scholarly journals Random Intersection Graphs and Missing Data

2020 ◽  
Vol 34 (04) ◽  
pp. 5579-5585
Author(s):  
Dror Salti ◽  
Yakir Berchenko
Keyword(s):  
Missing Data ◽  
Statistical Inference ◽  
Data Matrix ◽  
Intersection Graphs ◽  
Threshold Phenomena ◽  
Graph Properties ◽  
Random Intersection Graph ◽  
Theoretical Predictions ◽  
Random Graph Theory ◽  
The Relationship

Random-graphs and statistical inference with missing data are two separate topics that have been widely explored each in its field. In this paper we demonstrate the relationship between these two different topics and take a novel view of the data matrix as a random intersection graph. We use graph properties and theoretical results from random-graph theory, such as connectivity and the emergence of the giant component, to identify two threshold phenomena in statistical inference with missing data: loss of identifiability and slower convergence of algorithms that are pertinent to statistical inference such as expectation-maximization (EM). We provide two examples corresponding to these threshold phenomena and illustrate the theoretical predictions with simulations that are consistent with our reduction.

Learning Language Levels in Students Accurate with a History Academic Achievement History

2017 ◽  
Vol 1 (2) ◽  
pp. 137
Author(s):  
Noorlela Binti Noordin ◽  
Abdul Razaq Ahmad ◽  
Anuar Ahmad
Keyword(s):  
Academic Achievement ◽  
Statistical Inference ◽  
Quantitative Data ◽  
Quantitative Methods ◽  
Descriptive Statistics ◽  
Language Test ◽  
The Subject ◽  
The Difference ◽  
Learning Language ◽  
The Relationship

This study was aimed to evaluate the Malay proficiency among students in Form Two especially non-Malay students and its relationship to academic achievement History. To achieve the purpose of the study there are two objectives, the first is to look at the difference between mean of Malay Language test influences min of academic achievement of History subject among non-Malay students in Form Two and the second is the relationship between the level of Malay proficiency and their academic achievement for History. This study used quantitative methods, which involved 100 people of Form Two non-Malay students in one of the schools in Klang, Selangor. This study used quantitative data were analyzed using descriptive statistics and statistical inference with IBM SPSS Statistics v22 software. This study found that there was a relationship between the proficiency of Malay language among non-Malay students with achievements in the subject of History. The implications of this study are discussed in this article.

ExperimentSubset: an R package to manage subsets of Bioconductor Experiment objects

2021 ◽  
Author(s):  
Irzam Sarfraz ◽  
Muhammad Asif ◽  
Joshua D Campbell
Keyword(s):  
Single Cell ◽  
R Package ◽  
Poor Quality ◽  
Data Matrix ◽  
Supplementary Information ◽  
Data Provenance ◽  
Rna Seq ◽  
Efficient Management ◽  
The Matrix ◽  
The Relationship

Abstract Motivation R Experiment objects such as the SummarizedExperiment or SingleCellExperiment are data containers for storing one or more matrix-like assays along with associated row and column data. These objects have been used to facilitate the storage and analysis of high-throughput genomic data generated from technologies such as single-cell RNA sequencing. One common computational task in many genomics analysis workflows is to perform subsetting of the data matrix before applying down-stream analytical methods. For example, one may need to subset the columns of the assay matrix to exclude poor-quality samples or subset the rows of the matrix to select the most variable features. Traditionally, a second object is created that contains the desired subset of assay from the original object. However, this approach is inefficient as it requires the creation of an additional object containing a copy of the original assay and leads to challenges with data provenance. Results To overcome these challenges, we developed an R package called ExperimentSubset, which is a data container that implements classes for efficient storage and streamlined retrieval of assays that have been subsetted by rows and/or columns. These classes are able to inherently provide data provenance by maintaining the relationship between the subsetted and parent assays. We demonstrate the utility of this package on a single-cell RNA-seq dataset by storing and retrieving subsets at different stages of the analysis while maintaining a lower memory footprint. Overall, the ExperimentSubset is a flexible container for the efficient management of subsets. Availability and implementation ExperimentSubset package is available at Bioconductor: https://bioconductor.org/packages/ExperimentSubset/ and Github: https://github.com/campbio/ExperimentSubset. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Micromechanism of the Breakage of Two Spherical Gypsum Particles under Normal–Tangential Contact Conditions

2021 ◽  
Vol 11 (9) ◽  
pp. 4039
Author(s):  
Yiran Niu ◽  
Lin Li ◽  
Yanwei Zhang ◽  
Shicai Yu ◽  
Jian Zhou
Keyword(s):  
Tangential Force ◽  
Coarse Grained ◽  
Spherical Particles ◽  
Contact Conditions ◽  
Normal Contact ◽  
Tangential Contact ◽  
Theoretical Predictions ◽  
Tangential Forces ◽  
Predicted Values ◽  
The Relationship

Contact breakage of particles makes a large difference in the strength of coarse-grained soils, and exploring the characteristics within the process of the breakage is of great significance. Ignoring the influence of particle shape, the micromechanism of two spherical particles breaking under normal–tangential contact conditions was investigated theoretically and experimentally. Through theoretical analysis, the breakage form, the shape and size of the conical core, and the relationship between the normal and tangential forces at crushing were predicted. Particle contact tests of two gypsum spheres were carried out, in which the breakage forms, features of the conical cores and the normal and tangential forces at crushing were recorded for comparison with the predicted values. The test results and the theoretical predictions showed good agreement. Both the analysis and test demonstrate that the presence of tangential forces causes the conical core to assume the shape of an oblique cone, and the breakage form to change. Moreover, with increasing normal contact force, the tangential force needed for crushing increases gradually first and then decreases suddenly.

scholarly journals Kernel weighted least square approach for imputing missing values of metabolomics data

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Nishith Kumar ◽  
Md. Aminul Hoque ◽  
Masahiro Sugimoto
Keyword(s):  
Missing Data ◽  
Large Scale ◽  
Missing Values ◽  
Kernel Weight ◽  
Least Square ◽  
Data Matrix ◽  
Data Imputation ◽  
Metabolomics Data ◽  
Missing Value ◽  
Missing Data Imputation

AbstractMass spectrometry is a modern and sophisticated high-throughput analytical technique that enables large-scale metabolomic analyses. It yields a high-dimensional large-scale matrix (samples × metabolites) of quantified data that often contain missing cells in the data matrix as well as outliers that originate for several reasons, including technical and biological sources. Although several missing data imputation techniques are described in the literature, all conventional existing techniques only solve the missing value problems. They do not relieve the problems of outliers. Therefore, outliers in the dataset decrease the accuracy of the imputation. We developed a new kernel weight function-based proposed missing data imputation technique that resolves the problems of missing values and outliers. We evaluated the performance of the proposed method and other conventional and recently developed missing imputation techniques using both artificially generated data and experimentally measured data analysis in both the absence and presence of different rates of outliers. Performances based on both artificial data and real metabolomics data indicate the superiority of our proposed kernel weight-based missing data imputation technique to the existing alternatives. For user convenience, an R package of the proposed kernel weight-based missing value imputation technique was developed, which is available at https://github.com/NishithPaul/tWLSA.

scholarly journals On the Isolated Vertices and Connectivity in Random Intersection Graphs

2011 ◽  
Vol 2011 ◽  
pp. 1-9 ◽  
Author(s):  
Yilun Shang
Keyword(s):  
Random Graphs ◽  
Intersection Graph ◽  
Intersection Graphs ◽  
Random Intersection Graph ◽  
Probability Of Connectivity ◽  
Asymptotic Probability

We study isolated vertices and connectivity in the random intersection graph . A Poisson convergence for the number of isolated vertices is determined at the threshold for absence of isolated vertices, which is equivalent to the threshold for connectivity. When and , we give the asymptotic probability of connectivity at the threshold for connectivity. Analogous results are well known in Erdős-Rényi random graphs.

scholarly journals Variation in rms charge radii of deuteron and helium nuclei with s\sqrt s

Nukleonika ◽  
2020 ◽  
Vol 65 (4) ◽  
pp. 211-215
Author(s):  
Sarwat Zahra ◽  
Bushra Shafaq ◽  
Bushra Kanwal ◽  
Nosheen Akbar
Keyword(s):  
Center Of Mass ◽  
Form Factors ◽  
Mass Energy ◽  
Charge Radii ◽  
Center Of Mass Energy ◽  
Theoretical Predictions ◽  
Dependent Form ◽  
Energy Dependent ◽  
The Relationship ◽  
Good Agreement

AbstractBy considering energy-dependent form factors extracted from generalized Chou–Yang model, root mean square (rms) charge radii of deuteron and helium nuclei (alpha) are predicted at different values of center of mass energy which are in good agreement with theoretical predictions and experimental results. The rms radius is inversely proportional to mass of nuclei. Besides, the relationship between radii and energy are also derived.

scholarly journals Component Evolution in Random Intersection Graphs

10.37236/935 ◽  
2007 ◽  
Vol 14 (1) ◽  
Author(s):  
Michael Behrisch
Keyword(s):  
Real World ◽  
Linear Order ◽  
Graph Model ◽  
Vertex Degree ◽  
Intersection Graph ◽  
Giant Component ◽  
Logarithmic Order ◽  
Intersection Graphs ◽  
Similarity Network ◽  
Random Intersection Graph

We study the evolution of the order of the largest component in the random intersection graph model which reflects some clustering properties of real–world networks. We show that for appropriate choice of the parameters random intersection graphs differ from $G_{n,p}$ in that neither the so-called giant component, appearing when the expected vertex degree gets larger than one, has linear order nor is the second largest of logarithmic order. We also describe a test of our result on a protein similarity network.

Bubble Dynamics and Cavitation Inception in Cavitation Susceptibility Meters

1986 ◽  
Vol 108 (4) ◽  
pp. 444-452 ◽  
Author(s):  
G. L. Chahine ◽  
Y. T. Shen
Keyword(s):  
Bubble Dynamics ◽  
Scaling Effects ◽  
Mean Flow ◽  
Cavitation Inception ◽  
Theoretical Predictions ◽  
Order Of Magnitude ◽  
Tentative Explanation ◽  
Bursting Events ◽  
Acoustic Device ◽  
The Relationship

To improve the understanding of the scaling effects of nuclei on cavitation inception, bubble dynamics, multibubble interaction effects, and bubble-mean flow interaction in a venturi Cavitation Susceptibility Meter are considered theoretically. The results are compared with classical bubble static equilibrium predictions. In a parallel effort, cavitation susceptibility measurements of ocean and laboratory water were carried out using a venturi device. The measured cavitation inception indices were found to relate to the measured microbubble concentration. The relationship between the measured cavitation inception and bubble concentration and distribution can be explained by using the theoretical predictions. A tentative explanation is given for the observation that the number of cavitation bursting events measured by an acoustic device is sometimes an order of magnitude lower than the number of microbubbles measured by the light scattering detector. The questions addressed here add to the fundamental knowledge needed if the cavitation susceptibility meter is to be used effectively for the measurement of microbubble size distributions.

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