Prediction of Network Delay with Variable Standard Deviation, Skewness and Kurtosis

2010 ◽  
pp. 587-593
Author(s):  
Renads Safins
Keyword(s):  
Standard Deviation ◽  
Network Delay ◽  
Skewness And Kurtosis

scholarly journals Blood Oxygenation Level Dependent Magnetic Resonance Imaging (MRI), Dynamic Contrast Enhanced MRI and Diffusion Weighted MRI for Benign and Malignant Breast Cancer Discrimination: A Preliminary Experience

Cancers ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 2421
Author(s):  
Roberta Fusco ◽  
Vincenza Granata ◽  
Mauro Mattace Raso ◽  
Paolo Vallone ◽  
Alessandro Pasquale De Rosa ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Univariate Analysis ◽  
Mean Value ◽  
Blood Oxygenation ◽  
Breast Lesions ◽  
Dce Mri ◽  
Malignant Lesions ◽  
The Mean ◽  
And Diffusion ◽  
Skewness And Kurtosis

Purpose. To combine blood oxygenation level dependent magnetic resonance imaging (BOLD-MRI), dynamic contrast enhanced MRI (DCE-MRI), and diffusion weighted MRI (DW-MRI) in differentiation of benign and malignant breast lesions. Methods. Thirty-seven breast lesions (11 benign and 21 malignant lesions) pathologically proven were included in this retrospective preliminary study. Pharmaco-kinetic parameters including Ktrans, kep, ve, and vp were extracted by DCE-MRI; BOLD parameters were estimated by basal signal S0 and the relaxation rate R2*; and diffusion and perfusion parameters were derived by DW-MRI (pseudo-diffusion coefficient (Dp), perfusion fraction (fp), and tissue diffusivity (Dt)). The correlation coefficient, Wilcoxon-Mann-Whitney U-test, and receiver operating characteristic (ROC) analysis were calculated and area under the ROC curve (AUC) was obtained. Moreover, pattern recognition approaches (linear discrimination analysis and decision tree) with balancing technique and leave one out cross validation approach were considered. Results. R2* and D had a significant negative correlation (−0.57). The mean value, standard deviation, Skewness and Kurtosis values of R2* did not show a statistical significance between benign and malignant lesions (p > 0.05) confirmed by the ‘poor’ diagnostic value of ROC analysis. For DW-MRI derived parameters, the univariate analysis, standard deviation of D, Skewness and Kurtosis values of D* had a significant result to discriminate benign and malignant lesions and the best result at the univariate analysis in the discrimination of benign and malignant lesions was obtained by the Skewness of D* with an AUC of 82.9% (p-value = 0.02). Significant results for the mean value of Ktrans, mean value, standard deviation value and Skewness of kep, mean value, Skewness and Kurtosis of ve were obtained and the best AUC among DCE-MRI extracted parameters was reached by the mean value of kep and was equal to 80.0%. The best diagnostic performance in the discrimination of benign and malignant lesions was obtained at the multivariate analysis considering the DCE-MRI parameters alone with an AUC = 0.91 when the balancing technique was considered. Conclusions. Our results suggest that the combined use of DCE-MRI, DW-MRI and/or BOLD-MRI does not provide a dramatic improvement compared to the use of DCE-MRI features alone, in the classification of breast lesions. However, an interesting result was the negative correlation between R2* and D.

scholarly journals Northern Hemisphere Climatology and Trends of Statistical Moments Documented from GHCN-Daily Surface Air Temperature Station Data from 1950 to 2010

2014 ◽  
Vol 27 (14) ◽  
pp. 5396-5410 ◽  
Author(s):  
Nicholas R. Cavanaugh ◽  
Samuel S. P. Shen
Keyword(s):  
Standard Deviation ◽  
Northern Hemisphere ◽  
Spatial Patterns ◽  
Air Temperature ◽  
Probability Distributions ◽  
Temporal Trends ◽  
Surface Air Temperature ◽  
Statistical Moments ◽  
Station Data ◽  
Skewness And Kurtosis

Abstract The first four statistical moments and their trends are calculated for the average daily surface air temperature (SAT) from 1950 to 2010 using the Global Historical Climatology Network–Daily station data for each season relative to the 1961–90 climatology over the Northern Hemisphere. Temporal variation of daily SAT probability distributions are represented as generalized linear regression coefficients on the mean, standard deviation, skewness, and kurtosis calculated for each 10-yr moving time window from 1950–59 to 2001–10. The climatology and trends of these statistical moments suggest that daily SAT probability distributions are non-Gaussian and are changing in time. The climatology of the first four statistical moments has distinct spatial patterns with large coherent structure for mean and standard deviation and relatively smaller and more regionalized patterns for skewness and kurtosis. The linear temporal trends from 1950 to 2010 of the first four moments also have coherent spatial patterns. The linear temporal trends in the characterizing statistical moments are statistically significant at most locations and have differing spatial patterns for different moments. The regionalized variations specific to higher moments may be related to the climate dynamics that contribute to extremes. The nonzero skewness and kurtosis makes this detailed documentation on the higher statistical moments useful for quantifying climate changes and assessing climate model uncertainties.

A study of silo samples for wheat protein in Victoria

1966 ◽  
Vol 6 (21) ◽  
pp. 193 ◽  
Author(s):  
JV Mullaly ◽  
KC Mander ◽  
R Jardine
Keyword(s):  
Standard Deviation ◽  
Soil Fertility ◽  
Indirect Evidence ◽  
Wheat Protein ◽  
Frequency Distributions ◽  
Negatively Associated ◽  
General Improvement ◽  
Coefficient Of Skewness ◽  
Constant Yield ◽  
Skewness And Kurtosis

This study of wheat protein per cent for 92 silos in the Victorian Mallee and Wimmera from 1945-46 to 1964-65 gives indirect evidence of a general improvement in soil fertility in the region due to the introduction of barrel medic pasture into rotations in the late 1940's. Assuming a constant yield over the period, the analysis showed that mean protein per cent would have increased by 0.5 per cent in the first ten years and by 1.4 per cent during the second ten years. The yearly frequency distributions of protein per cent were also characterized by the standard deviation and coefficients of skewness and kurtosis. These characteristics showed no trend with time, but the coefficient of skewness was negatively associated with mean protein per cent.

scholarly journals The Effects of Forensically Relevant Face Coverings on the Acoustic Properties of Fricatives

2017 ◽  
Vol 3 (2) ◽  
pp. 40-52
Author(s):  
Julie Saigusa
Keyword(s):  
Standard Deviation ◽  
Physical Environment ◽  
Acoustic Properties ◽  
Spectral Moments ◽  
Voice Identification ◽  
Centre Of Gravity ◽  
Minimal Pairs ◽  
Motorcycle Helmet ◽  
The Individual ◽  
Skewness And Kurtosis

This forensically motivated study investigates the effects of a motorcycle helmet, balaclava, and plastic mask on the acoustics of three English non-sibilant fricatives, /f/, /θ/, and /v/ in two individuals. It examines variation within the individual as an effect of the physical environment. Two speakers recorded a list of minimal pairs in each of the three guises and with no face covering. The results showed that facewear significantly affected fricative intensity and the four spectral moments: centre of gravity, standard deviation, skewness, and kurtosis. The acoustic changes caused by facewear have implications for judging the reliability of earwitnesses’ content recall and voice identification as well as forensic speech scientists’ examination of content and speaker identity in disputed recordings.

scholarly journals Estratégias de Momento no Mercado Cambial

2018 ◽  
Vol 16 (1) ◽  
pp. 39
Author(s):  
Kesley Leandro Da Silva ◽  
Marcelo Fernandes
Keyword(s):  
Standard Deviation ◽  
Moving Average ◽  
Emerging Market ◽  
Evaluation Criteria ◽  
Linear Momentum ◽  
Crash Risk ◽  
Momentum Strategies ◽  
Management Procedure ◽  
Nonlinear Trends ◽  
Skewness And Kurtosis

We use weekly data to investigate the profitability of momentum strategies in the currency market based on two different extract methods of nonlinear trends. We compare their performance with the traditional moving average rules broadly used by market professionals. We find that the performance of all strategies is extremely sensitive to the choice of currency, lags parameters and the evaluation criteria. Nevertheless, nonlinear trends entail better results for G10 currencies, whereas we find mixed results for emerging market currencies. We also examine a volatility management procedure to alleviate crash risk. It indeed lowers maximum weekly losses, standard deviation, skewness and kurtosis for most currencies in both strategies. Finally, nonlinear momentum strategies with volatility management improve both raw and risk-adjusted performance of about two thirds of the linear momentum strategies.

Automated Detection of Underwater Military Munitions Using Fusion of 2D and 2.5D Features From Optical Imagery

2014 ◽  
Vol 48 (4) ◽  
pp. 61-71 ◽  
Author(s):  
A.S.M. Shihavuddin ◽  
Nuno Gracias ◽  
Rafael Garcia ◽  
Ricard Campos ◽  
Arthur C.R. Gleason ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Classification Accuracy ◽  
Plane Surface ◽  
Automated Detection ◽  
Principal Plane ◽  
Structure Information ◽  
Texture Information ◽  
Optical Imagery ◽  
Polynomial Surface ◽  
Skewness And Kurtosis

Abstract Technologies that can efficiently and objectively detect, identify, and map underwater military munitions are needed. The knowledge of benthic environments adjacent to underwater military munitions is crucial for remediation decisions. When attempting to identify munitions from optical imagery, tridimensional structure information obtained from the surveyed area can complement the texture information that is available in the images. In this work, we use a fusion of two-dimensional (2D) and two-and-a-half-dimensional (2.5D) features to classify munitions on the seabed from a sequence of images of an optical survey of the seabed. The 2D features respond to texture, whereas the 2.5D features respond to geometry. The 2.5D features used were coefficients of polynomial surface fitting, standard deviation, skewness, and kurtosis of the elevation, slope of principal plane, mean and standard deviation of the distance of 2.5D points to the principal plane, surface normal, curvatures, rugosity and symmetry measures. Adding the 2.5D features increased classification accuracy relative to using only 2D features when detecting discarded military munitions.

scholarly journals Influence of Different Sieving Methods on Estimation of Sand Size Parameters

Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 879 ◽  
Author(s):  
Poullet ◽  
Muñoz-Perez ◽  
Poortvliet ◽  
Mera ◽  
Contreras ◽  
...  
Keyword(s):  
Standard Deviation ◽  
The Other ◽  
Coastal Dynamics ◽  
Other Hand ◽  
Mechanical Shaker ◽  
Operational Methods ◽  
Skewness And Kurtosis ◽  
Sand Size

Sieving is one of the most used operational methods to determine sand size parameters which are essential to analyze coastal dynamics. However, the influence of hand versus mechanical shaking methods has not yet been studied. Herein, samples were taken from inside the hopper of a trailing suction dredger and sieved by hand with sieves of 10 and 20 cm diameters on board the dredger. Afterwards, these same samples were sieved with a mechanical shaker in the laboratory on land. The results showed differences for the main size parameters D50, standard deviation, skewness, and kurtosis. Amongst the main results, it should be noted that the highest values for D50 and kurtosis were given by the small sieves method. On the other hand, the lowest values were given by the mechanical shaker method in the laboratory. Furthermore, standard deviation and skewness did not seem to be affected by the sieving method which means that all the grainsize distribution was shifted but the shape remained unchanged. The few samples that do not follow these patterns have a higher percentage of shells. Finally and definitely, the small sieves should be rejected as a sieving method aboard.

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