• Journal of Institute of Control, Robotics and Systems
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• v.6 no.1
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• pp.15-24
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• 2000

Stand-alone global position system receiver based on C/A code tracking generates position error of 100m mainly due to the selective availability and ionospheric and tropospheric delay errors. The differential GPS is the most commonly used method for removing those bias range error components. The relative GPS, although somewhat restrictive in its use, is ideally suited to the car monitoring system for improved Automatic Vehicle location, especially where the DGPS infrastructure is not available. The RGPS does not require any additional hardware, facility or external infrastructure and can be operated within the system with existing host computer and communication link. This paper presents detailed description of the RGPS concept and its implementation for real-time data processing. Performance of RGPS is evaluated with real data and is compared with DGPS.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.485-489
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• 2006

In last decades, several linearization methods for the AOA measurements have been proposed, for example, Gauss-Newton method and closed-form solution. Gauss-Newton method can achieve high accuracy, but the convergence of the iterative process is not always ensured if the initial guess is not accurate enough. Closed-form solution provides a non-iterative solution and it is less computational. It does not suffer from convergence problem, but estimation error is somewhat larger. This paper proposes a self-tuning weighted least square AOA algorithm that is a modified version of the conventional closed-form solution. In order to estimate the error covariance matrix as a weight, two-step estimation technique is used. Simulation results show that the proposed method has smaller positioning error compared to the existing methods.

• Communications for Statistical Applications and Methods
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• v.12 no.2
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• pp.305-312
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• 2005

In the cluster analysis, Hotelling's $T^2$ can be used to estimate the unknown number of clusters based on the idea of multiple comparison procedure. Especially, its threshold is obtained according to the probability of committing the type one error. Examples are used to compare Hotelling's $T^2$ with other classical location test statistics such as Sum-of-Squared Error and Wilks' $\Lambda$ The hierarchical clustering is used to reveal the underlying structure of the data. Also related criteria are reviewed in view of both the between variance and the within variance.

• Structural Engineering and Mechanics
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• v.13 no.2
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• pp.117-134
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• 2002

This paper presents a computational method for a confidence region of identified parameters which are affected by measurement noise and error contained in prescribed parameters. The method is based on sensitivities of the identified parameters with respect to model parameter error and measurement noise along with the law of error propagation. By conducting numerical experiments on simple models, it is confirmed that the confidence region coincides well with the results of numerical experiments. Furthermore, the optimum arrangement of sensor locations is evaluated when uncertainty exists in prescribed parameters, based on the concept that square sum of coefficients of variations of identified results attains minimum. Good agreement of the theoretical results with those of numerical simulation confirmed validity of the theory.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.1
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• pp.45-49
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• 2022

In this paper, we propose a method for estimating the error of the Ultra-Wideband (UWB) distance measurement using the channel impulse response (CIR) of the UWB signal based on machine learning. Due to the recent demand for indoor location-based services, wireless signal-based localization technologies are being studied, such as UWB, Wi-Fi, and Bluetooth. The constructive obstacles constituting the indoor environment make the distance measurement of UWB inaccurate, which lowers the indoor localization accuracy. Therefore, we apply machine learning to learn the characteristics of UWB signals and estimate the error of UWB distance measurements. In addition, the performance of the proposed algorithm is analyzed through experiments in an indoor environment composed of various walls.

• Journal of the Korea Society of Computer and Information
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• v.26 no.11
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• pp.1-9
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• 2021

3D-NAND flash memory provides high capacity per unit area by stacking 2D-NAND cells having a planar structure. However, due to the nature of the lamination process, there is a problem that the frequency of error occurrence may vary depending on each layer or physical cell location. This phenomenon becomes more pronounced as the number of write/erase(P/E) operations of the flash memory increases. Most flash-based storage devices such as SSDs use ECC for error correction. Since this method provides a fixed strength of data protection for all flash memory pages, it has limitations in 3D NAND flash memory, where the error rate varies depending on the physical location. Therefore, in this paper, pages and layers with different error rates are classified into clusters through the K-means machine learning algorithm, and differentiated data protection strength is applied to each cluster. We classify pages and layers based on the number of errors measured after endurance test, where the error rate varies significantly for each page and layer, and add parity data to stripes for areas vulnerable to errors to provides differentiate data protection strength. We show the possibility that this differentiated data protection policy can contribute to the improvement of reliability and lifespan of 3D NAND flash memory compared to the protection techniques using RAID-like or ECC alone.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.873-875
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• 2008

In sensor network, the elimination of NLOS information is a necessity to improve the accuracy of the localization. For this reason, we proposed an algorithm iteratively eliminating the NLOS information to enhance the accuracy of the localization of a tag location, and simulated the proposed algorithm to confirm the performance. The proposed algorithm can estimate the location of the error distance within 3.5m when it has 10 LOS coordinates with LOS information. In addition, it can enhance the accuracy according to decreasing NLOS coordinates.

• Proceedings of the KSME Conference
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• 2001.06d
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• pp.201-207
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• 2001

We modeled the liquid film dryout(LFD) process for both tube and annulus which have uniformly heated vertical channels. We set phenomenological initial conditions in the model. The initial void fraction on the onset of the annular flow location is derived from the physical chum-to-annular flow criterion with the help of the drift-flux-model. The initial thermodynamic-equilibrium-quality is calculated by iteration with the flow quality to find the onset of the annular-flow location. Present model tends to predict very well at the lower exit quality but under-estimates at the higher exit quality. We found that the prediction error of the present model is gradually bigger as the inlet subcooling approaches near the saturation. We obtained excellent results for both tube and annulus channels as the mean of 0.97 and root-mean-square error of 11% for the number of 3883 experimental data on tubes, and of 0.96 and of 12% for 593 on annuli. The present model extended the applicable range to the relatively low exit quality region than previous LFD models.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.259-262
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• 2003

In this paper, we studied the path determination algorithm of the guidance robot for the visually impaired. Using the guidance robot for the visually impaired, the visually impaired can go to the destination where they want without other's heir. The navigation path of the guidance robot for the visually impaired must be the optimal path not only the shortest but also the most safe, which is different from a shortest path for common people. GPS and electronic map are used for the location information of the visually impaired. We corrected the error by converting the coordinates of location information from GPS, which includes maximum several tens of meters error, to the coordinates of electronic map. Information such as simple path and direction to the destination is not enough because it may be different between a going path from the start to the destination and a coming path from the destination to the start as around environment. So, we added information which can be dangerous for the visually impaired such as driveway, sidewalk without braille blocks, crosswalk, stairs and overpass, each has weight value as dangerous degree, when matching the GPS information to the electronic map, enough large as 1:5,000 scale.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.5
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• pp.909-937
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• 2011

Energy efficiency is one of the most critical issues in the design of wireless sensor networks. In object-tracking sensor networks, the data storage and query processing should be energy-conserving by decreasing the message complexity. In this paper, a Prediction-based Energy-conserving Approximate StoragE schema (P-EASE) is proposed, which can reduce the query error of EASE by changing its approximate area and adopting predicting model without increasing the cost. In addition, focusing on reducing the unnecessary querying messages, P-EASE enables an optimal query algorithm to taking into consideration to query the proper storage node, i.e., the nearer storage node of the centric storage node and local storage node. The theoretical analysis illuminates the correctness and efficiency of the P-EASE. Simulation experiments are conducted under semi-random walk and random waypoint mobility. Compared to EASE, P-EASE performs better at the query error, message complexity, total energy consumption and hotspot energy consumption. Results have shown that P-EASE is more energy-conserving and has higher location precision than EASE.