• Journal of Advanced Navigation Technology
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• v.16 no.1
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• pp.145-150
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• 2012

This paper explains a performance analysis of an error detection system running on nested session management of cloud computing collaboration environment using rule-based DEVS modeling and simulation techniques. In DEVS, a system has a time base, inputs, states, outputs, and functions. This paper explains the design and implementation of the FDA(Fault Detection Agent). FDA is a system that is suitable for detecting software error for multimedia remote control based on nested session management of cloud computing collaboration environment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.677-680
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• 2011

Error detection and correcting codes are typically used to protect against soft errors. In addition, scrubbing is applied which is a fundamental technique to avoid the accumulation of soft errors. This paper introduces an optimal scrubbing scheme, which is suitable for a system with auto error detection and correction logic. An auto error detection and correction logic can correct soft errors without CPU's writing operation. The proposed scrubbing scheme leads to maximum reliability by considering both allowable scrubbing load and the periodic accesses to memory by the tasks running in the system.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.27 no.10
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• pp.635-641
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• 2014

In this study, the temperature control device was designed for the study in order to detect the output in frequency of temperature, and the study confirmed accurate temperature values treated systemically by using expanded A/D converting Technology. The control technology of functional sensor included the output error Detection. For the future study, it is necessary to implement a control device by building multiple circuits integrally with different types of sensors such as a automatically and intelligent notification function sensors.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.11
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• pp.83-96
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• 1996

On PR-IV magnetic recording systems, the maximum likelihood sequence detection (MLSD) method is optimum. But it has the problem of the complexity of the structure. The three level detection (TLD) method can be used, which has simpler structure than MLSD, but requires almost twice of power to achieve the same probbility of error as MLSD does. Therefore a new detection method (error controlled detection: ECD) is proposed which has much simpler structure than MLSD and gives much better performance than TLD. The simulation resutls show that the performance of ECD is better than that of TLD by approximaterly 0.5~1.3dB both in linear and nonlinear channels.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.476-478
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• 1997

A new speed detection method using low resolution incremental encoders, especially excellent in the low speed region and in the transient state, is proposed. The half period error of an incremental encoder is greater than the period error. So it's not recommended to quadruple the number of pulses per revolution, because it increase the ripple of speed. To overcome this restriction a speed detection, method has been proposed. But it requires so many latch circuits. Therefore we propose a new speed detection method that has different concept and has fewer latch circuits.

• Structural Engineering and Mechanics
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• v.45 no.2
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• pp.159-168
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• 2013

The effect of structural uncertainties or measurement errors on damage detection results makes the robustness become one of the most important features during identification. Due to the wide use of vibration signatures on damage detection, the development of vibration-based techniques has attracted a great interest. In this work, a review on vibration-based robust detection techniques is presented, in which the robustness is considerably improved through modeling error compensation, environmental variation reduction, denoising, or proper sensing system design. It is hoped that this study can give help on structural health monitoring or damage mitigation control.

• The Journal of the Acoustical Society of Korea
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• v.20 no.6
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• pp.75-81
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• 2001

In this paper we analyzed the localization error of near-field detection algorithm in the sea. The near-field detection algorithms using triangulation and wavefront curvature basically assume a signal in two dimension of bearing and range. But the assumption causes localization error because there is three dimension of bearing, range, and depth in the sea. Even through three dimensional effect is considered, the localization error is occurred if multipath propagation in the sea is ignored. To analyze the localization error in the sea, we simulate the near-field localization using acoustic propagation model and focused beamforming considering wavefront curvature. The simulation results indicate that localization error always occurs in the sea and the error varied with sound velocity profile, water depth, bottom slope, source range, etc.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.10
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• pp.75-82
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• 2008

In this paper, we propose an efficient symbol detection algorithm for multiple-input multiple-output spatial multiplexing (MIMO-SM) systems and present its design and implementation results. By enhancing the performance of the first detected symbol which causes error propagation, the proposed algorithm achieves a considerable performance gain as compared to the conventional sorted QR decomposition (SQRD) based detection and the ordered successive detection (OSD) algorithms. The bit error rate (BER) performance of the proposed detection algorithm is evaluated by the simulation. In case of 16QAM MIMO-SM system with 4 transmit and 4 receive ($4{\times}4$) antennas, at $BER=10^{-3}$ the proposed algorithm obtains the gai improvement of about 2.5-13.5 dB over the conventional algorithms. The proposed detection algorithm was designed in a hardware description language (HDL) and synthesized to gate-level circuits using 0.18um 1.8V CMOS standard cell library. The results show that the proposed algorithm can be implemented without increasing the hardware costs significantly.

• Nuclear Engineering and Technology
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• v.55 no.2
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• pp.603-622
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• 2023

Human error (HE) is an important concern in safety-critical systems such as nuclear power plants (NPPs). HE has played a role in many accidents and outage incidents in NPPs. Despite the increased automation in NPPs, HE remains unavoidable. Hence, the need for HE detection is as important as HE prevention efforts. In NPPs, HE is rather rare. Hence, anomaly detection, a widely used machine learning technique for detecting rare anomalous instances, can be repurposed to detect potential HE. In this study, we develop an unsupervised anomaly detection technique based on generative adversarial networks (GANs) to detect anomalies in manually collected surveillance data in NPPs. More specifically, our GAN is trained to detect mismatches between automatically recorded sensor data and manually collected surveillance data, and hence, identify anomalous instances that can be attributed to HE. We test our GAN on both a real-world dataset and an external dataset obtained from a testbed, and we benchmark our results against state-of-the-art unsupervised anomaly detection algorithms, including one-class support vector machine and isolation forest. Our results show that the proposed GAN provides improved anomaly detection performance. Our study is promising for the future development of artificial intelligence based HE detection systems.

• Aerospace Engineering and Technology
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• v.13 no.1
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• pp.27-36
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• 2014

Generally, satellites continuously monitor that its major functions are working properly and their hardware are in a good status using several SOH data. In case a fault that is not recognized as a temporal problem or a failure that can be considered to propagate its damage to the other parts are detected, fault management logic is performed automatically without any contact of ground station. In this paper, attitude error detection using sun sensors on a rotating solar array is proposed. Attitude error can be detected by comparing the offset angle between the actual data computed from the sun sensor and the data predicted from the orbit and ephemeris information for the two types of solar array operation method. During the eclipse, the output of attitude error detection method becomes zero because the sun sensor output cannot be provided. Finally, the proposed method is analyzed through the data processing using on-orbit data.