• Journal of the Korean Ceramic Society
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• v.49 no.5
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• pp.404-411
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• 2012

The reliability of solid oxide fuel cells (SOFCs) particularly depends on the high quality of solid oxide electrolytes. The application of thinner electrolytes and multi electrolyte layers requires a more reliable characterization method. Most of the investigations on thin film solid electrolytes have been made for the parallel transport along the interface, which is not however directly related to the fuel cell performance of those electrolytes. In this work an array of ion-blocking metallic Ti/Au microelectrodes with about a $160{\mu}m$ diameter was applied on top of an ultrathin ($1{\mu}m$) yttria-stabilized-zirconia/gadolinium-doped-ceria (YSZ/GDC) heterolayer solid electrolyte in a micro-SOFC prepared by PLD as well as an 8-${\mu}m$ thick YSZ layer by screen printing, to study the transport characteristics in the perpendicular direction relevant for fuel cell operation. While the capacitance variation in the electrode area supported the working principle of the measurement technique, other local variations could be related to the quality of the electrolyte layers and deposited electrode points. While the small electrode size and low temperature measurements increaseed the electrolyte resistances enough for the reliable estimation, the impedance spectra appeared to consist of only a large electrode polarization. Modulus representation distinguished two high frequency responses with resistance magnitude differing by orders of magnitude, which can be ascribed to the gadolinium-doped ceria buffer electrolyte layer with a 200 nm thickness and yttria-stabilized zirconia layer of about $1{\mu}m$. The major impedance response was attributed to the resistance due to electron hole conduction in GDC due to the ion-blocking top electrodes with activation energy of 0.7 eV. The respective conductivity values were obtained by model analysis using empirical Havriliak-Negami elements and by temperature adjustments with respect to the conductivity of the YSZ layers.

• Asian-Australasian Journal of Animal Sciences
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• v.17 no.10
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• pp.1383-1389
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• 2004

The nutritive value and utilization of whole crop rice silage (WCRS), Hamasari, at yellow mature stage was determined by three studies. In first study, chemical composition, in vivo digestibility and metabolizable energy (ME) content of WCRS was determined by Holstein steers. WCRS contains 6.23% CP, its digestibility is 48.4% and estimated TDN is 56.4%. Its ME content was 1.91 Mcal/kg DM. Gross energy (GE) retention (% of GE intake) in steers is only 22.7% most of which was lost through feces (44.7% of GE intake). It takes 81 minutes to chew a kg of WCRS by steers. In another study, the effect of Hamasari at yellow mature stage at three stages of lactation (early, mid and late lactation) and two levels of concentrate (40 or 60%) on voluntary intake, ME content and ME intake, milk yield and composition using lactating Holstein dairy cows were investigated. Total intake increased with the concentrate level in early and mid lactation, but was similar irrespective of concentrate level in late lactation. WCRS intake was higher with 40% concentrate level than with 60% concentrate. ME intake by cows increased with the concentrate level and WCRS in early lactating cows with 40% concentrate can support only 90% of the ME requirement. Milk production in accordance with ME intake increased with the increase in concentrate level in early and mid lactating cows but was similar in late lactating cows irrespective of concentrate level. Fat and protein percent of milk in mid and late lactating cows were higher with for 60% concentrate than 40%, but reverse was in early lactating cows. Solids-not-fat was higher with for 60% concentrate than 40% concentrate. Finally in situ degradability of botanical fractions such as leaf, stem, head and whole WCRS, Hamasari at yellow mature stage was incubated from 0 to 96 h in Holstein steers to determine DM and N degradability characteristics of botanical fractions and whole WCRS. Both DM and N solubility, rate of degradation and effective degradability of leaf of silage was lower, but slowly degradable fraction was higher compared to stem and head. Solubility of DM and N of stem was higher than other fractions. The 48 h degradability, effective degradability and rate of degradation of leaf were always lower than stem or head. In conclusion, voluntary intake of silage ranged from 5 to 12 kg/d and was higher with low levels of concentrate, but milk yield was higher with high levels of concentrate. Fat corrected milk yield ranged from 19 to 37 kg per day. For consistency of milk, early lactating cows should not be allowed more than 40% whole crop rice silage in the diet, but late lactating cows may be allowed 60% whole crop rice silage.

• Clean Technology
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• v.25 no.4
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• pp.302-310
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• 2019

A constructed wetland with the aerobic tank and anaerobic/anoxic tank connected in series was employed in order to treat highly polluted stream water. The aerobic tank was maintained aerobic with a continuous supply of air through the natural air draft system. Five pilot plants having different residence times were employed together to obtain parameters for the best performances of the wetland. BOD and COD removals at the aerobic tank followed the first order kinetics. COD removal rate constants were slightly lower than BOD. The temperature dependence of COD (θ = 1.0079) and BOD (θ = 1.0083) was almost the same, but the temperature dependence (θ_N) of T-N removal was 1.0189. The SS removal rate was as high as 98% and the removal efficiency showed a tendency to increase with increasing hydraulic loading rate (Q/A). The main mechanism of BOD and COD removal at the anaerobic/anoxic tank was entirely different from that of the aerobic tank. BOD and COD were supplied as the carbon source for biological denitrification. T-P was believed to be removed though the cation exchange between orthophosphate and gravels within the anaerobic and anoxic tanks. The wetland could successfully be operated without being blocked by the filtered solid which subsequently decomposed at an extremely fast rate.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.6
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• pp.625-633
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• 2015

In this study, a coupled probabilistic framework is developed to assess wind risk on apartment buildings by using the convolution of wind hazard and fragility functions. In this framework, typhoon induced extreme wind is estimated by applying the developed Monte Carlo simulation model to the climatological data of typhoons affecting Korean peninsular from 1951 to 2013. The Monte Carlo simulation technique is also used to assess wind fragility function for 4 different damage states by comparing the probability distributions of the window system's resistance performance and wind load. Wind hazard and fragility functions are modeled by the Weibull and lognormal probability distributions based on simulated wind speeds and failure probabilities. The modeled functions are convoluted to obtain the wind risk for the different damage levels. The developed probabilistic framework clearly shows that wind risk are influenced by various important characteristics of terrain and apartment building such as location of building, exposure category, topographic condition, roof angle, height of building, etc. The risk model presented in this paper can be used as tools to predict economic loss estimation and to establish wind risk mitigation plan for the existing building inventory.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.24 no.1
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• pp.79-85
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• 2011

Bridge Weigh-in-Motion(BWIM) system calculates a travelling vehicle's weight without interruption of traffic flow by analyzing the signals that are acquired from various sensors installed in the bridge. BWIM system or data accumulated from the BWIM system can be utilized to development of updated live load model for highway bridge design, fatigue load model for estimation of remaining life of bridges, etc. Field test with moving trucks including various load cases should be performed to guarantee successful development of precise BWIM system. In this paper, a numerical simulation technique is adopted as an alternative or supplement to the vehicle traveling test that is indispensible but expensive in time and budget. The constructed numerical model is validated by comparison experimentally measured signal with numerically generated signal. Also vehicles with various dynamic characteristics and travelling conditions are considered in numerical simulation to investigate the variation of bridge responses. Considered parameters in the numerical study are vehicle velocity, natural frequency of the vehicle, height of entry bump, and lateral position of the vehicle. By analyzing the results, it is revealed that the lateral position and natural frequency of the vehicle should be considered to increase precision of developing BWIM system. Since generation of vehicle travelling signal by the numerical simulation technique costs much less than field test, a large number of test parameters can effectively be considered to validate the developed BWIM algorithm. Also, when artificial neural network technique is applied, voluminous data set required for training and testing of the neural network can be prepared by numerical generation. Consequently, proposed numerical simulation technique may contribute to improve precision and performance of BWIM systems.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.6
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• pp.19-27
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• 2010

This paper proposes a method for enhancing detection performance and reducing computational cost when detecting a human face by applying B-spline active contour to the frame difference of consecutive images. Firstly, the method estimates amount of user's motion using kurtosis. If the kurtosis is smaller than a pre-defined threshold, it is considered that the amount of user's motion is insufficient and thus the contour fitting is not applied. Otherwise, the contour fitting is applied by exploiting the fact that the amount of motion is sufficient. Secondly, for the contour fitting, difference edges are detected by combining the distance transformation of the binarized frame difference and the edges of current frame. Lastly, the face is located by assigning the contour fitting process to the detected difference edges. Kurtosis-based motion amount estimation can reduce a computational cost and stabilize the results of the contour fitting. In addition, distance transformation-based difference edge detection can enhance the problems of contour lag and discontinuous difference edges. Experimental results confirm that the proposed method can reduce the face localization error caused by the contour lag and discontinuity of edges, and decrease the computational cost by omitting approximately 39% of the contour fitting.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.6
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• pp.10-18
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• 2010

This paper proposes an image stabilization algorithm for close watching UAV(Unmanned Aerial Vehicle) using motion separation and stabilization mode. The motion of UAV is composed of its actual navigating motion and unwanted vibrating motion so that image sequences obtained from UAV are shaken randomly. In order to stabilize these images we separate the vibrating motion component from UAV motion and remove the effect caused by it from image sequences. In the proposed algorithm the motion and global intensity change of two consecutive images are modeled with 6 motion parameters and 2 intensity change parameters respectively. These modeled parameters are estimated by non-linear least square method based on Gauss-Newton algorithm. The vibrating motion component is separated from the estimated motion using IIR filtering and the geometric deformation caused by it is removed from image sequences. In order to apply the proposed method to real aerial image sequences with many abrupt changes of camera view, we proposed a stabilizing method using two different modes named as stabilizing and non-stabilizing mode. Experimental results show that the accuracy of motion estimation is 99% and the efficiency of removing the vibrating motion component is 90%. We apply the proposed method to real aerial image sequences and verified its stabilizing performance.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.3
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• pp.23-31
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• 2010

The increasing demands on low-power, and low-complexity video encoder have been motivating extensive research activities on distributed video coding (DVC) in which the encoder compresses frames without utilizing inter-frame statistical correlation. In DVC encoder, contrary to the conventional video encoder, an error control code compresses the video frames by representing the frames in the form of syndrome bits. In the meantime, the DVC decoder generates side information which is modeled as a noisy version of the original video frames, and a decoder of the error-control code corrects the errors in the side information with the syndrome bits. The noisy observation, i.e., the side information can be understood as the output of a virtual channel corresponding to the orignal video frames, and the conditional probability of the virtual channel model is assumed to follow a Laplacian distribution. Thus, performance improvement of DVC systems depends on performances of the error-control code and the optimal reconstruction step in the DVC decoder. In turn, the performances of two constituent blocks are directly related to a better estimation of the parameter of the correlation channel. In this paper, we propose an algorithm to estimate the parameter of the correlation channel and also a low-complexity version of the proposed algorithm. In particular, the proposed algorithm minimizes squared-error of the Laplacian probability distribution and the empirical observations. Finally, we show that the conventional algorithm can be improved by adopting a confidential window. The proposed algorithm results in PSNR gain up to 1.8 dB and 1.1 dB on Mother and Foreman video sequences, respectively.

• The Journal of the Acoustical Society of Korea
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• v.21 no.6
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• pp.552-558
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• 2002

Recently, based on the human speech recognition (HSR) model of Fletcher, the multi-band speech recognition has been intensively studied by many researchers. As a new automatic speech recognition (ASR) technique, the multi-band speech recognition splits the frequency domain into several sub-bands and recognizes each sub-band independently. The likelihood scores of sub-bands are weighted according to reliabilities of sub-bands and re-combined to make a final decision. This approach is known to be robust under noisy environments. When the noise is stationary a sub-band SNR can be estimated using the noise information in non-speech interval. However, if the noise is non-stationary it is not feasible to obtain the sub-band SNR. This paper proposes the inverse sub-band distance (ISD) weighting, where a distance of each sub-band is calculated by a stochastic matching of input feature vectors and hidden Markov models. The inverse distance is used as a sub-band weight. Experiments on 1500∼1800㎐ band-limited white noise and classical guitar sound revealed that the proposed method could represent the sub-band reliability effectively and improve the performance under both stationary and non-stationary band-limited noise environments.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.2
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• pp.93-98
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• 2016

For accurate precipitation forecasts the choice of weather factors and prediction method is very important. Recently, machine learning has been widely used for forecasting precipitation, and artificial neural network, one of machine learning techniques, showed good performance. In this paper, we suggest a new method for forecasting precipitation using DBN, one of deep learning techniques. DBN has an advantage that initial weights are set by unsupervised learning, so this compensates for the defects of artificial neural networks. We used past precipitation, temperature, and the parameters of the sun and moon's motion as features for forecasting precipitation. The dataset consists of observation data which had been measured for 40 years from AWS in Seoul. Experiments were based on 8-fold cross validation. As a result of estimation, we got probabilities of test dataset, so threshold was used for the decision of precipitation. CSI and Bias were used for indicating the precision of precipitation. Our experimental results showed that DBN performed better than MLP.