The scientific field of data analysis is constantly expanding due to the rapid growth of the computer industry and the wide applicability of computational and algorithmic techniques, in conjunction with new advances in statistical, stochastic and analytic tools. There is a constant need for new, high-quality publications to cover the recent advances in all fields of science and engineering. This book is a collective work by a number of leading scientists, computer experts, analysts, engineers, mathematicians, probabilists and statisticians who have been working at the forefront of data…mehr
The scientific field of data analysis is constantly expanding due to the rapid growth of the computer industry and the wide applicability of computational and algorithmic techniques, in conjunction with new advances in statistical, stochastic and analytic tools. There is a constant need for new, high-quality publications to cover the recent advances in all fields of science and engineering.
This book is a collective work by a number of leading scientists, computer experts, analysts, engineers, mathematicians, probabilists and statisticians who have been working at the forefront of data analysis and related applications. The chapters of this collaborative work represent a cross-section of current concerns, developments and research interests in the above scientific areas. The collected material has been divided into appropriate sections to provide the reader with both theoretical and applied information on data analysis methods, models and techniques, along with related applications.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Konstantinos N. Zafeiris is Associate Professor of Demography within the Department of History and Ethnology at the Democritus University of Thrace, Greece. Christos H. Skiadas was the Founder and Director of Data Analysis and Forecasting and Former Vice-Rector at the Technical University of Crete, Greece. Yiannis Dimotikalis is Assistant Professor of Quantitative Methods within the Department of Management Science and Technology at the Hellenic Mediterranean University, Greece. Alex Karagrigoriou is Professor of Probability and Statistics, Director of the Laboratory of Statistics and Data Analysis and Actuarial-Financial Mathematics at the University of the Aegean, Greece. Christiana Karagrigoriou-Vonta is a (socio) linguist, translator and subtitler. She works as a freelance translator and editor of scientific texts and provides postproduction services (subtitling) for private companies and broadcasting corporations.
Inhaltsangabe
Preface xvii Konstantinos N. ZAFEIRIS, Yiannis DIMOTIKALIS, Christos H. SKIADAS, Alex KARAGRIGORIOU and Christiana KARAGRIGORIOU-VONTA
Part 1 1
Chapter 1. Performance of Evaluation of Diagnosis of Various Thyroid Diseases Using Machine Learning Techniques 3 Burcu Bektas GÜNE^, Evren BURSUK and Rüya ^AMLI
1.1. Introduction 3
1.2. Data understanding 5
1.3. Modeling 6
1.4. Findings 8
1.5. Conclusion 10
1.6. References 10
Chapter 2. Exploring Chronic Diseases' Spatial Patterns: Thyroid Cancer in Sicilian Volcanic Areas 13 Francesca BITONTI and Angelo MAZZA
2.1. Introduction 14
2.2. Epidemiological data and territory 16
2.3. Methodology 18
2.3.1. Spatial inhomogeneity and spatial dependence 18
2.3.2. Standardized incidence ratio (SIR) 19
2.3.3. Local Moran's I statistic 21
2.4. Spatial distribution of TC in eastern Sicily 22
2.4.1. SIR geographical variation 22
2.4.2. Estimate of the spatial attraction 24
2.5. Conclusion 25
2.6. References 26
Chapter 3. Analysis of Blockchain-based Databases in Web Applications 31 Orhun Ceng BOZO and Rüya ^AMLI
3.1. Introduction 31
3.2. Background 32
3.2.1. Blockchain 32
3.2.2. Blockchain types 32
3.2.3. Blockchain-based web applications 33
3.2.4. Blockchain consensus algorithms 33
3.2.5. Other consensus algorithms 34
3.3. Analysis stack 34
3.3.1. Art Shop web application 34
3.3.2. SQL-based application 34
3.3.3. NoSQL-based application 35
3.3.4. Blockchain-based application 35
3.4. Analysis 36
3.4.1. Adding records 36
3.4.2. Query 38
3.4.3. Functionality 39
3.4.4. Security 39
3.5. Conclusion 41
3.6. References 41
Chapter 4. Optimization and Asymptotic Analysis of Insurance Models 43 Ekaterina BULINSKAYA
4.1. Introduction 43
4.2. Discrete-time model with reinsurance and bank loans 44
4.2.1. Model description 44
4.2.2. Optimization problem 45
4.2.3. Model stability 46
4.3. Continuous-time insurance model with dividends 48
4.3.1. Model description 48
4.3.2. Optimal barrier strategy 49
4.3.3. Special form of claim distribution 50
4.3.4. Numerical analysis 54
4.4. Conclusion and further research directions 55
4.5. References 56
Chapter 5. Statistical Analysis of Traffic Volume in the 25 de Abril Bridge 57 Frederico CAEIRO, Ayana MATEUS and Conceicao VEIGA de ALMEIDA
5.1. Introduction 57
5.2. Data 58
5.3. Methodology 60
5.3.1. Main limit results 60
5.3.2. Block maxima method 61
5.3.3. Largest order statistics method 62
5.3.4. Estimation of other tail parameters 63
5.4. Results and conclusion 63
5.5. Acknowledgements 65
5.6. References 65
Chapter 6. Predicting the Risk of Gestational Diabetes Mellitus through Nearest Neighbor Classification 67 Louisa TESTA, Mark A. CARUANA, Maria KONTORINAKI and Charles SAVONA-VENTURA
6.1. Introduction 67
6.2. Nearest neighbor methods 69
6.2.1. Background of the NN methods 69
6.2.2. The k-nearest neighbors method 70
6.2.3. The fixed-radius NN method 70
6.2.4. The kernel-NN method 71
6.2.5. Algorithms of the three considered NN methods 72
Preface xvii Konstantinos N. ZAFEIRIS, Yiannis DIMOTIKALIS, Christos H. SKIADAS, Alex KARAGRIGORIOU and Christiana KARAGRIGORIOU-VONTA
Part 1 1
Chapter 1. Performance of Evaluation of Diagnosis of Various Thyroid Diseases Using Machine Learning Techniques 3 Burcu Bektas GÜNE^, Evren BURSUK and Rüya ^AMLI
1.1. Introduction 3
1.2. Data understanding 5
1.3. Modeling 6
1.4. Findings 8
1.5. Conclusion 10
1.6. References 10
Chapter 2. Exploring Chronic Diseases' Spatial Patterns: Thyroid Cancer in Sicilian Volcanic Areas 13 Francesca BITONTI and Angelo MAZZA
2.1. Introduction 14
2.2. Epidemiological data and territory 16
2.3. Methodology 18
2.3.1. Spatial inhomogeneity and spatial dependence 18
2.3.2. Standardized incidence ratio (SIR) 19
2.3.3. Local Moran's I statistic 21
2.4. Spatial distribution of TC in eastern Sicily 22
2.4.1. SIR geographical variation 22
2.4.2. Estimate of the spatial attraction 24
2.5. Conclusion 25
2.6. References 26
Chapter 3. Analysis of Blockchain-based Databases in Web Applications 31 Orhun Ceng BOZO and Rüya ^AMLI
3.1. Introduction 31
3.2. Background 32
3.2.1. Blockchain 32
3.2.2. Blockchain types 32
3.2.3. Blockchain-based web applications 33
3.2.4. Blockchain consensus algorithms 33
3.2.5. Other consensus algorithms 34
3.3. Analysis stack 34
3.3.1. Art Shop web application 34
3.3.2. SQL-based application 34
3.3.3. NoSQL-based application 35
3.3.4. Blockchain-based application 35
3.4. Analysis 36
3.4.1. Adding records 36
3.4.2. Query 38
3.4.3. Functionality 39
3.4.4. Security 39
3.5. Conclusion 41
3.6. References 41
Chapter 4. Optimization and Asymptotic Analysis of Insurance Models 43 Ekaterina BULINSKAYA
4.1. Introduction 43
4.2. Discrete-time model with reinsurance and bank loans 44
4.2.1. Model description 44
4.2.2. Optimization problem 45
4.2.3. Model stability 46
4.3. Continuous-time insurance model with dividends 48
4.3.1. Model description 48
4.3.2. Optimal barrier strategy 49
4.3.3. Special form of claim distribution 50
4.3.4. Numerical analysis 54
4.4. Conclusion and further research directions 55
4.5. References 56
Chapter 5. Statistical Analysis of Traffic Volume in the 25 de Abril Bridge 57 Frederico CAEIRO, Ayana MATEUS and Conceicao VEIGA de ALMEIDA
5.1. Introduction 57
5.2. Data 58
5.3. Methodology 60
5.3.1. Main limit results 60
5.3.2. Block maxima method 61
5.3.3. Largest order statistics method 62
5.3.4. Estimation of other tail parameters 63
5.4. Results and conclusion 63
5.5. Acknowledgements 65
5.6. References 65
Chapter 6. Predicting the Risk of Gestational Diabetes Mellitus through Nearest Neighbor Classification 67 Louisa TESTA, Mark A. CARUANA, Maria KONTORINAKI and Charles SAVONA-VENTURA
6.1. Introduction 67
6.2. Nearest neighbor methods 69
6.2.1. Background of the NN methods 69
6.2.2. The k-nearest neighbors method 70
6.2.3. The fixed-radius NN method 70
6.2.4. The kernel-NN method 71
6.2.5. Algorithms of the three considered NN methods 72
6.2.6. Parameter and distance metric selection 74
6.3. Experimental re
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