• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.7
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• pp.99-106
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• 1996

Estimation and removal procedures for baseline drift have been developed using linear, cubic spline, and bilineared transformed high pass filter. Linear and cubic spline interpolation with the PQ and TP segmens, which are considered to be isoelectric, as fiducial points ahve been estimated respectively. For a quantitative validation of the estimation procedure, 4 ECGs with arfificial baseline drift were constructed and analyzed by mean square error calculations and amplitude histograms. Also real ECGs were analyzed in a test set of the CSE data set 3 and set 4. Baseline drift detecton rule were designed and new method for the decision of fiducial point were constructed to avoid distorting as the case of premature ventricular or atrial contraction. From these comparison, proposed cubic spline method with PQ and TP segment (CS_PQ & TP) emerged as the most efficient method.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.52
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• pp.1-8
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• 1999

This study was conducted to collect data concerning the preferred driving postures and adopted seat adjustment levels and to grasp relationships among drivers' body sizes, postural angles, and adopted seat positions and angles. Also optimum driving posture and seat adjustment level estimation models were constructed. An experiment was conducted to investigate observed optimum driving posture, and seat adjustment level. Thirty-six subjects (male=20, female=16) was selected to include a wide range of percentiles in the dimensions important for automotive driving workstation design and to be representative of the automotive driving population in Korea. New guidelines and estimation models for optimum postural comfort were developed. There were significant differences between male and female in postural angles but not in seat adjustment levels. Taller subjects preferred a more open and reclined posture. Estimation models enable us to estimate the quantitative optimum driving posture and seat adjustment level with some drivers' physical dimensions.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2011.05a
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• pp.191-192
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• 2011

The construction projects contain a lot of variables and risk affecting productivity. The duration of the project must be recognized important as for quality, unit cost and safety. There is need for improving work efficiency by investigating relationship of works to prevent delay. This study focuses on analysing the delay factors of steel staircase system to suggest regression model that enables construction productivity estimation. The position of the observers and construction delay factors were expressed by the independent variable of the regression model and productivity was expressed by a dependent variable. This paper suggests quantitative productivity and it is expected that will be helpful estimating application in construction new technologies.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.2
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• pp.273-282
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• 1996

This work is conceded with the estimation of output derivatives and their use for the design of robust controller for linear systems with system uncertainties due to modeling errors and disturbances. It is assumed that a nominal transfer function model and quantitative bounds for system uncertainties and known. The developed control schemes are shown to achieve regulation of the system output and ensures boundedness of the system states without imposing any structural conditions on system uncertainties and disturbances. Output derivative estimation is first conducted through restructuring of the plant in a specific parameterization. They are utilized for constructing robust nonlinear high-gain feedback controller of a SMC(Sliding Mode Control)type. The performances of the developed controller are evaluated and shown to be effective and useful through simulation study.

• Proceedings of the KWS Conference
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• 1992.10a
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• pp.91-95
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• 1992

The resistance spot welding process has been extensively used for joining of sheet metals, which are subject to variation of many process variables. Many qualitive analyses of sampled process variables have been attempted to predict nugget size. In this paper, dynamic resistance and electrode movement signal which is a good indicative of the nugget size was examined by introducing an artificial neural network estimator. An artificial neural feedforward network with back-propagation of error was applied for the estimation of the nugget size. The prediction by the neural network is in good agreement with the actual nugget size for resistance spot welding of galvanized steel. The results are quite promising in that the quantitative estimation of the invisible nugget size can be achieved without conventional destructive testing of welds.

• ETRI Journal
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• v.45 no.3
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• pp.379-393
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• 2023

Underwater communication (UWC) is widely used in coastal surveillance and early warning systems. Precise channel estimation is vital for efficient and reliable UWC. The sparse direct-adaptive filtering algorithms have become popular in UWC. Herein, we present an improved adaptive convex-combination method for the identification of sparse structures using a reweighted normalized leastmean-square (RNLMS) algorithm. Moreover, to make RNLMS algorithm independent of the reweighted l₁-norm parameter, a modified sparsity-aware adaptive zero-attracting RNLMS (AZA-RNLMS) algorithm is introduced to ensure accurate modeling. In addition, we present a quantitative analysis of this algorithm to evaluate the convergence speed and accuracy. Furthermore, we derive an excess mean-square-error expression that proves that the AZA-RNLMS algorithm performs better for the harsh underwater channel. The measured data from the experimental channel of SPACE08 is used for simulation, and results are presented to verify the performance of the proposed algorithm. The simulation results confirm that the proposed algorithm for underwater channel estimation performs better than the earlier schemes.

• Nuclear Engineering and Technology
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• v.52 no.9
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• pp.2119-2129
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• 2020

Flow-accelerated corrosion (FAC), liquid droplet impingement erosion (LDIE), cavitation and flashing can cause continuous wall-thinning in nuclear secondary pipes. In order to prevent pipe rupture events resulting from the wall-thinning, most NPPs (nuclear power plants) implement their management programs, which include periodic thickness inspection using UT (ultrasonic test). Meanwhile, it is well known in field experiences that the thickness measurement errors (or deviations) are often comparable with the amount of thickness reduction. Because of these errors, it is difficult to estimate wall-thinning exactly whether the significant thinning has occurred in the inspected components or not. In the previous study, the authors presented an approximate estimation procedure as the first step for thickness measurement deviations at each inspected component and the statistical & quantitative characteristics of the measurement deviations using plant experience data. In this study, statistical significance was quantified for the current methods used for wall-thinning determination. Also, the authors proposed new estimation procedures for determining local wall-thinning to overcome the weakness of the current methods, in which the proposed procedure is based on analysis of variance (ANOVA) method using subgrouping of measured thinning values at all measurement grids. The new procedures were also quantified for their statistical significance. As the results, it is confirmed that the new methods have better estimation confidence than the methods having used until now.

• Korean Journal of Ecology and Environment
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• v.57 no.2
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• pp.111-122
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• 2024

Zooplankton biomass is essential for understanding the quantitative structure of lake food webs and for the functional assessment of biotic interactions. In this study, we aimed to propose a biomass (dry weight) estimation method using the body length of cyclopoid copepods. These copepods play an important role as omnivores in lake zooplankton communities and contribute significantly to biomass. We validated several previously proposed estimation equations against direct measurements and compared the suitability of prosomal length versus total length of copepods to suggest a more appropriate estimation equation. After comparing the regression analysis results of various candidate equations with the actual values measured on a microbalance-using the coefficient of variation, mean absolute error, and coefficient of determination-it was determined that the Total Length-DW exponential regression equation [W=0.7775×e^2.0183L; W (㎍), L (mm)] could be used to calculate biomass with higher accuracy. However, considering practical issues such as the morphological similarity between species and genera of copepods and the limitations of classifying copepodid stages, we derived a general regression equation for the pooled copepod community rather than a species-specific regression equation.

• Journal of Soil and Groundwater Environment
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• v.17 no.6
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• pp.69-81
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• 2012

Diverse geostatistical tools such as kriging have been used to estimate the volume and spatial coverage of contaminated soil needed for remediation. However, many approaches frequently yield estimation errors, due to inherent geostatistical uncertainties. Such errors may yield over- or under-estimation of the amounts of polluted soils, which cause an over-estimation of remediation cost as well as an incomplete clean-up of a contaminated land. Therefore, it is very important to use a better estimation tool considering uncertainties arising from incomplete field investigation (i.e., contamination survey) and mathematical spatial estimation. In the current work, as better estimation tools we propose stochastic simulation approaches which allow the remediation volume to be assessed more accurately along with uncertainty estimation. To test the efficiency of proposed methods, heavy metals (esp., Pb) contaminated soil of a shooting range area was selected. In addition, we suggest a quantitative method to delineate the confident interval of estimated volume (and spatial extent) of polluted soil based on the spatial aspect of uncertainty. The methods proposed in this work can improve a better decision making on soil remediation.

• Journal of Korea Water Resources Association
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• v.51 no.5
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• pp.439-449
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• 2018

Many potential sources of bias are used in several steps of the radar-rainfall estimation process because the hydrological and meteorological radars measure the rainfall amount indirectly. Previous studies on radar-rainfall uncertainties were performed to reduce the uncertainty of each step by using bias correction methods in the quantitative radar-rainfall estimation process. However, these studies do not provide comprehensive uncertainty for the entire process and the relative ratios of uncertainty between each step. Consequently, in this study, a suitable approach is proposed that can quantify the uncertainties at each step of the quantitative radar-rainfall estimation process and show the uncertainty propagation through the entire process. First, it is proposed that, in the suitable approach, the new concept can present the initial and final uncertainties, variation of the uncertainty as well as the relative ratio of uncertainty at each step. Second, the Maximum Entropy Method (MEM) and Uncertainty Delta Method (UDM) were applied to quantify the uncertainty and analyze the uncertainty propagation for the entire process. Third, for the uncertainty quantification of radar-rainfall estimation at each step, two quality control algorithms, two radar-rainfall estimation relations, and two bias correction methods as post-processing through the radar-rainfall estimation process in 18 rainfall cases in 2012. For the proposed approach, in the MEM results, the final uncertainty (from post-processing bias correction method step: ME = 3.81) was smaller than the initial uncertainty (from quality control step: ME = 4.28) and, in the UDM results, the initial uncertainty (UDM = 5.33) was greater than the final uncertainty (UDM = 4.75). However uncertainty of the radar-rainfall estimation step was greater because of the use of an unsuitable relation. Furthermore, it was also determined in this study that selecting the appropriate method for each stage would gradually reduce the uncertainty at each step. Therefore, the results indicate that this new approach can significantly quantify uncertainty in the radar-rainfall estimation process and contribute to more accurate estimates of radar rainfall.