• The Journal of the Korea Contents Association
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• v.4 no.4
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• pp.79-87
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• 2004

In this paper, we propose a probability map based genetic algorithm to detect lips from portrait image. The existing genetic algorithm used to get an optimal solution is modified in order to get multiple optimal solutions for lips detection. Each individual consists of two chromosomes to represent coordinates x, y in space. Also the algorithm introduce a preserving zone in the population, a modified uniform crossover, a selection without individual duplication. Using probability map of H, 5 components, the proposed algorithm has adaptability in the segmentation of objects with similar colors. In experiments, we analyzed relationships of primary parameters and found that the algorithm can apply to the detection of other ROIs easily

• The Journal of Korean Association of Computer Education
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• v.6 no.1
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• pp.29-39
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• 2003

In this paper we proposed dynamic adaptive model based on discrete probabilistic distribution functions and user's profile for web media systems(web based hypermedia systems). The model represented that the application domain is modelled using a weighted direct graph and the user's behaviour is modelled using a probabilistic approach that dynamically constructs a discrete probability distribution functions. The proposed probabilistic interpretation of the web media structure is used to characterize latent properties of the user's behaviour, which can be captured by tracking user's browsing activity. Using that distribution the system attempts to assign the user to the best profile that fits user's expectations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.1
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• pp.35-46
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• 1994

In this paper, the performance of DS/SS acquisition system over frequency nonselective Rician fading channel is analyzed by means of packet loss probability. The power ratio of the fading component to the specular compnent. seccessive constant fadong chips k. and correlation coefficient among k chipe are taken for channel parameters. The false alarm probabilities and detection probabilities are derived, and packet loss probability is evaluated in terms of these probablities in the stats transition diagram. From the results of the performance test, these exists the region of packet loss probability in crease because of autocorrelation sidelobe. As k increases, the packet loss probabolotoes decrease.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.9 s.339
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• pp.11-18
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• 2005

In ad hoc networks, many applications use the broadcast service that is elementary operation to support various important functions such as route discovery procedure. This paper presents several adaptive probabilistic broadcast schemes base on local information to alleviate the broadcast storm problem for wireless ad hoc network. Our schemes dynamically determine the rebroadcast probability at each node based on the neighbor information within two-hop span. Simulation results are presented, which show our schemes have a better performance over the deterministic flooding approach.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.4
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• pp.65-73
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• 1997

This paper proposes a new method of the structure pruning of dynamic recurrent neural networks (DRNN) using evolutionary computations. In general, evolutionary computations are population-based search methods, therefore it is very useful when several different properties of neural networks need to be optimized. In order to prune the structure of the DRNN in this paper, we used the evolutionary programming that searches the structure and weight of the DRNN and evolution strategies which train the weight of neuron and pruned the net structure. An addition or elimination of the hidden-layer's node of the DRNN is decided by mutation probability. Its strategy is as follows, the node which has mhnimum sum of input weights is eliminated and a node is added by predesignated probability function. In this case, the weight is connected to the other nodes according to the probability in all cases which can in- 11:ract to the other nodes. The proposed pruning scheme is exemplified on the stabilization and position control of the inverted-pendulum system and visual servoing of a robot manipulator and the effc: ctiveness of the proposed method is demonstrated by numerical simulations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.7B
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• pp.1351-1360
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• 1999

In frequency selective channels, conventional PN code acquisition schemes are not ideal candidates. This is because they are primarily designed for the AWGN channel. In this paper, a direct-sequence spread-spectrum(DSSS) PN code acquisition system based on digital matched filtering (DMF) with automatic threshold control(ATC) algorithm is presented and analyzed with regards to probability of detection and probability of false alarm. These two important probabilities, the probability of detection ($P_D$) and the probability of false alarm ($P_{FA}$) are derived and analyzed in considering Doppler shift, sampling rate, mean acquisition time, and PN chip rate in frequency selective Rayleigh fading channel when using serial-search method as detection technique. From computer simulation results of a DMF acquisition system model, it is shown that the performance of the acquisition system using ATC algorithm is better than that of constant threshold system.

• Journal of Labour Economics
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• v.33 no.2
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• pp.1-26
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• 2010

Introducing a concept of 'the Effect of My Mom's Friend's Son'(MMFS Effect) into the conventional job search theory to develop it further, we try to estimate its effects on the hazard rate of youth pre-employment duration with some proxy variables such as his/her parents' schooling, monthly temporary/daily workers ratio, monthly average wage differentials between the workers of large and small firms. The results confirm us the fact that so called 'MMFS Effect' has been strengthened gradually up to recently. Their policy implications are as followings. Firstly, from the standpoint of shortening job searching period of youth and raising the hazard rate of their unemployment, the trend that the differentials of wages and quality of jobs in the labor market are expanding continuously is not desirable at all. Secondly, the problems of youth unemployment cannot be solved easily only by providing correct and relevant informations about the labor markets simply.

• Journal of the Korean Geotechnical Society
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• v.29 no.9
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• pp.71-80
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• 2013

This work studies the reliability analysis of a slope that considers multiple failure modes. The analysis consists of two parts. First, significant failure modes that contribute most to system reliability are determined. The so-called barrier method proposed by Der Kiureghian and Dakessian to identify significant failure modes successively is employed. Second, the failure probability for the slope is estimated on the basis of the identified significant failure modes and corresponding design points. For reliability problems entailing multiple design points, failure probability can be estimated by the multi-point first-order reliability method (FORM), Ditlevsen's bounds method, and Monte Carlo simulation. In this paper, a comparative study between these methods has been made through example problems. Analysis results showed that while a soil slope may have a large number of potential slip surfaces, its system failure probability is usually governed by a few significant slip surfaces. Therefore, the most important step in the system reliability analysis for a soil slope is to identify all the significant failure modes in an efficient way.

• The KIPS Transactions:PartB
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• v.16B no.4
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• pp.319-326
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• 2009

PSO(Particle Swarm Optimization) is an optimization algorithm in which simple particles search an optimal solution using shared information acquired through their own experiences. PSO applications are so numerous and diverse. Lots of researches have been made mainly on the parameter settings, topology, particle's movement in order to achieve fast convergence to proper regions of search space for optimization. In standard PSO, since each particle uses only information of its and best neighbor, swarm does not explore diverse regions and intended to premature to local optima. In this paper, we propose a new particle's movement strategy in order to explore diverse regions of search space. The strategy is that each particle moves according to relative weights of several better neighbors. The strategy of exploring diverse regions is effective and produces less local optimizations and accelerating of the optimization speed and higher success rates than standard PSO. Also, in order to raise success rates, we propose a strategy for checking whether swarm falls into local optimum. The new PSO algorithm with these two strategies shows the improvement in the search speed and success rate in the test of benchmark functions.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.4
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• pp.572-578
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• 2008

We analyze the search space considered by the previously proposed R-CORE method for learning Bayesian network structures of large scale. Experimental analysis on the search space of the method is also shown. The R-CORE method reduces the search space considered for Bayesian network structures by recursively clustering the random variables and restricting the orders between clusters. We show the R-CORE method has a similar search space with the previous method in the worst case but has a much less search space in the average case. By considering much less search space in the average case, the R-CORE method shows less tendency of overfitting in learning Bayesian network structures compared to the previous method.