• Journal of Information Processing Systems
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• v.16 no.3
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• pp.530-540
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• 2020

In order to solve the problem of low tracking accuracy caused by complex noise in the fault diagnosis of complex nonlinear system, a fault diagnosis method of high precision cost reference particle filter (CRPF) is proposed. By optimizing the low confidence particles to replace the resampling process, this paper improved the problem of sample impoverishment caused by the sample updating based on risk and cost of CRPF algorithm. This paper attempts to improve the accuracy of state estimation from the essential level of obtaining samples. Then, we study the correlation between the current observation value and the prior state. By adjusting the density variance of state transitions adaptively, the adaptive ability of the algorithm to the complex noises can be enhanced, which is expected to improve the accuracy of fault state tracking. Through the simulation analysis of a fuel unit fault diagnosis, the results show that the accuracy of the algorithm has been improved obviously under the background of complex noise.

• Nuclear Engineering and Technology
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• v.49 no.6
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• pp.1157-1164
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• 2017

The Monte Carlo criticality simulation of decoupled systems, as for instance in large reactor cores, has been a challenging issue for a long time. In particular, due to limited computer time resources, the number of neutrons simulated per generation is still many order of magnitudes below realistic statistics, even during the start-up phases of reactors. This limited number of neutrons triggers a strong clustering effect of the neutron population that affects Monte Carlo tallies. Below a certain threshold, not only is the variance affected but also the estimation of the eigenvectors. In this paper we will build a time-dependent diffusion equation that takes into account both spatial correlations and population control (fixed number of neutrons along generations). We will show that its solution obeys a traveling wave dynamic, and we will discuss the mechanism that explains this biasing of local tallies whenever leakage boundary conditions are applied to the system.

• Journal of Korea Water Resources Association
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• v.32 no.6
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• pp.657-664
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• 1999

This paper introduced the basic theory of LRCS(Linear Reservoir and Channel System) rainfall runoff model proposed by Korean researchers(Lee and Lee, 1995), and discussed the change of model output according to objective functions in sensitivity analysis and calibration process of model. It proposed "hat" matrix and affluence measures for affluence analysis of parameters in calibration, and investigated relationship between change of model output according to error propagation in parameter estimation, and sensitivity of model output according to variance of model output and change of parameters. Accuracy of parameter estimates was known by analysis of sensitivity coefficient, diagonal element $h_i$ and $D_i$._i$.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.7 no.2
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• pp.1-6
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• 1989

The adjustment of levelling net is being done to the order of nets independently by using the least square method. For the small size net, it has difficulties in verification and statistical analysis of the net since the degree of freedom is low At the same time, it is also difficult to evaluate the error of lower order net correctly. The aim of this study is to analyse the properties of combined adjustment method compared with the independent adjustment method by using the data which have been measured during 1967-1987. Another aim is to analyse the influences of normal orthometric correction and changes of datum. Finally, Korean leveling net has been evaluated by applying real redundancy and variance component estimation.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.3
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• pp.75-85
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• 2021

This study evaluated variations in the paddy rice water demand based on the continuous changing in rice transplanting period and ponding depth at the four study paddy fields, which represent typical rice producing regions in Korea. Total 7 scenarios on rice transplanting periods were applied while minimum ponding depth of 0 and 20 mm were applied in accordance with maximum ponding depth ranging from 40 mm to 100 mm with 20 mm interval. The weather data from 2013 to 2019 was also considered. The results indicated that the highest rice water demand occurred at high temperature and low rainfall region. Increased rice transplanting periods showed higher rice water demand. The rice water demand for 51 transplanting days closely matched with the actual irrigation water supply. In case of ponding depth, the results showed that the minimum ponding depth had a proportional relationship with rice water demand, while maximum ponding depth showed the contrary results. Minimum ponding depth had a greater impact on rice water demand than the maximum ponding depth. Therefore, these results suggest that increasing the rice transplanting period, which reflects the current practice is desirable for a reliable estimation of rice water demand.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.819-826
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• 2021

This study aims to determine the impact of product consumption strategy and financial autonomy on the competitiveness of technology firms in Vietnam. This study employs panel data of 27 technology firms collected from listed financial statements of the business for the period (2010-2019). The study also uses some indicators reflecting the macroeconomic situation of the economy collected from the World Bank. Instead of Exploratory Factor Analysis which has been used before, the study uses the feasible generalized least squares (FGLS) estimation as the main method. The FGLS corrects the variance changes and autocorrelation on the dataset of these Vietnamese technology firms. The results reveal that the strategy of product consumption and financial autonomy positively affect the competitiveness of technology firms. These are also two core factors of the technology industry, which have a strong impact on the increase in the competitiveness of firms. The findings of this study suggest that technology firms do not need to invest in many long-term assets, but mainly in short-term assets in order to quickly respond to the strategies for consuming new technology products of the business. In addition, the increase in Gross Domestic Product per capita also positively affects the increase in the competitiveness of technology firms.

• Journal of information and communication convergence engineering
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• v.20 no.2
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• pp.79-89
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• 2022

To compute the mean and variance of component-based reliability software, we focused on path-based reliability analysis. System reliability depends on the transition probabilities of components within a system and reliability of the individual components as basic input parameters. The uncertainty in these parameters is estimated from the test data of the corresponding components and arises from the software architecture, failure behaviors, software growth models etc. Typically, researchers perform Monte Carlo simulations to study uncertainty. Thus, we considered a Markov chain Monte Carlo (MCMC) simulation to calculate uncertainty, as it generates random samples through sequential methods. The MCMC approach determines the input parameters from the probability distribution, and then calculates the average approximate expectations for a reliability estimation. The comparison of different techniques for uncertainty analysis helps in selecting the most suitable technique based on data requirements and reliability measures related to the number of components.

• Journal of Animal Science and Technology
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• v.55 no.1
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• pp.7-11
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• 2013

The purpose of this study was to estimate (co) variance components of three milk production traits for genetic evaluation using a multiple lactation model. Each of the first five lactations was treated as different traits. For the parameter estimation study, a data set was set up including lactations from cows calved from 2001 to 2009. The total number of raw lactation records in first to fifth parities reached 1,416,589. At least 10 cows were required for each contemporary group, herd-year-season effect. Sires with fewer than 10 daughters were discarded. Lactations with 305d milk yield exceeding 15,000 kg were removed. In total, 1,456 sires of cows were remained after all the selection steps. A complete pedigree consisting of 292,382 records was used for the study. A sire model containing herd-year-season, caving age, and sire additive genetic effects was applied to the selected lactation data and pedigree for estimating (co) variance components via VCE. Heritabilities and genetic or residual correlations were then derived from the (co) variance estimates using R package. Genetic correlations between lactations ranged from 0.76 to 0.98 for milk yield, 0.79~1.00 for fat yield, 0.75~1.00 for protein yield. On individual lactation basis, relatively low heritability values were obtained 0.14~0.23, 0.13~0.20 and 0.14~0.19 for milk, fat, and protein yields, respectively. For the combined lactation heritability values were 0.29, 0.28, and 0.26 for milk, fat, and protein yields. The estimated parameters will be used in national genetic evaluations for production traits.

• Journal of Global Scholars of Marketing Science
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• v.19 no.2
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• pp.17-26
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• 2009

As the lifestyle of consumers changes and the need for various products increases, new products are being developed in the market. Each household owns various home appliances which are purchased through the choice of a decision maker. These appliances include not only large-sized products such as TV, refrigerator, and washing machine, but also small-sized products such as microwave oven and air cleaner. There exists latent correlation among possession of home appliances, even though they are purchased independently. The purpose of this research is to analyze the effect of demographic factors on the purchase and possession of each home appliances, and to derive some relationships among various appliances. To achieve this purpose, the present status on the possession of each home appliances are investigated through consumer survey data on the electric and energy product. And a multivariate probit(MVP) model is applied for the empirical analysis. From the estimation results, some appliances show a substitutive or complementary pattern as expected, while others which look apparently unrelated have correlation by co-incidence. This research has several advantages compared to previous literatures on home appliances. First, this research focuses on the various products which are purchased by each household, while previous researches such as Matsukawa and Ito(1998) and Yoon(2007) focus just on a particular product. Second, the methodology of this research can consider a choice process of each product and correlation among products simultaneously. Lastly, this research can analyze not only a substitutive or complementary relationship in the same category, but also the correlation among products in the different categories. As the data on the possession of home appliances in each household has a characteristic of multiple choice, not a single choice, a MVP model are used for the empirical analysis. A MVP model is derived from a random utility model, and has an advantage compared to a multinomial logit model in that correlation among error terms can be derive(Manchanda et al., 1999; Edwards and Allenby, 2003). It is assumed that the error term has a normal distribution with zero mean and variance-covariance matrix ${\Omega}$. Hence, the sign and value of correlation coefficients means the relationship between two alternatives(Manchanda et al., 1999). This research uses the data of 'TEMEP Household ICT/Energy Survey (THIES) 2008' which is conducted by Technology Management, Economics and Policy Program in Seoul National University. The empirical analysis of this research is accomplished in two steps. First, a MVP model with demographic variables is estimated to analyze the effect of the characteristics of household on the purchase of each home appliances. In this research, some variables such as education level, region, size of family, average income, type of house are considered. Second, a MVP model excluding demographic variables is estimated to analyze the correlation among each home appliances. According to the estimation results of variance-covariance matrix, each households tend to own some appliances such as washing machine-refrigerator-cleaner-microwave oven, and air conditioner-dish washer-washing machine and so on. On the other hand, several products such as analog braun tube TV-digital braun tube TV and desktop PC-portable PC show a substitutive pattern. Lastly, the correlation map of home appliances are derived using multi-dimensional scaling(MDS) method based on the result of variance-covariance matrix. This research can provide significant implications for the firm's marketing strategies such as bundling, pricing, display and so on. In addition, this research can provide significant information for the development of convergence products and related technologies. A convergence product can decrease its market uncertainty, if two products which consumers tend to purchase together are integrated into it. The results of this research are more meaningful because it is based on the possession status of each household through the survey data.

• Journal of the Korea Computer Graphics Society
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• v.16 no.1
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• pp.9-20
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• 2010

In order to visualize participating media in 3D space, they usually calculate the incoming radiance by subdividing the ray path into small subintervals, and accumulating their respective light energy due to direct illumination, scattering, absorption, and emission. Among these light phenomena, scattering behaves in very complicated manner in 3D space, often requiring a great deal of simulation efforts. To effectively simulate the light scattering effect, several approximation techniques have been proposed. Volume photon mapping takes a simple approach where the light scattering phenomenon is represented in volume photon map through a stochastic simulation, and the stored information is explored in the rendering stage. While effective, this method has a problem that the number of necessary photons increases very fast when a higher variance reduction is needed. In an attempt to resolve such problem, we propose a different approach for rendering particle-based volume data where kernel smoothing, one of several density estimation methods, is explored to represent and reconstruct the light in-scattering effect. The effectiveness of the presented technique is demonstrated with several examples of volume data.