• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.6
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• pp.93-101
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• 2019

This study aims to analyze the influences of applications of two different evapotranspiration (ET) estimation methods on the irrigation water requirements (IWR) for paddy rice and water supply reliability of agricultural reservoirs. The modified Penman (MP), traditional method, and the Penman-Monteith (PM), the new adopted method, were applied on 149 reservoirs located in Honam province for this study. The weather date was used from 1987 to 2016, and analysed the trends of temperature and rainfall during rice growing season between past and current 10 years respectively. The increased average temperature and rainfall were observed from the current 10 years compared to the past years. This phenomena impacts on the results of ET and IWR estimations with decreased IWR obtained from high rainfall regions and increased ET obtained high temperature regions. For the comparisons of application results of two ET approaches, the PM method showed lower ET and IWR, and hence more reliable storage capacity of the reservoirs respect to water supply to paddy fields. The results also showed that the influences of different ET methods applications on the water supply reliability of reservoirs are negligible for the cases of over 3.7 watershed ratio and 670 mm unit reservoir storage, while significant variations of the results obtain from the applications between two ET approaches for the opposite cases. Further studies are necessary to consider various field conditions for practical applications of the PM method estimating ET in the fields of paddy farming.

• Structural Engineering and Mechanics
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• v.83 no.3
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• pp.327-340
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• 2022

The Collapse Margin Ratio (CMR) is a notable index used for seismic assessment of the structures. As proposed by FEMA P695, a set of analyses including the Nonlinear Static Analysis (NSA), Incremental Dynamic Analysis (IDA), together with Fragility Analysis, which are typically time-taking and computationally unaffordable, need to be conducted, so that the CMR could be obtained. To address this issue and to achieve a quick and efficient method to estimate the CMR, the Artificial Neural Network (ANN), Response Surface Method (RSM), and Adaptive Neuro-Fuzzy Inference System (ANFIS) will be introduced in the current research. Accordingly, using the NSA results, an attempt was made to find a fast and efficient approach to derive the CMR. To this end, 5016 IDA analyses based on FEMA P695 methodology on 114 various Reinforced Concrete (RC) frames with 1 to 12 stories have been carried out. In this respect, five parameters have been used as the independent and desired inputs of the systems. On the other hand, the CMR is regarded as the output of the systems. Accordingly, a double hidden layer neural network with Levenberg-Marquardt training and learning algorithm was taken into account. Moreover, in the RSM approach, the quadratic system incorporating 20 parameters was implemented. Correspondingly, the Analysis of Variance (ANOVA) has been employed to discuss the results taken from the developed model. Additionally, the essential parameters and interactions are extracted, and input parameters are sorted according to their importance. Moreover, the ANFIS using Takagi-Sugeno fuzzy system was employed. Finally, all methods were compared, and the effective parameters and associated relationships were extracted. In contrast to the other approaches, the ANFIS provided the best efficiency and high accuracy with the minimum desired errors. Comparatively, it was obtained that the ANN method is more effective than the RSM and has a higher regression coefficient and lower statistical errors.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1B
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• pp.7-14
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• 2006

The radar relationship was estimated for the selected rainfall event at Yeongchun station within Chungjudam basin where the discharge record was the range of from 1,000 CMS to 9,000 CMS. By calibrating the rainfall coefficient parameter estimated by radar relationship in small hydrology basin, rainfall with the topography properties was calculated. Three different rainfall estimation methods were compared:(1) radar relationship method (2) Thiessen method (3) Isohyetal method (4) Inverse distance method. Basin model was built by applying HEC-GeoHMS which uses digital elevation model to extract hydrological characteristic and generate river network. The proposed basin model was used as an input to HEC-HMS to build a runoff model. The runoff estimation model applying radar data showed the good result. It is proposed that the radar data would produce more rapid and accurate runoff forecasting especially in the case of the partially concentrated rainfall due to the atmospheric change. The proposed radar relationship could efficiently estimate the rainfall on the study area(Chungjudam basin).

• Korean Journal of Remote Sensing
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• v.28 no.4
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• pp.435-448
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• 2012

Evapotranspiration (ET) including evaporation from a land surface and transpiration from photosynthesis of vegetation is a sensitive hydrological factor with outer circumstances. Though both direct measurements with an evaporation pan and a lysimeter, and empirical methods using eddy covariance technique and the Bowen ratio have been widely used to observe ET accurately, they have a limitation that the observation can stand for the exact site, not for an area. In this study, remote sensing technique is adopted to compensate the limitation of ground observation using the Moderate Resolution Imaging Spectroradiometer (MODIS) multispectral sensor mounted on Terra satellite. We improved to evapotranspiration model based on remote sensing (Mu et al., 2007) and estimated Penman-Monteith evapotranspiration considering regional characteristics of Korea that was using only MODIS product. We validated evapotranspiration of Sulma (SMK)/Cheongmi (CFK) flux tower observation and calculation. The results showed high correlation coefficient as 0.69 and 0.74.

• 한국신재생에너지학회:학술대회논문집
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• 2010.11a
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• pp.73.1-73.1
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• 2010

For the successful cold starting of a fuel cell engine, either internal of external heat supply must be made to overcome the formation of ice from water below the freezing point of water. In the present study, switchable vanadium oxide compounds as variable temperature-electrical resistance materials onto the surface of flat metallic bipolar plates have been prepared by a dip-coating technique via an aqueous sol-gel method. Subsequently, the chemical composition and micro-structure of the polycrystalline solid thin films were analyzed by X-ray diffraction, X-ray fluorescence spectroscopy, and field emission scanning electron microscopy. In addition, it was carefully measured electrical resistance hysteresis loop over a temperature range from $-20^{\circ}C$ to $80^{\circ}C$ using the four-point probe method. The experimental results revealed that the thin films was mainly composed of Karelianite $V_2O_3$ which acts as negative temperature coefficient materials. Also, it was found that thermal dissipation rate of the vanadium oxide thin films partially satisfy about 50% saving of the substantial amount of energy required for ice melting at $-20^{\circ}C$. Moreover, electrical resistances of the vanadium-based materials converge on an extremely small value similar to that of pure flat metallic bipolar plates at higher temperature, i.e. $T{\geq}40^{\circ}C$. As a consequence, experimental studies proved that it is possible to apply the variable temperature-electrical resistance material based on vanadium oxides for the cold starting enhancement of a fuel cell vehicle and minimize parasitic power loss and eliminate any necessity for external equipment for heat supply in freezing conditions.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.2 s.302
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• pp.31-38
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• 2005

Recently, Biometrics-based personal identification is regarded as an effective method of person's identity with recognition automation and high performance. In this paper, the palmprint recognition method based on Hu invariant moment is proposed. And the low-resolution(750dpi) palmprint image$(5.5Cm\times5.5Cm)$ is used for the small scale database of the effectual palmprint recognition system. The proposed system is consists of two parts: firstly, the palmprint fixed equipment for the acquisition of the correctly palmprint image and secondly, the algorithm of the efficient processing for the palmprint recognition. And the palmprint identification step is limited 3 times. As a results, when the coefficient is 0.001 then FAR and GAR are $0.038\%$ and $98.1\%$ each other. The authors confirmed that FAR is improved $0.002\%$ and GAR is $0.1\%$ each other compared with [3].

• Journal of the Korean Chemical Society
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• v.55 no.5
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• pp.733-740
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• 2011

Multiple regression analysis was used for the calculation of pKa values of 15 substituted benzaldoximes by using various types of descriptors as parameters. These descriptors are based on quantum mechanical treatments. They were derived by employing semi-empirical calculation represented by the PM3 model and an Abinitio method expressed by Hartree-Fock(HF) model performed at the 6-311 G(d, p) level of theory. The parameters tested for their ability to represent the variations observed in the experimental pKa(s) are atomic and structural properties including Muliken charges on the atoms of hydroxyl group and C=N bond, the angle $C_6-C_1-C_7$, and length of O-H bond. Molecular properties are also used like energies of HOMO and LUMO, hardness(${\eta}$), chemical potential(${\mu}$), total energy(TE), dipole of molecule(DM), and electrophilicity index(W). The relation between pKa values and each of these parameters of the studied compounds is investigated. Depending on these relations, two sets of parameters were constructed for comparison between the PM3 and HF methods. The results obtained favor the Abinitio method for such applications although both models proved to have high predictive power and have sufficient reliability to describe the effect of substituents on pKa values of benzaldoxime compounds under consideration which is clear from the values of correlation coefficient $R^2$ obtained and the consistency between the experimental and the calculated values.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.44-44
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• 2017

The objective of this study was to evaluate firmness, and sweetness index (SI) of tomatoes (Lycopersicum esculentum) by using hyperspectral imaging (HSI) in the range of 1000-1400 nm. The mean spectra of the 95 matured tomato samples were extracted from the hyperspectral images, and the reference firmness and sweetness index of the same sample were measured and calibrated with their corresponding spectral data by partial least squares (PLS) regression with different preprocessing method. The results showed that the regression model developed by PLS regression based on Savitzky-Golay (S-G) second-derivative preprocessed spectra resulted in better performance for firmness, and SI of tomatoes compared to models developed by other preprocessing methods, with correlation coefficients (rpred) of 0.82, and 0.74 with standard error of prediction (SEP) of 0.86 N, and 0.63 respectively. Then, the feature wavelengths were identified using model-based variable selection method, i.e., variable important in projection (VIP), resulting from the PLS regression analyses and finally chemical images were derived by applying the respective regression coefficient on the spectral image in a pixel-wise manner. The resulting chemical images provided detailed information on firmness, and sweetness index (SI) of tomatoes. Therefore, these research demonstrated that HIS technique has a potential for rapid and non-destructive evaluation of the firmness and sweetness index of tomatoes.

• Journal of Ocean Engineering and Technology
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• v.28 no.6
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• pp.552-559
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• 2014

In general, the number of underwater transient signals is very limited for research on automatic recognition. Data-dependent feature extraction is one of the most effective methods in this case. Therefore, we suggest WPCC (Wavelet packet ceptsral coefficient) as a feature extraction method. A wavelet packet best tree for each data set is formed using an entropy-based cost function. Then, every terminal node of the best trees is counted to build a common wavelet best tree. It corresponds to flexible and non-uniform filter bank reflecting characteristics for the data set. A GMM (Gaussian mixture model) is used to classify five classes of underwater transient data sets. The error rate of the WPCC is compared using MFCC (Mel-frequency ceptsral coefficients). The error rates of WPCC-db20, db40, and MFCC are 0.4%, 0%, and 0.4%, respectively, when the training data consist of six out of the nine pieces of data in each class. However, WPCC-db20 and db40 show rates of 2.98% and 1.20%, respectively, while MFCC shows a rate of 7.14% when the training data consists of only three pieces. This shows that WPCC is less sensitive to the number of training data pieces than MFCC. Thus, it could be a more appropriate method for underwater transient recognition. These results may be helpful to develop an automatic recognition system for an underwater transient signal.

• Geomechanics and Engineering
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• v.5 no.5
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• pp.379-399
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• 2013

In practice, analysis of laterally loaded piles is carried out using beams on non-linear Winkler springs model (often known as p-y method) due to its simplicity, low computational cost and the ability to model layered soils. In this approach, soil-pile interaction along the depth is characterized by a set of discrete non-linear springs represented by p-y curves where p is the pressure on the soil that causes a relative deformation of y. p-y curves are usually constructed based on semi-empirical correlations. In order to construct API/DNV proposed p-y curve for clay, one needs two values from the monotonic stress-strain test results i.e., undrained strength ($s_u$) and the strain at 50% yield stress (${\varepsilon}_{50}$). This approach may ignore various features for a particular soil which may lead to un-conservative or over-conservative design as not all the data points in the stress-strain relation are used. However, with the increasing ability to simulate soil-structure interaction problems using highly developed computers, the trend has shifted towards a more theoretically sound basis. In this paper, principles of Mobilized Strength Design (MSD) concept is used to construct a continuous p-y curves from experimentally obtained stress-strain relationship of the soil. In the method, the stress-strain graph is scaled by two coefficient $N_C$ (for stress) and $M_C$ (for strain) to obtain the p-y curves. $M_C$ and $N_C$ are derived based on Semi-Analytical Finite Element approach exploiting the axial symmetry where a pile is modelled as a series of embedded discs. An example is considered to show the application of the methodology.