• Title/Summary/Keyword: optimal smoothing

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Tetrahedral Mesh Generation by Using the Advancing-Front Method and the Optimal Surface Triangular Mesh Generation Technique (전진경계기법과 최적 표면 삼각형 요소망 생성 기법을 이용한 사면체 요소망의 생성)

  • Lee M.C.;Joun M.S.
    • Korean Journal of Computational Design and Engineering
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    • v.11 no.2
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    • pp.138-147
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    • 2006
  • A systematic approach to tetrahedral element or mesh generation, based on an advancing-front method and an optimal triangular mesh generation technique on the surface, is presented in this paper. The possible internal nodes are obtained by the octree-decomposition scheme. The initial tetrahedral mesh system is constructed by the advancing-front method and then it is improved by the quality improvement processes including mesh swapping and nodal smoothing. The approach is evaluated by investigating the normalized length, the normalized volume, the dihedral angle and the normalized quality

The Safety Stock Determination by the Optimal Service Level and the Forecasting Error Correcting (최적서비스수준과 예측오차수정에 의한 안전재고 결정)

  • 안동규;이상용
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.19 no.37
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    • pp.31-40
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    • 1996
  • The amount of safety stock is decided from various information such as the forecasted demand, the lead time, the size of the order quantity and the desired service level. There are two cases to consider the problem of setting safety stock when both the demand in a period and the lead time are characterized as random variables: the first case is the parameters of the demand and lead time distributions are known, the second case is they are unknown and must be estimated. The objective of this study is to present the procedure for setting safety stocks in the case the parameters of the demand and lead time distributions are unknown and must be estimated. In this study, a simple exponential smoothing model is used. to generate the estimates of demand in each period and a discrete distribution of the lead time is developed from historical data, and the optimal service level is used which determined to consider both of a backorder and lost sale.

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A Study on the Optimal Design for the reconstruction Filter in Single Photon Emission Computed Tomography (SPECT) (단일광자방출 전산화 단층촬영상에서 재구성 필터의 최적설계에 관한 연구)

  • 김정희;김광익
    • Journal of Biomedical Engineering Research
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    • v.18 no.2
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    • pp.113-120
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    • 1997
  • This paper presents an optimal design for the SPECT reconstruction filter, based on a physical limit of SPECT lesion detection capability. To increase the performance of the filter on lesion detectability, the filter design was focused on increasing the local SyW ratio of a threshold lesion, that was determined by minimum detectable lesion size (MDU) from SPECT lesion detectabllity contrast-detail curve. The proposed filter showed flexible window characteristics of resolution recovery and noise smoothing for MDLSs in the resolution-limited and photon-limited regions, respectively, compennting for the relative impact of the main limitation factors on threshold detectability. The simulated results showed good adaptability of the proposed filter to the changes in physical parameters of photon counts, object contrast, and detector system resolution.

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Color image quantization considering distortion measure of local region block on RGB space (RGB 공간상의 국부 영역 블록의 왜곡척도를 고려한 칼라 영상 양자화)

  • 박양우;이응주;김경만;엄태억;하영호
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.21 no.4
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    • pp.848-854
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    • 1996
  • Many image display devices allow only a limited number of colors to be simultaneously displayed. in disphaying of natural color image using color palette, it is necessary to construct an optimal color palette and the optimal mapping of each pixed of the original image to a color from the palette. In this paper, we proposed the clustering algorithm using local region block centered one color cluster in the prequantized 3-D histogram. Cluster pairs which have the least distortion error are merged by considering distortion measure. The clustering process is continued until to obtain the desired number of colors. The same as the clustering process, original color value. The proposed algorithm incroporated with a spatial activity weighting value which is reflected sensitivity of HVS quantization errors in smoothing region. This method produces high quality display images and considerably reduces computation time.

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An Optimal SAR Speckle Filter

  • Han, Chun-ming;Guo, Hua-Dong;Changlin, Wang;Dian, Fan
    • Proceedings of the KSRS Conference
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    • 2002.10a
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    • pp.476-483
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    • 2002
  • In the past 20 years or so, numerous methods to reduce speckle in SAR images have been proposed. The primary goal of these methods is to reduce speckle without destroying resolution and smearing edge information. But the experiments indicate that there is always a kind of tradeoff between smoothing out speckle and preserving edge information. In this paper, an optimal SAR speckle filter is developed. It can effectively smooth out speckle while preserve edge information.

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Predictive Modeling of the Bus Arrival Time on the Arterial using Real-Time BIS Data (실시간 BIS자료를 이용한 간선도로의 버스도착시간 예측모형구축에 관한 연구)

  • Kim, Tae Gon;Ahn, Hyeun Chul;Kim, Seung Gil
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.29 no.1D
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    • pp.1-9
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    • 2009
  • Bus information system(BIS), as a part of the intelligent transportation system(ITS), is one of the most advanced public transportation systems which provide the real-time bus traffic information for the users waiting the buses at the bus stop. However, correct bus information data, such as the present bus location, the user waiting time, the bus arrival time, etc. are not provided for the bus users because the proper bus arrival time predictive models are not used yet in most of the cities operating the bus information system, including the metropolitan City of Ulsan. Thus, the purpose in this study is to investigate real-time bus traffic characteristic data for identifying the bus operation characteristics on the arterial under the study in the metropolitan City of Ulsan, analyze real-time bus traffic characteristic data on the ID locations of the arterial under the study, construct the optimal unit segment models for the unit segments which are the bus stop, node and travel section using the exponential smoothing, weighted smoothing and Kalman Filter methods, respectively, and finally suggest the optimal integrated model for predicting the real-time bus arrival time at the bus stop of the arterial under the study.

Hierarchical time series forecasting with an application to traffic accident counts (계층적 시계열 분석을 이용한 지역별 교통사고 발생건수 예측)

  • Lee, Jooeun;Seong, Byeongchan
    • The Korean Journal of Applied Statistics
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    • v.30 no.1
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    • pp.181-193
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    • 2017
  • The paper introduces bottom-up and optimal combination methods that can analyze and forecast hierarchical time series. These methods allow forecasts at lower levels to be summed consistently to upper levels without any ad-hoc adjustment. They can also potentially improve forecast performance in comparison to independent forecasts. We forecast regional traffic accident counts as time series data in order to identify efficiency gains from hierarchical forecasting. We observe that bottom-up or optimal combination methods are superior to independent methods in terms of forecast accuracy.

Gaussian Filtering Effects on Brain Tissue-masked Susceptibility Weighted Images to Optimize Voxel-based Analysis (화소 분석의 최적화를 위해 자화감수성 영상에 나타난 뇌조직의 가우시안 필터 효과 연구)

  • Hwang, Eo-Jin;Kim, Min-Ji;Jahng, Geon-Ho
    • Investigative Magnetic Resonance Imaging
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    • v.17 no.4
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    • pp.275-285
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    • 2013
  • Purpose : The objective of this study was to investigate effects of different smoothing kernel sizes on brain tissue-masked susceptibility-weighted images (SWI) obtained from normal elderly subjects using voxel-based analyses. Materials and Methods: Twenty healthy human volunteers (mean $age{\pm}SD$ = $67.8{\pm}6.09$ years, 14 females and 6 males) were studied after informed consent. A fully first-order flow-compensated three-dimensional (3D) gradient-echo sequence ran to obtain axial magnitude and phase images to generate SWI data. In addition, sagittal 3D T1-weighted images were acquired with the magnetization-prepared rapid acquisition of gradient-echo sequence for brain tissue segmentation and imaging registration. Both paramagnetically (PSWI) and diamagnetically (NSWI) phase-masked SWI data were obtained with masking out non-brain tissues. Finally, both tissue-masked PSWI and NSWI data were smoothed using different smoothing kernel sizes that were isotropic 0, 2, 4, and 8 mm Gaussian kernels. The voxel-based comparisons were performed using a paired t-test between PSWI and NSWI for each smoothing kernel size. Results: The significance of comparisons increased with increasing smoothing kernel sizes. Signals from NSWI were greater than those from PSWI. The smoothing kernel size of four was optimal to use voxel-based comparisons. The bilaterally different areas were found on multiple brain regions. Conclusion: The paramagnetic (positive) phase mask led to reduce signals from high susceptibility areas. To minimize partial volume effects and contributions of large vessels, the voxel-based analysis on SWI with masked non-brain components should be utilized.

Toward Optimal System of Financial Support for Higher Education (대학교육 지원체계의 합리화 방향 - 소득연계식 학자금융자제도를 중심으로 -)

  • Yun, Jungyoll
    • Journal of Labour Economics
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    • v.37 no.4
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    • pp.89-112
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    • 2014
  • This paper characterizes an optimal combination of grant and income-contingent loans (ICL) from efficiency and equity points of view as a government subsidy program for higher-education. In particular, we show that it is always desirable to introduce ICL for students regardless of their household incomes, and also provide arguments for the superiority of tax-financing system to loans with risk-premium as a financing mechanism of ICL. From policy point of view, this paper suggests a need for the extended coverage of our ICL system, while justifying its current tax-financing system.

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Implementation of Image Enhancement Filter System Using Genetic Algorithm (유전자 알고리즘을 이용한 영상개선 필터 시스템 구현)

  • Gu, Ji-Hun;Dong, Seong-Su;Lee, Jong-Ho
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.51 no.8
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    • pp.360-367
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    • 2002
  • In this paper, genetic algorithm based adaptive image enhancement filtering scheme is proposed and Implemented on FPGA board. Conventional filtering methods require a priori noise information for image enhancement. In general, if a priori information of noise is not available, heuristic intuition or time consuming recursive calculations are required for image enhancement. Contrary to the conventional filtering methods, the proposed filter system can find optimal combination of filters as well as their sequent order and parameter values adaptively to unknown noise types using structured genetic algorithms. The proposed image enhancement filter system is mainly composed of two blocks. The first block consists of genetic algorithm part and fitness evaluation part. And the second block consists of four types of filters. The first block (genetic algorithms and fitness evaluation blocks) is implemented on host computer using C code, and the second block is implemented on re-configurabe FPGA board. For gray scale control, smoothing and deblurring, four types of filters(median filter, histogram equalization filter, local enhancement filter, and 2D FIR filter) are implemented on FPGA. For evaluation, three types of noises are used and experimental results show that the Proposed scheme can generate optimal set of filters adaptively without a pioi noise information.