• Title/Summary/Keyword: statistical approach

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Efficient generation of CGH using statistical redundancy of 3-D images

  • Kim, Seung-Cheol;Kim, Eun-Soo
    • 한국정보디스플레이학회:학술대회논문집
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    • 2008.10a
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    • pp.722-725
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    • 2008
  • In this paper, we propose a new approach for fast generation of CGHs of a 3-D object by using the run-length encoding and N-LUT methods. In this approach, object points to be involved in calculation of the CGH pattern can be dramatically reduced and as a result a significant increase of computational speed can be obtained.

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Integrated Partial Sufficient Dimension Reduction with Heavily Unbalanced Categorical Predictors

  • Yoo, Jae-Keun
    • The Korean Journal of Applied Statistics
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    • v.23 no.5
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    • pp.977-985
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    • 2010
  • In this paper, we propose an approach to conduct partial sufficient dimension reduction with heavily unbalanced categorical predictors. For this, we consider integrated categorical predictors and investigate certain conditions that the integrated categorical predictor is fully informative to partial sufficient dimension reduction. For illustration, the proposed approach is implemented on optimal partial sliced inverse regression in simulation and data analysis.

A New Traffic Model for Internet Load Estimation (트래픽별 특성 규명을 통한 인터넷 부하 측정에 관한 연구)

  • Kim, Hu-Gon
    • Korean Management Science Review
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    • v.26 no.1
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    • pp.161-169
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    • 2009
  • A traffic analysis on the Internet has an advantage for obtaining the characteristics of transferred packets. There were many studies to understand the characteristics of the Internet traffic with mathematical statistical approach. The approach of this study is different from previous studies. We first introduced a virtual network concept to present the Internet as a simplified mathematical model. It also represents each traffic flowing on the Internet as a parallel Gaussian channel on the virtual network. We suggest the optimal capacity of each parallel Gaussian channel using some related studies on the Gaussian channel model.

The Statistical Approach for Determining the Parallel-Bundle Strength from Single-Filament Data of PET (PET single filament 데이터로부터의 번들강도 결정을 위한 통계적 접근)

  • Cho, Kee-Hwan;Jeong, Sung-Hoon
    • Proceedings of the Korean Fiber Society Conference
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    • 2003.10b
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    • pp.291-292
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    • 2003
  • Although the tensile strength of textile materials are determined by that of their components, it is well known that the tensile strength of fiber bundles and yams is not accurately predicted from that of single-fibers by simple averaging methods or mathematical calculations, because of variations in their strength. Therefore, there have been attempts to interpret the bundle strength from that of its elements by the stochastical approach. (omitted)

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STATISTICAL PHYSICS APPROACH TO BIOLOGICAL PHENOMENA

  • Sung, Wokyng
    • Proceedings of the Korean Biophysical Society Conference
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    • 1996.07a
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    • pp.7-7
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    • 1996
  • A new trend that emerges at the turn of the century is the physical approach to biological phenomena. It is expected that biology provides novel materials for condensed matter physics and, most importantly, a revolutionary paradigm for physics at large. On the other hand, physics, if properly extended, is expected to provide systematic and quantitative understanding of biological phenomena, and multitude of biotechnological applications. (omitted)

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Predicting Nuclear Power Plant Accidents in Korea (국내 원자력발전소 사고 예측)

  • Yang, Hee-Joong
    • IE interfaces
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    • v.6 no.2
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    • pp.79-89
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    • 1993
  • We develop a statistical model to describe nuclear power plant accidents and predict time to next accident of various levels. We adopt Bayesian approach to obtain posterior and predictive distributions for the time to next accident. We also derive an approximation method to solve many dimensional numerical integration problems that we often encounter in a Bayesian approach. We introduce Influence Diagrams in modeling, and parameter updating, thereby the dependency or independency among model parameters are clearly shown. Also Separable Updating Theorem is utilized to easily obtain the posterior distributions.

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Analysis of various statistical techniques used in the articles published during last 19 years in The Journal of Korean Acupuncture & Moxibusition Society (침구학회지 논문에 응용된 통계방식에 관한 연구 -1984 창간호부터 2002년 19권 6호까지 19년간-)

  • Lee, Seung-deok
    • Journal of Acupuncture Research
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    • v.20 no.1
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    • pp.144-158
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    • 2003
  • This study was carried out to investigate what kinds of statistical techniques have been used to analyze data from oriental medicine research, For study, 551 original articles which used statistical techniques in their data analysis were selected form the articles published in The journal of Korean Acupuncture & Moxibustion Society(JKAMS) between 1984 to 2002. among them, 122 articles used descriptive statistics while 429 articles used inferential statistics for data analysis. For that 429 articles, t-test (189 articles), analysis fo variance (111 articles), chi-square test (14 articles), correlation (10 articles), regression analysis (4 articles), factor analysis(5 articles), or nonparametric test (23 articles) were chose to analyze the data. Nonparametric approach has substantial power in case data do not meet the assumption of normality. This method is not only easy to use ut also provides measures of the statistical variation of nominal and ordinal scale. This study shows that more and more recent papers use nonparametric test compared to the old articles. nine different statistical software or packages (SAS, SPSS, Statview, Minitab, Sigma plot, ISP, Graphpad prism, Excel, Access) have been used in the articles published JKMAS. High level statistical techniques such as SAS, SPSS, and Statview are user friendly and used most for acupuncture and Moxibustion research. Including tables and plots in an article facilitates understanding family process data from a descriptive standpoint, minimized erroneous statistical conclusions, and clarifies theoretically important relationships among variables. Table and plots have been used 500 and 233 articles, respectively. A computer procedure is proposed and illustrated with statistical packages using SAS, SPSS, Statview and ISP.

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Determination of a Homogeneous Segment for Short-term Traffic Count Efficiency Using a Statistical Approach (통계적인 기법을 활용한 동질성구간에 따른 교통량 수시조사 효율화 연구)

  • Jung, YooSeok;Oh, JuSam
    • International Journal of Highway Engineering
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    • v.17 no.4
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    • pp.135-141
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    • 2015
  • PURPOSES: This study has been conducted to determine a homogeneous segment and integration to improve the efficiency of short-term traffic count. We have also attempted to reduce the traffic monitoring budget. METHODS: Based on the statistical approach, a homogeneous segment in the same road section is determined. Statistical analysis using t-test, mean difference, and correlation coefficient are carried out for 10-year-long (2004-2013) short-term count traffic data and the MAPE of fresh data (2014) are evaluated. The correlation coefficient represents a trend in traffic count, while the mean difference and t-score represent an average traffic count. RESULTS : The statistical analysis suggests that the number of target segments varies with the criteria. The correlation coefficient of more than 30% of the adjacent segment is higher than 0.8. A mean difference of 36.2% and t-score of 19.5% for adjacent segments are below 20% and 2.8, respectively. According to the effectiveness analysis, the integration criteria of the mean difference have a higher effect as compared to the t-score criteria. Thus, the mean difference represents a traffic volume similarity. CONCLUSIONS : The integration of 47 road segments from 882 adjacent road segments indicate 8.87% of MAPE, which is within an acceptable range. It can reduce the traffic monitoring budget and increase the count to improve an accuracy of traffic volume estimation.

FracSys와 UDEC을 이용한 사면 파괴 양상 분석 통계적 절리망 생성 기법 및 Monte Carlo Simulation을 통한 사면 안정성 해석

  • 김태희;최재원;윤운상;김춘식
    • Proceedings of the Korean Geotechical Society Conference
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    • 2002.03a
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    • pp.651-656
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    • 2002
  • In general, the most important problem in slope stability analysis is that there is no definite way to describe the natural three-dimensional Joint network. Therefore, the many approaches were tried to anlayze the slope stability. Numerical modeling approach is one of the branch to resolve the complexity of natural system. UDEC, FLAC, and SWEDGE are widely used commercial code for the purpose on stability analysis. For the purpose on the more appropriate application of these kind of code, however, three-dimensional distribution of joint network must be identified in more explicit way. Remaining problem is to definitely describe the three dimensional network of joint and bedding, but it is almost impossible in practical sense. Three dimensional joint generation method with random number generation and the results of generation to UDEC have been applied to settle the refered problems in field site. However, this approach also has a important problem, and it is that joint network is generated only once. This problem lead to the limitation on the application to field case, in practical sense. To get rid of this limitation, Monte Carlo Simulation is proposed in this study 1) statistical analysis of input values and definition of the applied system with statistical parameter, 2) instead of the consideration of generated network as a real system, generated system is just taken as one reliable system, 3) present the design parameters, through the statistical analysis of ouput values Results of this study are not only the probability of failure, but also area of failure block, shear strength, normal strength and failure pattern, and all of these results are described in statistical parameters. The results of this study, shear strength, failure area, pattern etc, can provide the direct basement on the design, cutoff angle, support pattern, support strength and etc.

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Shear strength prediction for SFRC and UHPC beams using a Bayesian approach

  • Cho, Hae-Chang;Park, Min-Kook;Hwang, Jin-Ha;Kang, Won-Hee;Kim, Kang Su
    • Structural Engineering and Mechanics
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    • v.74 no.4
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    • pp.503-514
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    • 2020
  • This study proposes prediction models for the shear strength of steel fiber reinforced concrete (SFRC) and ultra-high-performance fiber reinforced concrete (UHPC) beams using a Bayesian parameter estimation approach and a collected experimental database. Previous researchers had already proposed shear strength prediction models for SFRC and UHPC beams, but their performances were limited in terms of their prediction accuracies and the applicability to UHPC beams. Therefore, this study adopted a statistical approach based on a collected database to develop prediction models. In the database, 89 and 37 experimental data for SFRC and UHPC beams without stirrups were collected, respectively, and the proposed equations were developed using the Bayesian parameter estimation approach. The proposed models have a simplified form with important parameters, and in comparison to the existing prediction models, provide unbiased high prediction accuracy.