• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1820-1825
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• 2005

DSP chip parameters of a digital hearing aid (HA) should be optimally selected or fitted for hearing impaired persons. The more precise parameter fitting guarantees the better compensation of the hearing loss (HL). Digital HAs adopt DSP chips for more precise fitting of various HL threshold curve patterns. A specific DSP chip such as Gennum GB3211 was designed and manufactured in order to match up to about 4.7 billion different possible HL cases with combination of 7 limited parameters. This paper deals with a digital HA fitting program which is developed for optimal fitting of GB3211 DSP chip parameters. The fitting program has completed features from audiogram input to DSP chip interface. The compensation effects of the microphone and the receiver are also included. The paper shows some application examples.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.6
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• pp.530-538
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• 2006

DSP chip parameters of a digital hearing aid (HA) should be optimally selected or fitted for hearing impaired persons. The more precise parameter fitting guarantees the better compensation of the hearing loss (HL). Digital HAs adopt DSP chips for more precise fitting of various HL threshold curve patterns. A specific DSP chip such as Gennum GB3211 was designed and manufactured in order to match up to about 4.7 billion different possible HL cases with combination of 7 limited parameters. This paper deals with a digital HA fitting program which is developed for optimal fitting of GB3211 DSP chip parameters. The fitting program has completed features from audiogram input to DSP chip interface. The compensation effects of the microphone and the receiver are also included. The paper shows some application examples.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10c
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• pp.479-481
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• 1998

Noise가 있는 data에서 shape나 parameter를 찾았을 때 일반적으로 Hough transform이나 regression을 적용한다. Hough transform은 parameter space의 차수가 커지면 memory 문제가 존재하며, regression 모델은 한 개의 변수를 다른 변수의 함수로 가정하여 error를 최소화하여 데이터중 1 set의 parameter만 존재한다는 가정을 하여야 하는 문제점이 있다. 본 논문에서는 이러한 두 방법의 단점들을 보완하며, Fuzzy개념을 도입한 data fitting 방법을 제안하였다. 이 문제는 genetic algorithm을 도입하여 data를 Fuzzy membership을 갖는 것으로 가정한 최적화 문제로 해결하였다. 직선과 평면에 대한 실험 결과를 보인다.

• The Journal of Engineering Geology
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• v.31 no.2
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• pp.165-178
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• 2021

The influence of Soil-Water Characteristic Curve (SWCC) fitting parameters for an unsaturated natural slope was evaluated through seepage and slope stability analysis as a function of rainfall. Soil samples were collected from the study area in Jirisan National Park and the physical and mechanical characteristics of unsaturated soil layers were measured in laboratory tests. The saturation depth was calculated via seepage analysis by changing fitting parameters α, the parameter related to the Air Entry Value (AEV) and n, the parameter related to the slope of the SWCC in the range of natural conditions. Slope stability analysis using the limit equilibrium method considered the calculated depth of saturation. Results from seepage analysis for various rainfall conditions indicate the saturation depth in the soil layer suddenly increased as the fitting parameter α decreased; the saturation time for the entire soil layer also decreased. Slope stability analysis considering the calculated depth of saturation shows that the slope safety factor rapidly decreased as the fitting parameter α decreased, whereas the variation in slope safety factor was very small when n increased. Hence, fitting parameter α has a large effect on saturation depth during rainfall and therefore on slope stability, whereas slope stability is relatively unaffected by the fitting parameter n.

• Korean Journal of Computational Design and Engineering
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• v.14 no.1
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• pp.10-17
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• 2009

Surface detection and parameter estimation in point cloud is a relevant subject in CAD/CAM, reverse engineering, computer vision, coordinate metrology and digital factory. In this paper we present a software for a fully automatic surface detection and parameter estimation in unordered, incomplete and error-contaminated point cloud with a large number of data points. The software consists of three algorithmic modules each for object identification, point segmentation, and model fitting, which work interactively. Our newly developed algorithms for orthogonal distance fitting(ODF) play a fundamental role in each of the three modules. The ODF algorithms estimate the model parameters by minimizing the square sum of the shortest distances between the model feature and the measurement points. We demonstrate the performance of the software on a variety of point clouds generated by laser radar, computer tomography, and stripe-projection method.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.7 s.112
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• pp.769-776
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• 2006

A measured frequency response function can be represented as a ratio of two polynomials. A curve-fitting of frequency responses with Legendre polynomialis suggested in the paper. And the suggested curve-fitting algorithm is based on the least-square error method. Since the Legendre polynomials satisfy the orthogonality condition, the curve-fitting with the polynomials results to more reliable curve-fitting than ordinary polynomial method. Though the proposed curve-fitting with Legendre polynomials cannot cover all frequency range of interest, example shows that the suggested method is quite applicable in a limited frequency band.

• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.5
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• pp.117-125
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• 2003

Since the recorded information used for operation of a catchment modelling system contain errors that influence the calibration of catchment modelling system control parameter values, the accurate estimation of these parameters is difficult. Despite these influences, existing traditional calibration approaches focus only on achieving the best "curve fitting" between simulated and recorded data, and not on generic evaluation of control parameter values. This paper introduces an Early Stopping Technique which is aimed at avoiding the procedure of curve-fitting through monitoring improvements in the objective function used for assessing the optimal parameter set. Application of this approach to the calibration of SWMM (Storm Water Management Model) on the Centennial Park catchment in Sydney, Australia is outlined. outlined.

• Journal of Korea Multimedia Society
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• v.3 no.5
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• pp.495-505
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• 2000

In this paper, we propose an efficient auto-fitting system for digital hearing-aids which automatically adjusts the fitting parameters according to the auditory characteristics of hearing handicapped person. The fitting parameters are extracted from audiogram of hearing handicapped and are applied to digital hearing-aid purposed GM3036 chip. The characteristics of each parameter are compared with those from theoretical 2cc graph. The purposed system has applied to 50 patients and their satisfaction ratios show to the very high. As results, it shows effectiveness of proposed system.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2010-2014
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• 2005

Object detection and parameter estimation in point cloud data is a relevant subject to robotics, reverse engineering, computer vision, and sport mechanics. In this paper a software is presented for fully-automatic object detection and parameter estimation in unordered, incomplete and error-contaminated point cloud with a large number of data points. The software consists of three algorithmic modules each for object identification, point segmentation, and model fitting. The newly developed algorithms for orthogonal distance fitting (ODF) play a fundamental role in each of the three modules. The ODF algorithms estimate the model parameters by minimizing the square sum of the shortest distances between the model feature and the measurement points. Curvature analysis of the local quadric surfaces fitted to small patches of point cloud provides the necessary seed information for automatic model selection, point segmentation, and model fitting. The performance of the software on a variety of point cloud data will be demonstrated live.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.415-418
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• 2005

DSP chip parameters of a digital hearing aid (HA) should be optimally selected or fitted for hearing impaired persons. The more precise parameter fitting guarantees the better compensation of the hearing loss (HL). Digital HAs adopt DSP chips for more precise fitting of various HL threshold curve patterns. A specific DSP chip such as Gennum GB3211 was designed and manufactured in order to match up to about 4.7 billion different possible HL cases with combination of 7 limited parameters. This paper deals with a digital HA fitting program which is developed for optimal fitting of GB3211 DSP chip parameters. The fitting program has completed feature from audiogram input to DSP chip interface. The compensation effects of the microphone and the receiver are also included. The paper shows some application examples.