• Journal of Environmental Science International
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• v.3 no.3
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• pp.185-195
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• 1994

Masan bay is one of the polluted enclosed bays, which has red tides problem and the formation of oxygen deficient water in the bottom layer. Most important factors that cause eutrophication and red tide is nutrient materials containing nitrogen and phosphorus which stem from terrestrial sources and nutrients released from sediment. Therefore, to improve of water quality, reduction of these nutrient loads should be indispensible. At this study, the three-dimensional numerical hydrodynamic and eutrophication model, which were developed by Institute for Resources and Environment of Japan, were applied to analyze the processes affecting the phytoplankton production and also to evaluate the effect of water quality improvement plans on phytoplankton production. In field sorvey, the range of concentrations of chlorophyll-a at surface area was found to be 29.17 - 212.5mg/m3, which were exceeding eutrophication criteria. The constant currents defined by integrating the simulated tidal currents over 1 tidal cycle showed the counterclockwise eddies in the southern part of Budo. The general directions of constant currents were found to be southward at surface and northward at bottom over all the bay. The eutrophication model was calibrated with the data surveyed in the field area in June, 1993. The calculated results are in fairly good agreement with values within relative error of 30%. The pollutant load from the sources such as the input from terrestrial release from the sediment was reduced by the rate of 50, 70, 90, 98% to effect of phytoplankton production. Phytoplankton production was reduced to of the 90% reduction of the input loads from terrestrial sources and 8% in 90% reduction of the load from sediment.

• Journal of Korea Water Resources Association
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• v.40 no.10
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• pp.823-832
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• 2007

In this study, the separation of short and long durations for estimation the parameters of IDF curve is suggested by using Multi-Objective Genetic Algorithm (MOGA). Objective functions are to minimize root mean squared error (RMSE) and relative RMSE between observed and computed values. The criteria for separation are two; the first one is to estimate more precisely the parameters of IDF curve and the second is to make a single IDF curve without non-continuous duration point. For this purpose 22 rainfall recording gauges operated by Korea Meteorological Administration are selected and three IDF curves that are used generally in South Korea are tested. The result shows that the IDF curve developed by Heo et al. (1999) would be the best of three tested IDF curves, and the suggested parameter estimation method using MOGA can compute more reliable parameters compared with empirical regression analysis.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.4
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• pp.931-940
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• 2015

Roller Compacted Concrete Pavement (RCCP), is a type of pavement using compaction roller and asphalt finisher on concrete mixture that contains low amount of water. RCCP strength and durability are greatly affected by compaction level. Quality control is performed by ensuring the degree of compaction at site based on dry density. In the field, Modified Proctor Test is used in order to obtain optimum dry density. However, there is no clear compaction curve analysis criteria of Modified Proctor Test for RCCP. In this study, compaction curve built by three samples of Modified Proctor Test was produced and it was used to compare with compaction curve contented lower number of samples (one and two samples) in order to analyze their reliability. Thus, a conclusion was drawn from the results; by comparing to the result from Modified Proctor Test of three samples, the use of two samples represented result with only 0.5% of error which means the reliability is 99.5%.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.403-406
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• 2005

In order to evaluate the Capability of ETM+ remotely- sensed data to provide 'Forest-shrub land-Rangeland' cover type map in areas near the timberline of northern forests of Iran, the data were analyzed in a portion of nearly 790 ha located in Neka-Zalemroud region. First, ortho-rectification process was used to correct the geometric errors of the image, yielding 0/68 and 0/69 pixels of RMS. error in X and Y axis, respectively. The original and panchromatic bands were fused using PANSHARP Statistical module. The ground truth map was made using 1 ha field plots in a systematic-random sampling grid, and vegetative form of trees, shrubs and rangelands was recorded as a criteria to name the plots. A set of channels including original bands, NDVI and IR/R indices and first components of PCI from visible and infrared bands, was used for classification procedure. Pair-wise divergence through CHNSEL command was used, In order to evaluate the separability of classes and selection of optimal channels. Classification was performed using ML classifier, on both original and fused data sets. Showing the best results of $67\%$ of overall accuracy, and 0/43 of Kappa coefficient in original data set. Due to the results represented above, it's concluded that ETM+ data has an intermediate capability to fulfill the spectral variations of three form- based classes over the study area.

• Journal of Korean Society for Atmospheric Environment
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• v.23 no.4
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• pp.449-456
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• 2007

Dispersion coefficient preprocessing schemes have been examined to improve plume dispersion model performance in complex coastal areas. The performances of various schemes for constructing the sigma correction order were evaluated through estimations of statistical measures, such as bias, gross error, R, FB, NMSE, within FAC2, MG, VG, IOA, UAPC and MRE. This was undertaken for the results of dispersion modeling, which applied each scheme. Environmental factors such as sampling time, surface roughness, plume rising, plume height and terrain rolling were considered in this study. Gaussian plume dispersion model was used to calculate 1 hr $SO_2$ concentration 4 km downwind from a power plant in Boryeung coastal area. Here, measured data for January to December of 2002 were obtained so that modelling results could be compared. To compare the performances between various schemes, integrated scores of statistical measures were obtained by giving weights for each measure and then summing each score. This was done because each statistical measure has its own function and criteria; as a result, no measure can be taken as a sole index indicative of the performance level for each modeling scheme. The best preprocessing scheme was discerned using the step-wise method. The most significant factor influencing the magnitude of real dispersion coefficients appeared to be sampling time. A second significant factor appeared to be surface roughness, with the rolling terrain being the least significant for elevated sources in a gently rolling terrain. The best sequence of correcting the sigma from P-G scheme was found to be the combination of (1) sampling time, (2) surface roughness, (3) plume rising, (4) plume height, and (5) terrain rolling.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.11
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• pp.1959-1975
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• 2011

Adaptive Bit Loading (ABL) in Multiple-Input Multiple-Output Orthogonal Frequency-Division Multiplexing (MIMO-OFDM) is often used to achieve the desired Bit Error Rate (BER) performance in wireless systems. In this paper, we discuss some of the bit loading algorithms, compare them in terms of the BER performance, and present an effective and concise Adaptive Grouped Loading (AGL) algorithm. Furthermore, we propose a "weight factor" for loading algorithm to converge rapidly to the final solution for various data rate with variable Signal to Noise Ratio (SNR) gaps. In particular, we consider the bit loading in near optimal Singular Value Decomposition (SVD) based MIMO-OFDM system. While using SVD based system, the system requires perfect Channel State Information (CSI) of channel transfer function at the transmitter. This scenario of SVD based system is taken as an ideal case for the comparison of loading algorithms and to show the actual enhancement achievable by our AGL algorithm. Irrespective of the CSI requirement imposed by the mode of the system itself, ABL demands high level of feedback. Grouped Loading (GL) would reduce the feedback requirement depending upon the group size. However, this also leads to considerable degradation in BER performance. In our AGL algorithm, groups are formed with a number of consecutive sub-channels belonging to the same transmit antenna, with individual gains satisfying predefined criteria. Simulation results show that the proposed "weight factor" leads a loading algorithm to rapid convergence for various data rates with variable SNR gap values and AGL requires much lesser CSI compared to GL for the same BER performance.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.1
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• pp.32-42
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• 2000

This paper presents an on-line learning algorithm for sequential construction of generalized radial basis function networks (GRBFNs) to model nonlinear systems from empirical data. The GRBFN, an extended from of standard radial basis function (RBF) networks with constant weights, is an architecture capable of representing nonlinear systems by smoothly integrating local linear models. The proposed learning algorithm has a two-stage learning scheme that performs both structure learning and parameter learning. The structure learning stage constructs the GRBFN model using two construction criteria, based on both training error criterion and Mahalanobis distance criterion, to assign new hidden units and the linear local models for given empirical training data. In the parameter learning stage the network parameters are updated using the gradient descent rule. To evaluate the modeling performance of the proposed algorithm, simulations and their results applied to two well-known benchmarks are discussed.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.6
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• pp.44-51
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• 1999

The HMM-Net is a neural network architecture that implements the computation of output probabilities of a hidden Markov model (HMM). The architecture is developed for the purpose of combining the discriminant power of neural networks with the time-domain modeling capability of HMMs. Criteria of maximum likehood(ML) and minimization of mean squared error(MMSE) are used for learning HMM-Net classifiers. The criterion MMSE is better than ML when initial learning condition is well established. However Ml is more useful one when the condition is incomplete[3]. Therefore we propose an efficient learning method of HMM-Net classifiers using a hybrid criterion(ML/MMSE). In the method, we begin a learning with ML in order to get a stable start-point. After then, we continue the learning with MMSE to search an optimal or near-optimal solution. Experimental results for the isolated numeric digits from /0/ to /9/, a training and testing time-series pattern set, show that the performance of the proposed method is better than the others in the respects of learning and recognition rates.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.5
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• pp.459-467
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• 2014

ILM(Incremental Launching Method) bridges pass both the middle of spans and supports during launching. The launching noses are used to minimize the maximum positive moments and negative moments of the superstructure occurring during launching for ILM bridges. In this study, the simplified analysis formula considering diaphragm to calculate the bending moment that occurs during launching is induced and analyzes the optimum design conditions considering diaphragm. The accuracy of the proposed simplified analysis formular compared to the MIDAS Civil has an error of less than 5%. There is a difference up to 13% in the moment between the cases when the diaphragm is considered and is not. In addition, the criteria for deciding the unit weight of equivalent cross section and average stiffness value of equivalent cross section that can be applied to the simplified analysis formula is proposed. In this study, an effective way to optimize the launching nose is proposed that the optimum design is taken in the condition of minimizing the negative moment because of the mechanic characteristic of ILM bridges.

• Journal of East-West Nursing Research
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• v.24 no.1
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• pp.44-51
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• 2018

Purpose: The purpose of this study was to examine the actor and partner effects of self efficacy, marital adjustment and family support on Yangseang in infertile couples using the actor-partner interdependence model. Methods: The participants were 108 infertile couples. Data were collected using the Yangsaeng Scale, Infertility Self Efficacy Scale, Revised Dyadic Adjustment Scale, and Perceived Social Support Scale from March to April in 2016. The Actor-Partner Interdependence Model was used to analyze the actor and partner effects of self-efficacy, marital adjustment and family support on Yangsaeng. Results: The fit indices for the model were Comparative Fit Index (CFI) = 0.99, Normed Fit Index (NFI) = 0.99, Tucker-Lewis Index (TLI) = 0.90, and Root Mean Square Error of Approximation (RMSEA) = 0.01, which met the criteria. We found that only self efficacy had an actor effect on Yangsaeng. Marital adjustment and family support of infertile husbands had an actor effect on the Yangsaeng. In addition, marital adjustment showed an interaction effect. Conclusions: The findings of this study indicate that the level of Yangseang in infertile couples was positively associated with the levels of self efficacy and martial adjustment. Partner effects may be hidden due to much stronger actor effects on Yangseang.