• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.3
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• pp.157-163
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• 2014

This paper demonstrates the benefit of using MOOS-IvP in the development of control system for Unmanned Underwater Vehicles(UUV). The demand for autonomy in UUVs has significantly increased due to the complexity in missions to be performed. Furthermore, the increased number of sensors and actuators that are interconnected through a network has introduced a need for a middleware platform for UUVs. In this context, MOOS-IvP, which is an open source software architecture, has been developed by several researchers from MIT, Oxford University, and NUWC. The MOOS software is a communication middleware based on the publish-subscribe architecture allowing each application to communicate through a MOOS database. The IvP Helm, which is one of the MOOS modules, publishes vehicle commands using multi-objective optimization in order to implement autonomous decision making. This paper explores the benefit of MOOS-IvP in the development of control software for UUVs by using a case study with an auto depth control system based on self-organizing fuzzy logic control. The simulation results show that the design and verification of UUV control software based on MOOS-IvP can be carried out quickly and efficiently thanks to the reuse of source codes, modular-based architecture, and the high level of scalability.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.5
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• pp.716-721
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• 2010

In this work we address the use of support vector machine (SVM) in the multi-class gas classification system. The objective is to classify single gases and their mixture with a semiconductor-type electronic nose. The SVM has some typical multi-class classification models; One vs. One (OVO) and One vs. All (OVA). However, studies on those models show weaknesses on calculation time, decision time and the reject region. We propose a hierarchical clustering method (HCM) based on the SVM for real-time gas mixture classification. Experimental results show that the proposed method has better performance than the typical multi-class systems based on the SVM, and that the proposed method can classify single gases and their mixture easily and fast in the embedded system compared with BP-MLP and Fuzzy ARTMAP.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.4
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• pp.315-323
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• 2013

Vessel Traffic Service (VTS) is being used at ports and in coastal areas of the world for preventing accidents and improving efficiency of the vessels at sea on the basis of "IMO RESOLUTION A.857 (20) on Guidelines for Vessel Traffic Services". Currently, VTS plays an important role in the prevention of maritime accidents, as ships are required to participate in the system. Ships are diversified and traffic situations in ports and coastal areas have become more complicated than before. The role of VTS operator (VTSO) has been enlarged because of these reasons, and VTSO is required to be clearly aware of maritime situations and take decisions in emergency situations. In this paper, we propose a prediction table to improve the work of VTSO through the Cognitive Work Analysis (CWA), which analyzes the VTS work very systematically. The required data were collected through interviews and observations of 14 VTSOs. The prediction tool supports decision-making in terms of a proactive measure for the prevention of maritime accidents.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.3
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• pp.441-457
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• 2011

In this study, the axiomatic design(AD) method is applied to construct the hierarchical structure of evaluation criteria and the AHP method is used to calculate the weights of criteria in order to develop the proposal evaluation index for the overseas weapon system purchasing projects. The common evaluation items as main categories are selected through the review of evaluation criteria from the previous works and projects, relevant regulations and defense policy, and the design matrix using fuzzy concept is established and evaluated by the expert group in each design phase to determine the independency, that is the satisfaction of decoupled or uncoupled design, for each criteria in the same hierarchy when they are derived from the main categories. The establishment of decoupled or uncoupled design matrix provides mutually exclusiveness of how small number of DPs can be accounted for FRs within the same hierarchy. The proposal evaluation index developed in this study will be used as a general proposal evaluation index for the overseas weapon system purchasing projects which there are no systematically established evaluation tools.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.3
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• pp.327-336
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• 2004

In distributed autonomous mobile robot system, each robot (predator or prey) must behave by itself according to its states and environments, and if necessary, must cooperate with other robots in order to carry out a given task. Therefore it is essential that each robot have both learning and evolution ability to adapt to dynamic environment. This paper proposes a pursuing system utilizing the artificial life concept where virtual robots emulate social behaviors of animals and insects and realize their group behaviors. Each robot contains sensors to perceive other robots in several directions and decides its behavior based on the information obtained by the sensors. In this paper, a neural network is used for behavior decision controller. The input of the neural network is decided by the existence of other robots and the distance to the other robots. The output determines the directions in which the robot moves. The connection weight values of this neural network are encoded as genes, and the fitness individuals are determined using a genetic algorithm. Here, the fitness values imply how much group behaviors fit adequately to the goal and can express group behaviors. The validity of the system is verified through simulation. Besides, in this paper, we could have observed the robots' emergent behaviors during simulation.

• Journal of the Korean Society of Propulsion Engineers
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• v.20 no.2
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• pp.56-66
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• 2016

Robustness is essential for model based FDI (Fault Detection and Isolation) and it is inevitable to have modeling errors and sensor signal noises during the process of FDI. This study suggests an improved method by applying NARX (Nonlinear Auto Regressive eXogenous) model and Kalman estimator in order to cope with problems caused by linear model errors and sensor signal noises in the process of fault diagnoses. Fault decision is made by the probability of the trend of gradually accumulated errors applying Fuzzy logic, which are robust to instantaneous sensor signal noises. Reliability of fault diagnosis is verified under various fault simulations.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.77-82
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• 2006

Automatic vessel collision-avoidance systems have been studied in the fields of artificial intelligence and navigation for decades. And to facilitate automatic collision-avoidance decision-making in two-vessel-encounter situation, several expert and fuzzy expert systems have been developed. However, none of them can negotiate with each other as seafarers usually do when they intend to make a more economic overall plan of collision avoidance in the COLREGS-COST-HIGH situations where collision avoidance following the International Regulations for Preventing Collisions at Sea(COLREGS) costs too much. Automatic Identification System(AIS) makes data communication between two vessels possible, and negotiation methods can be used to optimize vessel collision avoidance. In this paper, a negotiation framework is put forward to enable vessels to negotiate to optimize collision avoidance in the COLREGS-COST-HIGH situations at open sea. A vessel vector space is defined and therewith a cost model is put forward to evaluate the cost of collision-avoidance actions. Negotiations between a give-way vessel and a stand-on vessel and between two give-way vessels are considered respectively to reach overall low cost agreements. With the framework proposed in this paper, two vessels involved in a COLREGS-COST-HIGH situation can negotiate with each other to get a more economic overall plan of collision avoidance than that suggested by the traditional collision-avoidance expert systems.

• Industrial Engineering and Management Systems
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• v.11 no.1
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• pp.54-69
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• 2012

Chan and Qi (SCM 8/3 (2003) 209) developed an innovative measurement method that aggregates performance measures in a supply chain into an overall performance index. The method is useful and makes a significant contribution to supply chain management. Nevertheless, it can be cumbersome in computation due to its highly complex algorithmic fuzzy model. In aggregating the performance information, weights used by Chan and Qi-which aim to address the imprecision of human judgments-are incompatible with weights in additive models. Furthermore, the default assumption of linearity of its scoring procedure could lead to an inaccurate assessment of the overall performance. This paper addresses these limitations by developing an alternative measurement that takes care of the above. This research integrates three different approaches to multiple criteria decision analysis (MCDA)-the multiattribute value theory (MAVT), the swing weighting method and the eigenvector procedure-to develop a comprehensive assessment of supply chain performance. One case study is presented to demonstrate the measurement of the proposed method. The performance model used in the case study relies on the Supply Chain Operations Reference (SCOR) model level 1. With this measurement method, supply chain managers can easily benchmark the performance of the whole system, and then analyze the effectiveness and efficiency of the supply chain.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.3
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• pp.250-255
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• 2012

Face recognition has wide applications in security and surveillance systems as well as in robot vision and machine interfaces. Conventional challenges in face recognition include pose, illumination, and expression, and face recognition at a distance involves additional challenges because long-distance images are often degraded due to poor focusing and motion blurring. This study investigates the effectiveness of applying photon-counting linear discriminant analysis (Pc-LDA) to face recognition in harsh environments. A related technique, Fisher linear discriminant analysis, has been found to be optimal, but it often suffers from the singularity problem because the number of available training images is generally much smaller than the number of pixels. Pc-LDA, on the other hand, realizes the Fisher criterion in high-dimensional space without any dimensionality reduction. Therefore, it provides more invariant solutions to image recognition under distortion and degradation. Two decision rules are employed: one is based on Euclidean distance; the other, on normalized correlation. In the experiments, the asymptotic equivalence of the photon-counting method to the Fisher method is verified with simulated data. Degraded facial images are employed to demonstrate the robustness of the photon-counting classifier in harsh environments. Four types of blurring point spread functions are applied to the test images in order to simulate long-distance acquisition. The results are compared with those of conventional Eigen face and Fisher face methods. The results indicate that Pc-LDA is better than conventional facial recognition techniques.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 1998.10a
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• pp.263-269
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• 1998

The forecasting of container cargo volumes should be estimated correctly because it has a key roles on the establishment of port development planning, and the decision of port operating system. Container cargo volumes have a dynamic characteristics which was changed by effect of competitive ports. Accordingly forecasting was needed overall approach about competitive port's development, alternation and information. But, until now, traffic forecasting was not executed according to competitive situation, and that was accomplished at the point of unit port. Generally, considering the competition situation, simulation method was desirable at forecasting because system's scale was increased, and the influence power was intensified. In this paper, considering this situation, the objectives can be outlined as follows. 1) Structural model constructs by System dynamics method. 2) Structural simulation model develops according to modelling of competitive situation by expended SD method which included HEP(Hierarchical Fuzzy Process) And actually, effectiveness was verified according to proposed model to major port in northeast asia.