• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.2
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• pp.162-166
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• 2012

The instantaneous amplitude (IA) based on the higher order differential energy operator is proposed. And its general form for arbitrary order is also proposed. The various definitions of the IA and the instantaneous frequency (IF) estimators are considered. The IA and IF estimators based on the energy operators need less computational cost than the conventional IF and IA estimators exploiting the Hilbert transform. The IF and IA estimators are compared in terms of the frequency and amplitude tracking accuracy of the AM-FM signals. For noiseless case, the IA and IF estimators based on the Teager-Kaiser energy operator show better tracking performance than the IF and IA estimators based on the higher energy operators. However, under noisy condition, the IF and IA estimator based on the higher order energy operators with the order 3 and 4 show better tracking than the Teager-Kaiser energy based estimators. The IF and IA estimators are applied to signals in the various power anomalies to show their usefulness as the disturbance detectors.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.737-739
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• 1996

Abnormal conditions and disturbances in distribution system cause an immediate influence to the customers. Conventional detection schemes for the distribution abnormalities have been applied in limited extents mainly because of their low reliability. In this paper, we developed a disturbance identification system which monitors the load level after a transient, checks the harmonic behavior of the load, and finally makes decision on the cause of the disturbance. This system identifies and discriminates overcurrent faults, arcing ground faults, recloser activities, and foreign object or tree contacts. In the implementation of the identification system, we applied fuzzy logic to better represent some variables whose Quantities are expressed only in non-numerical terms.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.396-399
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• 2003

This paper proposes a simple digital image stabilization(DIS) algorithm for roll motion, which has not been compensated in the 2-axes mechanical stabilization system, using aero-crossing of the rotational motion vectors. The 2-axes stabilization system cannot stabilize rolled images, which causes the deteriorated performance of the object detection and recognition. In this paper, we propose the rotational motion stabilization algorithm which estimates and compensates global motion in terms of rotational center and rotational angle. Both the synthetic images with undesirable rotational disturbance and the real images from 2-axes stabilization system are used to evaluate the proposed algorithm. The results show that our proposed algorithm suppresses the undesirable rotational disturbance effectively.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.530-531
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• 2021

In this paper, I proposed a technique for identifying discrepancies between data input in the IoT sensor environment. The proposed technique can manage numerically input sensor data so that it can be applied to actual field problems. The proposed technique can detect when contradictory data is input from two or more sensors in an actual IoT sensor environment, and through this, it can be developed into a method that can identify and resolve sensor failure or intentional data disturbance.

• Journal of Korean Clinical Nursing Research
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• v.19 no.1
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• pp.57-68
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• 2013

Purpose: In assessing patients' neurological status following a stroke it is very important to have a valid tool for early detection of neurological deterioration. NIHSS is considered the best tool to reflect neurological status in patients with ischemic stroke. An education program on use of NIHSS was planned for nurses caring for these patients and the effects of the program were evaluated. Methods: The NIHSS education program (NEP) which includes online and video lectures, and practical education was provided to the nurses from April to July, 2010. To examine the effect of NEP, nursing records of patients with ischemic stroke who were admitted to a stroke center were analyzed. Two groups, a historical control group (n=100) and the study group (n=115) were included. Results: Nursing records for neurologic symptoms for each patient increased (41.0% versus 100.0%, p<.001), and especially, visual disturbance, facial palsy. limb paralysis and ataxia, language disturbance, dysarthria, and neglect symptoms significantly increased (all p<.001). Nurse notification to the doctor of patients with neurological changes increased (21.0% versus 39.1%, p=.004), and nurses' neurological deterioration detection rates also increased (37.5% versus 84.6%, p=.009). Conclusion: NEP improved the quality of nursing records for neurological assessment and the detection rate of neurological deterioration.

• Smart Structures and Systems
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• v.17 no.2
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• pp.167-194
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• 2016

This paper investigates the Synergetics based Damage Detection Method (SDDM) for frame structures by using surface-bonded PZT (Lead Zirconate Titanate) patches. After analyzing the mechanism of pattern recognition from Synergetics, the operating framework with cooperation-competition-update process of SDDM was proposed. First, the dynamic identification equation of structural conditions was established and the adjoint vector (AV) set of original vector (OV) set was obtained by Generalized Inverse Matrix (GIM).Then, the order parameter equation and its evolution process were deduced through the strict mathematics ratiocination. Moreover, in order to complete online structural condition update feature, the iterative update algorithm was presented. Subsequently, the pathway in which SDDM was realized through the modified Synergetic Neural Network (SNN) was introduced and its assessment indices were confirmed. Finally, the experimental platform with a two-story frame structure was set up. The performances of the proposed methodology were tested for damage identifications by loosening various screw nuts group scenarios. The experiments were conducted in different damage degrees, the disturbance environment and the noisy environment, respectively. The results show the feasibility of SDDM using piezoceramic sensors and actuators, and demonstrate a strong ability of anti-disturbance and anti-noise in frame structure applications. This proposed approach can be extended to the similar structures for damage identification.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.1
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• pp.222-229
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• 2016

Active synthetic aperture sonar on the small UUV is generated several trajectory disturbances under the influences of underwater environments, and causing a large error in the synthetic aperture processing. In this paper, we analyzed the effects of azimuth resolution for the phase mismatch of the synthetic aperture focus processing when the periodic or random trajectory disturbances was generated on the side direction. The simulation results show that ghost targets are generated and azimuth resolution is very deteriorated when disturbance amplitude is greater than $0.3{\lambda}$ and disturbance period is greater than $2L_{sa}$ in the periodic trajectory disturbances environments. And detection performance on the seabed small objects by the synthetic aperture processing is shown that there is a significant effects on the azimuth resolution depending on the types and conditions of the platform trajectory disturbance variations.

• Korean Journal of Remote Sensing
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• v.34 no.6_4
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• pp.1531-1544
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• 2018

We detected the coseismic ionospheric disturbance generated by the earthquakes of magnitude 5.0 and greater in Korean Peninsula. We considered the seismic events such as Gyeongju earthquake in September 2016 with magnitude 5.8, the Pohang earthquake in November 2017 with magnitude 5.4, and the underground nuclear explosion from North Korea in September 2017 with magnitude 5.7. Although all GPS stations were not detected, the ionospheric disturbance induced by these earthquakes occurred approximately 10-30 minutes and 40-60 minutes after the events. We inferred that the time difference within each variation is due to the different focal depth and the geometry of epicenter, satellite, and GPS station. In the case of the Gyeongju earthquake, the earthquake had relatively deeper depth than the other earthquakes. However, the seismic magnitude was bigger and it occurred at nighttime when the ionospheric activity was stable. So we could observe such anomalous variations. It is considered that the ionospheric disturbance caused by the difference in velocity of the upward propagating waves generated by earthquake appears more than once. Our results indicate that the detection of ionospheric disturbances varies depending on the geometry of the GPS station, satellite, and epicenter or the detection method and that the apparent growth of amplitude in the time series varies depending on the focal depth or the site-satellite-epicenter geometry.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.10
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• pp.983-990
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• 2008

This paper presents the fault detection and diagnosis(FDD) algorithm to enhance reliability of a longitudinal controller for an autonomous All-Terrain Vehicle(ATV). The FDD is designed to monitor and identify faults which may occur in distributed hardware used for longitudinal control, e.g., DSPs, CAN, sensors, and actuators. The proposed FDD is an integrated approach of decentralized and centralized FDD. While the former is processed in a DSP and suitable to detect faults in a single hardware, it is sensitive to noise and disturbance. On the other hand, the latter is performed via communication and it detects and diagnoses faults through analyzing concurrent performances of multiple hardware modules, but it is limited to isolate faults specifically in terms of components in the single hardware. To compensate for disadvantages of each FDD approach, two layered structure including both decentralized and centralized FDD is proposed and it allows us to make more robust fault detection and more specific fault isolation. The effectiveness of the proposed method will be validated experimentally.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.37-39
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• 2009

In the research of speech recognition, locating the beginning and end of a speech utterance in a background of noise is of great importance. Since the background noise presenting to record will introduce disturbance while we just want to get the stationary parameters to represent the corresponding speech section, in particular, a major source of error in automatic recognition system of isolated words is the inaccurate detection of beginning and ending boundaries of test and reference templates, thus we must find potent method to remove the unnecessary regions of a speech signal. The conventional methods for speech endpoint detection are based on two simple time-domain measurements - short-time energy, and short-time zero-crossing rate, which couldn't guarantee the precise results if in the low signal-to-noise ratio environments. This paper proposes a novel approach that finds the Lyapunov exponent of time-domain waveform. This proposed method has no use for obtaining the frequency-domain parameters for endpoint detection process, e.g. Mel-Scale Features, which have been introduced in other paper. Comparing with the conventional methods based on short-time energy and short-time zero-crossing rate, the novel approach based on time-domain Lyapunov Exponents(LEs) is low complexity and suitable for Digital Isolated Word Recognition System.