• Title/Summary/Keyword: Mean deviation method

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Evaluation of Tracheal Deviation in Patients with Thyroid Cancer (갑상선 암 환장서 기관지 편이 정도를 평가하는 방법의 연구)

  • Yoo, Young-Sam
    • Korean Journal of Bronchoesophagology
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    • v.16 no.2
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    • pp.138-144
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    • 2010
  • Background: Tracheal deviations are encountered frequently in head and neck tumors especially in thyroid cancer. Dyspnea and stridor are symptom calling for surgery. The method of evaluation in tracheal deviation is not well established yet. This paper is aimed to suggest objective tools to evaluate tracheal deviation in relation to cervical vertebra. Material and Method: Ten cases of thyroid cancers were recruited retrospectively. Tracheal inner shadow and shape of cervical vertebra were reconstructed three dimensionally using 3D-doctor to compare position of trachea in relation to vertebral body. Extent of deviation was scored in relation to both lateral borders of vertebral body. Angles between trachea and spinous process were measured in axial CT and compared between study group and control group. Results: Deviation scores were statistically significant between study group (mean=1.1) and control group (mean=0) (p=0.0008). Deviation angles at maximal tumor size in study group (mean=160.3 Degrees) and deviation angles of control group (mean=177.1 Degrees) were statistically significant (p=0.0007). Angles at maximal deviation of three dimensional images ages in study group (mean=162.6 Degrees) and deviation angles of control group (mean=177.1 Degrees) were statistically significant (p=0.0089). Conclusion: Tracheal deviation can be evaluated using scoring of three dimensional images and measuring angle between trachea and vertebral spine.

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A Study for Robustness of Objective Function and Constraints in Robust Design Optimization

  • Lee Tae-Won
    • Journal of Mechanical Science and Technology
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    • v.20 no.10
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    • pp.1662-1669
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    • 2006
  • Since randomness and uncertainties of design parameters are inherent, the robust design has gained an ever increasing importance in mechanical engineering. The robustness is assessed by the measure of performance variability around mean value, which is called as standard deviation. Hence, constraints in robust optimization problem can be approached as probability constraints in reliability based optimization. Then, the FOSM (first order second moment) method or the AFOSM (advanced first order second moment) method can be used to calculate the mean values and the standard deviations of functions describing constraints and object. Among two methods, AFOSM method has some advantage over FOSM method in evaluation of probability. Nevertheless, it is difficult to obtain the mean value and the standard deviation of objective function using AFOSM method, because it requires that the mean value of function is always positive. This paper presented a special technique to overcome this weakness of AFOSM method. The mean value and the standard deviation of objective function by the proposed method are reliable as shown in examples compared with results by FOSM method.

Development of Nonlinear Fatigue Model Based on Particle Filter Method (파티클 필터기법을 통한 비선형 피로모델 개발 연구)

  • Mun, Sungho
    • International Journal of Highway Engineering
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    • v.18 no.4
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    • pp.63-68
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    • 2016
  • PURPOSES : The nonlinear model of fatigue cracking is typically used for determining the maintenance period. However, this requires that the model parameters be known. In this study, the particle filter (PF) method was used to determine various statistical parameters such as the mean and standard deviation values for the nonlinear model of fatigue cracking. METHODS : The PF method was used to determine various statistical parameters for the nonlinear model of fatigue cracking, such as the mean and standard deviation. RESULTS : On comparing the values obtained using the PF method and the least square (LS) method, it was found that PF method was suitable for determining the statistical parameters to be used in the nonlinear model of fatigue cracking. CONCLUSIONS : The values obtained using the PF method were as accurate as those obtained using the LS method. Furthermore, reliability design can be applied because the statistical parameters of mean and standard deviation can be obtained through the PF method.

Variable Sampling Interval $\bar{X}$ Control Chart Using Weighted Standard Deviation Method (가중표준편차를 이용한 가변표본채취간격 $\bar{X}$ 관리도)

  • Chang, Youngsoon
    • Journal of the Korean Operations Research and Management Science Society
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    • v.39 no.1
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    • pp.1-12
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    • 2014
  • This article proposes a variable sampling interval (VSI) $\bar{X}$ control chart using weighted standard deviation (WSD) method for skewed populations. The WSD method decomposes the standard deviation of a quality characteristic into upper and lower deviations and adjusts control limits and warning limits of a control chart in accordance with the direction and degree of skewness. A control chart constant is derived for estimating the standard deviation of skewed distributions with the mean of sample standard deviations. The proposed chart is compared with the conventional VSI $\bar{X}$ control chart under some skewed distributions. Simulation study shows that the proposed WSD VSI chart can control the in-control average time to signal (ATS) as an adequate level better than the conventional VSI chart, and the proposed chart can detect a decrease in the process mean of a quality characteristic following a positively skewed distribution more quickly than the standard VSI chart.

The Consideration of Consistent Use of Sample Standard Deviation in the Confidence Interval Estimation of Population Mean and Population Ratio (모평균과 모비율의 구간추정에서 표본표준편차의 일관된 사용에 대한 고찰)

  • Park, Sun Yong;Yoon, Hyoung Seok
    • Journal of Educational Research in Mathematics
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    • v.24 no.3
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    • pp.375-385
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    • 2014
  • This study compares the confidence interval estimation of population mean with that of population ratio, and considers whether these two estimations ensures consistency. As a result, this study suggests the following acquisition method of consistency : dealing with population mean and population ratio in the same mode, substituting the observed or experimental value of sample standard deviation for standard deviation in population in setting a confidence interval of both population mean and population ratio, and distinguishing population ratio $\hat{P}$ from its observed vale $\hat{p}$.

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Calculating Mean Life of Generators with Aging failures Data Using Data Analytic Method (통계적 분석 방법을 이용한 발전설비의 평균수명 계산)

  • Lee Sung Hoon;Lee Seung Hyuk;Kim Jin O;Jeon Dong Hoon;Kim Tae Kyun
    • Proceedings of the KIEE Conference
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    • summer
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    • pp.464-466
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    • 2004
  • This paper proposes a method to consider an aging failure probability and survival probability of power system components unlike uses only aging failure probability in existing mean life calculation. The estimates of the mean and its standard deviation is calculated by using Weibull distribution and each estimated parameters is obtained from Data Analytic Method (Type II Censoring). The parameter estimation using Data Analytic Method is simpler and faster than a traditional calculation method. This paper shows how to calculate the mean life and its standard deviation by the proposed method and illustrates a exactness using real historical records of generator utilities in korea.

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Scene Change Detection using the Automated Threshold Estimation Algorithm

  • Ko Kyong-Cheol;Rhee Yang-Won
    • The Journal of Information Systems
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    • v.14 no.3
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    • pp.117-122
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    • 2005
  • This paper presents a method for detecting scene changes in video sequences, in which the $chi^{2}$-test is modified by imposing weights according to NTSC standard. To automatically determine threshold values for scene change detection, the proposed method utilizes the frame differences that are obtained by the weighted $chi^{2}$-test. In the first step, the mean and the standard deviation of the difference values are calculated, and then, we subtract the mean difference value from each difference value. In the next step, the same process is performed on the remained difference values, mean-subtracted frame differences, until the stopping criterion is satisfied. Finally, the threshold value for scene change detection is determined by the proposed automatic threshold estimation algorithm. The proposed method is tested on various video sources and, in the experimental results, it is shown that the proposed method is reliably estimates the thresholds and detects scene changes.

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The Experimental Study on the Development of Estimation Technique for the Mix Proportion of Hardened Concrete (경화 콘크리트의 배합비 추정기법 개발에 관한 실험적 연구)

  • 이준구;박광수;김석열;김명원;김관호;박미현
    • Proceedings of the Korea Concrete Institute Conference
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    • 2000.10b
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    • pp.961-966
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    • 2000
  • It is difficult to change or remedy concrete structure after hardened. It is usual to evaluate the quality of hardened concrete using several test method. This study was performed to make fundamental data that could be used to evaluate the quality of hardened concrete. This study is to estimate mix proportion of hardened concrete. Each elements of concrete needed different estimation methods. First, the cement that handled by the most important compounds measured by XRF(X-ray fluorecence) machine with scanning Ca-K${\alpha}$. Second, the coarse aggregate that divided by maximum size measured by the area comparison method that starts from the assumption of uniform distribution. Third, the fine aggregate measured by the weight comparison method that needs several prerequsite constants which concerned cement hydration reaction. Fourth, the water content would be estimated by expert system that has data base of design data, the contents of above estimation results, the characteristics of concrete strength. As the result of the above research, some conclusions are as follows. The cement estimation method resulted by reliability of mean 96.7%, standard deviation 3.92. The area comparison method resulted by reliability of mean 95.3%, standard deviation 2.08. The weight comparison method resulted by reliability of mean 93.3%, standard deviation 3.35.

Diagnosis of Thickness Quality Using Multivariate Statistical Analysis in Hot Finishing Mill

  • Kim, Heung-Mook
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.116.3-116
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    • 2001
  • A diagnosis methodology for thickness quality in hot finishing mill is proposed based on multivariate statistical analysis. The thickness of hot strip is a key quality factor that is measured by x-ray thickness gauge. Currently, the thickness quality is guaranteed by upper and lower limit of thickness deviation from target thickness. But if any over-limit is occurred, there is no in-line method to identify the causes. In this paper, many parameters are extracted from the thickness deviation signal such as mean deviation(top, middle, tail), rms deviation(top, middle, tail) and peak deviation(top, middle, tail) as time domain parameters ...

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Multiperiod Mean Absolute Deviation Uncertain Portfolio Selection

  • Zhang, Peng
    • Industrial Engineering and Management Systems
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    • v.15 no.1
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    • pp.63-76
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    • 2016
  • Multiperiod portfolio selection problem attracts more and more attentions because it is in accordance with the practical investment decision-making problem. However, the existing literature on this field is almost undertaken by regarding security returns as random variables in the framework of probability theory. Different from these works, we assume that security returns are uncertain variables which may be given by the experts, and take absolute deviation as a risk measure in the framework of uncertainty theory. In this paper, a new multiperiod mean absolute deviation uncertain portfolio selection models is presented by taking transaction costs, borrowing constraints and threshold constraints into account, which an optimal investment policy can be generated to help investors not only achieve an optimal return, but also have a good risk control. Threshold constraints limit the amount of capital to be invested in each stock and prevent very small investments in any stock. Based on uncertain theories, the model is converted to a dynamic optimization problem. Because of the transaction costs, the model is a dynamic optimization problem with path dependence. To solve the new model in general cases, the forward dynamic programming method is presented. In addition, a numerical example is also presented to illustrate the modeling idea and the effectiveness of the designed algorithm.