the incumbent President. The measurement tools, which were used in this study for collecting data, are test of parental social support, test of problem-solving ability, test of stress in college life, test of adjustment to college life, test of efficacy in career decision, and test of having confidence in selecting a major. For statistical analysis of the collected data, SPSS Program and AMOS Program were used. As a result, the model showed a good fit to the present data in the science-gifted undergraduates, TLI=.928, CFI=.941, RMSEA=.059. It was confirmed to be a model that is accepted in the group of the science-gifted undergraduates. Also, hypotheses, which were established on the basis of a theoretical quest, could be known to have been all adopted except one path. The results of this study can be offered as basic data for developing program and implementing a system in order to broaden the width of understanding about career and to help the career decision in the science-gifted.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.4
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• pp.253-265
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• 2016

We propose an obstacle classification method using multi-decision factors and decision sections based on Single 2D LiDAR. The existing obstacle classification method based on single 2D LiDAR has two specific advantages: accuracy and decreased calculation time. However, it was difficult to classify obstacle type, and therefore accurate path planning was not possible. To overcome this problem, a method of classifying obstacle type based on width data was proposed. However, width data was not sufficient to enable accurate obstacle classification. The proposed algorithm of this paper involves the comparison between decision factor and decision section to classify obstacle type. Decision factor and decision section was determined using width, standard deviation of distance, average normalized intensity, and standard deviation of normalized intensity data. Experiments using a real autonomous vehicle in a real environment showed that calculation time decreased in comparison with 2D LiDAR-based method, thus demonstrating the possibility of obstacle type classification using single 2D LiDAR.

• Journal of the Korea Society of Computer and Information
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• v.9 no.4 s.32
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• pp.203-214
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• 2004

This paper presents a practical application of possibilistic programming in a information system projects planning model. The estimate of the parameters of the model is often a problematic task for the decision maker(DM), Who has imprecise information or express his considerations subjectively. In this case. possibilistic decision making models can provide an important aspect in handling practical decision making problems. We suggest CPM(Critical Path Method) applying possibilistic programming. CPM is an approach to planning and coordinating large projects by directing managerial focus to the project's most critical aspects and providing completion time of project and beginning time of each activity. This model is an aid in the control of considering aspiration levels by the DM, the fuzziness of decision making, and computational efficiency. The problem is solved by using GINO computer package and the best compromised solution is found.