• Smart Structures and Systems
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• v.12 no.2
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• pp.121-136
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• 2013

This study proposes an innovative control approach to suppress the responses of a beam structural system under moving forces. The proposed control algorithm is a synthesis of the adaptive input estimation method (AIEM) and linear quadratic Gaussian (LQG) controller. Using the synthesis algorithm the moving forces can be estimated using AIEM while the LQG controller offers proper control forces to effectively suppress the beam structural system responses. Active control numerical simulations of the beam structural system are performed to evaluate the feasibility and effectiveness of the proposed control technique. The numerical simulation results show that the proposed method has more robust active control performance than the conventional LQG method.

• Journal of Biomedical Engineering Research
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• v.33 no.2
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• pp.65-71
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• 2012

In this paper, the Gaussian Mixture Model(GMM) which is very robust modeling for pattern classification is proposed to classify wrist motions using surface electromyograms(EMG). EMG is widely used to recognize wrist motions such as up, down, left, right, rest, and is obtained from two electrodes placed on the flexor carpi ulnaris and extensor carpi ulnaris of 15 subjects under no strain condition during wrist motions. Also, EMG-based feature is derived from extracted EMG signals in time domain for fast processing. The estimated features based in difference absolute mean value(DAMV) are used for motion classification through GMM. The performance of our approach is evaluated by recognition rates and it is found that the proposed GMM-based method yields better results than conventional schemes including k-Nearest Neighbor(k-NN), Quadratic Discriminant Analysis(QDA) and Linear Discriminant Analysis(LDA).

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2004.11a
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• pp.173-178
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• 2004

The estimation of springing responses for recent ships are carried out and application to a ship design are described. To this aim, springing effects on hull girder were re-evaluated including non-linear wave excitations and torsional vibrations of the hull. The Timoshenko beam model was used to calculate stress distribution on the hull girder by the superposition method. The strip method was employed to calculate the hydrodynamic forces and moments on the hull. In order to remove the irregular frequencies, we adopted 'rigid lid' on the hull free surface level and added asymptotic interpolation along the high frequency range. Several applications to the existing ships were carried out. They are Bishop and Price's container ship, S-175 container ship, large container, VLCC and ore carrier. One of them is compared with ship measurement result while another with that of model test. Comparison between analytical solution and numerical one for homogeneous beam type artificial ship shows good agreement. It is found that most springing energy came from high frequency waves for the ships having low natural frequency and North Atlantic route etc. Therefore, the high frequency tail of the wave spectrum should be increased by $\omega^{-3}\;instead\;of\;\omega^{-4}\;or\;\omega^{-5}$ for springing calculation.

• Preventive Nutrition and Food Science
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• v.13 no.2
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• pp.104-111
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• 2008

As a way to account for the variability of the primary model parameters in the secondary modeling of microbial growth, three different regression approaches were compared in determining the confidence interval of the temperature-dependent primary model parameters and the estimated microbial growth during storage: bootstrapped regression with all the individual primary model parameter values; bootstrapped regression with average values at each temperature; and simple regression with regression lines of 2.5% and 97.5% percentile values. Temperature dependences of converted parameters (log $q_o$, ${\mu}_{max}^{1/2}$, log $N_{max}$) of hypothetical initial physiological state, maximum specific growth rate, and maximum cell density in Baranyi's model were subjected to the regression by quadratic, linear, and linear function, respectively. With an advantage of extracting the primary model parameters instantaneously at any temperature by using mathematical functions, regression lines of 2.5% and 97.5% percentile values were capable of accounting for variation in experimental data of microbial growth under constant and fluctuating temperature conditions.

• Asian-Australasian Journal of Animal Sciences
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• v.28 no.4
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• pp.476-484
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• 2015

The objective of this study was to estimate genetic and phenotypic parameters for linear type traits, as well as milk yield (MY), fat yield (FY) and protein yield (PY) in 18,831 Holstein cows reared in 495 herds in Brazil. Restricted maximum likelihood with a bivariate model was used for estimation genetic parameters, including fixed effects of herd-year of classification, period of classification, classifier and stage of lactation for linear type traits and herd-year of calving, season of calving and lactation order effects for production traits. The age of cow at calving was fitted as a covariate (with linear and quadratic terms), common to both models. Heritability estimates varied from 0.09 to 0.38 for linear type traits and from 0.17 to 0.24 for production traits, indicating sufficient genetic variability to achieve genetic gain through selection. In general, estimates of genetic correlations between type and production traits were low, except for udder texture and angularity that showed positive genetic correlations (>0.29) with MY, FY, and PY. Udder depth had the highest negative genetic correlation (-0.30) with production traits. Selection for final score, commonly used by farmers as a practical selection tool to improve type traits, does not lead to significant improvements in production traits, thus the use of selection indices that consider both sets of traits (production and type) seems to be the most adequate to carry out genetic selection of animals in the Brazilian herd.

• Asian-Australasian Journal of Animal Sciences
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• v.26 no.7
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• pp.981-986
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• 2013

The nutrient digestibility, nitrogen balance and in vivo metabolizable energy supply of Mucuna pruriens whole pods fed to growing Pelibuey lambs was investigated. Eight Pelibuey sheep housed in metabolic crates were fed increasing levels of Mucuna pruriens pods: 0 (control), 100 (Mucuna100), 200 (Mucuna200) and 300 (Mucuna300) g/kg dry matter. A quadratic (p<0.002) effect was observed for dry matter (DM), neutral detergent fibre (aNDF), nitrogen (N) and gross energy (GE) intakes with higher intakes in the Mucuna100 and Mucuna200 treatments. Increasing M. pruriens in the diets had no effect (p>0.05) on DM and GE apparent digestibility (p<0.05). A linear reduction in N digestibility and N retention was observed with increasing mucuna pod level. This effect was accompanied by a quadratic effect (p<0.05) on fecal-N and N-balance which were higher in the Mucuna100 and Mucuna200 treatments. Urine-N excretion, GE retention and dietary estimated nutrient supply (metabolizable protein and metabolizable energy) were not affected (p>0.05). DM, N and GE apparent digestibility coefficient of M. pruriens whole pods obtained through multiple regression equations were 0.692, 0.457, 0.654 respectively. In vivo DE and ME content of mucuna whole pod were estimated in 11.0 and 9.7 MJ/kg DM. It was concluded that whole pods from M. pruriens did not affect nutrient utilization when included in an mixed diet up to 200 g/kg DM. This is the first in vivo estimation of mucuna whole pod ME value for ruminants.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.1
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• pp.184-192
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• 2011

In this study, we introduce a identification methodology for FCM-based fuzzy model. The two underlying design mechanisms of such networks involve Fuzzy C-Means (FCM) clustering method and Particle Swarm Optimization(PSO). The proposed algorithm is based on FCM clustering method for efficient processing of data and the optimization of model was carried out using PSO. The premise part of fuzzy rules does not construct as any fixed membership functions such as triangular, gaussian, ellipsoidal because we build up the premise part of fuzzy rules using FCM. As a result, the proposed model can lead to the compact architecture of network. In this study, as the consequence part of fuzzy rules, we are able to use four types of polynomials such as simplified, linear, quadratic, modified quadratic. In addition, a Weighted Least Square Estimation to estimate the coefficients of polynomials, which are the consequent parts of fuzzy model, can decouple each fuzzy rule from the other fuzzy rules. Therefore, a local learning capability and an interpretability of the proposed fuzzy model are improved. Also, the parameters of the proposed fuzzy model such as a fuzzification coefficient of FCM clustering, the number of clusters of FCM clustering, and the polynomial type of the consequent part of fuzzy rules are adjusted using PSO. The proposed model is illustrated with the use of Automobile Miles per Gallon(MPG) and Boston housing called Machine Learning dataset. A comparative analysis reveals that the proposed FCM-based fuzzy model exhibits higher accuracy and superb predictive capability in comparison to some previous models available in the literature.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.2
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• pp.416-424
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• 2017

In this study, we propose a design of digits recognition system based on RBFNNs through a comparative study of pre-processing algorithms in order to recognize digits in handwritten. Histogram of Oriented Gradient(HOG) is used to get the features of digits in the proposed digits recognition system. In the pre-processing part, a dimensional reduction is executed by using Principal Component Analysis(PCA) and (2D)2PCA which are widely adopted methods in order to minimize a loss of the information during the reduction process of feature space. Also, The architecture of radial basis function neural networks consists of three functional modules such as condition, conclusion, and inference part. In the condition part, the input space is partitioned with the use of fuzzy clustering realized by means of the Fuzzy C-Means algorithm. Also, it is used instead of gaussian function to consider the characteristic of input data. In the conclusion part, the connection weights are used as the extended type of polynomial expression such as constant, linear, quadratic and modified quadratic. By using MNIST handwritten digit benchmarking database, experimental results show the effectiveness and efficiency of proposed digit recognition system when compared with other studies.

• Proceedings of the KSRS Conference
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• v.1
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• pp.274-277
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• 2006

KARI is currently developing a geostationary ocean color imager (GOCI) for COMS. We report the progress in integrated optical modeling and analysis for stray light suppression and the end-to-end instrument performance verification including in-orbit calibration. The Sun is modeled as the emitting light source and the selected area around Korean peninsular as the observation target that scatters the sun light towards GOCI in orbit. The optical ray tracing employing active geometric scaling was then used for precise characterization of the spatial and radiometric performance at the instrument focal plane. The analysis results show positive reduction in the simulated stray light level with the design improvement including baffles. It also indicates that the ray traced in-orbit radiometric performances are effective tools for the independent assessment of more traditional linear and quadratic equation based estimation of water leaving radiance. The concept of integrated GOCI optical model and the computational method are presented.

• Journal of Animal Science and Technology
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• v.53 no.6
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• pp.505-509
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• 2011

This experiment was conducted to estimate the genetic parameters and breeding values of the economic traits measured from the cows (aged 15 months or older) using ultrasound and to use them as the information for the selection of stock animals at the farm level. The means and standard deviations of longissimus muscle area, backfat thickness and marbling score were $54.11\;cm^2{\pm}9.06$, $3.57\;mm{\pm}2.45$ and $2.65{\pm}2.88$, respectively. While the linear regression coefficients of longissimus muscle area, backfat thickness and marbling score for age (in months) were all positive (0.3532, 0.0868 and 0.0833), the quadratic regression coefficients of them for age (in months) were all negative (-0.0023, -0.0005 and -0.0006), and as the body condition score increased longissimus muscle area, backfat thickness and marbling score increased collectively. The heritability estimates for the longissimus muscle area, backfat thickness and marbling score were 0.39, 0.48 and 0.13, respectively and the estimated annual genetic gains for the longissimus muscle area, backfat thickness and marbling score were 0.00334 $cm^2$, -0.0073 mm and 0.0043 score, respectively, which were not significantly different from zero.