• ETRI Journal
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• v.41 no.6
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• pp.782-796
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• 2019

This paper presents a hierarchical framework for managing the sampling distribution of a particle filter (PF) that estimates the global positions of mobile robots in a large-scale area. The key concept is to gradually improve the accuracy of the global localization by fusing sensor information with different characteristics. The sensor observations are the received signal strength indications (RSSIs) of Wi-Fi devices as network facilities and the range of a laser scanner. First, the RSSI data used for determining certain global areas within which the robot is located are represented as RSSI bins. In addition, the results of the RSSI bins contain the uncertainty of localization, which is utilized for calculating the optimal sampling size of the PF to cover the regions of the RSSI bins. The range data are then used to estimate the precise position of the robot in the regions of the RSSI bins using the core process of the PF. The experimental results demonstrate superior performance compared with other approaches in terms of the success rate of the global localization and the amount of computation for managing the optimal sampling size.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.1
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• pp.41-48
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• 2014

This paper analyzes the Monte Carlo localization (MCL) method, which estimates the pose of an indoor mobile robot. A mobile robot must know where it is to navigate in an indoor environment. The MCL technique is one of the most influential and popular techniques for estimation of robot position and orientation using a particle filter. For the analysis, we perform experiments in an indoor environment with a differential drive robot and ultrasonic range sensor system. The analysis uses MATLAB for implementation of the MCL and investigates the effects of the control parameters on the MCL performance. The control parameters are the uncertainty of the motion model of the mobile robot and the noise level of the measurement model of the range sensor.

• Journal of the Korean Geophysical Society
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• v.6 no.2
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• pp.79-87
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• 2003

An in-situ four-electrode contact resistivity probe system was designed, and field-tested in submarine sediments. Seismic survey was also performed to support and compare the results of electric survey. The probe was designed to be driven to selected depths below the seafloor using a Vibracore system. The four insulated electrodes were, spaced equidistant across the wedge, were extended beyond the probe tip to minimize effects of sediment disturbance by the wedge insertion. In-situ measurements of resistivity were recorded on board by precision electronic equipment consisting of signal generators and processors, and by temperature- monitoring systems. Overall limits of uncertainty at respective depths below the seafloor are up to ±10% of the measured values. Best estimates of conductivity are considered to be ±3 percent of the reported values. Resistivity measurements were made at six sites in carbonate sediments to a maximum depth of penetration of about 5 m. Average values of conductivity range between 0.88 and 1.21 mho/m. The results show the seabed is composed of alternating layers of relatively high-conductivity material (0.8 to 1.4 mho/m) in thicknesses of more or less one meter and layers about 30 cm thick having relatively low conductivities (0.4 to 0.8 mho/m).

• Journal of Korea Multimedia Society
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• v.13 no.6
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• pp.890-900
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• 2010

The Bayesian networks methods provide an efficient tool for performing information fusion and decision making under conditions of uncertainty. This paper proposes Bayes estimators for the system effectiveness in energy saving of the wireless sensor networks by use of the Bayesian method under the non-informative prior knowledge about means of active and sleep times based on time frames of sensor nodes in a wireless sensor network. And then, we conduct a case study on some Bayesian estimation models for the system energy saving effectiveness of a wireless sensor network, and evaluate and compare the performance of proposed Bayesian estimates of the system effectiveness in energy saving of the wireless sensor network. In the case study, we have recognized that the proposed Bayesian system energy saving effectiveness estimators are excellent to adapt in evaluation of energy efficiency using non-informative prior knowledge from previous experience with robustness according to given values of parameters.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.1
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• pp.49.1-49.1
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• 2011

Utilizing single-epoch spectra and the empirical relation between the size of the broad-line region and AGN continuum luminosity, the so-called single-epoch method has been widely used for estimating AGN black hole masses. However, the systematic uncertainties and the potential biases of this method are not well examined. Taking the full advantage of the high-quality homogeneous spectra from the Lick AGN Monitoring Project (LAMP), we investigate in detail the uncertainties of single-epoch mass estimates by comparing with the reverberation-mapping results. We find that the uncertainty due to AGN variability is less than 0.1 dex, while there is a systematic offset between single-epoch masses and reverberation masses. Particularly, narrow-line Seyfert 1 galaxies show that the Hbeta line widths measured from single-epoch (or mean) spectra are systematically larger than those from rms spectra, indicating a potential bias of single-epoch masses. We will present the detailed measurement method, the test of virial assumption, and the systematic uncertainties.

• Structural Engineering and Mechanics
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• v.25 no.3
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• pp.331-345
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• 2007

Uncertainties enter a complex analysis from a variety of sources: variability, lack of data, human errors, model simplification and lack of understanding of the underlying physics. However, for many important engineering applications insufficient data are available to justify the choice of a particular probability density function (PDF). Sometimes the only data available are in the form of interval estimates which represent, often conflicting, expert opinion. In this paper we demonstrate that Bayesian estimation techniques can successfully be used in applications where only vague interval measurements are available. The proposed approach is intended to fit within a probabilistic framework, which is established and widely accepted. To circumvent the problem of selecting a specific PDF when only little or vague data are available, a hierarchical model of a continuous family of PDF's is used. The classical Bayesian estimation methods are expanded to make use of imprecise interval data. Each of the expert opinions (interval data) are interpreted as random interval samples of a parent PDF. Consequently, a partial conflict between experts is automatically accounted for through the likelihood function.

• Korean Journal of Veterinary Research
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• v.46 no.2
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• pp.159-164
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• 2006

A stochastic simulation model incorporated with Reed-Frost approach was derived for evaluating diagnostic performance of a test used for a screening program of an infectious disease. The Reed-Frost model was used to characterize the within-herd spread of the disease using a hypothetical example. Specifically, simulation model was aimed to estimate the number infected animals in an infected herd, in which imperfect serologic tests are performed on samples taken from herds and to illustrate better interpreting survey results at herd-level when uncertainty inevitably exists. From a risk analysis point of view, model output could be appropriate in developing economic impact assessment models requiring probabilistic estimates of herd-level performance in susceptible populations. The authors emphasize the importance of knowing the herd-level diagnostic performance, especially in performing emergency surveys in which immediate control measures should be taken following the survey. In this context this model could be used in evaluating efficacy of a survey program and monitoring infection status in the area concerned.

• Journal of Korean Society for Quality Management
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• v.29 no.3
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• pp.49-65
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• 2001

This paper presents new compromise ALT plan which is applied to situations that true relationship between stress and parameters is not known exactly. The assumed failure distribution of this study is one of location-scale family, i. e., exponential, Weibull, and lognormal distributions which have been ones of the popular choices of failure distributions. The method of applying the stress is constant, and the censoring mechanism is Type I censoring. Compared with existing compromise plans under true simple linear model in terms of statistical efficiency, the efficiency of new compromise plan is better than the corresponding other compromise ones in most cases. For case when true model is quadratic, this plan can be used without any severe loss in statistical efficiency. The proposed new compromise ALT plan is illustrated with a numerical example and sensitivity analyses are conducted to study effects of pre-estimates of design parameters.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2018.05a
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• pp.72-73
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• 2018

The accuracy of contingency estimation plays an important role for dealing with the uncertainty of the financial success of construction project. Its' estimation may be used for various purposes such as schedule control, emergency resolve, and quality expense, etc. This paper presents a contingency estimation method which is schedule control specific. The method 1) implements stochastic EVMS, 2) detects a specific timing for schedule compression, 3) identifies an optimal strategy for shortening planned schedule, 4) finds a probability density function (PDF) of project cost overrun, and 5) estimates the optimal contingency cost based on the level of confidence. The method facilitates expeditious decisions involved in project budgeting. The validity of the method is confirmed by performing test case.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.10a
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• pp.126-133
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• 2008

Geotechnical limit state design methods; LRFD of North America is an approach that estimates resistance using design model and then multiplies resistance factor by calculated resistance to reflect the uncertainty of geomaterials and design models; whereas, Eurocode of the Europe employs the partial resistance factor applied directly to each variable in the resistance equation that individual soil properties such as cohesion and angle of internal friction are applied. This discussion paper is a study on characteristic value which has globally been argued through processing of development of Eurocode 7 for geotechnical design even to the present. Estimating the characteristic value of soil properties affects not only determination of design value applied directly to design of geotechnical structures, but also economic feasibility and stability of the structures.