• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.12
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• pp.2511-2520
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• 2011

This paper describes the parameter adjustment method of fuzzy membership function to improve the performance of multi-sensor fusion system using adaptive fuzzy-Kalman filter and cross-validation. The adaptive fuzzy-Kanlman filter has two input parameters, variation of accelerometer measurements and residual error of Kalman filter. The filter estimates system noise R and measurement noise Q, then changes the Kalman gain. To evaluate proposed adaptive fuzzy-Kalman filter, we make the two-axis AHRS(Attitude Heading Reference System) using fusion of an accelerometer and a gyro sensor. Then we verified its performance by comparing to NAV420CA-100 to be used in various fields of airborne, marine and land applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.11
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• pp.3145-3162
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• 2023

As an important technology of the internetwork, wireless sensor network technique plays an important role in indoor localization. Non-line-of-sight (NLOS) problem has a large effect on indoor location accuracy. A location algorithm based on improved particle filter and directional probabilistic data association (IPF-DPDA) for WSN is proposed to solve NLOS issue in this paper. Firstly, the improved particle filter is proposed to reduce error of measuring distance. Then the hypothesis test is used to detect whether measurements are in LOS situations or NLOS situations for N different groups. When there are measurements in the validation gate, the corresponding association probabilities are applied to weight retained position estimate to gain final location estimation. We have improved the traditional data association and added directional information on the original basis. If the validation gate has no measured value, we make use of the Kalman prediction value to renew. Finally, simulation and experimental results show that compared with existing methods, the IPF-DPDA performance better.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.1
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• pp.108-114
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• 2014

This paper describes a method to set an intensity-based initial validation gate for tracking filter while preserves the ability of tracking a target with maximum speed. First, we collected real data set of signal versus distance of an airplane target. And at each data point, we computed maximum distance the target can move. And a function is modeled to expect the maximum moving pixels on the lateral direction based on the intensity of the detected target in IR image sequence. The initial prediction error covariance can be computed using this function to decide the size of the initial validation gate. The simulation results show the proposed method can set the appropriate initial validation gates to track the targets with the maximum speed.

• International Journal of Control, Automation, and Systems
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• v.6 no.3
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• pp.413-423
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• 2008

The template matching method is used as a simple method to track objects or patterns that we want to search for in the input image data from image sensors. It recognizes a segment with the highest correlation as a target. The concept of this method is similar to that of SNF (Strongest Neighbor Filter) that regards the measurement with the highest signal intensity as target-originated among other measurements. The SNF assumes that the strongest neighbor (SN) measurement in the validation gate originates from the target of interest and the SNF utilizes the SN in the update step of a standard Kalman filter (SKF). The SNF is widely used along with the nearest neighbor filter (NNF), due to computational simplicity in spite of its inconsistency of handling the SN as if it is the true target. Probabilistic Strongest Neighbor Filter for m validated measurements (PSNF-m) accounts for the probability that the SN in the validation gate originates from the target while the SNF assumes at any time that the SN measurement is target-originated. It is known that the PSNF-m is superior to the SNF in performance at a cost of increased computational load. In this paper, we suggest an image tracking algorithm that combines the template matching and the PSNF-m to estimate the states of a tracked target. Computer simulation results are included to demonstrate the performance of the proposed algorithm in comparison with other algorithms.

• Journal of the Korean Data and Information Science Society
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• v.15 no.2
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• pp.499-506
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• 2004

The Unscented Kalman Filter is known to outperform the Extended Kalman Filter for the nonlinear state estimation with a significance advantage that it does not require the computation of Jacobian but EKF has a competitive advantage to the UKF on the performance time. We compare both algorithms on training the artificial neural network. The validation data set is used to estimate parameters which are supposed to result in better fitting for the test data set. Experimental results are presented which indicate the performance of both algorithms.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.19 no.2
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• pp.81-87
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• 2009

Final purpose of this study was designed to develop the quality control(QC) sample for proficiency analytical testing of asbestos. This study consisted of two parts; first, development of manufacturing apparatus and sample preparing procedure for asbestos quality control(QC) sample: second, validation of the QC samples made by our developed method as asbestos proficiency analytical testing sample. The main results of the first part research are as followed We developed the apparatus for manufacturing the asbestos QC sample, consisted of filter hold, filter holder manifolder, vacuum system, and vacuum pump. The most proper filter of making the QC samples was a cellulose ester membrane filter with 25 mm diameter, pore size 0.8 um. And we presented the optimal procedure for preparing the asbestos QC sample by using the developed apparatus. We will verify the manufactured asbestos QC samples by this method, and present the validation results to confirm the reliability as a asbestos QC sample in next paper.

• Journal of Microbiology and Biotechnology
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• v.11 no.2
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• pp.326-328
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• 2001

Pseudomonas diminuta (ATCC 19146) has been typically used in the bacterial challenge test for validation of the sterilizing filtration process. Cell size is critical for determining the retention characteristics of membrane filters with pore-size of $0.2{\mu}m$. The changes of cell sizes after osmotic shocks at 150, 260, 500, and 700 mosM were measured by a particle size analyzer and the changes of their buoyant densities were analyzed with a Percoll gradient. The results indicated that there were no significant differences when cells were cultured in 260 mosM medium and osmotically shocked at 500 and 700 mosM. However, the osmotically shocked cells at 150 mosM showed a 38% increase of the cell size compared to the cells at 260 mosM. From these study, we concluded that the worst case condition for validation of a sterilizing filter would be 500 mosM, not because of changes in the cell size, but due to decrease in cell viability under those conditions.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.05a
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• pp.114-117
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• 2006

The air filter in engine intake system has a function of filtrating the dirt in the scavenging air as well as attenuating the noise. The noise attenuation within the air cleaner filter, however, has been regarded as negligible by the field engineers. In this paper, for the analysis of the acoustical performance of air filter, an acoustical model was suggested and the characteristics of air filter system were investigated. Fibrous structure of the filter element was modeled as a micro-perforated panel using the flow resistivity and porosity. The pleated geometry of the filter element was modeled as two coupled ducts that have permeable walls, in which each duct area was assumed being constant. Using such simplified geometry, a mathematical model was developed for the sound propagation within a narrow duct system. Visco-thermal effect was considered in modeling the sound propagation through such tubes; the filter box was modeled as a rigid rectangular box. By combining two models, a four-pole transfer matrix was derived. For the validation purpose, transmission loss was measured for a plastic rectangular box containing an air filter. A noticeable effect of the air filter element was observed by including the filter into the box. Comparing the predicted and measured data, we found that the predicted TL agrees well with experimental results, in particular, in magnitude and frequency at TL troughs.

• Journal of KIISE:Software and Applications
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• v.30 no.7_8
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• pp.744-751
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• 2003

A hybrid least square Support Vector Machine combined with First Principle(FP) knowledge is proposed. We compare hybrid least square Support Vector Machine(HLS-SVM) with early proposed models such as Hybrid Neural Network(HNN) and HNN with Extended Kalman Filter(HNN-EKF). In the training and validation stage HLS-SVM shows similar performance with HNN-EKF but better than HNN, whereas, in the testing stage, it shows three times better than HNN-EKF, hundred times better than HNN model.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.5
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• pp.401-408
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• 2017

This paper describes development and validation processes of a low-cost hardware based flight control computer designed for multi-rotor UAVs. The developed flight control computer controls multi-rotors stable and can handle complex flight missions using an integrated high-performance Linux computer. A complementary filter generates a navigation solution with 500 Hz, and a proposed observer significantly reduces measurement noise. A control algorithm utilizes a feed-forward term computed by a three-dimensional curve fitting method, and it increases tracking performance. The developed flight control system has been fully tested through several test flights, and it can apply to real flight environments.