• Biomedical Science Letters
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• v.11 no.2
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• pp.129-134
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• 2005

Three different deconvolution techniques for quantifying cerebral blood flow (CBF) from whole brain $T2^{\ast}-weighted$ bolus tracking images were implemented (parametric Fourier transform P-FT, parametric single value decomposition P-SVD and nonparametric single value decomposition NP-SVD). The techniques were tested on 206 regions from 38 hyperacute stroke patients. In the P-FT and P-SVD techniques, the tissue and arterial concentration time curves were fit to a gamma variate function and the resulting CBF values correlated very well $(CBF_{P-FT}\;=\;1.02{\cdot}CBF_{p-SVD},\;r^2\;=\;0.96)$. The NP-SVD CBF values correlated well with the P-FT CBF values only when a sufficient number of time series volumes were acquired to minimize tracer time curve truncation $(CBF_{P-FT}\;=\;0.92{\cdot}CBF_{NP-SVD},\;r^2\;=\;0.88)$. The correlation between the fitted CBV and the unfitted CBV values was also maximized in regions with minimal tracer time curve truncation $(CBV_{fit}\;=\;1.00{\cdot}CBV_{ Unfit},\;^r^2\;=\;0.89)$. When a sufficient number of time series volumes could not be acquired (due to scanner limitations) to avoid tracer time curve truncation, the P-FT and P-SVD techniques gave more reliable estimates of CBF than the NP-SVD technique.

• Structural Engineering and Mechanics
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• v.19 no.6
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• pp.679-705
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• 2005

This paper presents a practical method to evaluate the effective length factors for columns in multi-storey unbraced frames based on the concept of storey-based elastic buckling by means of decomposing a multi-storey frame into a series of single-storey partially-restrained (PR) frames. The lateral stiffness of the multi-storey unbraced frame is derived and expressed as the product of the lateral stiffness of each storey. Thus, the stability analysis for the multi-storey frame is conducted by investigating the lateral stability of each individual storey, which is facilitated through decomposing the multi-storey frame into a series of single-storey PR frames and applying the storey-based stability analysis proposed by the authors (Xu and Liu 2002) for each single-storey PR frame. Prior to introducing decomposition approaches, the end rotational stiffness of an axially load column is derived and rotational stiffness interaction between the upper and lower columns is investigated. Three decomposition approaches, characterized by means of distributing beam-to-column rotational-restraining stiffness between the upper and lower columns, are proposed. The procedure of calculating storey-based column effective length factors is presented. Numerical examples are then given to illustrate the effectiveness of the proposed procedure.

• Journal of Korean Society of Rural Planning
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• v.22 no.4
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• pp.25-36
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• 2016

The purpose of this study is to construct a quantitative evaluation method that can analyze the policy effectiveness with the construction of a implicit composite index incorporating spatial econometrics models. In order to propose a methodological framework for the program evaluation, this study conducts an empirical analysis with the application of the Comprehensive Rural Village Development Project (CRVDP) which explicitly claims to achieve comprehensive goal of community development. The present study pays particular attention to quantifying the composite evaluation index and drawing net effect through the application of a series of spatial econometrics models. The spatial unit of the analysis is drawn at Eup-Myeon level in rural areas in Korea, and the time horizon is in between 2005 and 2010. We utilize the Korean Agricultural Census data in 2005 and 2010. Three steps of methodological processes are needed to satisfy the objective of the present study. First, we apply factor analysis to construct the composite index that represents comprehensive settlement environment in rural area. The index should be matched with the main objective of the CRVDP. Second, we apply the derived index to a series of spatial econometrics model as dependent variable. Lastly, utilizing the estimated coefficients of the econometrics models, we apply decomposition technique to estimate CRVDP's net effect from both cross-sectional and longitudinal perspectives. We find that the results of the decomposition analysis by the execution of the CRVDP are positively associated with the explicit object of the project.

• Journal of Korea Port Economic Association
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• v.27 no.2
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• pp.27-38
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• 2011

The paper aims at examining the behavioral characteristics of the passenger car export of Gunsan, Pyeongtaek, and Ulsan port. This is accomplished by modelling export demand as exchange rate and the Unites States industrial production. All series span the period January 2001 to December 2010. I first show that both the series and the residuals are stationary at the 5 percent significance level. The result cannot reject the null hypothesis of a unit root in each of the level variables and of a unit root for the residuals from the cointegration regression at the 5 percent significance level. I hitherto make use of forecast error decomposition and historical decompositions The forecast error decomposition indicates that car export is endogenous to industrial production and exchange rate. The historical decompositions for the export show that the entire difference between actual export and the base forecast can be attributed to industrial production shocks since exchange rate moves closer to the actual data or the base forecast. It indicates that industrial production outperforms exchange rate in explaining the passenger car exports.

• Journal of Korea Water Resources Association
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• v.52 no.12
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• pp.1075-1086
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• 2019

Recently, as the incidence of climate warming and abnormal climate increases, the forecasting of hydrological factors such as precipitation and river flow is getting more complicated, and the risk of water shortage is also increasing. Therefore, this study aims to develop a model for predicting the amount of water intake in mid-term. To this end, the correlation between water intake and meteorological factors, including temperature and precipitation, was used to select input factors. In addition, the amount of water intake increased with time series and seasonal characteristics were clearly shown. Thus, the preprocessing process was performed using the time series decomposition method, and the support vector machine (SVM) was applied to the residual to develop the river intake prediction model. This model has an error of 4.1% on average, which is higher accuracy than the SVM model without preprocessing. In particular, this model has an advantage in mid-term prediction for one to two months. It is expected that the water intake forecasting model developed in this study is useful to be applied for water allocation computation in the permission of river water use, water quality management, and drought measurement for sustainable and efficient management of water resources.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2007.11a
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• pp.477-481
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• 2007

The purpose of this study is to provide the ideal forecasting model of cadastral survey work load through the Economeatric Analysis of Time Series, Granger Causality and VAR Model Analysis, it suggested the forecasting reference materials for the total amount of cadastral survey general work load. The main result is that the derive of the environment variables which affect cadastral survey general work load and the outcome of VAR(vector auto regression) analysis materials(impulse response function and forecast error variance decomposition analysis materials), which explain the change of general work load depending on altering the environment variables. And also, For confirming the stability of time series data, we took a unit root test, ADF(Augmented Dickey-Fuller) analysis and the time series model analysis derives the best cadastral forecasting model regarding on general cadastral survey work load. And also, it showed up the various standards that are applied the statistical method of econometric analysis so it enhanced the prior aggregate system of cadastral survey work load forecasting.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.4
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• pp.593-600
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• 2003

Structural optimization often requires the evaluation of design sensitivities. The Semi Analytic Method(SAM) fur computing sensitivity is popular in shape optimization because this method has several advantages. But when relatively large rigid body motions are identified for individual elements. the SAM shows severe inaccuracy. In this study, the improvement of design sensitivities corresponding to the rigid body mode is evaluated by exact differentiation of the rigid body modes. Moreover. the error of the SAM caused by numerical difference scheme is alleviated by using a series approximation for the sensitivity derivatives and considering the higher order terms. Finally the present study shows that the refined SAM including the iterative method improves the results of sensitivity analysis in dynamic problems.

• Journal of Environmental Science International
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• v.24 no.8
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• pp.1023-1036
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• 2015

A reliable streamflow forecasting is essential for flood disaster prevention, reservoir operation, water supply and water resources management. This study proposes a hybrid model for river stage forecasting and investigates its accuracy. The proposed model is the wavelet packet-based artificial neural network(WPANN). Wavelet packet transform(WPT) module in WPANN model is employed to decompose an input time series into approximation and detail components. The decomposed time series are then used as inputs of artificial neural network(ANN) module in WPANN model. Based on model performance indexes, WPANN models are found to produce better efficiency than ANN model. WPANN-sym10 model yields the best performance among all other models. It is found that WPT improves the accuracy of ANN model. The results obtained from this study indicate that the conjunction of WPT and ANN can improve the efficiency of ANN model and can be a potential tool for forecasting river stage more accurately.

• Bulletin of the Korean Chemical Society
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• v.12 no.5
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• pp.560-564
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• 1991

The gas-phase pyrolysis reactions of iminoethers (Ⅱ), 2-alkoxypyridines (Ⅲ), 2-N-alkylated pyridones (Ⅳ) and N-alkylated acetamides (Ⅴ) have been studied MO theoretically with the AM1 method. The decomposition of these compounds proceeds by a concerted retro-ene process through a six-membered cyclic transition state. The reactivity decreases in the order (Ⅱ) > (Ⅲ) > (Ⅳ) > (Ⅴ), with a greater reactivity for the imine series, (Ⅱ) and (Ⅲ), compared to the amide series, (Ⅳ) and (Ⅴ), and a difference in basicity between the N and O atoms. Within a given series, however, the reactivity is dictated mainly by the aromaticity in the transition state. The reactivity order with respect to side alkyl chain of a species was found to increase as the steric crowding effect increases. The AM1 reactivity in this work agree well with the experimental results.

• Journal of Korean Society of Water and Wastewater
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• v.37 no.6
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• pp.383-394
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• 2023

Currently, there is no definitive regulation for the appropriate frequency of data sampling in water distribution networks, yet it plays a crucial role in the efficient operation of these systems. This study proposes a new methodology for determining the optimal frequency of data acquisition in water distribution networks. Based on the decomposition of signals using harmonic series, this methodology has been validated using actual data from water distribution networks. By analyzing 12 types of data collected from two points, it was demonstrated that utilizing the factors and cumulative periodograms of harmonic series enables similar accuracy at lower data acquisition frequencies compared to the original signals. Type your abstract here.