• Environmental Engineering Research
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• v.21 no.4
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• pp.333-340
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• 2016

An Artificial Neural Network including a Radial Basis Function (RBF) and a Time Delay Neural Network (TDNN) was used to predict total dissolved solid (TDS) in the river Zayanderud. Water quality parameters in the river for ten years, 2001-2010, were prepared from data monitored by the Isfahan Regional Water Authority. A factor analysis was applied to select the inputs of water quality parameters, which obtained total hardness, bicarbonate, chloride and calcium. Input data to the neural networks were pH, $Na^+$, $Mg^{2+}$, Carbonate ($CO{_3}^{-2}$), $HCO{_3}^{-1}$, $Cl^-$, $Ca^{2+}$ and Total hardness. For learning process 5-fold cross validation were applied. In the best situation, the TDNN contained 2 hidden layers of 15 neurons in each of the layers and the RBF had one hidden layer with 100 neurons. The Mean Squared Error and the Mean Bias Error for the TDNN during the training process were 0.0006 and 0.0603 and for the RBF neural network the mentioned errors were 0.0001 and 0.0006, respectively. In the RBF, the coefficient of determination ($R^2$) and the index of agreement (IA) between the observed data and predicted data were 0.997 and 0.999, respectively. In the TDNN, the $R^2$ and the IA between the actual and predicted data were 0.957 and 0.985, respectively. The results of sensitivity illustrated that $Ca^{2+}$ and $SO{_4}^{2-}$ parameters had the highest effect on the TDS prediction.

• Structural Engineering and Mechanics
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• v.67 no.4
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• pp.359-368
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• 2018

In this paper, a method is presented to identify the physical and modal parameters of multistory shear building based on substructural technique using block pulse generalized operational matrix and genetic algorithm. The substructure approach divides a complete structure into several substructures in order to significantly reduce the number of unknown parameters for each substructure so that identification processes can be independently conducted on each substructure. Block pulse functions are set of orthogonal functions that have been used in recent years as useful tools in signal characterization. Assuming that the input-outputs data of the system are known, their original BP coefficients can be calculated using numerical method. By using generalized BP operational matrices, substructural dynamic vibration equations can be converted into algebraic equations and based on BP coefficient for each story can be estimated. A cost function can be defined for each story based on original and estimated BP coefficients and physical parameters such as mass, stiffness and damping can be obtained by minimizing cost functions with genetic algorithm. Then, the modal parameters can be computed based on physical parameters. This method does not require that all floors are equipped with sensor simultaneously. To prove the validity, numerical simulation of a shear building excited by two different normally distributed random signals is presented. To evaluate the noise effect, measurement random white noise is added to the noise-free structural responses. The results reveal the proposed method can be beneficial in structural identification with less computational expenses and high accuracy.

• Journal of Korean Society for Atmospheric Environment
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• v.15 no.5
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• pp.545-554
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• 1999

We would like to develop a short-term model to predict the time-related concentration of ozone whose reaction mechanism is complex. The paper targets Seoul where an ozone alert system has recently been employed. In order to develop a short-term prediction model for ozone, we suggested the Ozone Peak Indicator(OPI), an equivalent of the potential daily maximum ozone concentration, with precursors being the only limiting factor, and we calculated the Ozone Peak Indicarot as OPI={$rac{(O_3)_{max}cdot(H_{eH})_{max}(Rad)_{max}$ to preclude the influence of mixing height and solar radiation on the daily maximum ozone concentration. The OPI on the day of the prediction is to be calcultated by using the relation between OPI and the initial value of precursors. The basic prediction formula for time-related ozone concentration was established as $O_3(1)={(OPI)cdot Rad(t-2)H_{eH}}$, using the OPI, solar radiation two hours before prediction and mixing height. We developed, along with the basic formula for predicting photochemical oxidants, "SEOM"(Seoul Empirical Oxidants Model), a Fortran program that helps predict solar radiation and mixing height needed in the prediction of ozone pollution. When this model was applied to Seoul and an analysis of the correlation between the observed and the predicted ozone concentrations was made through SEOM, there appeared a very high correlation, with a coefficient of 0.815. SEOM can be described as a short-term prediction model for ozone concentration in large cities that takes into account the initial values of precursors, and changes in solar radiation and mixing height. SEOM can reflect the local characteristics of a particular and region can yield relatively good prediction results by a simple data input process.t process.

• 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.

• Elastomers and Composites
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• v.49 no.1
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• pp.73-81
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• 2014

Friction and wear behaviors of natural rubber(NR) compounds were investigated using a blade-type abrader. The effects of temperature, normal load, and rotation speed on wear rate were studied, and wear behaviors of deteriorated compounds were also evaluated. As the rotation speed of specimen and the normal load to specimen increased, the wear rate increased. However, as the experimental temperature increased, the frictional coefficient decreased and the wear rate decreased accordingly. It was found from the wear studies that a power-law relation works between the frictional work input and the wear rate. It was observed that the wear rate dramatically increased by the degradation of the rubber specimen. The wear pattern was developed and the bigger ridge space of the pattern was observed usually in the higher normal load applied. In determining the wear rate of rubber compound, the continuous measurements of wear distance using the blade-type abrader could be successfully used instead of intermittent measurements of wear-loss weight.

• Journal of Korean Society on Water Environment
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• v.23 no.5
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• pp.689-696
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• 2007

Kinetic analysis was important to develope the biological nutrient removal process effectively. In this research, anoxic-anaerobic-aerobic system was operated to investigate kinetic behavior on the nutrient removal reaction. Nitrification and denitrification were important microbiological reactions of nitrogen. The kinetics of organic removal and nitrification reaction have been investigated based on a Monod-type expression involving two growth limiting substrates : TKN for nitrification and COD for organic removal reaction. The kinetic constans and yield coefficients were evaluated for both these reactions. Experiments were conducted to determine the biological kinetic coefficients and the removal efficiencies of COD and TKN at five different MLSS concentrations of 5000, 4200, 3300, 2600, and 1900 mg/L for synthetic wastewater. Mathematical equations were presented to permit complete evaluation of the this system. Kinetic behaviors for the organic removal and nitrification reaction were examined by the determined kinetic coefficient and the assumed operation condition and the predicted model formulae using kinetic approach. The conclusions derived from this experimental research were as follows : 1. Biological kinetic coefficients were Y=0.563, $k_d=0.054(day^{-1})$, $K_S=49.16(mg/L)$, $k=2.045(day^{-1})$ for the removal of COD and $Y_N=0.024$, $k_{dN}=0.0063(day^{-1})$, $K_{SN}=3.21(mg/L)$, $k_N=31.4(day^{-1})$ for the removal of TKN respectively. 2. The predicted kinetic model formulae could determine the predicted concentration of the activated sludge and nitrifier, investigate the distribution rate of input carbon and nitrogen in relation to the solid retention time (SRT).

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.2
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• pp.97-105
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• 2015

This paper discusses the implementation of Bruun's FFT on a SIMD processor. FFT is an algorithm used in digital signal processing area and its effective processing is important in the enhancement of signal processing performance. Bruun's FFT algorithm is one of fast Fourier transform algorithms based on recursive factorization. Compared to popular Cooley-Tukey algorithm, it is advantageous in computations because most of its operations are based on real number multiplications instead of complex ones. However it shows more complicated data alignment patterns and requires a larger memory for storing coefficient data in its implementation on a SIMD processor. According to our experiment result, in the processing of the FFT with 1024 complex input data on a SIMD processor, The Bruun's algorithm shows approximately 1.2 times higher throughput but uses approximately 4 times more memory (20 Kbyte) than the Cooley-Tukey algorithm. Therefore, in the case with loose constraints on silicon area, the Bruun's algorithm is proper for the processing of FFT on a SIMD processor.

• Nuclear Engineering and Technology
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• v.52 no.8
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• pp.1871-1880
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• 2020

Round robin analyses for vessel failure probabilities due to PTS events are proposed for plant-specific analyses of all types of reactors developed in Korea. Four organizations, that are responsible for regulation, operation, research and design of the nuclear power plant in Korea, participated in the round robin analysis. The vessel failure probabilities from the probabilistic fracture mechanics analyses are calculated to assure the structural integrity of the reactor pressure vessel during transients that are expected to initiate PTS events. The failure probabilities due to various parameters are compared with each other. All results are obtained based on several assumptions about material properties, flaw distribution data, and transient data such as pressure, temperature, and heat transfer coefficient. The realistic input data can be used to obtain more realistic failure probabilities. The various results presented in this study will be helpful not only for benchmark calculations, result comparisons, and verification of PFM codes developed but also as a contribution to knowledge management for the future generation.

• Tuberculosis and Respiratory Diseases
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• v.39 no.3
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• pp.242-247
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• 1992

Background: The ability to precisely measure specific mRNA levels by hybridization to complementary DNA probes is an important tool for analyzing the regulation of gene expression. Surfactant proteins have important roles in regulating surfactant metabolism as well as in determing its physical properties. Method: The complete coding regions for rat surfactant protein complementary DNA of surfactant protein B were subcloned into pGem 3Z or 4Z such that either antisense or sense transcripts were obtained by using SP 6 RNA polymerase. Surfactant protein B mRNA was measured by filter hybridization. Results: Equation of standard curve between counts per minute (Y) and surfactant protein B mRNA transcript input (X) was Y=2034.9 X+159.1. Correlation coefficient was 1.0. Couclusions: Filter hybridization assay is suited to situation when rapid, accurate quantitation of multiple samples is required.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.1
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• pp.1-7
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• 2017

In this paper, a design method for a compact stepped open slot antenna for an operation in the UWB band is studied. The proposed antenna is miniaturized by inserting L-shaped slots on the ground plane of the stepped open slot antenna through the creation of a resonance in the low frequency, and a strip director is appended to the antenna in order to increase the gain in the middle and high frequency regions. The effects of varying the length of the L-shaped slots, the distance between the director and the slot antenna, and the director length on input reflection coefficient and realized gain characteristics of the proposed antenna are analyzed. The optimized antenna with the size of $30mm{\times}30mm$ is fabricated on an FR4 substrate, and the experiment results show that the antenna has a frequency band of 3.02-11.04 GHz for a VSWR < 2, which assures the operation in the UWB band.