• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06a
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• pp.806-811
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• 1994

Two kinds of static and dynamic state estimation methods are newly discussed for the problem of the measurement disturbance of environmental low-frequency noise in the presence of wind-induced noise. First, the probability characteristics of wind-induced noise are discussed in the form of probability distribution conditioned by wind speed, based on the simultaneous observation of the wind-induced noise and wind speed near a microphone. Next, especially form the viewpoint of simplicity for practical use, two kinds of static and dynamic state estimation methods are discussed. The static estimation method using the information on wind speed is fundamentally supported by the conservation principle of energy sum. The dynamic one is the method by using a recursive digital filter with the parameters successively renewed by the information on wind speed. This can be also simplified by using well-know Kalman filter under the assumption of the Gaussian distribution. The effectiveness of proposed two estimation methods are shown through experiments under a breezy condition in the open filed.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.25 no.5
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• pp.313-320
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• 2015

A 2-axis gimbal-type X-band antenna has been widely used to effectively transmit the high resolution image data from the observation satellite to the desired ground station. However, a discontinuous stepper motor activation for rotating the pointing mechanism in azimuth and elevation directions induces undesirable micro-vibration disturbances which can result in the image quality degradation of a high-resolution observation satellite. To enhance the image quality of the observation satellite, attenuating the micro-vibration induced by an activation of the stepper motor for rotational movements of the antenna is important task. In this study, we proposed a low-rotational-stiffness blade gear applied to the output shaft of the stepper motor to obtain the micro-vibration isolation performance. The design of the blade gear was performed through the structure analysis such that this gear is satisfied with the margin of safety rule under the derived torque budget. In addition, the micro-vibration isolation performance of the blade gear was verified through the micro-vibration measurement test using the dedicated micro-vibration measurement device proposed in this study.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.535-540
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• 2006

The relationship between the observable noise model and the satellite elevation angle can be modeled quite well by an exponential function.[Jin, 1996] Noise size and dependence on the elevation angle are, however, different for each observation and receiver type. Therefore, the coefficient determination of this model is an issue, and various methods including PR-CP, single difference, and time difference have been suggested. The limitations of them are difficulty to model the carrier phase noise and to eliminate bias. To overcome these disadvantages for using Jin's model, we suggest zero baseline double difference (DD) and noise sorting algorithm. Data DD technique in zero baseline is useful to eliminate all the troublesome GPS biases, and the remaining error is the sum of GPS measurement noises from two satellites. These DD residuals for hours should be sorted by the combination of satellite elevation angles, and then variance value of the residual for each combination can be estimated. Using these values, we construct an over-determined linear equation whose solution is a set of noise variance for each satellite elevation angle. With 24hr Trimble 4000ssi data, we easily worked out the coefficients of the noise model not only for pseudorange but also for carrier phase. We estimated the standard deviation of the measurement DD using our model, and plotted 1 and 3 sigma lines for every epoch to verify the representation of the residual error. 63.3% of pseudorange residual and 65.9% of phase error did not exceed the 1 sigma lines. Additionally, 99.2% and 99.5% of them lied within 3sigma line. These figures prove that the Gaussian property of measurement noise, and that the suggested model by our algorithm corresponds to the observable noise information.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2853-2864
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• 2018

Discriminant analysis predicts a class label of a new observation with an unknown label, using information from the existing labeled data. Hence, observed labels play a critical role in the analysis and we usually assume that these labels are correct. If the observed label contains an error, the data has label noise. Label noise can frequently occur in real data, which would affect classification performance. In order to resolve this, a comparative study was carried out using simulated data with label noise. In particular, we considered 4 different classification techniques such as LDA (linear discriminant analysis classifiers), QDA (quadratic discriminant analysis classifiers), KNN (k-nearest neighbour), and SVM (support vector machine). Then we evaluated each method via average accuracy using generated data from various scenarios. The effect of label noise was investigated through its occurrence rate and type (noise location). We confirmed that the label noise is a significant factor influencing the classification performance.

• Investigative Magnetic Resonance Imaging
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• v.2 no.1
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• pp.50-57
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• 1998

MR acoustic sound or noise due to gradient pulsings has been one of the problems in MRI, both in patient scanning as well as in many areas of psychiatric and neuroscience research, such as brain fMRI. Especially in brain fMRI, sound noise is one of the serious noise sources which obscures the small signals obtainable from the subtle changes occurring in oxygenation status in the cortex and blood capillaries. Therfore, we have studied the effects of acoustic or sound noise arising in fMR imaging of the auditory, motor and visual cortices. The results show that the acoustical noise effects on motor and visual responses are opposite. That is, for the motor activity, it shows an increased total motor activation while for the visual stimulation, corresponding(visual) cortical activity has diminished substantially when the subject is exposed to a loud acoustic sound. Although the current observations are preliminary and require more experimental confirmation, it appears that the observed acoustic-noise effects on brain functions, such as in the motor and visual cortices, are new observations and could have significant consequences in data observation and interpretation in future fMRI studies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.12
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• pp.3242-3265
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• 2023

Ensuring reliability of a machinery system involve the prediction of remaining useful life (RUL). In most RUL prediction approaches, noise is always considered for removal. Nevertheless, noise could be properly utilized to enhance the prediction capabilities. In this paper, we proposed a novel RUL prediction approach based on noise injection and a Kalman filter ensemble of modified bagging predictors. Firstly, we proposed a new method to insert Gaussian noises into both observation and feature spaces of an original training dataset, named GN-DAFC. Secondly, we developed a modified bagging method based on Kalman filter averaging, named KBAG. Then, we developed a new ensemble method which is a Kalman filter ensemble of KBAGs, named DKBAG. Finally, we proposed a novel RUL prediction approach GN-DAFC-DKBAG in which the optimal noise-injected training dataset was determined by a GN-DAFC-based searching strategy and then inputted to a DKBAG model. Our approach is validated on the NASA C-MAPSS dataset of aero-engines. Experimental results show that our approach achieves significantly better performance than a traditional Kalman filter ensemble of single learning models (KESLM) and the original DKBAG approaches. We also found that the optimal noise-injected data could improve the prediction performance of both KESLM and DKBAG. We further compare our approach with two advanced ensemble approaches, and the results indicate that the former also has better performance than the latters. Thus, our approach of combining optimal noise injection and DKBAG provides an effective solution for RUL estimation of machinery systems.

• Journal of Digital Contents Society
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• v.19 no.9
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• pp.1739-1749
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• 2018

We propose a marine observation system using existing light buoys to observe various marine information of marine locations. Our proposed ocean observation system is composed of the existing standard light buoy type and can be easily connected to the light buoy. The proposed marine observation system measures the mean wave height, maximum wave height, mean wave height and water temperature measured in the ocean. Besides, it can measure the air pressure, temperature, wind speed and wind speed in real time. In order to measure important peaks in marine observations, 2200 peak data are collected for 10 minutes, and the collected data are subjected to spectral analysis to extract significant wave and wave period data. The developed system removes the noise by using the filter because the marine observation system attaches to the light buoy. We compare and analyze the measurement data of the existing proven floating marine observation system and the standard equivalent system developed. Also, it is proved that the data of the standard type backbone ocean observation system developed through the comparative experiment is similar to that of the existing ocean observation system.

• Journal of Digital Convergence
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• v.13 no.8
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• pp.295-300
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• 2015

In vocabulary recognition using an HMM model which models the prior distribution for the observation of a discrete probability distribution indicates the advantages of low computational complexity, but relatively low recognition rate. The Bayesian techniques to improve vocabulary recognition model, it is proposed using a convergence of two methods to improve recognition noise-canceling recognition. In this paper, using a convergence of the prior probability method and techniques of Bayesian posterior probability based on HMM remove noise and improves the recognition rate. The result of applying the proposed method, the recognition rate of 97.9% in vocabulary recognition, respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.5
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• pp.663-674
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• 1993

In this paper, a DCT image coding algorithm using the human visual property is proposed. Human visual is relatively sensitive to noise in the darker region, insensitive to noise in the brighter region. This property was proved by Weber's law through psycovisual experiment. Weber's law states that the just noticeable difference (j.n.d.) is proportional to intensity. Therefore, the implication of this observation for image processing is that reducing noise in the darker region is more important than reducing noise in the brighter region. In this proposed coding scheme AC coefficients in the darker region are more finely quantized than those in the brighter region. Results showed that, at low bit rate, the subjective quality of reconstructed images by proposed coding scheme is improved than that of coding scheme without considering human visual property.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.8C
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• pp.709-712
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• 2010

In this paper, the two sample locally optimum rank detector is obtained in the weakly dependent noise with non-zero temporal correlation between noise observations. The test statistic of the locally optimum rank detector is derived from the Neyman-Pearson lemma suitable for the two sample observation models, where it is assumed that reference observations are available in addition to regular observations. Two-sample locally optimum rank detecter shows the same performance with the one-sample locally optimum rank detector asymptotically. The structure of the two-sample rank detector is simpler than that of the one-sample rank detector because the sign statistic is not processed separately.