• Journal of the Korean Society for Precision Engineering
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• v.20 no.8
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• pp.213-220
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• 2003

By the localization of electro-chemical dissolution region, we succeeded in a few micrometer size hole drilling on stainless steel with the radial machining gap of about 1 ${\mu}{\textrm}{m}$. Tens of nanosecond duration voltage pulses were applied between WC micro-shaft and stainless steel in the 0.1 M $H_2SO_4$ solution. Pt balance electrode was used to drill the high aspect ratio micro-hole without generation of Cr oxide layer on the machined surface. The effects of applied voltage, pulse duration, and pulse period on localization distance were investigated according to machining time. We suggested the taper reduction technique especially brought up on blind-hole machining. High quality micro-holes with 8 ${\mu}m$ diameter with 20 ${\mu}m$ depth and 12 ${\mu}m$ diameter with 100 ${\mu}m$ depth were drilled on 304 stainless steel foil. The various hole shapes were also produced including stepped holes and taper free holes.

• BMB Reports
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• v.43 no.10
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• pp.677-682
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• 2010

Kv4.2, a pore-forming $\alpha$-subunit of voltage-gated A-type potassium channels, is expressed abundantly in the soma and dendrites of hippocampal neurons, and is responsible for somatodendritic $I_A$ current. Recent studies have suggested that changes in the surface levels of Kv4.2 potassium channels might be relevant to synaptic plasticity. Although the function and expression of Kv4.2 protein have been extensively studied, the dendritic localization of Kv4.2 mRNA is not well described. In this study, Kv4.2 mRNAs were shown to be localized in the dendrites near postsynaptic regions. The dendritic transport of Kv4.2 mRNAs were mediated by microtubule-based movement. The 500 nucleotides of specific regions within the 3'-untranslated region of Kv4.2 mRNA were found to be necessary and sufficient for its dendritic localization. Collectively, these results suggest that the dendritic localization of Kv4.2 mRNAs might regulate the dendritic surface level of Kv4.2 channels and synaptic plasticity.

• Ocean and Polar Research
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• v.30 no.2
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• pp.129-140
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• 2008

As a preliminary effort to establish a data assimilative ocean forecasting system, we reviewed the theory of the Ensemble Kamlan Filter (EnKF) and developed practical techniques to apply the EnKF algorithm in a real ocean circulation modeling system. To verify the performance of the developed EnKF algorithm, a wind-driven double gyre was established in a rectangular ocean using the Regional Ocean Modeling System (ROMS) and the EnKF algorithm was implemented. In the ideal ocean, sea surface temperature and sea surface height were assimilated. The results showed that the multivariate background error covariance is useful in the EnKF system. We also tested the sensitivity of the EnKF algorithm to the localization and inflation of the background error covariance and the number of ensemble members. In the sensitivity tests, the ensemble spread as well as the root-mean square (RMS) error of the ensemble mean was assessed. The EnKF produces the optimal solution as the ensemble spread approaches the RMS error of the ensemble mean because the ensembles are well distributed so that they may include the true state. The localization and inflation of the background error covariance increased the ensemble spread while building up well-distributed ensembles. Without the localization of the background error covariance, the ensemble spread tended to decrease continuously over time. In addition, the ensemble spread is proportional to the number of ensemble members. However, it is difficult to increase the ensemble members because of the computational cost.

• Corrosion Science and Technology
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• v.7 no.6
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• pp.319-323
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• 2008

The polarization resistance of mild steel in 0.5M hydrochloric acid has been evaluated by using impedance (Z) and linear polarization (LPR) techniques and compared to the noise resistance obtained from electrochemical noise data. The degree of localization of this general corrosion has also been discussed by evaluating localization index and power spectral density. Polarization resistance obtained by LPR technique ($28\Omega$) was higher than that obtained by impedance technique ($15\Omega$). Noise resistance ($11\Omega$) was much lower than polarization resistance measured by both of above techniques. Higher polarization resistance obtained by LPR technique is generally caused by passivation effect in the presence of scales or deposits which can introduce an increased resistance as can low conductivity electrolytes. The reason why noise resistance is lower than polarization resistance is the effect of background noise detected by using three platinum electrodes cell in 0.5M hydrochloric acid. Slope($-\beta$) of power spectral density (PSD) obtained from analysis of noise data ($-\beta$ = 3.3) was much higher than 2 which indicates mild steel corroded uniformly. Localization index (LI) calculated from statistical analysis (LI=0.08) is much lower than 1 which indicates that mild steel did not corroded locally. However, LI value is still higher than $1x10^{-3}$ and this indicates that mild steel corroded locally in microscopic point of view.

• The Journal of Korea Robotics Society
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• v.5 no.3
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• pp.186-196
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• 2010

In this paper, we present a global localization and position error compensation method in a known indoor environment using magnet hall sensors. In previous our researches, it was possible to compensate the pose errors of $x_e$, $y_e$, ${\theta}_e$ correctly on the surface of indoor environment with magnets sets by regularly arrange the magnets sets of identical pattern. To improve the proposed method, new strategy that can realize the global localization by changing arrangement of magnet pole is presented in this paper. Total six patterns of the magnets set form the unique landmarks. Therefore, the virtual map can be built by using the six landmarks randomly. The robots search a pattern of magnets set by rotating, and obtain the current global pose information by comparing the measured neighboring patterns with the map information that is saved in advance. We provide experimental results to show the effectiveness of the proposed method for a differential drive wheeled mobile robot.

• Journal of Positioning, Navigation, and Timing
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• v.6 no.4
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• pp.159-166
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• 2017

The position of autonomous driving vehicle is basically acquired through the global positioning system (GPS). However, GPS signals cannot be received in tunnels. Due to this limitation, localization of autonomous driving vehicles can be made through sensors mounted on them. In particular, a 3D Light Detection and Ranging (LIDAR) system is used for longitudinal position error correction. Few feature points and structures that can be used for localization of vehicles are available in tunnels. Since lanes in the road are normally marked by solid line, it cannot be used to recognize a longitudinal position. In addition, only a small number of structures that are separated from the tunnel walls such as sign boards or jet fans are available. Thus, it is necessary to extract usable information from tunnels to recognize a longitudinal position. In this paper, fire hydrants and evacuation guide lights attached at both sides of tunnel walls were used to recognize a longitudinal position. These structures have highly distinctive reflectivity from the surrounding walls, which can be distinguished using LIDAR reflectivity data. Furthermore, reflectivity information of tunnel walls was fused with the road surface reflectivity map to generate a synthetic reflectivity map. When the synthetic reflectivity map was used, localization of vehicles was able through correlation matching with the local maps generated from the current LIDAR data. The experiments were conducted at an expressway including Maseong Tunnel (approximately 1.5 km long). The experiment results showed that the root mean square (RMS) position errors in lateral and longitudinal directions were 0.19 m and 0.35 m, respectively, exhibiting precise localization accuracy.

• KIPS Transactions on Software and Data Engineering
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• v.1 no.1
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• pp.43-54
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• 2012

This paper presents a new localization technique of an UGV(Unmanned Ground Vehicle) by matching ortho-edge images generated from a DSM (Digital Surface Map) which represents the 3D geometric information of an outdoor navigation environment and 3D range data which is obtained from a LIDAR (Light Detection and Ranging) sensor mounted at the UGV. Recent UGV localization techniques mostly try to combine positioning sensors such as GPS (Global Positioning System), IMU (Inertial Measurement Unit), and LIDAR. Especially, ICP (Iterative Closest Point)-based geometric registration techniques have been developed for UGV localization. However, the ICP-based geometric registration techniques are subject to fail to register 3D range data between LIDAR and DSM because the sensing directions of the two data are too different. In this paper, we introduce and match ortho-edge images between two different sensor data, 3D LIDAR and DSM, for the localization of the UGV. Details of new techniques to generating and matching ortho-edge images between LIDAR and DSM are presented which are followed by experimental results from four different navigation paths. The performance of the proposed technique is compared to a conventional ICP-based technique.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.2
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• pp.221-228
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• 2020

A sonobuoy is dropped onto the surface of water to estimate the bearing of an underwater target. A Directional Frequency Analysis and Recording (DIFAR) sonobuoy has an error in the specific angular section due to the method of estimating bearing and noise, which causes an error in target localization using multiple sonobuoys. In addition, the position of the sonobuoy continues to move, but since a sonobuoy with a GPS is intermittently arranged, it is difficult to estimate the exact position of the sonobuoy. This also causes target localization performance degradation. In this paper, we propose a technique to improve the target localization performance by compensating for bearing errors using characteristics of the DIFAR sonobuoy and multiple-sonobuoy position errors based on the intermittently arranged active sonobuoy with a GPS.

• The Journal of the Acoustical Society of Korea
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• v.24 no.6
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• pp.317-324
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• 2005

Detection and localization of a quiet target in shallow water environments is a challenging problem because of the complicated acoustic Propagation and the Prevalence of loud surface ship interference. Matched Field Processing (MFP) can help address the concern by using a Propagation model to determine the steering vectors, thus Providing optimal away gain and localization accuracy. However, Performance of MFP have yet realized in practice, for several reasons. The most important limitation is that precise information on the underwater environments is generally not available. To examine the Performance of MFP in the East Sea of Korea, we have accomplished a series of matched acoustic Properties and localization experiment (MAPLE). We analyzed the array data measured from MAPLE which is accomplished using a vertical line array and a towed acoustic source off the east cost of Korea in Oct. 2003. We localized the acoustic source using MFP. It is well known that the temperature structure in the experimental site is affected by the short period fluctuation such as internal wave. In this paper, it is found that the sidelobe level on the MFP ambiguity surface is increased being affected by the short period fluctuation.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.6
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• pp.114-122
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• 2011

We propose an automatic localization technique based on Uniform Arc Length Sampling (UALS) of 360 degree range sensor data. The proposed method samples 3D points from dense a point-cloud which is acquired by the sensor, registers the sampled points to a digital surface model(DSM) in real-time, and determines the location of an Unmanned Ground Vehicle(UGV). To reduce the sampling and registration time of a sequence of dense range data, 3D range points are sampled uniformly in terms of ground sample distance. Using the proposed method, we can reduce the number of 3D points while maintaining their uniformity over range data. We compare the registration speed and accuracy of the proposed method with a conventional sample method. Through several experiments by changing the number of sampling points, we analyze the speed and accuracy of the proposed method.