• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.50
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• pp.373-380
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• 1999

This paper summerizes the former 5 papers that studied computer programming for the estimation of the Weibull, Extreme value, Hazard, Normal and Log-normal parameters which have a close relation with the reliability of the various kinds of industrial products. Probability paper is very commonly used in estimating the parameters, however, it is very hard to neglect the errors in plotting the data, and especially in drawing the regression line. The main purpose of this paper is to reduce these errors and to help the engineers to use the parameters in improving the reliability of their prod- ucts. The following parts are included in the computer programming with the em- phases on significant digits and rounding of numerical values : $\bullet$ data input part for various cases $\bullet$ parameter estimation part $\bullet$ printing part for input data $\bullet$ printing part for the results $\bullet$ printing part for the graphic(probability paper). And the running results(monitor displays) of the program for a fictitious example of Weibull distribution is given for the interested ones.

• KEPCO Journal on Electric Power and Energy
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• v.6 no.1
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• pp.35-40
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• 2020

The purpose of this paper is to improve the grounding point measurement method for the maintenance of the earth resistance of the distribution line. This study defines the correlation among humidity of the soil, the earth resistivity and the grounding resistance. Based on the results of the study, the grounding resistance value measurement should be limited to the location where the earth resistivity change is large, and the measurement time and cost can be greatly reduced.

• ETRI Journal
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• v.40 no.1
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• pp.101-110
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• 2018

In wireless positioning systems using range measurements non-line-of-sight (NLOS) links cause estimation errors. Several studies have attempted to improve the positioning performance by mitigating these NLOS errors. These studies, however, have focused on the performance of a dataset consisting of three or more links. Therefore, measurement errors induced by links are averaged, and a reliable link is not fully utilized in the dataset. This paper proposes a Link Reliability based on Range Measurement (LRRM) scheme, which specifies the relative reliability of each link using residuals. The link reliability becomes the input to a Link Residual Weighting (LRW) scheme, which is also proposed as a weighted positioning scheme. Moreover, LRRM and LRW constitute new turbo positioning, where the estimation errors are reduced considerably by iterative updates.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.9
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• pp.1249-1256
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• 2018

For the screening factor of the tunnel and overbridge structure in the electrified railway, the ITU-T regulation denotes only a theoretical estimation method, and the actual numeric values are notified differently by the official announcement of each nations. In this study, the factors which can affect the screening factor are investigated and analysed by FEM and a suitable calculation method based on multi-conductor line theory for the current pre-estimation formula for the induction noise voltage in the national notice is presented. The case studies are performed using the real data of the tunnel and the overbridge of the electrified railway, and a satisfactory formula for the determining of screening factor is derived.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.40.5-40
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• 2001

In this paper, a new on-line parameter estimation methodology for the general continuous time Takagi-Sugeno(T-S) fuzzy model whose parameters are poorly known or uncertain is presented. An estimator with an appropriate adaptive law for updating the parameters is designed and analyzed based on the Lyapunov theory. The adaptive law is designed so that the estimation model follows the plant parameterized model. By the proposed estimator, the parameters of the T-S fuzzy model can be estimated by observing the behavior of the system and it can be a basis for the indirect adaptive fuzzy control.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.1
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• pp.52-59
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• 1987

A new on-line estimation algorithm for a time varying time delay is proposed. This algorithm is based on the concept of minimization of prediction error. As only the parameters directly related to the poles and zeros of the process are estimated in the algorithm, persistently exciting condition for the convergence of parameters can be less restrictive. Under some assumptions which is necessary in adaptive control, it is shown that this algorithm estimates time varying time delay accurately. In view of computational burden, this algorithm needs far less amount of calculations than other methods. The larger the time delay is, the more effective this algorithm is . Computer simulation shows good properties of the algorithm. This algorithm can be used effectively in adaptive control of large dead time processes.

• The Bulletin of The Korean Astronomical Society
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• v.45 no.1
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• pp.63.1-63.1
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• 2020

We investigate the effect of recent star formation (RSF) on the α-elements-to-iron ratio ([α/Fe]) estimation for galaxies. Measuring galactic [α/Fe] is a powerful tool to pinpointing the timescale of chemical evolution and star formation. Our working hypothesis is that, with increasing stellar surface temperature, absorption equivalent width (EW) of α-elements decreases faster than that of Fe-peak elements, and thus RSF will lower the line ratio of EW(α)/EW(Fe). Moreover, young stars outshine, effectively lowering EW(α)/EW(Fe) of integrated light of RSF galaxies. Here we test our hypothesis using SDSS (optical spectrophotometric), GALEX (UV photometric) and IllustrisTNG datasets, and show that, if RSF is not considered thoroughly, EW(α)/EW(Fe) lowered by RSF can be routinely misinterpreted as low [α/Fe]. We discuss possible implications of the result in the context of the conventional [α/Fe]-mass relation of galaxies.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.1
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• pp.65-71
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• 2024

An indirect visual SLAM takes raw image data and exploits geometric information such as key-points and line edges. Due to various environmental changes, SLAM performance may decrease. The main problem is caused by dynamic objects especially in highly crowded environments. In this paper, we propose a robust feature-based visual SLAM, building on ORB-SLAM, via multi-channel dynamic objects estimation. An optical flow and deep learning-based object detection algorithm each estimate different types of dynamic object information. Proposed method incorporates two dynamic object information and creates multi-channel dynamic masks. In this method, information on actually moving dynamic objects and potential dynamic objects can be obtained. Finally, dynamic objects included in the masks are removed in feature extraction part. As a results, proposed method can obtain more precise camera poses. The superiority of our ORB-SLAM was verified to compared with conventional ORB-SLAM by the experiment using KITTI odometry dataset.

• Journal of Integrative Natural Science
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• v.17 no.3
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• pp.113-122
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• 2024

Advancements in sensor technology, particularly Inertial Measurement Units (IMU), are crucial in modern pose estimation. IMUs typically consist of accelerometers and gyroscopes (6-axis), with some models including magnetometers (9-axis). This study investigates the impact of sensor frequency on pose estimation accuracy using data from a 256Hz IMU sensor. The data sets analyzed include "spiralStairs," "stairsAndCorridor," and "straightLine," with frequencies varied to 128Hz, 64Hz, and 32Hz, and conditions categorized as stationary or dynamic. The results indicate that sensitivity remains high at lower frequencies under stationary conditions but declines in dynamic conditions. Performance comparison, based on Root Mean Square Error (RMSE) values, showed that lower frequencies lead to increased RMSE, thus diminishing model accuracy. Additionally, the Extended Kalman Filter (EKF) was tested as an alternative to Madgwick's algorithm but faced challenges due to insufficient sensor noise data.

• Structural Engineering and Mechanics
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• v.32 no.1
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• pp.95-126
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• 2009

The present contribution addresses the parallelization of advanced simulation methods for structural reliability analysis, which have recently been developed for large-scale structures with a high number of uncertain parameters. In particular, the Line Sampling method and the Subset Simulation method are considered. The proposed parallel algorithms exploit the parallelism associated with the possibility to simultaneously perform independent FE analyses. For the Line Sampling method a parallelization scheme is proposed both for the actual sampling process, and for the statistical gradient estimation method used to identify the so-called important direction of the Line Sampling scheme. Two parallelization strategies are investigated for the Subset Simulation method: the first one consists in the embarrassingly parallel advancement of distinct Markov chains; in this case the speedup is bounded by the number of chains advanced simultaneously. The second parallel Subset Simulation algorithm utilizes the concept of speculative computing. Speedup measurements in context with the FE model of a multistory building (24,000 DOFs) show the reduction of the wall-clock time to a very viable amount (<10 minutes for Line Sampling and ${\approx}$ 1 hour for Subset Simulation). The measurements, conducted on clusters of multi-core nodes, also indicate a strong sensitivity of the parallel performance to the load level of the nodes, in terms of the number of simultaneously used cores. This performance degradation is related to memory bottlenecks during the modal analysis required during each FE analysis.