• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.2
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• pp.82-98
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• 2009

This study applied SWAT model to analyze suspended sediment load that is influence on the high density turbid water in Donghyang and Cheoncheon basin, which are located in the upstream of Yongdam Dam. GIS data such as DEM, land cover map and soil map, and meteorological data were used as the input data of SWAT model. And the rating curve equation and Q-SS equation of Donghyang and Cheoncheon gauge station were applied as the measured values of them. As the result of flowout, the coefficient of determination ($R^2$) and the Nash-Sutcliffe coefficient of efficiency (EI) of model calibration showed high as 0.87 and 0.87 at Donghyang gauge station, and the $R^2$ and EI of model validation were high as 0.95 at Cheoncheon gauge station. Also, as the result of suspended sediment load, the $R^2$ and EI of model calibration were high as 0.77 and 0.76 at Donghyang gauge station, and the $R^2$ and EI of model validation marked high as 0.867 and 0.80 at Cheoncheon gauge station. It is considered that the suspended sediment load of 2003 showed the highest due to rainfall amounts and rainfall intensity in using SWAT model. The results of suspended sediment modeled in this study can be applied to the decision-making support data for the evaluation of soil erosion possibility and turbid water potential in the management of reservoir.

• Journal of Environmental Impact Assessment
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• v.23 no.6
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• pp.432-444
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• 2014

When the water quality modelling is done with a manual calibration, it is possible that the researcher's opinion may affect the objectivity of the research. Hence, the role of the automatic calibration is highly important. This research applies a technique to automatically calibrate the water quality parameters by implementing an optimization method. This involves estimating the optimum water quality parameters targeting influential parameters towards the lake's BOD, DO, Phosphorus, Nitrogen and Phytoplankton. To accurately calculate the water temperature and hydraulic characteristics of a deep, stratifying lake, EFDC, a 3-dimensional hydraulic model which can be linked to the WASP7 was applied. With EFDC, the segment of the lake is formed and utilized as an input data of the WASP7. For the calibration of the water quality parameters of the WASP7, an influence coefficient algorithm and a genetic algorithm was applied. Of the five water quality variables for calibration, the normalized residuals of the observed and calculated values of DO, TN, CBOD were relatively small and the three water quality variables were calibrated properly. Yet the accuracy of the calibration of TP and Chl-a was relatively low.

• Journal of Biosystems Engineering
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• v.37 no.3
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• pp.155-165
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• 2012

This study was performed to offer the data for design of the seedling bed transfer equipment to make the automation of working process in a plant factory. The seedling bed transfer equipment pushing the seedling bed with bearing wheels on the rail for interconnecting each working process by a pneumatic cylinder was made and examined. The examined transfer force to push the seedling bed with a weight of 178.9 N by the pneumatic cylinder with length of 60 cm and section area of 5 $cm^2$ was measured by experiments. The examined transfer forces was compared with theoretical ones calculated by the theoretical formula derived from dynamic system analysis according to the number of the seedling bed and pushing speed of the pneumatic cylinder head at no load. The transfer function of the equipment with the input variable as the pushing speed $V_{h0}$(m/s) and the output variable as the transfer force f(t)(N) was represented as $F(s)=(V_{h0}/k)(s+B/M)/(s(s^2+Bs/M+1/(kM))$ where M(kg), k(m/N) and B(Ns/m) are the mass of the bed, the compression coefficient of the pneumatic cylinder and the dynamic friction coefficient between the seedling bed and the rail, respectively. The examined transfer force curves and the theoretical ones were represented similar wave forms as to use the theoretical formular to design the device for the seedling bed transfer. The condition of no vibration of the transfer force curve was $kB^2>4M$. The condition of transferring the bed by the repeatable impact and vibration force according to difference of transfer distance of the pneumatic cylinder head from that of the bed was as $Ce^{-\frac{3{\pi}D}{2\omega}}<-1$, where ${\omega}=\sqrt{\frac{1}{kM}-\frac{B^2}{4M^2}}$, $C=\{\frac{\frac{B}{2M}-\frac{1}{kB}}{\omega}\}$, $D=\frac{B}{2M}$. The examined mean peak transfer force represented 4 times of the stead state transfer force. Therefore it seemed that the transfer force of the pneumatic cylinder required for design of the push device was 4Bv where v is the pushing speed.

• Science of Emotion and Sensibility
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• v.15 no.4
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• pp.503-516
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• 2012

According to the researches of robot and software agent until now, computational emotion model is dependent on system, so it is hard task that emotion models is separated from existing systems and then recycled into new systems. Therefore, I introduce the Engine of computational Emotion model (shall hereafter appear as EE) to integrate with any robots or agents. This is the engine, ie a software for independent form from inputs and outputs, so the EE is Emotion Generation to control only generation and processing of emotions without both phases of Inputs(Perception) and Outputs(Expression). The EE can be interfaced with any inputs and outputs, and produce emotions from not only emotion itself but also personality and emotions of person. In addition, the EE can be existed in any robot or agent by a kind of software library, or be used as a separate system to communicate. In EE, emotions is the Primary Emotions, ie Joy, Surprise, Disgust, Fear, Sadness, and Anger. It is vector that consist of string and coefficient about emotion, and EE receives this vectors from input interface and then sends its to output interface. In EE, each emotions are connected to lists of emotional experiences, and the lists consisted of string and coefficient of each emotional experiences are used to generate and process emotional states. The emotional experiences are consisted of emotion vocabulary understanding various emotional experiences of human. This study EE is available to use to make interaction products to response the appropriate reaction of human emotions. The significance of the study is on development of a system to induce that person feel that product has your sympathy. Therefore, the EE can help give an efficient service of emotional sympathy to products of HRI, HCI area.

• Journal of Korean Society of Environmental Engineers
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• v.31 no.4
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• pp.300-307
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• 2009

The transport of landfill leachate in the subsurface formations of unlined landfill sites is considered. The impacts of hydrogeological and chemical heterogeneities on the leachate transport are assessed by examining the results from a series of Monte-Carlo simulations. The landfill system simulated in this study is hypothetically represented with three levels of spatial variability for the hydrogeological and chemical parameter; (1) homogeneous hydraulic conductivity (K) and distribution coefficient ($K_d$), (2) K heterogeneity only, and (3) combined heterogeneities of K and $K_d$. To calculate the transport of leachate through negatively-correlated random hypothetical K-$K_d$ fields generated using geostatistical input parameters, a saturated flow model is linked with a contaminant transport model. Point statistic values such as mean, standard deviation, and coefficient of variation of the concentration were obtained from 100 Monte-Carlo trials. Results of point statistics show that the heterogeneities of K and $K_d$ in the landfill site prove to be an important parameter in controlling leachate concentrations. Consideration of combined K and $K_d$ heterogeneities results in enhancing the variability of contaminant transport. The variability in the leachate concentration for different realizations also increases as the distance between source and monitoring well increase.

• Korean Journal of Remote Sensing
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• v.29 no.4
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• pp.415-421
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• 2013

A new approach to retrieve the single-scattering albedo (SSA) of Asian dust plume, mixed with pollution particles, using multi-wavelength Raman lidar system was suggested in this study. Asian dust plume was separated as dust and non-dust particle (i.e. spherical particle) by the particle depolarization ratio at 532 nm. The vertical profiles of optical properties (the particle extinction coefficient at 355 and 532 nm and backscatter coefficient at 355, 532 and 1064 nm) for non-dust particle were used as input parameter for the inversion algorithm. The inversion algorithm provides the vertical distribution of microphysical properties of non-dust particle only so that the estimation of the SSA for the Asian dust in mixing state was suggested in this study. In order to estimate the SSA for the mixed Asian dust, we combined the SSA of non-dust particles retrieved by the inversion algorithms with assumed the SSA of 0.96 at 532 nm for dust. The retrieved SSA of Asian dust plume by lidar data was compared with the Aerosol Robotics Network (AERONET) retrieved values and showed good agreement.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1150-1158
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• 2010

In this study, the Polynomial-based Radial Basis Function Neural Networks is proposed as one of the recognition part of overall face recognition system that consists of two parts such as the preprocessing part and recognition part. The design methodology and procedure of the proposed pRBFNNs are presented to obtain the solution to high-dimensional pattern recognition problem. First, in preprocessing part, we use a CCD camera to obtain a picture frame in real-time. By using histogram equalization method, we can partially enhance the distorted image influenced by natural as well as artificial illumination. We use an AdaBoost algorithm proposed by Viola and Jones, which is exploited for the detection of facial image area between face and non-facial image area. As the feature extraction algorithm, PCA method is used. In this study, the PCA method, which is a feature extraction algorithm, is used to carry out the dimension reduction of facial image area formed by high-dimensional information. Secondly, we use pRBFNNs to identify the ID by recognizing unique pattern of each person. The proposed pRBFNNs architecture consists of three functional modules such as the condition part, the conclusion part, and the inference part as fuzzy rules formed in 'If-then' format. In the condition part of fuzzy rules, input space is partitioned with Fuzzy C-Means clustering. In the conclusion part of rules, the connection weight of pRBFNNs is represented as three kinds of polynomials such as constant, linear, and quadratic. Coefficients of connection weight identified with back-propagation using gradient descent method. The output of pRBFNNs model is obtained by fuzzy inference method in the inference part of fuzzy rules. The essential design parameters (including learning rate, momentum coefficient and fuzzification coefficient) of the networks are optimized by means of the Particle Swarm Optimization. The proposed pRBFNNs are applied to real-time face recognition system and then demonstrated from the viewpoint of output performance and recognition rate.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.12
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• pp.7-12
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• 2004

In this paper, CPW wideband distributed amplifier was designed and fabricated using 0.1 $\mum$ InGaAs/InAlAs/GaAs Metamorphic HEMT(High Electron Mobility Transistor). The DC characteristics of MHEMT are 442 mA/mm of drain current density, 409 mS/mm of maximum transconductance. The current gain cut-off frequency(fT) is 140 GHz and the maximum oscillation frequency(fmax) is 447 GHz. The distributed amplifier was designed using 0.1 $\mum$ MHEMT and CPW technology. We designed the structure of CPW curve, tee and cross to analyze the discontinuity characteristics of the CPW line. The MIMIC circuit patterns were optimized electromagnetic field through momentum. The designed distributed amplifier was fabricated using our MIMIC standard process. The measured results show S21 gain of above 6 dB from DC to 45 GHz. Input reflection coefficient S11 of -10 dB, and output reflection coefficient S22 of -7 dB at 45 GHz, respectively. The chip size of the fabricated CPW distributed amplifier is 2.0 mm$\times$l.2 mm.

• The Journal of the Acoustical Society of Korea
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• v.24 no.1
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• pp.29-37
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• 2005

This paper proposes an automatic genre classification system for Korean traditional music. The Proposed system accepts and classifies queried input music as one of the six musical genres such as Royal Shrine Music, Classcal Chamber Music, Folk Song, Folk Music, Buddhist Music, Shamanist Music based on music contents. In general, content-based music genre classification consists of two stages - music feature vector extraction and Pattern classification. For feature extraction. the system extracts 58 dimensional feature vectors including spectral centroid, spectral rolloff and spectral flux based on STFT and also the coefficient domain features such as LPC, MFCC, and then these features are further optimized using SFS method. For Pattern or genre classification, k-NN, Gaussian, GMM and SVM algorithms are considered. In addition, the proposed system adopts MFC method to settle down the uncertainty problem of the system performance due to the different query Patterns (or portions). From the experimental results. we verify the successful genre classification performance over $97{\%}$ for both the k-NN and SVM classifier, however SVM classifier provides almost three times faster classification performance than the k-NN.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.3
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• pp.52-65
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• 2012

The net biomass accumulation (or net primary production, NPP) and gross primary production (GPP) have closely related with carbon accumulations(or carbon exchange) in vegetation. There are many approaches to estimate biomass using remote sensing techniques. The vegetation indices (VIs) can be a methodology to estimate biomass which assumes total chlorophyll contents. Various VIs were characterized with difference development conditions as vegetation species, input datasets. The hyperspectral data have also different spatial/spectral resolutions for aerial surveying. Additionally they need particular spectral bands selection difficulty to calculate the VIs. The objective of this study is to evaluate the correlations with airborne hyperspectral data (compact airborne spectrographic imager, CASI) and spectral unmixing model (or spectral mixture analysis, SMA) to characterize vegetation indices in forest area. The spectral mixture analysis was used to model the spectral purity of each pixel as an endmember. The endmembers are the fraction components derived from hyperspectral data through the SMA. In this study, we choose three endmembers represented vegetation pixels in the hyperspectral data. These endmembers were compared with 9 VIs by the Pearson's correlation coefficient. The results show MTVI1 and TVI have same correlation coefficient with 0.877. The MCARI, especially has very high relationship with vegetation endmembers as 0.9061 at less vegetation and soil distributed site. The MTVI1 and TVI have high correlations with the vegetation endmembers as 0.757 in whole test sites.