scholarly journals On The Relationship Between Speech-Based Breathing Signal Prediction Evaluation Measures and Breathing Parameters Estimation

2021 ◽  
Author(s):  
Zohreh Mostaani ◽  
Venkata Srikanth Nallanthighal ◽  
Aki Harma ◽  
Helmer Strik ◽  
Mathew Magimai-Doss
Keyword(s):  
Parameters Estimation ◽  
Evaluation Measures ◽  
Signal Prediction ◽  
The Relationship ◽  
Prediction Evaluation

Fit Quality Evaluation and Fit Capability Analysis

1999 ◽  
Author(s):  
Y. Zhang ◽  
X. Daniel Fang
Keyword(s):  
Process Monitoring ◽  
Process Design ◽  
Quality Evaluation ◽  
Process Capability Indices ◽  
Analysis Method ◽  
Evaluation Measures ◽  
Capability Indices ◽  
Capability Analysis ◽  
The Relationship

Abstract A new measure for evaluating fit quality of mating parts via Fit Capability Indices (FCIs) is introduced as an interface between fit quality and process control of the mating parts. Fit Capability Analysis method is discussed based on the relationship between FCIs and Process Capability Indices (PCIs). A new statistical tolerancing approach for assuring predetermined fit quality is developed on the basis of fit quality evaluation measures and fit capability analysis, which can be used as a guideline to process design and process monitoring of the mating parts.

Hardness Prediction Based on P-h Curves and Inverse Material Parameters Estimation

2015 ◽  
Vol 776 ◽  
pp. 233-238
Author(s):  
I. Nyoman Budiarsa
Keyword(s):  
Material Properties ◽  
Element Model ◽  
Parameters Estimation ◽  
Spherical Indentation ◽  
Vickers Indentation ◽  
Material Parameters ◽  
Wide Range ◽  
Constitutive Material ◽  
The Relationship ◽  
Hardness Values

The Finite Element model of Vickers indentation has been developed. The model was validated against published testing data. An approach to predict the P-h curves from constitutive material properties has been developed and evaluated based the relationship between the curvature and material properties and representative stress. The equation and procedure established was then successfully used in predict the full Vickers indentation P-h curve. FE Spherical indentation models of different radius have been developed and replay file model was developed that is able to produce data of different materials properties. Two new approaches to characterise the P-h curves of spherical indentation have been developed and evaluated. One is the full curve fitting approach while the other is depth based approach. Both approaches were proven to be adequate and effective in predicting indentation P-h curves. The concept and methodology developed is successfully used to predict hardness values (HV and HRB) of materials through direct analysis and validated with experimental data on selected sample of steels. The approaches (i.e. predict hardness from P-h curves) established was successfully used to produce hardness values of a wide range of material properties, which is then used to establish the relationship between the hardness values (HV and/or HRB) with representative stress. This provided a useful tool to evaluate the feasibility of using hardness values in predicting the constitutive material parameters with reference to accuracy and uniqueness by mapping through all potential materials ranges

The Difference of Preference versus Performance can Differ for Concurrent versus Retrospective Ratings

2000 ◽  
Vol 44 (37) ◽  
pp. 617-620 ◽  
Author(s):  
Srinivas Raghavan ◽  
Gary Perlman
Keyword(s):  
Subjective Ratings ◽  
Evaluation Measures ◽  
Objective Performance ◽  
Subjective Preference ◽  
Separate Treatment ◽  
Objective Performance Measures ◽  
Preference Ratings ◽  
The Difference ◽  
Relationship Of ◽  
The Relationship

Several studies have found differences between subjective preference ratings and objective performance measures. Bailey [Bailey 93] summarizes several, and argues for separate treatment of these concepts. Our results in a multifactor multivariate experiment support Bailey's contention, but adds a new dimension of concern: the use of concurrent versus retrospective subjective ratings. The presentation here will focus on the relationship of performance and concurrent versus retrospective preference ratings. Retrospective ratings may represent users' lasting impressions of a system after a trial use, but may not be good predictors of performance. Concurrent ratings of confidence of accuracy were found, in this study, to be better predictors performance. We offer recommendations about how to make the best use of these different evaluation measures, particularly when they differ.

MEAN RESIDUAL LIFE AND OTHER PROPERTIES OF WEIBULL RELATED BATHTUB SHAPE FAILURE RATE DISTRIBUTIONS

2004 ◽  
Vol 11 (02) ◽  
pp. 113-132 ◽  
Author(s):  
C. D. LAI ◽  
LINGYUN ZHANG ◽  
M. XIE
Keyword(s):  
Failure Rate ◽  
Residual Life ◽  
Weibull Model ◽  
Parameters Estimation ◽  
Mean Residual Life ◽  
Bathtub Shape ◽  
Reliability Characteristics ◽  
Rate Functions ◽  
Life Distributions ◽  
The Relationship

The two-parameter Weibull distribution is widely used in reliability analysis. Because of its monotonic ageing behaviour, its applicability is hampered in certain reliability situations. Several generalizations and extensions of the Weibull model have been proposed in the literature to overcome this limitation but their properties have not yet been described in a unified manner. In this paper, graphical displays of the mean residual life curves of several families of Weibull related life distributions are given together with their corresponding failure rate functions. The relationship between these two functions are visibly demonstrated. We focus our attention on the Weibull related families that have bathtub or modified bathtub shape failure rates. Important reliability characteristics such as burn-in, change point and flatness of bathtub of these families are examined. Model selection and parameters estimation are also discussed.

scholarly journals Breast Tumor Simulation and Parameters Estimation Using Evolutionary Algorithms

2008 ◽  
Vol 2008 ◽  
pp. 1-6 ◽  
Author(s):  
Manu Mital ◽  
Ramana M. Pidaparti
Keyword(s):  
Finite Element ◽  
Evolutionary Algorithms ◽  
Surface Temperature ◽  
Temperature Profile ◽  
Heat Generation ◽  
Breast Tumor ◽  
Fitness Function ◽  
Parameters Estimation ◽  
Finite Element Software ◽  
The Relationship

An estimation methodology is presented to determine the breast tumor parameters using the surface temperature profile that may be obtained by infrared thermography. The estimation methodology involves evolutionary algorithms using artificial neural network (ANN) and genetic algorithm (GA). The ANN is used to map the relationship of tumor parameters (depth, size, and heat generation) to the temperature profile over the idealized breast model. The relationship obtained from ANN is compared to that obtained by finite element software. Results from ANN training/testing were in good agreement with those obtained from finite element model. After ANN validation, GA is used to estimate tumor parameters by minimizing a fitness function involving comparing the temperature profiles from simulated or clinical data to those obtained by ANN. Results show that it is possible to determine the depth, diameter, and heat generation rate from the surface temperature data (with 5% random noise) with good accuracy for the 2D model. With 10% noise, the accuracy of estimation deteriorates for deep-seated tumors with low heat generation. In order to further develop this methodology for use in a clinical scenario, several aspects such as 3D breast geometry and the effects of nonuniform cooling should be considered in future investigations.

The Numerical and its Application in the Interval Estimates and Hypothesis Test

2010 ◽  
Vol 143-144 ◽  
pp. 1391-1395
Author(s):  
Xin Chun Wang ◽  
Xing Hua Ma ◽  
Bing Han
Keyword(s):  
Confidence Interval ◽  
Hypothesis Testing ◽  
Statistical Inference ◽  
Hypothesis Test ◽  
Interval Estimation ◽  
Parameters Estimation ◽  
Unknown Parameters ◽  
Significance Level ◽  
The Relationship ◽  
Statistical Work

The whole unknown parameters estimation and hypothesis testing is the most common and most commonly used statistical inference,so clarify the relationship between them is very important.Clearing both unity and not uniformity will help to amend the emergence of some specious argument of statistical work. In this paper, some differences were analyzed on interval estimation and hypothesis testing of statistical inference theory,the scope of their application of two methods was discussed, the dualityof Neyman —Pearson hypothesis testing and confidence interval was described Then provided the method of determining the unknown parameters’ confidence interval in hypothesis test.at the same time, it provided the ideas how to solve the problem of refusal field of hypothesis test througn confidence interval . As the confidence interval of the statistics varies with the selected significance level and sample size, it is heavily influenced by subjective factors.

Interstellar gas in the central region of the Galaxy

1967 ◽  
Vol 31 ◽  
pp. 239-251 ◽  
Author(s):  
F. J. Kerr
Keyword(s):  
Central Region ◽  
Galactic Plane ◽  
Neutral Hydrogen ◽  
Continuum Emission ◽  
Galactic Centre ◽  
Interstellar Gas ◽  
Hydrogen Recombination ◽  
The Galaxy ◽  
Centre Region ◽  
The Relationship

A review is given of information on the galactic-centre region obtained from recent observations of the 21-cm line from neutral hydrogen, the 18-cm group of OH lines, a hydrogen recombination line at 6 cm wavelength, and the continuum emission from ionized hydrogen.Both inward and outward motions are important in this region, in addition to rotation. Several types of observation indicate the presence of material in features inclined to the galactic plane. The relationship between the H and OH concentrations is not yet clear, but a rough picture of the central region can be proposed.

The relationship of the scleractinian corals to the rugose corals

Paleobiology ◽  
1980 ◽  
Vol 6 (02) ◽  
pp. 146-160 ◽  
Author(s):  
William A. Oliver
Keyword(s):  
Critical Points ◽  
Scleractinian Corals ◽  
Convincing Evidence ◽  
Early Triassic ◽  
Rugose Corals ◽  
History Of ◽  
The Subject ◽  
Relationship Of ◽  
The Relationship ◽  
Biologic Factors

The Mesozoic-Cenozoic coral Order Scleractinia has been suggested to have originated or evolved (1) by direct descent from the Paleozoic Order Rugosa or (2) by the development of a skeleton in members of one of the anemone groups that probably have existed throughout Phanerozoic time. In spite of much work on the subject, advocates of the direct descent hypothesis have failed to find convincing evidence of this relationship. Critical points are:(1) Rugosan septal insertion is serial; Scleractinian insertion is cyclic; no intermediate stages have been demonstrated. Apparent intermediates are Scleractinia having bilateral cyclic insertion or teratological Rugosa.(2) There is convincing evidence that the skeletons of many Rugosa were calcitic and none are known to be or to have been aragonitic. In contrast, the skeletons of all living Scleractinia are aragonitic and there is evidence that fossil Scleractinia were aragonitic also. The mineralogic difference is almost certainly due to intrinsic biologic factors.(3) No early Triassic corals of either group are known. This fact is not compelling (by itself) but is important in connection with points 1 and 2, because, given direct descent, both changes took place during this only stage in the history of the two groups in which there are no known corals.

Choosing a Markov blanket

2020 ◽  
Vol 43 ◽  
Author(s):  
Thomas Parr
Keyword(s):  
Markov Blanket ◽  
Target Article ◽  
The Relationship

Abstract This commentary focuses upon the relationship between two themes in the target article: the ways in which a Markov blanket may be defined and the role of precision and salience in mediating the interactions between what is internal and external to a system. These each rest upon the different perspectives we might take while “choosing” a Markov blanket.

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