• Journal of Auto-vehicle Safety Association
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• v.14 no.2
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• pp.26-38
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• 2022

This paper proposes multiple RLS and actuator performance index-based adaptive actuator fault-tolerant control and detection algorithms for longitudinal autonomous driving. The proposed algorithm computes the desired acceleration using feedback law for longitudinal autonomous driving. When actuator fault or performance degradation exists, it is designed that the desired acceleration is adjusted with the calculated feedback gains based on multiple RLS and gradient descent method for fault-tolerant control. In order to define the performance index, the error between the desired and actual accelerations is used. The window-based weighted error standard deviation is computed with the design parameters. Fault level decision algorithm that can represent three fault levels such as normal, warning, emergency levels is proposed in this study. Performance evaluation under various driving scenarios with actuator fault was conducted based on co-simulation of Matlab/Simulink and commercial software (CarMaker).

• Journal of Positioning, Navigation, and Timing
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• v.12 no.4
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• pp.423-430
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• 2023

One recent notable method for real-time elimination of ionospheric errors in geodetic applications is the Predicted Global Ionosphere Map (PGIM). This study analyzes the level of accuracy achievable when applying the PGIM provided by the Center for Orbit Determination of Europe (CODE) to the Korean Peninsula region. First, an examination of the types and lead times of PGIMs provided by the International GNSS Service (IGS) Analysis Center revealed that CODE's two-day prediction model, C2PG, is available approximately eight hours before midnight. This suggests higher real-time usability compared to the one-day prediction model, C1PG. When evaluating the accuracy of PGIM by assuming the final output of the Global Ionosphere Map (GIM) as a reference, it was found that on days with low solar activity, the error is within ~2 TECU, and on days with high solar activity, the error reaches ~3 TECU. A comparison of the errors introduced when using PGIM and three solar activity indices-Kp index, F10.7, and sunspot number-revealed that F10.7 exhibits a relatively high correlation coefficient compared to Kp-index and sunspot number, confirming the effectiveness of the prediction model.

• Journal of the Korean Mathematical Society
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• v.61 no.5
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• pp.875-898
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• 2024

This study estimates the true price of an asset and finds the optimal bid/ask prices for market makers. We provide a novel state-space model based on the exponential Ornstein-Uhlenbeck volatility and the Heston models with Gaussian noise, where the traded price and volume are available, but the true price is not observable. An objective of this study is to use Bayesian filtering to estimate the posterior distribution of the true price, given the traded price and volume. Because the posterior density is intractable, we employ the guided particle filtering algorithm, with which adaptive rejection metropolis sampling is used to generate samples from the density function of an unknown distribution. Given a simulated sample path, the posterior expectation of the true price outperforms the traded price in estimating the true price in terms of both the mean absolute error and root-mean-square error metrics. Another objective is to determine the optimal bid/ask prices for a market maker. The profit-and-loss of the market maker is the difference between the true price and its bid/ask prices multiplied by the traded volume or bid/ask size of the market maker. The market maker maximizes the expected utility of the PnL under the posterior distribution. We numerically calculate the optimal bid/ask prices using the Monte Carlo method, finding that its spread widens as the market maker becomes more risk-averse, and the bid/ask size and the level of uncertainty increase.

• Journal of Advanced Marine Engineering and Technology
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• v.33 no.8
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• pp.1268-1274
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• 2009

Various evaluation systems using simulators have been adopted widely for the purpose of training and examination, including marine engineering education area. This paper suggests a PC based evaluation scoring system for simulators where the operation ability of machineries and background knowledges of trainees or examinees are able to be assessed relatively. The scores are based on the 100 point resulted from their responses for a given evaluation scenario under a PID tuning simulation. The mistakes they make during the operation time are integrated firstly to get error sum, and the error sum is transformed secondly to 100 point score according to a formula where the knowledge level of examinee's groups can be compensated and considered reasonably. The implementation result of evaluation system for the given control loop is described and analyzed to show the effectiveness of the suggested configuration as an evaluation tool.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.12C
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• pp.965-970
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• 2010

In the NAND flash memory storing two bits per cell, data is discriminated among four levels of electrical charges. We refer to these four levels as E, P1, P2, and P3 from the low voltage. In the statistics, many errors occur when E and P3 are stored at the next cells. Therefore, we propose a coding scheme for avoiding E-P3 or P3-E data patterns. We investigate two modulation codes for 9/10 code (9 bit input and 5 symbol codeword) and 11/12 code (11 bit input and 6 symbol codeword).

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.7
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• pp.49-55
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• 2016

In digital forensic images, there is a serious problem that is distributed with various image types. For the problem solution, this paper proposes a classification algorithm of the forensic image types. The proposed algorithm extracts the 21-dim. feature vector with the contrast and energy from GLCM (Gray Level Co-occurrence Matrix), and the entropy of each image type. The classification test of the forensic images is performed with an exhaustive combination of the image types. Through the experiments, TP (True Positive) and FN (False Negative) is detected respectively. While it is confirmed that performed class evaluation of the proposed algorithm is rated as 'Excellent(A)' because of the AUROC (Area Under Receiver Operating Characteristic Curve) is 0.9980 by the sensitivity and the 1-specificity. Also, the minimum average decision error is 0.1349. Also, at the minimum average decision error is 0.0179, the whole forensic image types which are involved then, our classification effectiveness is high.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4968-4986
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• 2017

In this paper, we primarily address the difficulty of automatic generation of a plausible depth map from a single image in an unstructured environment. The aim is to extrapolate a depth map with a more correct, rich, and distinct depth order, which is both quantitatively accurate as well as visually pleasing. Our technique, which is fundamentally based on a preexisting DepthTransfer algorithm, transfers depth information at the level of superpixels. This occurs within a framework that replaces a pixel basis with one of instance-based learning. A vital superpixels feature enhancing matching precision is posterior incorporation of predictive semantic labels into the depth extraction procedure. Finally, a modified Cross Bilateral Filter is leveraged to augment the final depth field. For training and evaluation, experiments were conducted using the Make3D Range Image Dataset and vividly demonstrate that this depth estimation method outperforms state-of-the-art methods for the correlation coefficient metric, mean log10 error and root mean squared error, and achieves comparable performance for the average relative error metric in both efficacy and computational efficiency. This approach can be utilized to automatically convert 2D images into stereo for 3D visualization, producing anaglyph images that are visually superior in realism and simultaneously more immersive.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.9
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• pp.1688-1695
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• 2016

Underwater communication has multipath error because of reflection by sea-level and sea-bottom. The multipath of underwater channel causes signal distortion and error floor. The excessive multipath encountered in underwater communication channel creates inter symbol interference, which is a limiting factor to achieve a high data rate and bit error rate performance. Therefore, to increase throughput efficiency and improve performance, this paper consider FTN (Faster-than-Nyquist) signalling based on turbo equalization. FTN signalling is a technique of transmitting information at a rate higher than the allowed Nyquist limit. This paper presented efficient decoder structure of FTN transmission in the environment of multipath underwater channel and we compare the performance between FTN method and conventional punctured method in lake experimentation. As a results of lake experiment, we confirmed FTN method based on turbo equalization is applicable and efficiency in underwater communication.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.4
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• pp.58-64
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• 1997

FLC(Fuzzy Logic Controller) is stronger to the disturbance than a classical controller and its overshoot of the intialized value is excellent. In case an unknown process or the mathematical modeling of a complicated system is impossible, a fit control quantity can be acquired by the Fuzzy inference. But FLC can not converge correctly to the desirable value because the FLC's output value by the size of the quantization level of the Fuzzy variable always has a minor error. There are many ways to eliminate the minor error, but I will suggest GA-FLC and EP-FLC Hybrid controller which csombines FLC with GA(Genetic Algorithm) and EP(Evo1ution Programming). In this paper, the output characteristics of this Hybrid controller will be compared and analyzed with those of FLC, it will he showed that this Hybrid controller converge correctly to the desirable value without any error, and !he convergence speed performance of these two kinds of Hyhrid controller also will be compared.

• Journal of the Korea Convergence Society
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• v.6 no.4
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• pp.249-255
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• 2015

The study was to investigate the effects of stimulus velocity and passer's skill level on anticipation timing performance. Fourteen subjects(seven novices and seven experts) were required to make a total 12 passes in coincidence with an experimentally manipulated moving light signal in randomly presented three different conditions(4m/s, $3m/s{\rightarrow}5m/s$, $5m/s{\rightarrow}3m/s$). Results of analyses showed that absolute error(AE) and constant error(CE) were greater in constant acceleration of the moving stimulus. In addition, experts were more accuracy and consistency than novices on absolute, constant and variable error(VE). These findings indicated that stimulus velocity served as the major determination of anticipation timing performance of passing.