• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.05a
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• pp.1443-1448
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• 2006

The reduction of the vehicle interior noise has been the main interest of NVH engineers. The driver's perception on the vehicle noise is affected largely by psychoacoustic characteristic of the noise as well as the SPL. In particular, the HVAC sound among the vehicle interior noise has been reflected sensitively in the side of psychology. Even though the HVAC noise is not louder than overall noise level, it clearly affects subjective perception in the way of making a diver become nervous or annoyed. Therefore, these days a vehicle engineer takes aim at developing sound quality as well as reduction of noise. In this paper, we acquired noises in the HVAC from many vehicles. Through the objective and subjective sound quality evaluation with acquiring noises caused by the vehicle HVAC system, the simple and multiple regression models were obtained for the subjective evaluation 'Pleasant' using the sound quality metrics. The regression procedure also allows you to produce diagnostic statistics to evaluate the regression estimates including appropriation and accuracy. Furthermore, the neural network model were obtained using three inputs(loudness, sharpness and roughness) of the sound quality metrics and one output(subjective 'Pleasant'). And then the models were compared with correlations between sound quality index outputs and hearing test results for 'Pleasant'. As a result of application of the sound quality index, the neural network was verified with the largest correlation of the sound quality index.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.695-699
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• 2003

It is general to use the control network in control systems in order to reduce the complexity of the related wiring harnesses and to improve the system flexibility. CAN becomes one of the most popular network protocols because of its low price, multiple sources, high performance and reliability. This paper describes a CAN based real-time control of the fire detection system for the intelligent building system. The proposed fire detection and alarm system is stronger than the previous one against noises and communication media faults and can solve many problems such as complex cabling and increment of I/O ports by using many sensors. Furthermore, MMI can be achieved easily with the personal computer that is used for replacing the traditional monitoring system. The proposed system is implemented and the experimental results are given.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.1-6
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• 1993

This report proposes a novel method of identification of continuous time-delay systems from sampled input-output data. By the aid of a digital pre-filter, an approximated discrete-time estimation model is first derived, in which the system parameters remain in their original form and the time delay need not be an integral multiple of th sampling period. Then an identification method combining the common linear least squares(LS) method or the instrumental variable(IV) method with the genetic algorithm(GA) is proposed. That is, the time-delay is selected by the GA, and the system parameters are estimated by the LS or IV method. Furthermore, the proposed method is extended to the case of multi-input multi-output systems where the time-delays in the individual input channels may differ each other. Simulation resutls show that our method yields consistent estimates even in the presence of high measurement noises.

• Journal of electromagnetic engineering and science
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• v.3 no.1
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• pp.7-11
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• 2003

CDMA(code division multiple access) has very large peak to average power ratio(PAR) and behave as noise-like wide band digital signals with 1.2288 Mbps transmission rate. For signals with high PAR like CDMA, it is reasonable to prescribe occupied bandwidth(OBW) as average occupied bandwidth. Bandwidth measurements of CDMA signals at remote site are affected by co-channel and adjacent channel interference from adjacent CDMA base station, distortion of signal by fading effect, spurious emission and environment noises. In this study, we have compared OBW measurements in an on-air environment with those measured in a base station using adjacent channel leakage ratio(ACLR) as a reference measurement factor. As results of analysis, the OBW at ACLR$\geq$35 ㏈ shows nearly same statistical characteristics regardless of the measurement locations and environments.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.71-74
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• 2003

The signal processing algorithm for a PSD(Position Sensitive Detector) using amplitude modulation/demodulation is addressed in this paper. Dark currents and external noises such as daylight and fluorescent lights are eliminated by using amplitude modulation/demodulation and a low pass filter. The proposed amplitude modulation/demodulation method for a PSD sensor is compared with pulse amplitude modulation method. The proposed amplitude modulation is proved to be more accurate and robust than PAM method by analysis and experiments. Multiple measurements using one PSD sensor by amplitude modulation/demodulation is also addressed. The Power variation of light source is compensated by normalization process using a divider.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1998.04a
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• pp.27-33
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• 1998

The powertrain is a system of exciters which are connected by vibration transmitters and noise radiators. The powertrain has infinite natural frequencies. If the engine explosion, excites a certain natural frequency, then the powertrain system seriously vibrates. The torsional vibration arises from here. Torsional vibration like this can cause various noises as rattle and booming. In this study, the simulation models of multiple degrees of freedom were developed to reduce the torsional vibration of the powertrain. These models are combined mass moment of inertias with torsional springs. The free and forced vibration analyses were carried out by these models; and the validity of the simulation models were checked by the field test. The reduction effect of the torsional vibration along the driveline design factor is presented by the analytical results.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.897-898
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• 2008

Array comparative genomic hybridization (aCGH) has been used to detect chromosomal regions of amplifications or deletions, which allows identification of new cancer related genes. As aCGH, a large-scale spatial data, contains significant amount of noises in its raw data, it has been an important research issue to segment genomic DNA regions to detect its true underlying copy number aberrations (CNAs). In this study, we focus on applying a segmentation method to multiple data sets. We compare two different threshold values for analyzing aCGH data with CBS method [1]. The proposed threshold values are p-value or $Q{\pm}1.5IQR$ and $Q{\pm}1.5IQR$.

• Journal of KSNVE
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• v.10 no.6
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• pp.941-948
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• 2000

Active noise control is an approach to reduce the noise by utilizing a secondary noise source that destructively interferes with the unwanted noise. In general, active noise control systems rely on multiple sensors to measure the unwanted noise field and the effect of the cancellation. This paper develops an approach that utilizes a single sensor. The noise field is modeled as a stochastic process, and an adaptive algorithm is used to adaptively estimate the parameters of the process. Based on these parameter estimates, a canceling signal is generated. Oppenheim assumed that transfer function characteristics from the canceling source to the error sensor is only a propagation delay. This paper proposes a modified Oppenheim algorithm by considering transfer characteristics of speaker-path-sensor This transfer characteristics is adaptively cancelled by the proposed adaptive modeling technique. Feasibility of the proposed method is proved by computer simulations with artificially generated random noises and sine wave noise. The details of the proposed architecture. and theoretical simulation of the noise cancellation system for three dimension enclosure are presented in the Paper.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.3
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• pp.166-173
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• 2005

Preserving image features, edges and details in the process of impulsive noise filtering is an important problem. To avoid image blurring, only corrupted pixels must be filtered. In this paper, we propose an effective impulse noise detection method using Self-Organizing Neural Network(SONN) which applies median filter selectively for removing random-valued impulse noises while preserving image features, edges and details. Using a $3\times3$ window, we obtain useful local features with which impulse noise patterns are classified. SONN is trained with sample image patterns and each pixel pattern is classified by its local information in the image. The results of the experiments with various images which are the noise range of $5-15\%$ show that our method performs better than other methods which use multiple threshold values for impulse noise detection.

• Structural Engineering and Mechanics
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• v.42 no.3
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• pp.425-448
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• 2012

In this paper, a new damage detection and quantification method has been presented to perform detection and quantification of structural damage under ambient vibration loadings. To extract modal properties of the structural system under ambient excitation, natural excitation technique (NExT) and eigensystem realization algorithm (ERA) are employed. Sensitivity matrices of the dynamic residual force vector have been derived and used in the parameter subset selection method to identify multiple damaged locations. In the sequel, the steady state genetic algorithm (SSGA) is used to determine quantified levels of the identified damage by minimizing errors in the modal flexibility matrix. In this study, performance of the proposed damage detection and quantification methodology is evaluated using a finite element model of a truss structure with considerations of possible experimental errors and noises. A series of numerical examples with five different damage scenarios including a challengingly small damage level demonstrates that the proposed methodology can efficaciously detect and quantify damage under noisy ambient vibrations.