• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.8
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• pp.238-244
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• 2013

In energy dispersive X-ray fluorescence analysis, the removal of the continuum on which the X-ray spectrum is superimposed is one of the most important processes, since it has a strong influence on the analysis result. The existing methods which have been used for it usually require tight constraints or prior information on the continuum. In this paper, an efficient background correction method is proposed for Energy Dispersive X-ray fluorescence (EDXRF) spectra. The proposed method has two steps of background modeling and background correction. It is based on the basic concept which differentiates background areas from the peak areas in a spectrum and the SNIP algorithm, one of the popular methods for background removal, is used to enhance the performance. After detecting some points which belong to the background from a spectrum, its background is modeled by a curve fitting method based on them. And then the obtained background model is subtracted from the raw spectrum. The method has been shown to give better results than some of traditional methods, while working under relatively weak constraints or prior information.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.3
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• pp.47-61
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• 2012

parallel transmitting system with channel bonding method have been proposed to transmit mass content such as UHD(Ultra High Definition) in HFC(Hybrid Fiber Coaxial) networks. However, this system may lead to channel resource problem because the system needs many channels to transmit mass content. In this paper, we analyze three effective bandwidth approximation algorithms to use the bonding channel efficiently. These algorithms are the effective bandwidth of Gaussian approximation method algorithm proposed by Guerin, the effective bandwidth based on statistics of video frames proposed by Lee and the effective bandwidth based on Gaussian traffic proposed by Nagarajan. We also evaluate compatibility of algorithms to the mass broadcasting service. OPNET simulator is used to evaluate the performance of the algorithms. For accuracy of simulation, we make mass source from real HD broadcasting stream.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.15 no.1
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• pp.43-58
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• 2002

A methodology to nondestructively locate and estimate size of damage in beam-type structures using a few natural frequencies or a few mode shapes is presented. A damage-localization algorithm to locate damage from changes in natural frequencies and a damage-sizing algorithm to estimate crack-size from natural frequency perturbation are outlined. A damage index algorithm to localize and estimate severity of damage from monitoring changes in mode shapes is outlined. The frequency-based method and the mode-shape-based method are evaluated for several damage scenarios by locating and sizing damage in PS concrete beams lot which a few natural frequencies and mode shapes are generated from finite element models. The result of the analyses indicates that the two methods correctly localize and closely estimate the size of the crack simulated in the test beam.

• Journal of the Korea Society for Simulation
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• v.17 no.3
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• pp.35-44
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• 2008

Facility location problem is an important subject in many areas of modern business environment. In this paper, we deal with uncapacitated and multi-period facility location problem where the object is a maximization of total profit within predetermined cost. We assume that all demand have to be met. Particularly, we represent various types of customer based on four well-known urban spatial structures to represent a spread of customers. Those are concentric zone model, sector model, multiple nuclei model and star model respectively. We apply to the genetic algorithm to simulate a large scaled problem and develop simulator. We analyze both optimal numbers and locations of facilities for each urban structure. Furthermore, we examine the appropriate time to further expansion of the facilities in the planning horizon. The experimental results show that the developed algorithm can be applied effectively to the facility location problem in the various types of urban area.

• Journal of Korea Game Society
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• v.16 no.6
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• pp.79-90
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• 2016

Recently, many researchers have paid attention to the improved generation of AI agent in the area of game industry. Monte-Carlo Tree Search(MCTS) is one of the algorithms to search an optimal solution through random search with perfect information, and it is suitable for the purpose of calculating an approximate value to the solution of an equation which cannot be expressed explicitly. Games in Trading Card Game(TCG) genre such as the heartstone has imperfect information because the cards and play of an opponent are not predictable. In this study, MCTS is suggested in imperfect information card games so as to generate AI agents. In addition, the practicality of MCTS algorithm is verified by applying to heartstone game which is currently used.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.7
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• pp.893-898
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• 2005

Due to the merits that only a small amount of computation is needed for solutions and stochastic policies can be handled explicitly, the actor-critic algorithm, which is a class of reinforcement learning methods, has recently attracted a lot of interests in the area of artificial intelligence. The actor-critic network composes of tile actor network for selecting control inputs and the critic network for estimating value functions, and in its training stage, the actor and critic networks take the strategy, of changing their parameters adaptively in order to select excellent control inputs and yield accurate approximation for value functions as fast as possible. In this paper, we consider a new actor-critic algorithm employing an RLS(Recursive Least Square) method for critic learning, and policy gradients for actor learning. The applicability of the considered algorithm is illustrated with experiments on the two linked robot arm.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.574-579
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• 2009

There have been much difficulties to construct an optimized neural network in complex nonlinear regression problems such as selecting the networks structure and avoiding overtraining problem generated by noise. In this paper, we propose a stepwise constructive method for neural networks using a flexible incremental algorithm. When the hidden nodes are added, the flexible incremental algorithm adaptively controls the number of hidden nodes by a validation dataset for minimizing the prediction residual error. Here, the ELM (Extreme Learning Machine) was used for fast training. The proposed neural network can be an universal approximator without user intervene in the training process, but also it has faster training and smaller number of hidden nodes. From the experimental results with various benchmark datasets, the proposed method shows better performance for real-world regression problems than previous methods.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.11
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• pp.90-98
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• 2013

The stereo system based on local matching is very popular due to its algorithmic simplicity, however it is limited to apply to various applications because it shows poor quality with low matching rates. In this paper, we propose and design a realtime stereo system based on an adaptive support-weight and the system shows low error rates and realtime performance. Generally, in the adaptive support-weight algorithm the intermediate computing results can not be reused to reduce the number of computations. In this research we modify the scheduling to reuse the intermediate results for the better performance by processing rows and columns separately. The nonlinear functions such as exponential or arc tangent have been designed with piecewise linear and step functions by empirical simulations and error analysis. The proposed architecture is composed of 9 processing elements for realtime performance. The proposed stereo system has been designed and synthesized using Donbu Hitek 0.18um standard cell library and can run up to 350Mhz operation frequency (33 frames per second) with 424K gates.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.6
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• pp.842-848
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• 2008

This paper deal with uncertainty problem by using Type-2 fuzzy logic set for nonlinear system modeling. We design Type-2 fuzzy logic system in which the antecedent and the consequent part of rules are given as Type-2 fuzzy set and also analyze the performance of the ensuing nonlinear model with uncertainty. Here, the apexes of the antecedent membership functions of rules are decided by C-means clustering algorithm and the apexes of the consequent membership functions of rules are learned by using back-propagation based on gradient decent method. Also, the parameters related to the fuzzy model are optimized by means of particle swarm optimization. The proposed model is demonstrated with the aid of two representative numerical examples, such as mathematical synthetic data set and Mackey-Glass time series data set and also we discuss the approximation as well as generalization abilities for the model.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.1B
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• pp.85-94
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• 2010

Many RFID systems use dynamic slotted ALOHA to identify the label information of the RFID tags. One of the key problems in the RFID system is how to estimate the number of RFID tags up to the desired level of accuracy. In this paper, we present the framework of tag estimation algorithm for the collision-oblivious (CO) reader which can only decide whether the tag response is successful or not. Thus, the CO reader must rely on the success estimator to predict the RFID tag population. We propose two estimation algorithms to predict the number of RFID tags, named the memoryless success estimator (MSE) and the intersection-based success estimator (ISE). The MSE considers only the estimate obtained at the current inventory round, while the ISE finds an appropriate intersection interval of the existing estimates collected at every inventory round. Through the simulation results, we demonstrate that the ISE is a fast, accurate, and controllable estimator whose performance is close to that of the collision/idle estimators.