• Journal of the Society of Naval Architects of Korea
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• v.51 no.6
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• pp.480-488
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• 2014

Vortex shedding which is the dominant feature of body wakes and of direct relevance to practical engineering problems, has been intensively studied for flows past a circular cylinder. In contrast, vortex shedding from a hydrofoil trailing edge has been studied to much less extent despite numerous practical applications. The physics of the problem is still poorly understood. The present study deals with $K{\acute{a}}rm{\acute{a}}n$ vortex shedding from a truncated trailing-edge hydrofoil in relatively high Reynolds number flows. The objectives of this paper are twofold. First, we aim to simulate unsteady turbulent flows past a two dimensional hydrofoil through a hybrid particle-mesh method and penalization method. The vortex-in-cell (VIC) method offers a highly efficient particle-mesh algorithm that combines Lagrangian and Eulerian schemes, and the penalization method enables to enforce body boundary conditions by adding a penalty term to the momentum equation. The second purpose is to investigate shedding frequencies of vortices behind a NACA 0009 hydrofoil operating at a zero angle of attack.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.483-487
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• 2005

We introduce a new architecture of hetero-hybridized feed-forward neural networks composed of fuzzy set-based polynomial neural networks (FSPNN) and polynomial neural networks (PM) that are based on a genetically optimized multi-layer perceptron and develop their comprehensive design methodology involving mechanisms of genetic optimization and Information Granulation. The construction of Information Granulation based HFSPNN (IG-HFSPNN) exploits fundamental technologies of Computational Intelligence(Cl), namely fuzzy sets, neural networks, and genetic algorithms(GAs) and Information Granulation. The architecture of the resulting genetically optimized Information Granulation based HFSPNN (namely IG-gHFSPNN) results from a synergistic usage of the hybrid system generated by combining new fuzzy set based polynomial neurons (FPNs)-based Fuzzy Neural Networks(PM) with polynomial neurons (PNs)-based Polynomial Neural Networks(PM). The design of the conventional genetically optimized HFPNN exploits the extended Group Method of Data Handling(GMDH) with some essential parameters of the network being tuned by using Genetie Algorithms throughout the overall development process. However, the new proposed IG-HFSPNN adopts a new method called as Information Granulation to deal with Information Granules which are included in the real system, and a new type of fuzzy polynomial neuron called as fuzzy set based polynomial neuron. The performance of the IG-gHFPNN is quantified through experimentation.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.3
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• pp.236-241
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• 2015

This paper presents a study on transformable multiple quadruped robots by docking between robots and waist joints. This robot is able to go on a variety of angles because of mecanum wheels. It is also a hybrid design which allows robot use legs to overcome obstacles on complex terrains and wheels to move on flat ground. The robot is applied kinematics of mecanum wheels and walking, and its walking is based on specific patterns. Docking module is located in front and backside of robot, docking algorithm is suggested and fulfilled for docking between 2 robots. A waist joint is at the center of robot body for transformation and after docking and transformation, robot can activate new functions that carry something.

• ETRI Journal
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• v.30 no.5
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• pp.653-662
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• 2008

Arbitration of tag collision is a significant issue for fast tag identification in RFID systems. A good tag anti-collision algorithm can reduce collisions and increase the efficiency of tag identification. EPCglobal Generation-2 (Gen2) for passive RFID systems uses probabilistic slotted ALOHA with a Q algorithm, which is a kind of dynamic framed slotted ALOHA (DFSA), as the tag anti-collision algorithm. In this paper, we analyze the performance of the Q algorithm used in Gen2, and analyze the methods for estimating the number of slots and tags for DFSA. To increase the efficiency of tag identification, we propose new tag anti-collision algorithms, namely, Chebyshev's inequality, fixed adjustable framed Q, adaptive adjustable framed Q, and hybrid Q. The simulation results show that all the proposed algorithms outperform the conventional Q algorithm used in Gen2. Of all the proposed algorithms, AAFQ provides the best performance in terms of identification time and collision ratio and maximizes throughput and system efficiency. However, there is a tradeoff of complexity and performance between the CHI and AAFQ algorithms.

• Journal of Korea Society of Industrial Information Systems
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• v.9 no.3
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• pp.38-45
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• 2004

The goal of this research is to develop a method of identifying a topic of a given text by looking at relationship of keywords defined in an ontology hierarchy. The keywords which are extracted from important sentences of the given text are mapped onto their correspond concepts which exist in the hierarchy. After all the words are mapped, the correspond concepts will be generalized into one single concept. The single concept will most likely be the topic of text. Our research have an approach that promotes both satisfaction in term of robustness and accuracy using ontologies and word frequency. So, this attempts are done in what they call as a hybrid approach. We try to take the challenge by using knowledge-statistical base approach. Experimental results show that proposed method outperforms the existing method using knowledge-base only.

• The Journal of the Korea institute of electronic communication sciences
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• v.2 no.3
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• pp.150-156
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• 2007

In this paper, we studied security systems for information security of several systems that use in network environment along with information society. Therefore, we designed symmetry style base mixing style cryptographic system that apply block and stream way to solve problems of complexity and lower processing speed etc. Symmetry style base mixing style cryptographic system including authentication operation holds performance that the processing speed and the calculation amount are more superior than asymmetry style. Result that design system by Synopsys 1999.10 and ALTERA MaxPlus 10.1 and do simulation, mixing style password system that we propose is that information security offers very efficient assistance and performance in necessary field in network environment.

• The KIPS Transactions:PartC
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• v.11C no.2
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• pp.203-212
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• 2004

There is a rapidly growing demand for wireless telecommunication. The restricted number of channels is a significant bottleneck for the capacity of mobile communication systems. Consequently, when assigning the channels to the different base stations, it is desirable to reuse the same channel af much as possible. It is then important to avoid any possible interference between different mobile users, while satisfying the given demand. The objective of this thesis is to develop a hybrid heuristic algorithm to find the channel assignment method for allocating the channels in an efficient way, which does not violate the compatibility constraints. We also show several benchmarking channel assignment problems using proposed channel assignment method for validation in this thesis.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.3
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• pp.75-85
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• 2014

This paper is to develop and estimate a closed form inflation model using the estimates for real marginal costs in manufacturing industries during the sample period 1975-2010. The production function in manufacturing industry incorporates labor, capital, domestic material, and foreign material, assuming constant returns to scale technology and AR(1) process of technological coefficient. We derive real marginal costs from firm's cost minimization with quarterly data and provide new evidences on the new Keynesian Phillips curve for Korea. The main empirical result is that the closed form coefficients ${\delta}_1$ and ${\delta}^{-1}_2$ in manufacturing for PPI inflation proved to be 0.5086 and 0.8779 respectively, similar to the estimates in the U.S. case. These results also are consistent with the functional relationship between the coefficients in hybrid model and its closed form. Thus the paper suggests that the empirical studies on inflation dynamics need to focus on the manufacturing industry with market power, treating PPI inflation as the dependent variable.

• Proceedings of the Korean System Dynamics Society
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• 1999.08a
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• pp.105-132
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• 1999

If a system such as a port has a large boundary and complexity, and the system's substance is considered as a black box, forecast accuracy will be very low. Furthermore various components in a port exert significant influence on each other. To copy with these problem the form of structure models were introduced by using SD method. The Competitive Ports Model had several sub-systems consisting of each Unit Port models, and each Unit Port model was made by quantitative, qualitative factors and their feedback loops. The fact that all components of one port have influence on the components of the other ports should be taken into account to construct Competitive Port Models. However, with the current approach that is impossible, and in this paper, therefore, models were simplified by HFP adapted to integrate level variables of unit port models. Although many studies on modelling of port competitive situation have been conducted, both theoretical frame and methodology are still very weak. In this study, 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.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.5
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• pp.361-366
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• 2013

Prediction of process parameters is very important in parameter design. If predictions are fairly accurate, the quality improvement process will be useful to save time and reduce cost. The concept of dual response approach based on response surface methodology has widely been investigated. Dual response approach may take advantages of optimization modeling for finding optimum setting of input factor by separately modeling mean and variance responses. This study proposes an alternative dual response approach based on machine learning techniques instead of statistical analysis tools. A hybrid neural network-genetic algorithm has been proposed for the purpose of parameter design. A neural network is first constructed to model the relationship between responses and input factors. Mean and variance responses correspond to output nodes while input factors are used for input nodes. Using empirical process data, process parameters can be predicted without performing real experimentations. A genetic algorithm is then applied to find the optimum settings of input factors, where the neural network is used to evaluate the mean and variance response. A drug formulation example from pharmaceutical industry has been studied to demonstrate the procedures and applicability of the proposed approach.