• Journal of Sensor Science and Technology
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• v.26 no.4
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• pp.286-291
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• 2017

With regards to heading estimation using gyroscope and magnetometer signals, magnetic disturbance added in the magnetometer signals is a main degradation factor in the estimation accuracy. Although there are a number of existing mechanisms that may properly compensate for the magnetic disturbances, they are designed to react only to the magnetic disturbances, but not to the time derivative of disturbances. Note that the sensors may experience abrupt changes in the magnetic disturbances, particularly for ambulatory applications. This paper proposes a magnetic disturbance model-embedded heading estimation filter for time-varying magnetic environments. The proposed magnetic disturbance model is based on a first-order Markov chain with a conditional switching technique depending on the time derivative of disturbances. Once a high amount of derivative is detected, the corrupted magnetometer signals are discarded to protect the filter from them. In our experimental results, the averaged heading error of tests was $1.46^{\circ}$, while that of the original approach without switching was $5.75^{\circ}$.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.17 no.3
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• pp.103-109
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• 2003

The validity of measured data is fundamental factor for the power system automation Measured values could have errors that are caused by the communication errors and malfunctioning measuring devices. The accuracy and reliability of measured values at a substation is an important condition for robust and fault tolerant automata. Errors can be reduced by state estimation, however, global reliability of state estimation goes down in case of the existence of some bad data In this paper, a least square state estimation and bad sensor detection algorithm based on chi-square theory, ale proposed and it is applied to a domestic 154kV distribution substations. A simulator together with user friendly graphic users interface is developed using C language and Visual Basic. TCP/IP is equipped for future connection with other operation systems.

• Journal of the Korean Institute of Landscape Architecture
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• v.20 no.4
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• pp.26-38
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• 1993

The purpose of this study was to suggest objective basic data for landscape research which cotained interdiciplinary approach between ecological and psychophysical method. For this, the naturalness and preference in greenary space, spatial image structure of physical elements have been analyzed by correlation coefficient and factor analysis algorithm. The results are as follows; 1. The relation between the estimation of naturalness and the preference in natural forest was deeply correlated. And the estimation of naturalness was higher than the estimation of DGN(Degree of Green Naturality). 2. The estimation of naturalnesss was decided by the physical features of forest and was different from the DGN. 3. Factors covering the spatial image of the forests have been found to be the 'overall evaluation', 'ability', 'naturalness' and 'idiosyncracy'. By using the control method for the number of factors, T.V. has been obtained as 61.68%. 4. The factors of the 'overall evauation', 'naturalness' were found to be the main factors determining the visual preference of greenary space.

• Nuclear Engineering and Technology
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• v.56 no.10
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• pp.4149-4157
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• 2024

Welding processes are used to connect several components in nuclear power plants. These welding processes can induce residual stress in welding joints, which has been identified as a significant factor in primary water stress corrosion cracking. Consequently, the assessment of welding residual stress plays a crucial role in determining the structural integrity of welded joints. In this study, a deep fuzzy neural networks (DFNN) with a rule-dropout method, which is an artificial intelligence (AI) method, was used to predict the residual stress of dissimilar metal welding. ABAQUS, a finite element analysis program, was used as the data collection tool to develop the AI model, and 6300 data instances were collected under 150 analysis conditions. A rule-dropout method and genetic algorithm were used to optimize the estimation performance of the DFNN model. DFNN with the rule-dropout model was compared to a deep neural network method, known as a general deep learning method, to evaluate the estimation performance of DFNN. In addition, a fuzzy neural network method and a cascaded support vector regression method conducted in previous studies were compared. Consequently, the estimation performance of the DFNN with the rule-dropout model was better than those of the comparison methods. The welding residual stress estimation results of this study are expected to contribute to the evaluation of the structural integrity of welded joints.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.8C
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• pp.617-626
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• 2008

Opportunistic Beamforming (OBF) offers a way to provide the multiuser diversity even in slow fading channel by using randomly generated beam weights, leading to the substantially reduced feedback in the form of the instantaneous SNR from users. In spite of the advantage of the reduced feedback, the imperfect channel estimation might influence the quality of the estimated SNR and channel scheduler so bad that the selected AMC level would be higher than the achievable rate of the actual channel, resulting the corruption of transmitted packet. In this paper, we propose a conservative link adaptation, where the estimated SNR is scaled down by a conservative factor which minimizes the variance of the maximum difference between the actual channel SNR and the resultant SNR. To support the proposed scheme, we analyze the statistics of the difference of the channel SNR and the estimated SNR. Simulation results show that the introduction of conservative factor achieves more than two-fold performance improvement in the presence of channel estimation error and the fairness of PF scheduler is maintained when the least squared channel estimator is applied.

• Journal of Environmental Science International
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• v.24 no.6
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• pp.743-753
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• 2015

In this study, it is an object to develop a regression model for the estimation of TOC (total organic carbon) concentration using investigated data for three years from 2010 to 2012 in the Gam Stream unit watershed, and applied in 2009 to verify the applicability of the regression model. TOC and $COD_{Mn}$ (chemical oxygen demand) were appeared to be derived the highest correlation. TOC was significantly correlated with 5 variables including BOD (biological oxygen demand), discharge, SS (suspended solids), Chl-a (chlorophyll a) and TP (total phosphorus) of p<0.01. As a result of PCA (principal component analysis) and FA (factor analysis), COD, TOC, SS, discharge, BOD and TP have been classified as a first factor. TOCe concentration was estimated using the model developed as an independent variable $BOD_5$ and $COD_{Mn}$. R squared value between TOC and measurement TOC is 0.745 and 0.822, respectively. The independent variable were added step by step while removing lower importance variable. Based on the developed optimal model, R squared value between measurement value and estimation value for TOC was 0.852. It was found that multiple independent variables might be a better the estimation of TOC concentration using the regression model equation(in a given sites).

• Journal of the Korean Institute of Gas
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• v.7 no.2 s.19
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• pp.7-13
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• 2003

Abstract This paper presents new emission mechanism and emission estimation model in volatile organic compounds(VOCs) emission sources. Also classifies applicable emission reduction techniques and presents new economical evaluation method for each techniques. We ultimately developed VEER(VOCs Emission Estimation and Reduction) software, which is backed by above mentioned model, emission source DB, Chemical properties DB, meteorological DB, and emission factor DB. With VEER, users in enterprise, central government and local self-governing body can get reliable emission results easily, and choose suitable emission reduction techniques.

• Journal of Korean Tunnelling and Underground Space Association
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• v.11 no.2
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• pp.141-150
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• 2009

When constructing a subsea tunnel in discontinuous rock mass, fluid flow in joints has a great influence on the behavior of the tunnel so that hydro-mechanical coupled analysis should be performed for the stability estimation. In practice, relaxed rock load is generally used for the design of tunnel concrete lining. In a continuum analysis, a method based on the distribution of local safety factor around a tunnel was proposed for the estimation of a potential relaxed zone. However, in the case of discontinuous rock mass in which joints are developed, the whole stability of tunnels depends on the behavior of the joints. In this study, therefore, a method is proposed for the estimation of a potential relaxed zone occurred by the excavation of a tunnel in discontinuous rock mass. The suggested method is validated by sensitivity analysis and the comparison with the results of continuum analysis.

• Explosives and Blasting
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• v.41 no.3
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• pp.73-92
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• 2023

With the increase of risk of gas explosion, various methods for indirectly estimating the explosion paramaters, which are required for the prediction of gas explosion scale and impact. In this study, the characteristics of the most frequently used methods such as TNT equivalent method, TNO multi-energy method, and BST method and the processes for determining the parameters of the methods were compared. In the case of TNT equivalent method, an adequate selection of the efficiency factor for various conditions such as the type of vapor cloud explosion and explosion material is needed. There is no objective guidelines for the selection of class number in TNO multi-energy method and it is not possible to estimate negative overpressure. It was found that there were some mistakes in the reported parameter values and suggested corrected values. BST method provides more detailed guidelines for the estimation of the explosion parameters including negative overpressure, but the graphs used in this methods are not clear. In order to overcome the problem, the graphs were redrawn. A more convenient estimation of explosion parameters with the numerical expression of the redrawn graphs will be available in the future.

• Proceedings of the Korea Concrete Institute Conference
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• 1993.04a
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• pp.142-147
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• 1993

In the reinforced concrete structure, as the height of building structure increases, the accurate estimation of differential column shortening is important factor in the structural design. In this study, the analysis of column shortening is applied to 36-story building structure to be built in time. As a result, it may found that, as the difference of compressive stress become larger, differential shortening effect due to creep and shrinkage are more signicant factor to structural designer.