scholarly journals Motivation for the development of patents in universities in the state of Pernambuco, Brazil

2020 ◽  
Vol 27 (4) ◽  
Author(s):  
Jabson Herber Profiro de Oliveira ◽  
João Policarpo Rodrigues Lima ◽  
Manoel Raimundo Sena Junior ◽  
Ana Cristina de Almeida Fernandes
Keyword(s):  
Technology Transfer ◽  
Principal Components Analysis ◽  
Principal Components ◽  
The State ◽  
Technology Transfer Office ◽  
Motivating Factors ◽  
Factors Associated ◽  
Components Analysis ◽  
Main Factors ◽  
Do So

Abstract: This paper presents the main factors associated with the motivation of researchers from two universities in the state of Pernambuco, Brazil, to develop patents. To do so, the researchers responded to a Likert-scale survey. Through a principal components analysis, it was verified that the factors that serve as barriers to the development of patents in the universities are associated with limitations in the support given by the TTO (Technology Transfer Office) and the amount of benefits offered to researchers. Likewise, the main motivating factors were associated with improvements in the TTO infrastructure and with the expansion of benefits.

scholarly journals Status of Education System: Interactions of Input and Output Composite Indicators

2017 ◽  
Vol 56 (1) ◽  
pp. 31-40
Author(s):  
Dovilė Stumbrienė ◽  
Audronė Jakaitienė ◽  
Rimantas Želvys
Keyword(s):  
Principal Components Analysis ◽  
Educational System ◽  
Principal Components ◽  
Education System ◽  
The State ◽  
Composite Indicators ◽  
Components Analysis ◽  
The Baltic ◽  
The Impact ◽  
Over Time

Education is one of keystones that guarantees well-being of a country, therefore the understanding about the educationsystem status might be crucial. It motivates to measure the state of the education system, to understand its determinants and tomonitor changes over time that would allow the implementation of evidence-based education policy. Measurement and assessment ofthe state of the education system is a complex task, as the analysis of individual indicators of the educational system is insufficient tomonitor and evaluate education as a multidimensional phenomenon. To achieve a comprehensive and generalized assessment of theeducation system, we have chosen to calculate the composite indicators, namely, indicators of resources and outcomes. Using thelatter indicators we evaluate state of resources and output of the educational system, understand the factors, determining the state, andcompare it over time and in the context of other countries. Indices were calculated for the Baltic countries and three “old” EUmember states: UK representing the Anglo-Saxon liberal model, Germany for the Continental corporatist model and Finland as anexample of the Scandinavian model. For the analysis we used 2002-2014 annual publicly available data from EUROSTAT, OECD,and IEA databases. We have employed a simple weighted additive method with equal weights and principal components analysis forthe construction of indices. We have found that the differences between composite indicators, constructed by the simple weightedadditive method with equal and principal components analysis weights, are limited. The increase in the number of sub-indicators byalmost two-thirds does not affect dynamics of the output indices over time. We have established that inertia of the education systemis different for the countries: the impact of the output on the results is observed with 2–4 year lag for the Baltic States, as there is notime lag or there is a one year lag for Germany and the United Kingdom. Finland's results are different as compared with the othercountries examined. The dynamics of the Baltic indices is similar and possibly constitutes a separate group.

scholarly journals In-Law Preferences in China: What Parents Look for in the Parents of Their Children’s Mates

2017 ◽  
Vol 15 (3) ◽  
pp. 147470491772391 ◽  
Author(s):  
Menelaos Apostolou ◽  
Yan Wang
Keyword(s):  
Principal Components Analysis ◽  
Principal Components ◽  
Chinese Parents ◽  
Components Analysis ◽  
Do So

Across different times and cultures, parents play an important role in influencing their children’s mating decisions. When they do so, they aim to forge useful alliances with other parents which raises the question of what parents look for in the latter. The current research aims to address this question. In particular, we employed an online sample of 925 Chinese parents who were asked to rate the desirability of 88 traits in the parents of prospective mates for their children. Principal components analysis classified these traits in eight factors for the mothers and 10 factors of interest for the fathers of their children’s mates. We also found that parents had a well-defined hierarchy of preferences, fathers, and mothers were in agreement in what they looked for in a prospective in-law, but their preferences were contingent to the sex of the in-law.

Delineation of climatic regions in Maine

1992 ◽  
Vol 22 (6) ◽  
pp. 801-811 ◽  
Author(s):  
R.D. Briggs ◽  
R.C. Lemin Jr.
Keyword(s):  
Cluster Analysis ◽  
Principal Components Analysis ◽  
Principal Components ◽  
Multivariate Analyses ◽  
The State ◽  
Climatic Zones ◽  
Climatic Regions ◽  
Weather Stations ◽  
Components Analysis ◽  
Component Scores

As part of a project to develop a productivity-oriented site classification system for spruce and fir in Maine, multivariate analyses of meteorological data were used to partition the state into homogeneous climatic zones. Data were obtained for 63 weather stations reporting both temperature and precipitation in Maine during the period 1954–1983. Monthly means were computed for each variable over the period of record and summarized by four 3-month seasons. Eighty-two percent of the variation in the 37 variables was accounted for by the first three principal components. Cluster analysis identified eight homogeneous groups of weather stations. Results from the principal components analysis were spatially extrapolated across the state using stepwise regression to define the relationship between the first two principal components and the location variables latitude, longitude, and elevation. Principal component scores were predicted across the state along a grid composed of township line intersections. The Triangulated Irregular Network of ARCINFO, a geographic information system software package, was used to spatially summarize the predicted component scores into climagraphic maps. The combined results from cluster analysis and spatial extrapolation of the principal components analysis suggested the presence of four broad climatic regions, which were further subdivided into nine climatic zones. Overlap among the four regions and nine zones was evaluated with a jackknifed classification of a linear discriminant function. Ninety-four percent of the weather stations were correctly classified by climatic region, whereas 76% were correctly classified by climatic zone. The high degree of correspondence between climatic zones and biophysical regions reinforced results of the multivariate analyses.

scholarly journals Research of the impact of the terrorism and other factors on the consumers behavior

2020 ◽  
Vol 7 ◽  
pp. 139-148
Author(s):  
Kateryna Horiachko
Keyword(s):  
Factor Analysis ◽  
Principal Components Analysis ◽  
Principal Components ◽  
Main Hypothesis ◽  
Military Conflict ◽  
Factors Influencing ◽  
Components Analysis ◽  
Main Factors ◽  
The Impact

The purpose of this study is to identify the main factors influencing consumer’s behavior while travelling to Ukraine. The object of the study was the sample of people who are consumers of touristic services in Ukraine. The main hypothesis of the study was that consumer’s behavior depends on variety of factors in Ukraine, including but not limited to military conflict or terrorism. To improve the knowledge about various factors impact on consumer’s behavior the factor analysis was used, joined by a method of a principal components analysis in SPSS. Using the SPSS the main factors were determined.

Diagnoses Generated by Numerical Taxonomic Methods Applied to Standard Blood Variables

1980 ◽  
Vol 19 (04) ◽  
pp. 205-209
Author(s):  
L. A. Abbott ◽  
J. B. Mitton
Keyword(s):  
Liver Cirrhosis ◽  
Renal Disease ◽  
Principal Components Analysis ◽  
Discriminant Function ◽  
Principal Components ◽  
Discriminant Function Analysis ◽  
Chronic Renal Disease ◽  
Function Analysis ◽  
Infectious Hepatitis ◽  
Components Analysis

Data taken from the blood of 262 patients diagnosed for malabsorption, elective cholecystectomy, acute cholecystitis, infectious hepatitis, liver cirrhosis, or chronic renal disease were analyzed with three numerical taxonomy (NT) methods : cluster analysis, principal components analysis, and discriminant function analysis. Principal components analysis revealed discrete clusters of patients suffering from chronic renal disease, liver cirrhosis, and infectious hepatitis, which could be displayed by NT clustering as well as by plotting, but other disease groups were poorly defined. Sharper resolution of the same disease groups was attained by discriminant function analysis.

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