Suchergebnisse

Since 2010, the European Union countries have been implementing the objectives of the Europe 2020 Strategy aimed at smart, sustainable, and inclusive growth. The Strategy formulates nine indicators that are systematically monitored and assessed. Not all the indicators of the Europe 2020 Strategy could be used in the analysis in a direct way. Due to the limited availability and comparability of statistical data, this problem is presented in detail in part 2 of the article. The assessment of the achievement level of the Europe 2020 Strategy targets, both at the level of the entire European Union (the EU-level targets approach) and its individual Member States (the national-level targets approach) is the primary research purpose of the study. The composite index proposed and constructed on the basis of a dynamic relative taxonomy was used in the conducted research to present the diversified distance of the individual European Union countries in relation to the EU-level targets as well as the national-level targets of the Europe 2020 Strategy. The research methodology allows conducting the analysis taking into account the missing data. Most methods of ordering objects based on aggregate measures are compensatory in nature. This problem was significantly reduced by taking into account the geometric mean in the construction of the aggregate measure. The research findings revealed that in the years 2010–2019 an ongoing improvement in the implementation of both the EU and the national targets of the Europe 2020 Strategy was observed. In addition, the differences existing between the European Union Member States were reduced. However, none of the countries achieved the EU-level targets. Their highest implementation level was recorded in Denmark, Sweden, Austria, and Finland. The achievement level of the strategic goals regarding the national-level targets was influenced by the choice of one of the two approaches indicated in the study and adopted by the individual EU Member States in determining the set target values of the indicators, i.e., either prudential or optimistic.

The aim of the paper is to measure the scope and degree of differences in the situation of young people in the labour market in the border regions of Poland, the Czech Republic and Germany in 2010 and 2018, using six metric variables. For the purpose of the study, a hybrid approach was adopted, which involved carrying out linear ordering of the studied regions on the basis of the results of multidimensional scaling. The synthetic assessment of the changes in the situation of young people in the labour market in border regions was performed using the aggregate measure and Theil's decomposition. The study was based on data from Eurostat's REGIO database. It demonstrated that the situation of young people in the labour market in all the examined regions had significantly improved in the studied period. It also showed that Polish border regions, in addition to being significantly diversified in this respect, are in a worse situation than their German or Czech counterparts, but overall, the interregional disproportions among the countries shrank in the analysed period.

Intro -- Preface -- Contents -- About the Editors -- Methods -- Fuzzy Cognitive Maps as a Toll for Structuring New Research Problems -- 1 Introduction -- 2 Factors Decisive in the Choice and Development of Smart Specialisations-a Literature Review -- 3 Stages of Structuring the Research Problem with the Use of Fuzzy Cognitive Maps -- 4 Research Results -- 5 Discussion and Conclusions -- References -- Identification of Key Concerns and Sentiments Towards Data Quality and Data Strategy Challenges Using Sentiment Analysis and Topic Modeling -- 1 Introduction -- 2 Literature Study -- 3 Experiments Description -- 3.1 Data Extraction -- 3.2 Texts' Preprocessing -- 3.3 Sentiment Analysis and Topic Modelling -- 4 Results -- 5 Conclusion -- References -- Survival Trees and Direct Adjusted Survival Curves-Prediction of Survival Probabilities -- 1 Introduction -- 2 Theoretical Backgrounds -- 3 Empirical Examples -- 3.1 Data -- 3.2 Survival Trees -- 3.3 Survival Function Estimation -- 4 Summary and Conclusions -- References -- A Measure of Cluster Stability in Dynamic Cluster Analysis -- 1 Introduction -- 2 Method -- 3 Distribution of CS* -- 4 Examples -- 5 Conclusions -- References -- Outlier Identification for Symbolic Data with the Application of the DBSCAN Algorithm -- 1 Introduction -- 2 DBSCAN Ensemble for Symbolic Data -- 3 Simulations and Their Results -- 4 Final Remarks -- References -- An Optimized Selection of Statistical Disclosure Control Methods-A Case Study Involving Microdata from the Polish Survey of Accidents at Work -- 1 Introduction -- 2 Statistical Disclosure Control-Basic Concepts -- 3 The SDC Process in the Survey of Accidents at Work -- 4 Results of the SDC Process -- 5 Final Conclusions -- References -- Applications in Finance.

Intro -- Preface -- Contents -- About the Editors -- Methodology -- 1 Evaluation of Two-Step Spectral Clustering Algorithm for Large Untypical Data Sets -- Abstract -- 1 Introduction -- 2 Limitations of Large Data Sets Classification -- 3 Proposal of New Algorithm -- 4 Simulation Experiment Results -- 5 Final Remarks and Conclusions -- References -- 2 Determining the Number of Groups in Cluster Analysis Using Classical Indexes and Stability Measures-Comparison of Results -- Abstract -- 1 Introduction -- 2 Measures of Cluster Stability -- 2.1 Ben-Hur and Guyon Stability Measure -- 2.2 Brock, Pihur, Datta, and Datta Stability Measure -- 2.3 Fang and Wang Stability Measure -- 3 A Data Set and the Scheme of Research -- 4 Empirical Results -- 4.1 Results for the Social Domain -- 4.2 Results for the Economic Domain -- 4.3 Results for the Environmental Domain -- 4.4 Results for the Institutional and Political Domain -- 5 Conclusions -- References -- 3 Identification of the Words Most Frequently Used by Different Generations of Twitter Users -- Abstract -- 1 Theory of Generations -- 2 Analysis of the Textual Data from the Social Network -- 2.1 Preparation of Text Data -- 2.2 Word Frequency Analysis -- 2.3 N-Gram Analysis -- 2.4 Agglomeration Methods of Hierarchical Clustering and Quality Assessment of Group Structure -- 3 Applications and Results -- 3.1 Twitter User Analysis -- 3.2 Analysis of the Words Occurring Most Commonly -- 3.3 Bigrams and Trigrams -- 4 Conclusion -- References -- 4 Classification Algorithms Applications for Information Security on the Internet: A Review -- Abstract -- 1 Introduction -- 2 Information Security -- 2.1 Cybersecurity Incidents Classification Taxonomy -- 2.2 Application on the Real Data -- 3 Methodology -- 4 Application of Classification Algorithms to Information Security -- 4.1 Popular Classification Algorithms.

Preface -- Methods -- Comparison of proposals of transformation of nominants into stimulants on the example of financial ratios of companies listed on the Warsaw Stock Exchange -- Silhouette index as clustering evaluation tool -- The Role of Discretization of Continuous Variables in SocioEconomic Classification Models on the Example of Logistic Regression Models and Artificial Neural Networks -- Intuitionistic fuzzy synthetic measure for ordinal data -- Improving Classification Accuracy of Ensemble Learning for Symbolic Data Trough Neural Networks' Feature Extraction -- Applications in Finance -- Inequality restricted least squares (IRLS) model of real estate prices -- Application of Hill estimator to assess extreme risks in the metals market -- Segmentation of Enterprises on the Basis of Their Duration Using Survival Trees. Results of an Analysis for Legal Persons and Organizational Entities without Legal Personality in the Łódzkie Voivodship -- Corporate Bankruptcy Prediction with the Use of the Logit Leaf Model -- The impact of longevity on a valuation of long-term investments returns: the case of selected European countries -- Applications in Economics.-Sustainable Development and Green Economy in the European Union Countries – statistical analysis -- The review of indicators of data quality in intra-Community trade in goods. The choice of an indicator and its effect on the ranking of countries -- Development of ICT in Poland in Comparison with the European Union Countries – Multivariate Statistical Analysis -- Sensitivity Analysis in Causal Mediation Effects for TAM Model -- Applications in Social Problems -- Prentice-Williams-Peterson models in the assessment of the influence of the characteristics of the unemployed on the intensity of subsequent registrations in the labour office -- Right-skewed distribution of features and the identification problem of the financial autonomy of local administrative units -- Multi-Criteria Rankings with Interdependent Criteria: Case of EU Countries on Their Way to Healthy Lives and Well-Being -- The comparison of income distributions for women and men in the European Union countries -- Common stochastic mortality trends for multiple European populations -- Impact of the selected factors on the men and women wages in Poland in 2014. The conjoint analysis application.