Principal components of innovation performance in European Union countries

2021 ◽  
Vol 66 (8) ◽  
pp. 24-45
Author(s):  
Agnieszka Kleszcz
Keyword(s):  
European Union ◽  
Principal Components ◽  
Alternative Assessment ◽  
Dimensional Space ◽  
Principal Component ◽  
Innovation Performance ◽  
Data Set ◽  
Eu Member States ◽  
Wide Range ◽  
European Union Countries

Innovation is one of the main determinants of economic development. Innovative activity is very complex, thus difficult to measure. The complexity of the phenomenon poses a great challenge for researchers to understand its determinants. The article focuses on the problem of innovation-related geographical disparities among European Union countries. Moreover, it analyses the principal components of innovation determined on the basis of the European Innovation Scoreboard (EIS) dimensions. The aim of the paper is to identify the principal components of the innovation index which differentiate countries by analysing the structure of the correlation between its components. All calculations were based on indicators included in the EIS 2020 Database, containing data from the years 2012–2019. A comparative analysis of the studied countries’ innovation performance was carried out, based on the principal component analysis (PCA) method, with the purpose of finding the uncorrelated principal components of innovation which differentiate the studied countries. The results were achieved by reducing a 10-dimensional data set to a 2-dimensional one, for a simpler interpretation. The first principal component (PC1) consisted of the human resources, attractive research systems, and finance and support dimensions (understood as academia and finance). The second principal component (PC2), involving the employment impacts and linkages dimensions, was interpreted as business-related. PC1 and PC2 jointly explained 68% of the observed variance, and similar results were obtained for the 27 detailed indicators outlined in the EIS. We can therefore assume that we have an accurate representation of the information contained in the EIS data, which allows for an alternative assessment and ranking of innovation performance. The proposed simplified index, described in a 2-dimensional space, based on PC1 and PC2, makes it possible to group countries in a new way, according to their level of innovation, which offers a wide range of application, e.g. PC1 captures geographic disparities in innovation corresponding to the division between the old and new EU member states.

scholarly journals Separating damage from environmental effects affecting civil structures for near real-time damage detection

2017 ◽  
Vol 17 (4) ◽  
pp. 850-868 ◽  
Author(s):  
William Soo Lon Wah ◽  
Yung-Tsang Chen ◽  
Gethin Wyn Roberts ◽  
Ahmed Elamin
Keyword(s):  
Damage Detection ◽  
Real Time ◽  
Environmental Effects ◽  
Environmental Conditions ◽  
Principal Component ◽  
Detection Methods ◽  
Real Time Monitoring ◽  
Civil Structures ◽  
Data Set ◽  
Wide Range

Analyzing changes in vibration properties (e.g. natural frequencies) of structures as a result of damage has been heavily used by researchers for damage detection of civil structures. These changes, however, are not only caused by damage of the structural components, but they are also affected by the varying environmental conditions the structures are faced with, such as the temperature change, which limits the use of most damage detection methods presented in the literature that did not account for these effects. In this article, a damage detection method capable of distinguishing between the effects of damage and of the changing environmental conditions affecting damage sensitivity features is proposed. This method eliminates the need to form the baseline of the undamaged structure using damage sensitivity features obtained from a wide range of environmental conditions, as conventionally has been done, and utilizes features from two extreme and opposite environmental conditions as baselines. To allow near real-time monitoring, subsequent measurements are added one at a time to the baseline to create new data sets. Principal component analysis is then introduced for processing each data set so that patterns can be extracted and damage can be distinguished from environmental effects. The proposed method is tested using a two-dimensional truss structure and validated using measurements from the Z24 Bridge which was monitored for nearly a year, with damage scenarios applied to it near the end of the monitoring period. The results demonstrate the robustness of the proposed method for damage detection under changing environmental conditions. The method also works despite the nonlinear effects produced by environmental conditions on damage sensitivity features. Moreover, since each measurement is allowed to be analyzed one at a time, near real-time monitoring is possible. Damage progression can also be given from the method which makes it advantageous for damage evolution monitoring.

scholarly journals Corporate law in Ukraine within the framework of approaching the European Union standards

2020 ◽  
pp. 181-188
Author(s):  
Valentyna Vasylieva ◽  
Anatolii Kostruba
Keyword(s):  
European Union ◽  
Corporate Law ◽  
Eu Law ◽  
The European Union ◽  
Eu Member States ◽  
Legal Nature ◽  
European Union Countries ◽  
History Of ◽  
National Systems ◽  
Supranational Level

The article is devoted to adaptation of the national corporate law to the law of European Union`s corporations. Special attention has been given to define the legal nature of the corporation. It is concluded that there is no established understanding of the above concepts in national legal science. The main approaches to the corporate legal nature in particular European systems of justice - in FRG, France, England - are considered in depth. Significant differences between the legislation of Ukraine and legislation of the European Union countries based on the history of their development and peculiarities of specific national systems of justice are detected. The regulation of corporate relations in the European Union at supranational level is considered. It is concluded that the European Union supranational law is its corporate law. The priority areas for unification of European corporate law at the supranational level are analyzed. The main instruments to adjust the activities of corporations in EU law are identified to be the Directives aimed at harmonizing and unifying national legislation of EU Member States.

scholarly journals Decomposing the Apoptosis Pathway Into Biologically Interpretable Principal Components

2018 ◽  
Vol 17 ◽  
pp. 117693511877108 ◽  
Author(s):  
Min Wang ◽  
Steven M Kornblau ◽  
Kevin R Coombes
Keyword(s):  
Principal Components ◽  
Myeloid Leukemia ◽  
Principal Component ◽  
R Package ◽  
Biological Data ◽  
Data Sets ◽  
Proteomics Data ◽  
Data Set ◽  
Apoptosis Pathway ◽  
Biological Interpretation

Principal component analysis (PCA) is one of the most common techniques in the analysis of biological data sets, but applying PCA raises 2 challenges. First, one must determine the number of significant principal components (PCs). Second, because each PC is a linear combination of genes, it rarely has a biological interpretation. Existing methods to determine the number of PCs are either subjective or computationally extensive. We review several methods and describe a new R package, PCDimension, that implements additional methods, the most important being an algorithm that extends and automates a graphical Bayesian method. Using simulations, we compared the methods. Our newly automated procedure is competitive with the best methods when considering both accuracy and speed and is the most accurate when the number of objects is small compared with the number of attributes. We applied the method to a proteomics data set from patients with acute myeloid leukemia. Proteins in the apoptosis pathway could be explained using 6 PCs. By clustering the proteins in PC space, we were able to replace the PCs by 6 “biological components,” 3 of which could be immediately interpreted from the current literature. We expect this approach combining PCA with clustering to be widely applicable.

scholarly journals Multivariate Characterization of Hydrogen Balmer Emission in Cataclysmic Variables

2006 ◽  
Vol 23 (3) ◽  
pp. 106-118 ◽  
Author(s):  
Gordon E. Sarty ◽  
Kinwah Wu
Keyword(s):  
Principal Components Analysis ◽  
Discriminant Function ◽  
Principal Components ◽  
Discriminant Function Analysis ◽  
Function Analysis ◽  
Cataclysmic Variables ◽  
Data Set ◽  
Analysis Methods ◽  
Wide Range ◽  
Components Analysis

AbstractThe ratios of hydrogen Balmer emission line intensities in cataclysmic variables are signatures of the physical processes that produce them. To quantify those signatures relative to classifications of cataclysmic variable types, we applied the multivariate statistical analysis methods of principal components analysis and discriminant function analysis to the spectroscopic emission data set of Williams (1983). The two analysis methods reveal two different sources of variation in the ratios of the emission lines. The source of variation seen in the principal components analysis was shown to be correlated with the binary orbital period. The source of variation seen in the discriminant function analysis was shown to be correlated with the equivalent width of the Hβ line. Comparison of the data scatterplot with scatterplots of theoretical models shows that Balmer line emission from T CrB systems is consistent with the photoionization of a surrounding nebula. Otherwise, models that we considered do not reproduce the wide range of Balmer decrements, including ‘inverted’ decrements, seen in the data.

scholarly journals Atypical forms of employment among young people in the European Union

2016 ◽  
Author(s):  
Luísa Oliveira ◽  
Helena Carvalho ◽  
Luísa Veloso
Keyword(s):  
European Union ◽  
Young People ◽  
Labour Market ◽  
Categorical Data ◽  
Market Integration ◽  
The European Union ◽  
Temporary Work ◽  
Eu Member States ◽  
European Union Countries ◽  
Components Analysis

The article analyses precarious work among the young people in the 27 EU member states. It seeks to contribute to an understanding of the conditions relating to the integration of young people into the labour market in three decades (precisely, in 1988, 1998 and 2008), from a perspective that compares the countries. The information is derived from Eurostat sources; as its central indicator it takes the rate of temporary work and the interrelations between the young people’s qualification levels and the reasons cited for being in temporary work. A multivariate analysis was carried out: principal components analysis for categorical data (CatPCA). This allows us to present the differences between European Union countries, as well as the link between education and labour-market integration processes.

scholarly journals Tax Smoothing in the Presence of the Maastricht Constraint

2007 ◽  
Vol 25 (2) ◽  
pp. 129-150
Author(s):  
David Duffy
Keyword(s):  
European Union ◽  
Fiscal Policy ◽  
Public Expenditure ◽  
Maastricht Treaty ◽  
Single Sample ◽  
Testing Methods ◽  
Data Set ◽  
Testing Procedures ◽  
Tax Smoothing ◽  
European Union Countries

Abstract A sample of European Union countries are examined for evidence of tax smoothing over the period 1970-2005. Two testing procedures are applied to a single sample of countries to assess the consistency of evidence across testing methods. This study includes the application of a new data set to the tax smoothing question which provides an estimate of the temporary component of public expenditure. This study also argues that the application of the constraints imposed on fiscal policy in the Maastricht Treaty will affect the conduct of a tax smoothing policy. The effects of the Maastricht Treaty on tax smoothing behaviour are investigated.

scholarly journals Failing Solidarity: Justified or Excused?

2020 ◽  
Vol 12 (02) ◽  
pp. 189-218
Author(s):  
Eleonora Milazzo
Keyword(s):  
European Union ◽  
Real World ◽  
Refugee Crisis ◽  
Member States ◽  
The Real ◽  
Eu Member States ◽  
Wide Range ◽  
To Come ◽  
The Eu

The concept of solidarity has been receiving growing attention from scholars in a wide range of disciplines. While this trend coincides with widespread unsuccessful attempts to achieve solidarity in the real world, the failure of solidarity as such remains a relatively unexplored topic. In the case of the so-called European Union (EU) refugee crisis, the fact that EU member states failed to fulfil their commitment to solidarity is now regarded as established wisdom. But as we try to come to terms with failing solidarity in the EU we are faced with a number of important questions: are all instances of failing solidarity equally morally reprehensible? Are some motivations for resorting to unsolidaristic measures more valid than others? What claims have an effective countervailing force against the commitment to act in solidarity?

scholarly journals Determination of genetic divergence in pointed gourd by principal component and non-hierarchical euclidean cluster analysis

2017 ◽  
Vol 9 (4) ◽  
pp. 2421-2426
Author(s):  
Priyanka Verma ◽  
S. K. Maurya ◽  
Hridesh Yadav ◽  
Ankit Panchbhaiya
Keyword(s):  
Cluster Analysis ◽  
Principal Components ◽  
Genetic Divergence ◽  
Principal Component ◽  
Female Flower ◽  
Research Centre ◽  
Cluster Number ◽  
Wide Range ◽  
Total Divergence ◽  
Pointed Gourd

The present investigation was carried out at Vegetable Research Centre, Pantnagar to estimate the ge-netic divergence using Mahalanobis D2 statistics for twelve characters on 35 genotypes of pointed gourd. Cluster analysis and principal component analysis (PCA) were used to identify the most discerning trait responsible for greater variability in the lines and on the basis of mean performance, genotypes were classified into different groups. Five principal components (PC) have been extracted using the mean performance of the genotypes and 83.23 per cent variation is yielded by the first five principal components, among them high mean positive value or higher weight age was obtained was obtained for days to first female flower anthesis and days to first fruit harvest among all the vectors, indicates that these traits are important component of genetic divergence in pointed gourd. Non- hierarchical Euclidean cluster analysis grouped the genotypes into seven clusters and the highest number of genotypes were found in cluster number IV i.e. eleven whereas maximum inter-cluster distance was found between the cluster III and VI i.e. 74.250, it indicates that a wide range of genetic divergence is present between the genotypes present among these two clusters. And as per contribution toward total divergence, traits like fruit yield per hectare and number of fruit per plant contributed 92.64% toward total divergence. The high diversity found in the genotypes showed its great potential for improving qualitative as well as quantitative traits in pointed gourd.

A study on the relationship between cultural dimensions and innovation performance in the European Union countries

2019 ◽  
Vol 52 (22) ◽  
pp. 2377-2391 ◽  
Author(s):  
Raphaël Murswieck ◽  
Mihaela Drăgan ◽  
Mihaela Maftei ◽  
Diana Ivana ◽  
Astrid Fortmüller
Keyword(s):  
European Union ◽  
Innovation Performance ◽  
Cultural Dimensions ◽  
The European Union ◽  
European Union Countries ◽  
The Relationship

scholarly journals A Frequency-Based Approach for the Detection and Classification of Structural Changes Using t-SNE †

Sensors ◽  
2019 ◽  
Vol 19 (23) ◽  
pp. 5097 ◽  
Author(s):  
David Agis ◽  
Francesc Pozo
Keyword(s):  
Structural Changes ◽  
Dimensional Space ◽  
Principal Component ◽  
Majority Voting ◽  
Data Set ◽  
Centroid Distance ◽  
Low Dimensional ◽  
Reduced Data

This work presents a structural health monitoring (SHM) approach for the detection and classification of structural changes. The proposed strategy is based on t-distributed stochastic neighbor embedding (t-SNE), a nonlinear procedure that is able to represent the local structure of high-dimensional data in a low-dimensional space. The steps of the detection and classification procedure are: (i) the data collected are scaled using mean-centered group scaling (MCGS); (ii) then principal component analysis (PCA) is applied to reduce the dimensionality of the data set; (iii) t-SNE is applied to represent the scaled and reduced data as points in a plane defining as many clusters as different structural states; and (iv) the current structure to be diagnosed will be associated with a cluster or structural state based on three strategies: (a) the smallest point-centroid distance; (b) majority voting; and (c) the sum of the inverse distances. The combination of PCA and t-SNE improves the quality of the clusters related to the structural states. The method is evaluated using experimental data from an aluminum plate with four piezoelectric transducers (PZTs). Results are illustrated in frequency domain, and they manifest the high classification accuracy and the strong performance of this method.

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