• Smart Structures and Systems
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• v.22 no.5
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• pp.561-574
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• 2018

In this paper, for efficiently reducing the computational cost of the model updating during the optimization process of damage detection, the structural response is evaluated using properly trained surrogate model. Furthermore, in practice uncertainties in the FE model parameters and modelling errors are inevitable. Hence, an efficient approach based on Monte Carlo simulation is proposed to take into account the effect of uncertainties in developing a surrogate model. The probability of damage existence (PDE) is calculated based on the probability density function of the existence of undamaged and damaged states. The current work builds a framework for Probability Based Damage Detection (PBDD) of structures based on the best combination of metaheuristic optimization algorithm and surrogate models. To reach this goal, three popular metamodeling techniques including Cascade Feed Forward Neural Network (CFNN), Least Square Support Vector Machines (LS-SVMs) and Kriging are constructed, trained and tested in order to inspect features and faults of each algorithm. Furthermore, three wellknown optimization algorithms including Ideal Gas Molecular Movement (IGMM), Particle Swarm Optimization (PSO) and Bat Algorithm (BA) are utilized and the comparative results are presented accordingly. Furthermore, efficient schemes are implemented on these algorithms to improve their performance in handling problems with a large number of variables. By considering various indices for measuring the accuracy and computational time of PBDD process, the results indicate that combination of LS-SVM surrogate model by IGMM optimization algorithm have better performance in predicting the of damage compared with other methods.

• Korean Journal of Agricultural Science
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• v.43 no.3
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• pp.394-400
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• 2016

The objective of this study was to estimate the environmental factors affecting milk ${\beta}$-hydroxybutyric acid (BHBA) and acetone (Ac) concentrations in Holstein cattle. A total of 264,221 test-day records collected from the Korea Animal Improvement Association (KAIA) during the period of 2012 to 2014 were used in this study. Analysis of variance (ANOVA) was performed to determine the factors significantly affecting ketone body concentrations. Parameters considered in the model were season of test, season of calving, parity, lactation stage, and milk collecting time (AM and PM). According to the ANOVA, the $R^2$ for milk BHBA and Ac were 0.5226 and 0.4961, respectively. 'Season of test' showed a considerable influence on ketone body concentration. Least square (LS) means for milk BHBA concentrations was the lowest ($39.04{\mu}M$) in winter while it increased up to $62.91{\mu}M$ in summer. But Ac concentration did not significantly change along with 'season of test'. The means of milk BHBA and Ac concentrations were high at first lactation stage, low around second lactation stage, and then gradually increased. Cows milked in the morning had lower mean BHBA and Ac concentrations ($48.49{\mu}M$ and $121.69{\mu}M$, respectively) in comparison to those milked in the evening ($53.46{\mu}M$ and $130.42{\mu}M$, respectively). The LS means of BHBA and Ac slightly increased over parities. These results suggest that proper maintenance of milk collection, herd management programs, and evaluation of ketone body levels in milk should be considered for the efficient management of resistance to ketosis.

• Proceedings of the KSRS Conference
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• v.2
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• pp.582-585
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• 2006

Augustine volcano is an active stratovolcano located southwest of Anchorage, Alaska. Augustine volcano experienced seven significantly explosive eruptions in 1812, 1883, 1908, 1935, 1963, 1976, and 1986, and a minor eruption in January 2006. To measure ground surface deformation of Augustine volcano, we applied satellite radar interferometry with ERS-1/2 and ENVISAT SAR images acquired from three descending and three ascending satellite tracks. Multiple interferograms are stacked to reduce artifacts due to changes in atmospheric condition and retrieve temporal deformation sequence. For this, we used Least Square (LS) method for reducing atmospheric effects and Singular Value Decomposition (SVD) method for the retrieval of a temporal deformation sequence. Interferograms before 2006 eruption show about 3 cm/year subsidence by contraction of pyroclastic flow deposits from the 1986 eruption. Interferograms during 2006 eruption do not show significant deformation around volcano crater. Interferograms after 2006 eruption show again a several cm subsidence by compaction and contraction of pyroclastic flow deposits for a few months. This study demonstrates that satellite radar interferometry can monitor deformation of Augustine volcano to help understand the magma plumbing system driving surface deformation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.7A
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• pp.623-631
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• 2010

In this paper, various of pilot-assisted channel estimation techniques for 3GPP LTE downlink are tested under multipath Rayleigh fading channel. At first, the conventional channel estimation techniques are applied with linear zero-forcing (ZF) equalizer, such as one dimensional least square (1-D LS) linear interpolation, two dimensional (2-D) wiener filter, the time and frequency dimension separate wiener filter and maximum likelihood estimator (MLE). Considering the practical implementation, we proposed two channel estimation techniques by combining time-dimension wiener filter and MLE in two manners, which showed a good tradeoff between system performance and complexity when comparing with conventional techniques. The nonlinear decision feedback equalizer (DFE) which can show a better performance than linear ZF equalizer is also implemented for mitigating inter-carrier interference (ICI) in our system. The complexity of these algorithms are calculated in terms of the number of complex multiplications (CMs) and the performances are evaluated by showing the bit error rate (BER).

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.129-132
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• 1999

스테레오 음향 반향 제거기는 입력 신호로 사용되는 두 채널간의 강한 상관관계로 인하여 수렴특성이 악화되는 문제점을 갖는다. 따라서 수렴속도를 향상시키기 위해 RLS또는 Affine Projection(AP) 알고리즘 같은 Least Square (LS)계 열의적응 알고리즘을 사용하는 것이 필요하다. 그러나, 이러한 알고리즘은 LMS 알고리즘과 같은 통계적 미분계열 알고리 즘에 비하여 과도한 계산량을 요구하므로 고속 알고리즘에 대한 연구가 진행되어왔다. 본 논문에서는 스테레오 환경에서 Gram-Schmidt(GS) 직교화를 이용하여 LMS 알고리즘 수준의 계산량을 갖는 근사화된 AP 알고리즘을 제안하였다. 제안한 알고리즘은 AP 알고리즘의 후행오차 성질을 이용하여 GS 직교화 구조로 구성되며, 계산량 감소를 위해 샘플단위의 재귀적 GS 직교화를 사용하였다. 또한 GS직교화를 스테레오 채널에 적용함으로써 적은 계산량으로 AS 알고리즘과 대등한 수렴 성능을 갖는다.

• Korean Journal of Optics and Photonics
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• v.15 no.6
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• pp.563-568
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• 2004

The high temperature proton exchange (HTPE) method was used to fabricate optical waveguides based on LiNbO$_3$, which gives rise to low propagation loss and high polarization extinction ratio. To characterize the refractive index distribution of the fabricated waveguides, the guided modes of each waveguide were observed using the prism coupling method and then the refractive index profile was calculated by the inverse WKB method with the least square fitting. Finally, we showed how the HTPE parameters such as the temperature of PE, the concentration of lithium additive, and the time of PE effect the refractive index profile.

• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1089-1098
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• 2018

This study aims at developing and applying a hybrid model to the wind power prediction (WPP). The hybrid model for a very-short-term WPP (VSTWPP) is achieved through analytical data, multiple linear regressions and least square methods (MLR&LS). The data used in our hybrid model are based on the historical records of wind power from an offshore region. In this model, the WPP is achieved in four steps: 1) transforming historical data into ratios; 2) predicting the wind power using the ratios; 3) predicting rectification ratios by the total wind power; 4) predicting the wind power using the proposed rectification method. The proposed method includes one-step and multi-step predictions. The WPP is tested by applying different models, such as the autoregressive moving average (ARMA), support vector machine (SVM), and artificial neural network (ANN). The results of all these models confirmed the validity of the proposed hybrid model in terms of error as well as its effectiveness. Furthermore, forecasting errors are compared to depict a highly variable WPP, and the correlations between the actual and predicted wind powers are shown. Simulations are carried out to definitely prove the feasibility and excellent performance of the proposed method for the VSTWPP versus that of the SVM, ANN and ARMA models.

• Geomechanics and Engineering
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• v.36 no.5
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• pp.489-509
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• 2024

Slope stability analysis and prediction are of critical importance to geotechnical engineers, given the severe consequences associated with slope failure. This research endeavors to forecast the factor of safety (FOS) for slopes through the implementation of six distinct ML techniques, including back propagation neural networks (BPNN), feed-forward neural networks (FFNN), Takagi-Sugeno fuzzy system (TSF), gene expression programming (GEP), and least-square support vector machine (Ls-SVM). 344 slope cases were analyzed, incorporating a variety of geometric and shear strength parameters measured through the PLAXIS software alongside several loss functions to assess the models' performance. The findings demonstrated that all models produced satisfactory results, with BPNN and GEP models proving to be the most precise, achieving an R² of 0.86 each and MAE and MAPE rates of 0.00012 and 0.00002 and 0.005 and 0.004, respectively. A Pearson correlation and residuals statistical analysis were carried out to examine the importance of each factor in the prediction, revealing that all considered geomechanical features are significantly relevant to slope stability. However, the parameters of friction angle and slope height were found to be the most and least significant, respectively. In addition, to aid in the FOS computation for engineering challenges, a graphical user interface (GUI) for the ML-based techniques was created.

• Korean Journal of Poultry Science
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• v.30 no.4
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• pp.235-244
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• 2003

This study was carried out to estimate the effects of strain and generation on the major production performances of Korean native chicken. The data were collected from 11,583 birds of the 7 generations over the year 1995 through 2001 at National Livestock Research Institute, Korea. Results obtained were summarized as follows: The body weights at 150 and 270 days of age were 1,557.7 and 1880.7, 1,471.7 and 1,738.2, 1,393.5 and 1,694.9, 1,591.2 and 1,910.0, 1,545.6 and 1,763.6g in Red Brown, Yellow Brown, Gray Brown, Black, and White strains, respectively. The Coefficient of Variations (CVs) of the body weights at 150 and 270 days of age were 9.65~13.79% and 13.29~15.16%. The ages at first egg were 150.0, 148.3, 149.5, 152,8 and 147.7 days in Red Brown, Yellow Brown, Gray Brown, Black and White strains, respectively and the CVs were between 9.33 and 10.11%. The egg weights at the first egg and 270 days of age were 33.2 and 50.8, 32.2 and 49.2, 32.2 and 49.1, 33.0 and 50.0, 30.7 and 47.8g respectively. The CVs of the egg weights of the first egg and at 270 days of age were 13.54~15.27% and 6.93~7.36%. The numbers of eggs produced by 270 days of age were 77.0, 79.3, 77.3, 73,7, 75.4, respectively, and observed CVs were between 29.98~36.99%. The significant strain effects were investigated in all the major economic traits in Korean native chicken. The significant strain effects were investigated in all the major economic traits in Korean native chicken. The highest least square (LS) means of the body weights at 150 and 270 days of age were observed in Black strain as 1,594.38 and 1,911.57g. The earliest LS mean of the ages at first egg was 146.88days in White strain. The heaviest LS means of egg weights at the first egg and 270 days of age were observed in Red Brown strain as 32.20 and 50.74g. The LS mean of the largest number of egg production was 79.50 eggs in Yellow Brown strain. Also, The significant generation effects were investigated in all the major economic traits. The highest LS means of the body weights at 150 and 270 days of age were observed in the generation 3 as 1,599.74 and 1,905.01g. The earliest LS mean of the age at first egg was 143.31 days in 4th generation. The heaviest LS means of egg weights at the first egg and 270 days of age were observed in 7th and 5th generation as 35.68 and 50.42g. The LS means of the largest number of egg production was 78.53 eggs in generation 6. In general, light body weight, short time for the age at first egg, heavy egg weight, and large number of egg production were observed as the generation proceeded.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.11 s.353
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• pp.141-148
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• 2006

This paper deals with the performance improvement by eliminating loop interference signal and inserting adaptive equalizer for phase compensation in OFDMA based Wibro relay station. The Wibro relay station is used for the extension of communication service area and for throughput improvement of base station. The loop interference is important factor of performance determination of relay station when transmitter and receiver is very closely located. In order to design interference canceller, we generated base-band OFDMA signal and then transmitted the signal along with pilot tones alined with two different combinations for training mode. And then, we generated received fading signal due to the loop interference added noise to the received signal. In the receiver, the transmitted signal is recovered by elimination of the interference signal with channel estimate and compensating phase by adaptive equalizer. The performance improvement was verified by computer simulation which show channel estimation, constellation of signal and BER characteristics according to the variation of SNR ratio.