• Journal of Navigation and Port Research
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• v.27 no.5
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• pp.493-498
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• 2003

Ship is being operated under a highly dynamic environments and many factors are related with ship's collision and those factors are interacting. So, An analysis on the ship's collision muses is very important to prepare countermeasures which will ensure the safe navigation. And the analysis confirmed that ship's collision is occurred most frequently and the muse is closely related with human factor. The main purpose of this study is to build a model of human factors in ship's collision muse using SD(System Dynamics} approach and to measure a effect which is risk control countermeasures of ship's collision. To achieve this aim, the structure analysis on the muses of ship's collision using FSM are performed, and the structure was changed by quantitative, qualitative factors and their feedback loops in casual map. This model was performed over 20 years(1993-2012) in a standard simulation model and 8 policy simulation models.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2744-2746
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• 2001

이 논문에서는 이동 로봇을 위하여 퍼지이론과 Dempster-Shafer 이론을 이용한 불확실한 환경에서의 센서기반 네비게이션 방법을 제안한다. 제안된 제어기는 장애물 회피 동작과 목적지 찾기 동작을 위한 2개의 행동 모듈로 구성되어 있다. 2개의 행동 모듈은 각각 퍼지 이론으로 학습되었고, 적절한 행동 선택 방법으로 선택되게끔 하였다. 견고한 퍼지 제어기를 가진 로봇이 실험 환경내에서 안전하게 움직이기 위하여 자동으로 지도를 구축(Map Building) 하도록 하였다. 이 실험에서 구성된 맵은 평면상의 격자를 중심으로 작성되었고 로봇의 센서에서 읽어들인 센서 값은 D-S 추론 이론을 이용하여 기존의 맵과 혼합되어진다. 즉, 로봇이 움직일때 마다 실험 환경내에서 새로운 정보를 읽어 들이고, 그 정보로 인하여 기존의 지도가 새로운 지도로 갱신되는 것이다. 이러한 작업을 거치면서 로봇은 장애물과 충돌없이 배회하는 것 뿐 아니라 설정된 목적지까지도 쉽게 찾아갈 수가 있다. 실험에 대한 안정성과 확신을 검증 받기 위하여 실제 로봇에 적용하기보다는 먼저 이동 로봇의 시뮬레이션으로 실험 해 보고자 한다.

• Journal of Mechanical Science and Technology
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• v.18 no.8
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• pp.1358-1367
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• 2004

As a part II of theis research, new local inspection planning strategy is proposed in this paper based on the proposed inspection feature extraction method. In the local inspection planning stage, each feature is decomposed into its constituent geometric elements for more effective inspection planning. The local inspection planning for the decomposed features are performed to determine: (1) the suitable number of measuring points, (2) their locations, and (3) the optimum probing paths to minimize measuring errors and times. The fuzzy set theory, the Hammersley's algorithm and the TSP method are applied for the local inspection planning. Also, a new collision checking algorithm is proposed for the probe and/or probe holder based on the Z-map concept. Finally, the results are simulated and analyzed to verify the effectiveness of the proposed methods.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.1-14
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• 2023

As markets and industries continue to evolve rapidly, technology opportunity discovery (TOD) has become critical to a firm's survival. From a common consensus that TOD based on a firm's capabilities is a valuable method for small and medium-sized enterprises (SMEs) and reduces the risk of failure in technology development, studies for TOD based on a firm's capabilities have been actively conducted. However, previous studies mainly focused on a firm's technological capabilities and rarely on business capabilities. Since discovered technologies can create market value when utilized in a firm's business, a firm's current business capabilities should be considered in discovering technology opportunities. In this context, this study proposes a TOD method that considers both a firm's business and technological capabilities. To this end, this study uses patent data, which represents the firm's technological capabilities, and trademark data, which represents the firm's business capabilities. The proposed method comprises four steps: 1) Constructing firm technology and business capability matrices using patent classification codes and trademark similarity group codes; 2) Transforming the capability matrices to preference matrices using the fuzzy function; 3) Identifying a target firm's candidate technology opportunities using the collaborative filtering algorithm; 4) Recommending technology opportunities using a portfolio map constructed based on technology similarity and applicability indices. A case study is conducted on a security firm to determine the validity of the proposed method. The proposed method can assist SMEs that face resource constraints in identifying technology opportunities. Further, it can be used by firms that do not possess patents since the proposed method uncovers technology opportunities based on business capabilities.

• Journal of the Korean Society of Industry Convergence
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• v.17 no.2
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• pp.42-53
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• 2014

Robust voice recognition (RVR) is essential for a robot to communicate with people. One of the main problems with RVR for robots is that robots inevitably real environment noises. The noise is captured with strong power by the microphones, because the noise sources are closed to the microphones. The signal-to-noise ratio of input voice becomes quite low. However, it is possible to estimate the noise by using information on the robot's own motions and postures, because a type of motion/gesture produces almost the same pattern of noise every time it is performed. In this paper, we propose an RVR system which can robustly recognize voice by adults and children in noisy environments. We evaluate the RVR system in a communication robot placed in a real noisy environment. Voice is captured using a wireless microphone. Navigation Strategy is shown Obstacle detection and local map, Design of Goal-seeking Behavior and Avoidance Behavior, Fuzzy Decision Maker and Lower level controller. The final hypothesis is selected based on posterior probability. We then select the task in the motion task library. In the motion control, we also integrate the obstacle avoidance control using ultrasonic sensors. Those are powerful for detecting obstacle with simple algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.233-238
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• 1993

In this paper, two diagnosis algorithms using the simple fuzzy, cognitive map (FCM) that is an useful qualitative model are proposed. The first basic algorithm is considered as a simple transition of Shiozaki's signed directed graph approach to FCM framework. And the second one is an extended version of the basic algorithm. In the extension, three important concepts, modified temporal associative memory (TAM) recall, temporal pattern matching algorithm and hierarchical decomposition are adopted. As the resultant diagnosis scheme takes short computation time, it can be used for on-line fault diagnosis of large scale and complex processes that conventional diagnosis methods cannot be applied. The diagnosis system can be trained by the basic algorithm and generates FCM model for every experienced process fault. In on-line application, the self-generated fault model FCM generates predicted pattern sequences, which are compared with observed pattern sequences to declare the origin of fault. In practical case, observed pattern sequences depend on transport time. So if predicted pattern sequences are different from observed ones, the time weighted FCM with transport delay can be used to generate predicted ones. The fault diagnosis procedure can be completed during the actual propagation since pattern sequences of tvo different faults do not coincide in general.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.2
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• pp.101-106
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• 2010

We propose an approach to estimate the real-time moving trajectory of an object in this paper. The object's position is obtained from the image data of a CCD camera, while a state estimator predicts the linear and angular velocities of the moving object. To overcome the uncertainties and noises residing in the input data, a Extended Kalman Filter(EKF) and neural networks are utilized cooperatively. Since the EKF needs to approximate a nonlinear system into a linear model in order to estimate the states, there still exist errors as well as uncertainties. To resolve this problem, in this approach the Kohonen networks, which have a high adaptability to the memory of the inputoutput relationship, are utilized for the nonlinear region. In addition to this, the Kohonen network, as a sort of neural network, can effectively adapt to the dynamic variations and become robust against noises. This approach is derived from the observation that the Kohonen network is a type of self-organized map and is spatially oriented, which makes it suitable for determining the trajectories of moving objects. The superiority of the proposed algorithm compared with the EKF is demonstrated through real experiments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.7
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• pp.1291-1300
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• 2008

In this paper, we propose a intelligent system to improve the accuracy of pattern recognition. The proposed intelligent system consist in SOFM, LVQ and FCM algorithm. We are confirmed the effectiveness of the proposed intelligent system through the several experiments that classify Fisher's Iris data and face image data that offered by ORL of Cambridge Univ. and EMG data. As the results of experiments, the proposed intelligent system has better accuracy of pattern recognition than general LVQ.

• Journal of the Korean Institute of Navigation
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• v.23 no.1
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• pp.75-84
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• 1999

Although many studies on modelling of port competitive situation have been conducted, both theoretical frame and methodology are still very weak. In this study, therefore, a new algorithm called ESD (Extensional System Dynamics) for the evaluation of port competition was presented, and applied to simulate port systems in northeast asia. The detailed objectives of this paper are to develop Unit fort Model by using SD(System Dynamics) method; to develop Competitive Port Model by ESD method; to perform sensitivity analysis by altering parameters, and to propose port development strategies. For these the algorithm for the evaluation of part's competition was developed in two steps. Firstly, SD method was adopted to develop the Unit Port models, and secondly HFP(Hierarchical Fuzzy Process) method was introduced to expand previous SD method. The proposed models were then developed and applied to the five ports - Pusan, Kobe, Yokohama, Kaoshiung, Keelung - with real data on each ports, and several findings were derived. Firstly, the extraction of factors for Unit Port was accomplished by consultation of experts such as research worker, professor, research fellows related to harbor, and expert group, and finally, five factor groups - location, facility, service, cargo volumes, and port charge - were obtained. Secondly, system's structure consisting of feedback loop was found easily by location of representative and detailed factors on keyword network of STGB map. Using these keyword network, feedback loop was found. Thirdly, for the target year of 2003, the simulation for Pusan port revealed that liner's number would be increased from 829 ships to 1,450 ships and container cargo volumes increased from 4.56 million TEU to 7.74 million TEU. It also revealed that because of increased liners and container cargo volumes, length of berth should be expanded from 2,162m to 4,729m. This berth expansion was resulted in the decrease of congested ship's number from 97 to 11. It was also found that port's charge had a fluctuation. Results of simulation for Kobe, Yokohama, Kaoshiung, Keelung in northeast asia were also acquired. Finally, the inter port competition models developed by ESB method were used to simulate container cargo volumes for Pusan port. The results revealed that under competitive situation container cargo volume was smaller than non-competitive situation, which means Pusan port is lack of competitive power to other ports. Developed models in this study were then applied to estimate change of container cargo volumes in competitive relation by altering several parameters. And, the results were found to be very helpful for port mangers who are in charge of planning of port development.