• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.1147-1151
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• 2009

In this study, we address the problem of producing probability forecasts of summer seasonal rainfall, on the basis of Hindcast experiments from a ensemble of GCMs(cwb, gcps, gdaps, metri, msc_gem, msc_gm2, msc_gm3, msc_sef and ncep). An advanced Hierarchical Bayesian weighting scheme is developed and used to combine nine GCMs seasonal hindcast ensembles. Hindcast period is 23 years from 1981 to 2003. The simplest approach for combining GCM forecasts is to weight each model equally, and this approach is referred to as pooled ensemble. This study proposes a more complex approach which weights the models spatially and seasonally based on past model performance for rainfall. The Bayesian approach to multi-model combination of GCMs determines the relative weights of each GCM with climatology as the prior. The weights are chosen to maximize the likelihood score of the posterior probabilities. The individual GCM ensembles, simple poolings of three and six models, and the optimally combined multimodel ensemble are compared.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.120-126
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• 2007

A principal components analysis of the entire median HRIRs in the CIPIC HRTF database reveals that the individual HRIRs can be adequately reconstructed by a linear combination of several orthonormal basis functions. The basis functions cover the inter-individual and inter-elevation variations in median HRIRs. There are elevation-dependent tendencies in the weights of basis functions, and the basis functions can be ordered according to the magnitude of standard deviation of the weights at each elevation. We propose a HRIR customization method via tuning of the weights of 3 dominant basis functions corresponding to the 3 largest standard deviations at each elevation. Subjective listening test results show that both front-back reversal and vertical perception can be improved with the customized HRIRs.

• International Journal of Control, Automation, and Systems
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• v.4 no.4
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• pp.456-465
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• 2006

The problem of recursive filtering far linear discrete-time systems with uncertainties is considered. A new suboptimal filtering algorithm is herein proposed. It is based on the fusion formula, which represents an optimal mean-square linear combination of local Kalman estimates with weights depending on cross-covariances between local filtering errors. In contrast to the optimal weights, the suboptimal weights do not depend on current measurements, and thus the proposed algorithm can easily be implemented in real-time. High accuracy and efficiency of the suboptimal filtering algorithm are demonstrated on the following examples: damper harmonic oscillator motion and vehicle motion constrained to a plane.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.635-639
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• 2004

In this paper, we present a novel approach for the structure of Fuzzy Neural Network(FNN) based on wavelet function and apply this network structure to the modeling of chaotic nonlinear systems. Generally, the wavelet fuzzy model(WFM) has the advantage of the wavelet transform by constituting the fuzzy basis function(FBF) and the conclusion part to equalize the linear combination of FBF with the linear combination of wavelet functions. However, it is very difficult to identify the fuzzy rules and to tune the membership functions of the fuzzy reasoning mechanism. Neural networks, on the other hand, utilize their learning capability for automatic identification and tuning. Therefore, we design a wavelet based FNN structure(WFNN) that merges these advantages of neural network, fuzzy model and wavelet transform. The basic idea of our wavelet based FNN is to realize the process of fuzzy reasoning of wavelet fuzzy system by the structure of a neural network and to make the parameters of fuzzy reasoning be expressed by the connection weights of a neural network. And our network can automatically identify the fuzzy rules by modifying the connection weights of the networks via the gradient descent scheme. To verify the efficiency of our network structure, we evaluate the modeling performance for chaotic nonlinear systems and compare it with those of the FNN and the WFM.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.1
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• pp.111-118
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• 2004

In this paper, we present a novel approach for the structure of Fuzzy Neural Network(FNN) based on wavelet function and apply this network structure to the solution of the tracking problem for mobile robots. Generally, the wavelet fuzzy model(WFM) has the advantage of the wavelet transform by constituting the fuzzy basis function(FBF) and the conclusion part to equalize the linear combination of FBF with the linear combination of wavelet functions. However, it is very difficult to identify the fuzzy rules and to tune the membership functions of the fuzzy reasoning mechanism. Neural networks, on the other hand, utilize their learning capability for automatic identification and tuning. Therefore, we design a wavelet based FNN structure(WFNN) that merges these advantages of neural network, fuzzy model and wavelet transform. The basic idea of our wavelet based FNN is to realize the process of fuzzy reasoning of wavelet fuzzy system by the structure of a neural network and to make the parameters of fuzzy reasoning be expressed by the connection weights of a neural network. And our network can automatically identify the fuzzy rules by modifying the connection weights of the networks via the gradient descent scheme. To verify the efficiency of our network structure, we evaluate the tracking performance for mobile robot and compare it with those of the FNN and the WFM.

• Asian-Australasian Journal of Animal Sciences
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• v.24 no.10
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• pp.1386-1392
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• 2011

The aim of the present work was to study the effects of a polyherbal supplement on cross bred does, starting from the last month of pregnancy to weaning, on milk yield, kid birth weight and growth rate. Thirty does were divided into three treatments of ten each in individual pens: low level supplementation (LS), high level supplementation (HS) and non-supplemented treatment (NS) as control. Low supplemented goats were given 125 mg/kg BW/d of polyherbal combination; high supplemented goats were given 250 mg/kg BW/d. The study was carried out in 2008. Fifty-nine kids were born from all the experimental animals. There was no difference on milk yield between supplemented groups and control (p>0.05), although polyherbal supplementation had positive effect on litter birth weight and growth rate compared to control. Weaning weights were higher (p<0.001) in LS and HS compared to NS does. In both supplemented treatments compared to control, mortalities and morbidities were also lower in kids born. It is concluded that pre-partum to weaning supplementation increases kids growth rates and weaning weights, as well as reduces kid mortalities, but it doesn't have significant effect on milk production.

• Toxicological Research
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• v.16 no.1
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• pp.33-37
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• 2000

Hershberger assay is known as one of the in vivo-short-term scrrning assays for endocrine disrupting chemicals (EDCs), but this method is not a validated test system. In the present study, the establishment of Hershberger assay to detect EDCs was tried using a model substance, di(n-butyl)phthalate (DBP), a plasticizer for plastics. Thirty-six immature male rats were randomly assigned to six groups: DBP 0, 40, 200, and 1000mg/kg, a positive control (flutamide 20 mg/kg), and a combination group(DBP 1000mg/kg and testosterone 50 ug/kg). DBP and flutamide were administered by gavage to male rats from day 21 to 40 post partum. Testosterone was subcutaneously injected during the same period. We evaluated body weigth gain, weights of ventral prostate, seminal vesicle, and levator ani and bulvocavernous muscle, and serum concentrations of testosterone and lutenizing hormone in male rats. The weights of seminal vesicle and levator ani and bulvocavernous muscle of males receiving 1000mg/kg of DBP was significantly lower than controls. There was no effect of DBP-treatment on body weight gain, prostate weight, and hormone concentrations. In the positive control group, the weights of seminal vesicle and levator ani and bulvocavernous muscle of males receiving 20mg/kg of flutamide were significantly lower than controls. In the combination group, there was no effect of co-treatment of DBP and testosterone on all parameters effect against DBP. This method was found to be a useful short-term screening assay system for EDCs.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.14 no.6
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• pp.77-83
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• 2015

This paper is a study of the functions required for the system to quantify the closest target weight by combining several random weights such as chips, snacks, fruits, and vegetables. The multi-head weigher is designed for high-performance applications requiring increased production rates and tight accuracy tolerances. This combination system has 12 heads considered in the form of a rectangular array of $2{\times}6$ or $3{\times}4$. Channel combination can usually occur between 1 and n, and the frequency was the highest with two or three combinations. Experimental result of a combination system for a total target weight was measured at the range from 100g to 500g by increments of 50g, and the average success rate was about 70%. The average elapsed time was about 1.7 seconds, which means it can be used for the packaging of agricultural products with a variety of items.

• Parasites, Hosts and Diseases
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• v.30 no.3
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• pp.219-226
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• 1992

This study was performed to observe the therapeutic effects of interferon-gamma ($IFN-{\gamma}$) and gamma-globulin (${\gamma}-globulin$) in experimental Pneumocystis carinii pneumonia of immune suppressed mice. After 9 weeks, trimethoprim-sulfamethoxaBole(TMP-SMZ; 10~50 mg/mouse/day), mouse $IFN-{\gamma}(5{\times}10^4$ units/mouse/day) and mouse ${\gamma}-globulin$(20 mg/mouse/day) were administered to the mice for 3 weeks by the experimental group. The therapeutic efficacy was evaluated by body weights, histopatholo단ic and electron microscopic findings of the lungs, and number of p. carinii cysts by Gomori's methenamine silver stain. Body weights of the mice were significantly increased in the group of combination therapy of TMP-SMZ with $IFN-{\gamma}{\;}or{\;}{\gamma}-globulin$, and in the group of TMP- SMZ treatment(p<0.05), however, little effect was found in the group of T-globulin alone. Histopathologic 6ndings of p. carinii pneumonia were much improved in the group of combination therapy of TMP-SMZ with $IFN-{\gamma}$. Treatment with either TMP-SMZ or $IFN-{\gamma}$ significantly reduced the number of cysts in the p. carinii pneumonia, but {\gamma}-globulin alone was ineffective. In electron microscopic findings of p. carinii pneumonia, the number of trophozoites and cysts were reduced by treatment with either TMP-SMZ or $IFN-{\gamma}$, and most of the cysts were empty or containing one or two intracystic bodies. The present results suggested, that combination therapy of TMP-SMZ with $IFN-{\gamma}$ had synergistic effects in treatment of P carinii pneumonia in experi- mental mice.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.7
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• pp.1749-1756
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• 2014

Knowledge about protein subcellular localization provides important information about protein function. This paper improves a label power-set multi-label classification for the accurate prediction of subcellular localization of proteins which simultaneously exist at multiple subcellular locations. Among multi-label classification methods, label power-set method can effectively model the correlation between subcellular locations of proteins performing certain biological function. With constrained optimization, this paper calculates combination weights which are used in the linear combination representation of a multi-label by other multi-labels. Using these weights, the prediction probabilities of multi-labels are combined to give final prediction results. Experimental results on human protein dataset show that the proposed method achieves higher performance than other prediction methods for protein subcellular localization. This shows that the proposed method can successfully enrich the prediction probability of multi-labels by exploiting the overlapping information between multi-labels.