scholarly journals Experimental and Statistical Validation of Data on Mesh-Coupled Annular Distributor Design for Swirling Fluidized Beds

Processes ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 632
Author(s):  
Shazia Shukrullah ◽  
Muhammad Yasin Naz ◽  
Abdul Ghaffar ◽  
Yasin Khan ◽  
Abdulrehman Ali Al-Arainy ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Fluidized Beds ◽  
Small Difference ◽  
Spherical Particles ◽  
Experimental Measurements ◽  
Blade Angle ◽  
Statistical Validation ◽  
Statistical Software ◽  
Velocity Response ◽  
Experimental Side

In this study, velocimetry and statistical analyses were conducted on a swirling fluidized bed. A bed of spherical particles (4 mm) was fluidized by using an annular distributor covered with mesh. The angles of rectangular blades in the distributor were set at 30°, 45°, 60°, 75° and 90°, and the cell size of the mesh cover was 2.5 × 2.5 mm2. The weight was varied from 500 to 1250 g and the effect of each variable on bed velocity response was quantified through velocimetry and statistical analysis. The statistical analysis was conducted using NCSS statistical software. The blade angle, bed weight and superficial velocity for 4 mm particles were statistically optimized at 750 g, 58.26° and 1.45 m/s, respectively. On the experimental side, these parameters have been optimized at 750 g, 60° and 1.41 m/s, respectively. A small difference of 1.74° was noticed in experimental and statistical predictions for the blade angle. The bed weights and superficial velocities were found to be same in both cases. The confidence interval (95%) for bed velocity was proposed in the range of 0.513 to 0.519 m/s. The experimentally optimized bed velocity remained within the proposed range. The well-agreeing results indicate good practical value of distributor design and high precision of the experimental measurements.

scholarly journals A Statistical Analysis on COVID19 Global Vaccination by Best Fit Regression Method

2021 ◽  
Author(s):  
Jaydip Datta
Keyword(s):  
Statistical Analysis ◽  
Pearson Correlation ◽  
Regression Method ◽  
Statistical Software ◽  
Polynomial Fit ◽  
Order Polynomial ◽  
Best Fit ◽  
Specific Country

Abstract In this analysis a best fit regression is executed in between two variables - population of specific country in million vs percentage of first dosage vaccinated till 25.04.21. The analysis is carried out by a standard statistical software with a significant Pearson correlation (r) of 4th order polynomial fit. The basis of first dosage already vaccinated is 1030 million globally.

scholarly journals A statistical analysis for pattern recognition of small cloud particles sampled with a PMS-2DC probe

1997 ◽  
Vol 15 (6) ◽  
pp. 840-846 ◽  
Author(s):  
A. Fouilloux ◽  
J. Iaquinta ◽  
C. Duroure ◽  
F. Albers
Keyword(s):  
Pattern Recognition ◽  
Statistical Analysis ◽  
Three Dimensional ◽  
Synthetic Data ◽  
Spherical Particles ◽  
Data Sets ◽  
Ice Water Content ◽  
Dimensional Shape ◽  
Exact Shape ◽  
Ice Water

Abstract. Although small particles (size between 25 µm and 200 µm) are frequently observed within ice and water clouds, they are not generally used properly for the calculation of structural, optical and microphysical quantities. Actually neither the exact shape nor the phase (ice or water) of these particles is well defined since the existing pattern recognition algorithms are only efficient for larger particle sizes. The present study describes a statistical analysis concerning small hexagonal columns and spherical particles sampled with a PMS-2DC probe, and the corresponding images are classified according to the occurrence probability of various pixels arrangements. This approach was first applied to synthetic data generated with a numerical model, including the effects of diffraction at a short distance, and then validated against actual data sets obtained from in-cloud flights during the pre-ICE'89 campaign. Our method allows us to differentiate small hexagonal columns from spherical particles, thus making possible the characterization of the three dimensional shape (and consequently evaluation of the volume) of the particles, and finally to compute e.g., the liquid or the ice water content.

scholarly journals Rigorous Statistical Methods for Rigorous Microbiome Science

mSystems ◽  
2019 ◽  
Vol 4 (3) ◽  
Author(s):  
Amy D. Willis
Keyword(s):  
Statistical Analysis ◽  
Statistical Methods ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Scientific Understanding ◽  
Biodiversity Data ◽  
Statistical Software ◽  
False Discoveries ◽  
Spurious Signals

ABSTRACT High-throughput sequencing has facilitated discovery in microbiome science, but distinguishing true discoveries from spurious signals can be challenging. The Statistical Diversity Lab develops rigorous statistical methods and statistical software for the analysis of microbiome and biodiversity data. Developing statistical methods that produce valid P values requires thoughtful modeling and careful validation, but careful statistical analysis reduces the risk of false discoveries and increases scientific understanding.

Solid circulation rate and particle collisions in quasi two-dimensional water fluidized beds of spherical particles

2014 ◽  
Vol 253 ◽  
pp. 295-303 ◽  
Author(s):  
Tatjana Kaluđerović Radoičić ◽  
Mihal Đuriš ◽  
Radmila Garić-Grulović ◽  
Zorana Arsenijević ◽  
Željko Grbavčić
Keyword(s):  
Fluidized Beds ◽  
Spherical Particles ◽  
Circulation Rate ◽  
Two Dimensional ◽  
Particle Collisions ◽  
Solid Circulation Rate

scholarly journals Association of Snoring and Cardiovascular Symptoms - A Survey

2020 ◽  
Vol 11 (SPL3) ◽  
pp. 653-658
Author(s):  
Malavika Pradeep ◽  
Sridevi G ◽  
Kavitha S
Keyword(s):  
Statistical Analysis ◽  
Chest Pain ◽  
Health Problems ◽  
Chi Square ◽  
Statistical Software ◽  
Loud Sound ◽  
Respiratory Disorders ◽  
Online Platform ◽  
Chi Square Test ◽  
Sleep Posture

Snoring is a loud sound that can be produced when air across the relaxed tissues of the throat. The causes of snoring include age, being overweight or out of shape, the way you are built, nasal and sinus problems, sleep posture, alcohol, smoking and medications. The present study was performed to find the association between the habit of snoring and health problems like hypertension, breathlessness, fatigue and chest pain among genders. A self-developed questionnaire to assess the snoring habits of the participants with their underlying health problems. The study was conducted on an online platform and the responses were collected. The datas were collected and analysed with the help of statistical software SPSS version 22 and chi-square test was used as a statistical analysis to find how snoring habit affects the participants based on the gender. The results revealed that male respondents who have the habit of snoring are more related to problems like breathlessness, hypertension, fatigue and chest pain compared to females. This result can be justified by the fact that females have strong hormonal support offered by estrogen that protects them from cardiovascular and respiratory disorders.

scholarly journals Provenance metadata for statistical data: An introduction to Structured Data Transformation Language (SDTL)

2020 ◽  
Vol 44 (4) ◽  
Author(s):  
George Alter ◽  
Darrell Donakowski ◽  
Jack Gager ◽  
Pascal Heus ◽  
Carson Hunter ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Statistical Data ◽  
Data Transformation ◽  
Structured Data ◽  
Automated System ◽  
Analysis Software ◽  
Statistical Software ◽  
Transformation Language ◽  
Data Tables ◽  
Statistical Analysis Software

Structured Data Transformation Language (SDTL) provides structured, machine actionable representations of data transformation commands found in statistical analysis software.   The Continuous Capture of Metadata for Statistical Data Project (C2Metadata) created SDTL as part of an automated system that captures provenance metadata from data transformation scripts and adds variable derivations to standard metadata files.  SDTL also has potential for auditing scripts and for translating scripts between languages.  SDTL is expressed in a set of JSON schemas, which are machine actionable and easily serialized to other formats.  Statistical software languages have a number of special features that have been carried into SDTL.  We explain how SDTL handles differences among statistical languages and complex operations, such as merging files and reshaping data tables from “wide” to “long”. 

scholarly journals Buchbesprechungen

2016 ◽  
Vol 26 (1) ◽  
Author(s):  
Johann Pfanzagl ◽  
Andreas Quatember ◽  
Bernhard Böhm ◽  
Ulrike Leopold-Wildburger ◽  
Norbert Kusolitsch ◽  
...  
Keyword(s):  
Time Series ◽  
Statistical Analysis ◽  
Life Insurance ◽  
Statistical Software ◽  
Semiparametric Econometrics

Mathematische Statistik II. (H. Witting, U. Müller-Funk)Schließende Statistik. (W. Polasek)The New Statistical Analysis of Data. (T.W. Anderson, J.D. Finn)Grundbegriffe der Biometrie. (R.J. Lorenz)Vorlesungen über Wahrscheinlichkeitstheorie. (N. Schmitz)Life Insurance Mathematics. (H.G. Gerber )Methodes of Moments and Semiparametric Econometrics for Limited DependentVariable Models. (M. Lee)Introduction to Time Series and Forecasting. (P.J. Brockwell, R.A. Davis)Soft Stat ’95. Advances in Statistical Software 5. (F. Faulbaum, W. Bandilla)Kurzbesprechungen

Comparison of Graduates' and Academics' Perceptions of the Skills Required for Big Data Analysis

2017 ◽  
pp. 126-152
Author(s):  
Busayasachee Puang-Ngern ◽  
Ayse A. Bilgin ◽  
Timothy J. Kyng
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
New Zealand ◽  
Statistical Analysis ◽  
Big Data Analysis ◽  
Skills Gap ◽  
Online Surveys ◽  
Statistical Software ◽  
Software Skills ◽  
R Programming

There is currently a shortage of graduates with the necessary skills for jobs in data analytics and “Big Data”. Recently many new university degrees have been created to address the skills gap, but they are mostly computer science based with little coverage of statistics. In this chapter, the perceptions of graduates and academics about the types of expertise and the types of software skills required for this field are documented based on two online surveys in Australia and New Zealand. The results showed that Statistical Analysis and Statistical Software Skills were the most necessary type of expertise required. Graduates in industry identified SQL as the most necessary software skill while academics teaching in relevant disciplines identified R programming as the most necessary software skill for Big Data analysis. The authors recommend multidisciplinary degrees where the appropriate combination of skills in statistics and computing can be provided for future graduates.

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