• Communications of the Korean Mathematical Society
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• v.29 no.3
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• pp.489-496
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• 2014

We drive a closed-form expression for the price of a European quanto call option in the double square root stochastic volatility model.

• Geophysics and Geophysical Exploration
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• v.2 no.1
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• pp.54-62
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• 1999

This paper describes a datuming scheme for a prestack dataset which uses wavefield depth extrapolation. The formulation of the prestack datuming algorithm is performed by finding the adjoint operator to the corresponding forward prestack wavefield extrapolation from a flat surface to an irregular surface. Here I used double-square-root (DSR) equation to extrapolate wavefield in prestack sense. This correspond to the forward model of the well known `survey sinking` prestack imaging algorithm.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.24 no.8
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• pp.627-635
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• 2012

This study aims at developing an artificial neural network(ANN)-based predictive and adaptive temperature control method to control the openings at internal and external skins, and heating systems used in a building with double skin envelope. Based on the predicted indoor temperature, the control logic determined opening conditions of air inlets and outlets, and the operation of the heating systems. The optimization process of the initial ANN model was conducted to determine the optimal structure and learning methods followed by the performance tests by the comparison with the actual data measured from the existing double skin envelope. The analysis proved the prediction accuracy and the adaptability of the ANN model in terms of Root Mean Square and Mean Square Errors. The analysis results implied that the proposed ANN-based temperature control logic had potentials to be applied for the temperature control in the double skin envelope buildings.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.8
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• pp.393-400
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• 2016

Recently, there have been various researches on efficient and automatic analysis on urban environment methods that utilize the computer vision and machine learning technology. Among many new analyses, urban safety analysis has received a major attention. In order to predict more accurately on safety score and reflect the human visual perception, it is necessary to consider the generic and local information that are most important to human perception. In this paper, we use Double-column Convolutional Neural network consisting of generic and local columns for the prediction of urban safety. The input of generic and local column used re-sized and random cropped images from original images, respectively. In addition, a new learning method is proposed to solve the problem of over-fitting in a particular column in the learning process. For the performance comparison of our Double-column Convolutional Neural Network, we compare two Support Vector Regression and three Convolutional Neural Network models using Root Mean Square Error and correlation analysis. Our experimental results demonstrate that our Double-column Convolutional Neural Network model show the best performance with Root Mean Square Error of 0.7432 and Pearson/Spearman correlation coefficient of 0.853/0.840.

• Journal of Environmental Science International
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• v.26 no.4
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• pp.421-432
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• 2017

In this study, we examined the suitability of ten disinfection models for predicting the inactivation of Artemia sp. via single or combined physical and chemical treatments. The effect of Hydraulic Retention Time (HRT) on the inactivation of Artemia sp. was examined experimentally. Disinfection models were fitted to the experimental data by using the GInaFiT plug-in for Microsoft Excel. The inactivation model were evaluated on the basis of RMSE (Root Mean Square Error), SSE (mean Sum Square Error) and $r^2$. An inactivation model with the lowest RMSE, SSE and $r^2$ close to 1 was considered the best. The Weibull+Tail model was found to be the most appropriate for predicting the inactivation of Artemia sp. via electrolytic treatment and electrolytic-ultrasonic combined treatment. The Log-linear+Tail model was the most appropriate for modeling inactivation via homogenization and combined electrolytic-homogenization treatment. The double Weibull disinfection model was the most suitable for the predicting inactivation via ultrasonic treatment.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.34 no.12
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• pp.73-82
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• 2018

The objective of this study was to evaluate particle collection performance of electrostatic precipitator (ESP) integrated with double skin façade in naturally ventilated residential buildings using numerical method. To evaluate the efficiency, computational fluid dynamics (CFD) simulation based on electric potential and Lagrangian method was applied. The CFD model was validated by comparing the simulated results with the experimental data including thermal characteristic of double skin façade (DSF) and particle removal characteristic of electrostatic precipitator. The validation results showed that the root mean square error (RMSE) between predicted values and measured values of velocity and temperature in intermediate space of DSF was 1.2%. The adequacy of ion space charge density and turbulent model were determined. The RMSE between predicted values and measured values of collection efficiency of ESP was 9.2%. In addition, the case study was performed to present the application of the numerical method based on validation results of ESP integrated with façade.

• Journal of information and communication convergence engineering
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• v.11 no.3
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• pp.190-198
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• 2013

Recently, one of the most vital advancement in the field of finance is high-performance trading using field-programmable gate array (FPGA). The objective of this paper is to design high-performance Black Scholes option trading system on an FPGA. We implemented an efficient Black Scholes Call Option System IP on an FPGA. The IP may perform 180 million transactions per second after initial latency of 208 clock cycles. The implementation requires the 64-bit IEEE double-precision floatingpoint adder, multiplier, exponent, logarithm, division, and square root IPs. Our experimental results show that the design is highly efficient in terms of frequency and resource utilization, with the maximum frequency of 179 MHz on Altera Stratix V.

• ETRI Journal
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• v.33 no.4
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• pp.487-496
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• 2011

Korea Multi-Purpose Satellite-5 (KOMPSAT-5) is the first satellite in Korea that provides 1 m resolution synthetic aperture radar (SAR) images. Precise orbit determination (POD) using a dual-frequency IGOR receiver data is performed to conduct high-resolution SAR images. We suggest orbit determination strategies based on a differential GPS technique. Double-differenced phase observations are sampled every 30 seconds. A dynamic model approach using an estimation of general empirical acceleration every 6 minutes through a batch least-squares estimator is applied. The orbit accuracy is validated using real data from GRACE and KOMPSAT-2 as well as simulated KOMPSAT-5 data. The POD results using GRACE satellite are adjusted through satellite laser ranging data and compared with publicly available reference orbit data. Operational orbit determination satisfies 5 m root sum square (RSS) in one sigma, and POD meets the orbit accuracy requirements of less than 20 cm and 0.003 cm/s RSS in position and velocity, respectively.

• Geophysics and Geophysical Exploration
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• v.17 no.4
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• pp.242-246
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• 2014

Spectral induced polarization (SIP) is a useful technique, which uses electrochemical properties, for exploration of metallic sulfide minerals. Equivalent circuit analysis is commonly conducted to calculate IP parameters from SIP data. An equivalent circuit model, which indicates the SIP response of rock, has a non-uniqueness problem. For this reason, it is very important to select the proper model for accurate analysis. Thus, this study focused on suggesting a new model, which suitable for the analysis of an anomalous SIP response, such as ore. A suitability of the new model was verified by comparing it with the existing Dias model and Cole-Cole models. Analysis errors were represented as a normalized root mean square error (NRMSE). The analysis result using the Dias model was the NRMSE of 10.50% and was the NRMSE using the Cole-Cole model of 17.03%. Howerver, because the NRMSE of the new model is 0.87%, it is considered that the new model is more useful for analyzing the anomalous SIP data than other models.

• Journal of Korea Water Resources Association
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• v.45 no.8
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• pp.783-794
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• 2012

The analysis for unsteady flow is necessary to design the hydraulic structures affected by water level and discharge changes through time. The numerical model has been generally used for unsteady flow analysis, however it is difficult to acquire field data to calibrate and validate the numerical model. Even though it is possible to collect field data for some case, high cost and labor are required and sometimes it is considered that the confidence of measured data is very low. In this case, the experimental data for unsteady flow can be used to calibrate and validate the numerical model as an alternative. Therefore, the discharge-supply system which could generate various type of unsteady flow hydrograph was developed in this study. Also, the accuracy of the unsteady flow hydrograph generated by developed dischargesupply system in the experiment was evaluated by comparing with target hydrograph. Accuracy errors and Root Mean Square Error (RMSE) were analyzed for the rectangular-type hydrograph with sudden changes of flow, triangular-type hydrograph with short peak time, and bell-type flood hydrograph. As a result, the generating error of the discharge-supply system for the rectangular-type hydrograph was about 59% which was maximum error among various types. Also, it was represented that RMSE for the triangular-type hydrographs with single and double peaks were approximately corresponding to 10%. However, RMSE for the bell-type flood hydrograph was lower than 2%.