scholarly journals The permutation distribution of matrix correlation statistics

2005 ◽  
pp. 223-245 ◽  
Author(s):  
A. D. Barbour ◽  
Louis H. Y. Chen
Keyword(s):  
Permutation Distribution ◽  
Matrix Correlation ◽  
Correlation Statistics

scholarly journals Planning skills by heads of science departmentand academic performance in science subjects in public secondary schools in Nandi county, Kenya

2020 ◽  
Vol 19 (1) ◽  
Author(s):  
Alfed Cheruiyot ◽  
Viviline Ngeno ◽  
Joash K. Kibett
Keyword(s):  
Academic Performance ◽  
Secondary Schools ◽  
Sample Size ◽  
Science Teachers ◽  
Instructional Planning ◽  
Mixed Method Research ◽  
Quality Performance ◽  
Training Needs Assessment ◽  
Academic Activities ◽  
Correlation Statistics

Curriculum and instructional planning is important to ensure that academic activities run without interruption in an academic year or term. Heads of departments (HODs of Science) play a pivotal role in implementation of curriculum in secondary schools. Planning is one of the functions vested on HODs to ensure proper implementation of curriculum in their departments. This paper therefore looks at HODs planning skills towards academic performance improvement in three science subjects in public secondary schools in Nandi County, Kenya. The decision to choose HODs of science was due to the importance that is placed on science subject but which has recorded below average performance compared to other subjects in Kenya Certificate of Secondary School. The three science subjects under investigation are; Physics, Biology and Chemistry for secondary schools. The study used mixed method research design. The study had three target populations that comprised of 231 heads of departments, 231 principals and 693 teachers. The sample size of the study was determined using Krejcie and Morgan formulae of determining sample size and comprised of 23 principals, 128 HODS of science and 247 teachers who were selected through stratified random sampling. Data collection was through questionnaires and interview schedule. Analysis of data was performed through quantitative and qualitative methods. The correlation analysis was computed from HODs and science teachers’ data. The study discovered that most of them only planned for science practicals to be conducted on occasional basis by teachers in the department. Moreover, the HODs of Science ensured that the planned activities were conducted as planned. However, the HODs of Science were found not to have proper planning skills on ICT usage, acquisition of instructional material and conducting training needs assessment for teachers. The computed correlation statistics showed that there existed significant influence (p<0.05) between planning skills by HODs of Science and academic performance of students in sciences in public secondary schools in Nandi County. The study recommends that HODs of Science need to be informed by Quality Assurance and Standards Officers (QASOs) that they need to be proactive and not reactive to the responsibilities under their docket. Participatory planning practices needs also to be embraced by HODs of Science for improved implementation and execution of set objectives and targets. Keywords: Planning, Skills, Quality, Performance, Sciences HODs

Methods for Studying Morphological Integration and Modularity

2010 ◽  
Vol 16 ◽  
pp. 213-243 ◽  
Author(s):  
Anjali Goswami ◽  
P. David Polly
Keyword(s):  
Distance Matrix ◽  
Japanese Macaques ◽  
Morphological Integration ◽  
Matrix Analysis ◽  
Euclidean Distance Matrix ◽  
Phenotypic Data ◽  
Graphical Modelling ◽  
Landmark Data ◽  
Competing Models ◽  
Matrix Correlation

Morphological integration and modularity are closely related concepts about how different traits of an organism are correlated. Integration is the overall pattern of intercorrelation; modularity is the partitioning of integration into evolutionarily or developmentally independent blocks of traits. Modularity and integration are usually studied using quantitative phenotypic data, which can be obtained either from extant or fossil organisms. Many methods are now available to study integration and modularity, all of which involve the analysis of patterns found in trait correlation or covariance matrices. We review matrix correlation, random skewers, fluctuating asymmetry, cluster analysis, Euclidean distance matrix analysis (EDMA), graphical modelling, two-block partial least squares, RV coefficients, and theoretical matrix modelling and discuss their similarities and differences. We also review different coefficients that are used to measure correlations. We apply all the methods to cranial landmark data from and ontogenetic series of Japanese macaques,Macaca fuscatato illustrate the methods and their individual strengths and weaknesses. We conclude that the exploratory approaches (cluster analyses of various sorts) were less informative and less consistent with one another than were the results of model testing or comparative approaches. Nevertheless, we found that competing models of modularity and integration are often similar enough that they are not statistically distinguishable; we expect, therefore, that several models will often be significantly correlated with observed data.

Criteria for optimal operation of automobiles on alternative fuels

2021 ◽  
Vol 13 (1) ◽  
pp. 124-132
Author(s):  
Volodymyr Rudzinskyi ◽  
◽  
Bohdan Yemets ◽  
Serhii Melnychuk ◽  
Oleksandr Ryabchuk ◽  
...  
Keyword(s):  
Economic Efficiency ◽  
Alternative Fuels ◽  
Local Level ◽  
Optimal Operation ◽  
Expert Assessment ◽  
Depth Analysis ◽  
Analysis And Synthesis ◽  
The Matrix ◽  
Matrix Correlation ◽  
High Degree

The article deals with some criteria that substantiate the design and operational performance of automobiles running on alternative fuels; economic efficiency of operation of such vehicles, their ecological conformity; the level of complexity of the design of converted automobiles; labor intensity of their maintenance, repair, etc. ; traction-speed and other different, in comparison with the basic, properties of automobiles while working on alternative fuel (AF); energy consumption and (or) cost price of AF; efficiency of power plant and (or) car on AF; the degree of commissioning (mass production) and further prospects for the development of the design of such automobiles; state of support developed structures at the national (local) level. An expert assessment of the adopted criteria in the order of their importance is made. Along with the analysis of scores, which are presented in points, it is used the ranking method to study the results of the survey of experts. This allows applying the values of the established optimal criteria to justify the operation of vehicles during their work on the AF. The analysis of the matrix correlation shows that the numerical estimates set by the accepted criteria are characterized by a high degree of correlation, and experts are generally unanimous in assessing their importance. The most important criteria for the operation of automobiles on the AF are economic efficiency, traction and speed and other, different compared to the basic, the properties of automobiles while working on the AF. Other criteria are also quite important, the weights for them are much higher than 7%, and they also should be taken into account while conducting an in-depth analysis and synthesis of indicators of optimal operation of automobiles on the AF. In addition, it is important that the group of criteria that characterize only one type of automobile when working on the AF (for example, the degree of commissioning) experts gave only about 17% of the importance.

Abstract 16877: Correlation of Antibody Binding Strength to Complement Fixation

Circulation ◽  
2014 ◽  
Vol 130 (suppl_2) ◽  
Author(s):  
Vishal Y Parikh ◽  
Nancy Reinsmoen ◽  
Jignesh Patel ◽  
Zhe Yu ◽  
Frank Liou ◽  
...  
Keyword(s):  
Fluorescence Intensity ◽  
Heart Transplant ◽  
Binding Assay ◽  
Complement Fixation ◽  
Antibody Binding ◽  
Binding Ability ◽  
Binding Strength ◽  
Desensitization Therapy ◽  
Positive Rate ◽  
Correlation Statistics

Background: In patients (pts) who are highly sensitized, desensitization therapy is commonly applied to reduce antibody (Abs) load and to reduce potential morbidity and mortality following heart transplant (HTx). It is not known as to what level of antibody binding is needed to initiate desensitization therapy. It is believed that high binding Abs may have the ability to fix complement and lead to cytotoxicity. Methods: Between 2011 and 2012 we assessed 13 highly sensitized pts who were noted to have standardized fluorescence intensity (SFI) >100,000 pretransplant. A complement binding assay (C1q binding assay) was then applied to these Abs to assess for a correlation of binding to cytotoxicity. Correlation statistics were used to derive significance between higher antibody binding and capacity to bind complement. Results: There seems to be no correlation between the different binding strength and C1q positivity. However, when evaluating Luminex 1:8 test, there seems to be correlation between class I binding strength with C1q positivity. There was C1q positive rate of 10.8% in SFI 200,000 range. Conclusions: Undiluted antibodies do not correlate to C1q binding ability. However the 1:8 dilution test seems to provide an better prediction of complement binding. 1:8 dilutions should be performed to accurately assess the ability for antibodies to bind complement.

scholarly journals Data-Driven Localization Mappings in Filtering the Monsoon–Hadley Multicloud Convective Flows

2018 ◽  
Vol 146 (4) ◽  
pp. 1197-1218
Author(s):  
Michèle De La Chevrotière ◽  
John Harlim
Keyword(s):  
Learning Algorithm ◽  
Data Driven ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Model Errors ◽  
Accurate Analysis ◽  
Perfect Model ◽  
Nonlinear Stochastic Model ◽  
Correlation Statistics ◽  
The Impact

This paper demonstrates the efficacy of data-driven localization mappings for assimilating satellite-like observations in a dynamical system of intermediate complexity. In particular, a sparse network of synthetic brightness temperature measurements is simulated using an idealized radiative transfer model and assimilated to the monsoon–Hadley multicloud model, a nonlinear stochastic model containing several thousands of model coordinates. A serial ensemble Kalman filter is implemented in which the empirical correlation statistics are improved using localization maps obtained from a supervised learning algorithm. The impact of the localization mappings is assessed in perfect-model observing system simulation experiments (OSSEs) as well as in the presence of model errors resulting from the misspecification of key convective closure parameters. In perfect-model OSSEs, the localization mappings that use adjacent correlations to improve the correlation estimated from small ensemble sizes produce robust accurate analysis estimates. In the presence of model error, the filter skills of the localization maps trained on perfect- and imperfect-model data are comparable.

scholarly journals Compositional Restricted Boltzmann Machines Unveil the Brain-Wide Organization of Neural Assemblies

2021 ◽  
Author(s):  
Thijs L van der Plas ◽  
Jérôme Tubiana ◽  
Guillaume Le Goc ◽  
Geoffrey Migault ◽  
Michael Kunst ◽  
...  
Keyword(s):  
Structural Connectivity ◽  
Connectivity Matrix ◽  
Restricted Boltzmann Machines ◽  
Pairwise Correlation ◽  
Neural Assemblies ◽  
Data Statistics ◽  
Endogenous Activity ◽  
Brain Data ◽  
Correlation Statistics ◽  
The Brain

Patterns of endogenous activity in the brain reflect a stochastic exploration of the neuronal state space that is constrained by the underlying assembly organization of neurons. Yet it remains to be shown that this interplay between neurons and their assembly dynamics indeed suffices to generate whole-brain data statistics. Here we recorded the activity from ~40,000 neurons simultaneously in zebrafish larvae, and show that a data-driven network model of neuron-assembly interactions can accurately reproduce the mean activity and pairwise correlation statistics of their spontaneous activity. This model, the compositional Restricted Boltzmann Machine, unveils ~200 neural assemblies, which compose neurophysiological circuits and whose various combinations form successive brain states. From this, we mathematically derived an interregional functional connectivity matrix, which is conserved across individual animals and correlates well with structural connectivity. This novel, assembly-based generative model of brain-wide neural dynamics enables physiology-bound perturbation experiments in silico.

scholarly journals CORDSAutomatic Generation of Correlation Statistics in DB2

2004 ◽  
pp. 1341-1344 ◽  
Author(s):  
I ILYAS ◽  
V MARKL ◽  
P HAAS ◽  
P BROWN ◽  
A ABOULNAGA
Keyword(s):  
Correlation Statistics

scholarly journals Characteristics of Correlation Statistics between Droplet Radius and Optical Thickness of Warm Clouds Simulated by a Three-Dimensional Regional-Scale Spectral Bin Microphysics Cloud Model

2012 ◽  
Vol 69 (2) ◽  
pp. 484-503 ◽  
Author(s):  
Yousuke Sato ◽  
Kentaroh Suzuki ◽  
Takamichi Iguchi ◽  
In-Jin Choi ◽  
Hiroyuki Kadowaki ◽  
...  
Keyword(s):  
Optical Thickness ◽  
Cloud Model ◽  
Regional Scale ◽  
Atmospheric Stability ◽  
Three Dimensional ◽  
Droplet Radius ◽  
Cloud Particle ◽  
Sbm Model ◽  
Bin Microphysics ◽  
Correlation Statistics

Abstract Three-dimensional downscaling simulations using a spectral bin microphysics (SBM) model were conducted to investigate the effects of aerosol amount and dynamical stabilities of the atmosphere on the correlation statistics between cloud droplet effective radius (RE) and cloud optical thickness (COT) of warm clouds off the coast of California. The regeneration process of aerosols was implemented into the SBM and was found to be necessary for simulating the satellite-observed microphysical properties of warm clouds by the SBM model used in this study. The results showed that the aerosol amount changed the correlation statistics in a way that changes the cloud particle number concentration, whereas the inversion height of the boundary layer, which is related to the atmospheric stability and the cloud-top height, changed the correlation statistics in a way that changes the liquid water path. These results showed that the dominant mechanisms that control the correlation statistics are similar to those suggested by previous modeling studies based on two-dimensional idealized simulations. On the other hand, the present three-dimensional modeling was also able to simulate some realistic patterns of the correlation statistics, namely, mixtures of characteristic patterns and the “high-heeled” pattern as observed by satellite remote sensing.

scholarly journals Extrinsic and Intrinsic Factors Influencing Employee Motivation: Lessons from AMREF Health Africa in Kenya

2016 ◽  
Vol 6 (9) ◽  
pp. 20 ◽  
Author(s):  
Stephen Morangi Nyambegera ◽  
Caroline Njambi Gicheru
Keyword(s):  
Management Practices ◽  
Work Organization ◽  
Sampling Technique ◽  
Employee Motivation ◽  
Extrinsic Factors ◽  
Intrinsic Factors ◽  
Salary Structure ◽  
Data Collection Instrument ◽  
Correlation Statistics ◽  
Extrinsic And Intrinsic Factors

<p>The purpose of the study was to determine the factors that influence employee motivation in Kenyan Organizations. The study was guided by the following research questions: (i) what are the extrinsic factors that influence employee motivation in AMREF Health Africa in Kenya? (ii) what intrinsic factors influence employee motivation in AMREF Health Africa in Kenya? A descriptive research design was adopted. Stratified random sampling technique was used to draw a sample size of 96 respondents. The data collection instrument was a structured questionnaire developed by the researchers.  A set of descriptive and correlation statistics were adopted for analysis. The study identified several intrinsic factors that influence employee motivation. These included employee achievements, recognition, work itself, responsibility and advancement, salary structure, the level to which the employees feel appreciated, and the employee perception of their jobs among other factors. The study further, established that the intrinsic factors that influence employee motivation include empowerment and autonomy, employees’ view of their work, organization trust, skill variety requirements among others. The study recommends that the organization should acknowledge and make use of a proper mix of extrinsic and intrinsic factors in their human resource management practices to ensure that employees are well motivated to perform their tasks.</p>

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