results the results show that the individual and demographic factor (idf), organizational factor (of), h & s training factor (tf), workplace-human factor (whf), factor related to type of accident occurrence (taf), h & s risk management system factor (rmsf), and accident time factor (atf) were considered to be effective and significant independent latent factors in occupational injuries. conclus...

Abstract We derive the math (objective and gradients) for three closely-related Gaussian-based data models. All three are based on Factor Analysis (FA). The first is a simplification of FA; the second is FA itself; the third is our extension of FA to use a smooth trace norm prior on the factor loading matrix (in place of the hard rank constraint used by FA). See [3] for some background on Facto...

quantitative relationships between molecular structure and azolo-adamantanes derivatives were discovered by different chemometric tools including factor analysis based multiple linear regressions (fa-mlr), principle component regression analysis (pcra), and genetic algorithm-partial least squares ga-pls. the fa-mlr describes the effect of geometrical and quantum indices on enzyme inhibition act...

A model is not an exact copy of its original, but only idealised reproduction that simpler, more understandable, accessible and easier, safer effective to work with. In the presented study, we used technique factor analysis (FA). We 44 parameters describe agroecosystem, which proportionally main components study agroecosystem. Based on Malinowsky error analysis, extracted a 6-factor solution. f...

Factor analysis (FA) is a statistical technique to explain the correlation structure among observed variables. It can e.g. be useful in the analysis of Patient Reported Outcomes, which typically use multiple questions to measure a single concept. Maximum likelihood factor analysis (ML-FA) relies on large sample theory, and it is consequently often recommended to use it only in large samples (e....

Factor analysis (FA) is a statistical technique similar to principal component analysis (PCA) for explaining the variance in a data set in terms of underlying linear factors. Unlike PCA, however, FA has not been widely exploited for face or object recognition. This paper explains the differences between PCA and FA, and confirms that PCA outperforms FA in a standard face recognition task. Howeve...

The purpose of this research is, selecting managements in research institute of petroleum industry (RIPI) according with main factors. These main factors are determined by reviewing the literature, and filling the questionnaires. The factor analysis (FA) method is applied to analysis information. According to the result of FA, main factors are classified in three categories: knowledge, skills, ...

Abstract Load flow analysis is one of the essential ways used by electrical power engineers to achieve high system quality owing relevance load in economic optimization, planning, and stability. This issue can be formulated as a set nonlinear algebraic equations, which solved iterative algorithms. Gauss-Seidel simple determining system, with acceleration factor being most considerable modificat...