• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.9C
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• pp.871-879
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• 2009

The performance variations of a spatio temporal smart antenna which is equipped at the basestation of CDMA cellular communication network due to the parametric change of multipath fading environment are studied in this paper. The smart antenna of interest employs space diversity based adaptive array structure in conjunction with rake receiver that has fingers the number of which is the same as that of multipath links. The beamforming is achieved via LMS(Least Mean Square) algorithm in which a reference signal is generated using decision directed formula. It has been shown by computer simulation that the performance of our smart antenna of interest depends significantly upon not only the degree of desired signal's DOA(Direction of Arrival)spread but the number of fingers of the rake receiver. The relative insensitivity of the smart antenna's performance on desired signal's delay spread has also been observed. Computer simulation has shown that the increase of the number of fingers brings in a nonlinear enhancement of the performance of our smart antenna. The renewal of weight vector in the beamforming procedure is taken place at post PN despread stage.

• Journal of the Korea Society of Computer and Information
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• v.15 no.5
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• pp.57-65
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• 2010

In this paper, we propose a new real-time algorithm detecting the flame and smoke in digital CCTV images. Because the forest fire causes the enormous human life and damage of property, the early management according to the early sensing is very important. The proposed algorithm for monitoring forest fire is classified into the flame sensing and detection of smoke. The flame sensing algorithm detects a flame through the conditional test at YCbCr color model from the single frame. For the detection of smoke, firstly the background range is set by using differences between current picture and the average picture among the adjacent frames in the weighted value, and the pixels which get out of this range and have a gray-scale are detected in the smoke area. Because the proposed flame sensing algorithm is stronger than the existing algorithms in the change of the illuminance according to the quantity of sunshine, and the smoke detection algorithm senses the pixel of a gray-scale with the smoke considering the amount of change for unit time, the effective early forest fire detection is possible. The experimental results indicate that the proposed algorithm provides better performance than existing algorithms.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.6
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• pp.72-79
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• 2017

In this paper, we present a new saliency detection algorithm using the mutual information of wavelet subbands. Our method constructs an intermediate saliency map using the power operation and Gaussian blurring for high-frequency wavelet coefficients. After combining three intermediate saliency maps according to the direction of wavelet subband, we find the main directional components using entropy measure. The amount of mutual information of each subband is obtained centering on the subband having the minimum entropy The final saliency map is detected using Minkowski sum based on weights calculated by the mutual information. As a result of the experiment on CAT2000 and ECSSD databases, our method showed good detection results in terms of ROC and AUC with few computation times compared with the conventional methods.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.5
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• pp.45-53
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• 2000

This paper presents an analysis of the dynamical behavor in the chaotic neuron fabricated using 0.8${\mu}{\textrm}{m}$ single poly CMOS technology. An approximated empirical equation models for the sigmoid output function and chaos generative block of the chaotic neuron are extracted from the measurement data. Then the dynamical responses of the chaotic neuron such as biurcation diagram, frequency responses, Lyapunov exponent, and average firing rate are calculated with numerical analysis. In addition, we construct the chaotic neural networks which are composed of two chaotic neurons with four synapses and obtain bifurcation diagram according to synaptic weight variation. And results of experiments in the single chaotic neuron and chaotic neural networks by two neurons with the $\pm$2.5V power supply and sampling clock frequency of 10KHz are shown and compared with the simulated results.

• Journal of Korea Water Resources Association
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• v.35 no.1
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• pp.51-64
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• 2002

In this study, the formulation of the developed mixed-integer programming model for a multi-reservoir system including hydro-electric power generation (park et al., 2001) has been improved for multiple reservoir system operation using risk evaluation criteria. Sequential linear programming(SLP) was applied for the linearization of the hydro-electric energy term in the model. In order to allocate monthly reservoir release reasonably the value of weight for hydro-electric energy was assigned by level of power generation hour. The improved model was applied to the five reservoirs system in the Han river. And could be confirmed the availibility of new formulation appling risk evaluation criteria.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.2
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• pp.186-190
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• 2015

Intelligent vehicle plans motion and navigate itself based on the surrounding environment perception. Hence, the precise environment recognition is an essential part of self-driving vehicle. There exist many vulnerable road users (e.g. vehicle, pedestrians) on vehicular driving environment, the vehicle must percept all the dynamic obstacles accurately for safety. In this paper, we propose an multiple vehicle tracking algorithm using microwave radar. Our proposed system includes various special features. First, exceptional radar measurement model for vehicle, concentrated on the corner, is described by mixture density network (MDN), and applied to particle filter weighting. Also, to conquer the curse of dimensionality of particle filter and estimate the time-varying number of multi-target states, reversible jump markov chain monte carlo (RJMCMC) is used to sampling step of the proposed algorithm. The robustness of the proposed algorithm is demonstrated through several computer simulations.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.6
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• pp.542-550
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• 2015

Usually, a new SSD (Solide State Drive) product is developed based on the software platform of the previous product. Therefore, when using the same test case was used to evaluate the previous generation evaluation of new products are a number of advantages may be, but a priority or weight is the inefficiency exists in the use of the evaluation resources due to not considered. A new method is proposed to prevent the waste of testing resources. Through the analysis of the evaluation data for the previous products, the combinations of testing cases with the highest probability for defect detections are identified. When the software is to be reused, most part of the base software platform is rarely modified and only some modules are added or modified. So, the whole software system may have similar types of defects with the previous products. By utilizing the evaluation data for the previous proucts, we can detect defects at an early stage.

• Journal of Intelligence and Information Systems
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• v.16 no.2
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• pp.95-108
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• 2010

In this paper, we present a hybrid neural network model for dynamic hand gesture recognition. The model consists of two modules, feature extraction module and pattern classification module. We first propose a modified CNN(convolutional Neural Network) a pattern recognition model for the feature extraction module. Then we introduce a weighted fuzzy min-max(WFMM) neural network for the pattern classification module. The data representation proposed in this research is a spatiotemporal template which is based on the motion information of the target object. To minimize the influence caused by the spatial and temporal variation of the feature points, we extend the receptive field of the CNN model to a three-dimensional structure. We discuss the learning capability of the WFMM neural networks in which the weight concept is added to represent the frequency factor in training pattern set. The model can overcome the performance degradation which may be caused by the hyperbox contraction process of conventional FMM neural networks. From the experimental results of human action recognition and dynamic hand gesture recognition for remote-control electric home appliances, the validity of the proposed models is discussed.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.11
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• pp.499-508
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• 2015

High utility itemset(HUI) mining refers to the discovery of itemsets with high utilities which are not less than a user-specified minimum utility threshold, by considering both the quantities and weight factors of items in a transaction database. Recently the utility-list based HUI mining algorithms have been proposed to avoid numerous candidate itemsets and the algorithms need the costly join operations. In this paper, we propose a new HUI mining algorithm, using the utility-list with additional attributes of transaction utility and common utility of itemsets. The new algorithm decreases the number of join operations and efficiently prunes the search space. Experimental results on both synthetic and real datasets show that the proposed algorithm outperforms other recent algorithms in runtime, especially when datasets are dense or contain many long transactions.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.5
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• pp.393-400
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• 2017

A virtual simulation test program to carry out the handling qualities of unmanned Rotorcraft has developed by using the MATLAB GUIDE(Graphic User Interface Development Environment). The handling quality evaluation program based on ADS-33E contributes to design the flight control system and to evaluate handling qualities. In addition, Linear Quadratic Tracker with Integrator(LQTI) attitude controller based on Linear Quadratic Regulator(LQR) for to rotorcraft BO-105C and the effects of the handling qualities is analyzed change to weight matrices of the Q and R.