• Journal of Internet Computing and Services
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• v.13 no.5
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• pp.1-8
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• 2012

In this paper, we propose a new clustering combination based on numerical data driven for rule generation mechanism. In large and complicated space, a clustering method can obtain limited performance results. To overcome the single clustering method problem, hybrid combined methods can solve problem to divided simple cluster estimation. Fundamental structure of the proposed method is combined by mountain clustering and modified Chen clustering to extract detail cluster information in complicated data distribution of non-parametric space. It has automatic rule generation ability with advanced density based operation when intelligent systems including neural networks and fuzzy inference systems can be generated by clustering results. Also, results of the mechanism will be served to information of decision support system to infer the useful knowledge. It can extend to healthcare and medical decision support system to help experts or specialists. We show and explain the usefulness of the proposed method using simulation and results.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.6
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• pp.51-60
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• 2011

Researches on indoor localization using the wireless sensor network have been actively carried out to be used for indoor area where GPS signal is not received. Computationally efficient WCL(Weighted Centroid Localization) algorithm is shown to perform relatively well. However, to get the best performance for WCL all the anchor nodes must send signal with power to cover 96% of the network. The fact that outside the transmission range of the fixed nodes drastic localization error occurs results in large mean error and deviation. Due to these problems the WCL algorithm is not easily applied for use in the real indoor environment. In this paper we propose SRS(Succesive Region Setting) algorithm which sequentially reduces the estimated location area using the signal strength from the anchor nodes. The proposed algorithm does not show significant performance degradation corresponding to transmission range of the anchor nodes. Simulation results show that the proposed SRS algorithm has mean localization error 5 times lower than that of the WCL under free space propagation environment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.6C
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• pp.560-569
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• 2005

This paper proposes an algorithm for transmit antenna selection in a multi-input multi-output(MIMO) spatial multiplexing system with per antenna rate control(PARC) and an ordered successive interference cancellation (OSIC) receiver. The active antenna subset is determined at the receiver and conveyed to the transmitter using feedback information on transmission rate per antenna. We propose a serial decision procedure consisting of a successive process that tests whether antenna selection gain exists when the antenna with the lowest pre-processing signal to interference and noise ratio(SINR) is discarded at each stage. Furthermore, we show that 'reverse detection ordering', whereby the signal with the lowest SINR is decoded at each stage of successive decoding, widens the disparities among fractions of the whole capacity allocated to each individual antenna and thus maximizes a gain of antenna selection. Numerical results show that the proposed reverse detection ordering based serial antenna selection approaches the closed-loop MIMO capacity and that it induces a negligible capacity loss compared with the heuristic selection strategy even with considerably reduced complexity.

• The KIPS Transactions:PartD
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• v.11D no.1
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• pp.219-228
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• 2004

Confidence interval estimators for proportions using normal approximation have been commonly used for coverage analysis of simulation output even though alternative approximate estimators of confidence intervals for proportions were proposed. This is -because the normal approximation was easier to use in practice than the other approximate estimators. Computing technology has no problem with dealing these alternative estimators. Recently, one of the approximation methods for coverage analysis which is based on arcsin transformation has been used for estimating proportion and for controlling the required precision in [12]. In this paper, we compare three approximate interval estimators, based on a normal distribution approximation, an arcsin transformation and an F-distribution approximation, of a single proportion. Three estimators were applied to sequential coverage analysis of steady-state means, in simulations of the M/M/1/$\infty$ and W/D/l/$\infty$ queueing systems on a single processor and multiple processors.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.5A
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• pp.284-293
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• 2003

Location service is usually provided by the GPS method using satellites. In the next generation mobile communication systems which use smart antennas, location service can be accomplished using direction of arrival (DOA) estimation techniques. In this paper, we propose a DOA estimation technique for the location service of the next generation mobile communication systems and investigate the validity of the proposed technique through computer simulation. First, DOA estimation problems of distributed sources are considered using vortical and horizontal array processors which are orthogonal to each other. The DOA of the elevation angle is estimated by the vertical array processor and then that of the azimuth angle is estimated by the horizontal array processor. Finally, the procedures of the location service for specific signal sources using three smart antennas are exhibited by computer simulation to show that the proposed DOA estimation technique can be used for the location service in the next generation mobile communication systems.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.13 no.4
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• pp.177-188
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• 1993

Model parameters of the WASP4 applied to Lake Paldang were estimated. The methodology is based on grouping water quality constituents and relevant parameters and successively estimating each group of parameters by a trial-and-error procedure. Chlorophyll a, nitrogen cycles, phosphorus cycles, BOD and DO were simulated at the complexity level 4. A water budget analysis using the monthly records of reservoir inflows and outflows in 1989 and 1990 was made to determine seasonally-averaged flowrates at model boundaries. Estimated flowrates were used, together with the seasonal average of water quality measurements in 1989 and 1990 for the calibration and verification, respectively, of the model. Grouping water quality constituents and associated parameters proved to be efficient in estimating a number of model parameters. From the results of model calibration and verification, it was found that quantitative evaluations of nonpoint and benthic sources of organic matters are essential. Benthic sources near the entrance of the Kyeongancheon were the most significant.

• The Korean Journal of Applied Statistics
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• v.24 no.2
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• pp.373-381
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• 2011

This paper discusses how to get the sums of squares due to treatment factors when Type I Analysis is used by projections for the analysis of data under the assumption of a two-way ANOVA model. The suggested method does not need to calculate the residual sums of squares for the calculation of sums of squares. There-fore, the calculation is easier and faster than classical ANOVA methods. It also discusses how eigenvectors and eigenvalues of the projection matrices can be used to get the calculation of sums of squares. An example is given to illustrate the calculation procedure by projections for unbalanced data.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.1
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• pp.6-14
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• 1996

In this paper we present an algorithm to discriminate an underwater target under track against an acoustic counter-measure(ACM) source, based on a sequential hypothesis test. The ACM source is separated from the target under track and generates, while drifting, measurements with false range and Doppler information. The purpose of the ACM is to mislead the target-tracking and to help the true target evade a pursuer. The algorithm uses as a test statistic a function of the innovation sequences from extended Kalman filters to estimate the target dynamics and the drifting position of the ACM source. Numerical experiments on various scenarios show that the proposed algorithm discriminates the target against an ACM source very fast with a high probability of success.

• Journal of the Korean Data and Information Science Society
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• v.22 no.6
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• pp.1167-1173
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• 2011

The goal of this paper is to suggest an algorithm to get forecasting for the numbers of students in the city or county in local government by using the double exponential smoothing method. By 2044 year, the third year of high school students in the Chilgok, Gumi, Gyeongsan, Andong, Pohang and Gimchen are reduced about 40-70%, the those of in the remaining city or county are reduced about 70-95%. In conclusion, the forecasting numbers of students of the 23 counties in Kyungbuk Province are on the decrease to 40%-100% until 2044 year in comparison with the numbers of students on 2010 years.

• The Korean Journal of Applied Statistics
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• v.34 no.6
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• pp.937-944
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• 2021

The problem of selecting variables is addressed in partial linear regression. Model selection for partial linear models is not easy since it involves nonparametric estimation such as smoothing parameter selection and estimation for linear explanatory variables. In this work, several approaches for variable selection are proposed using a fast forward selection algorithm, least angle regression (LARS). The proposed procedures use t-test, all possible regressions comparisons or stepwise selection process with variables selected by LARS. An example based on real data and a simulation study on the performance of the suggested procedures are presented.