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Biblioteca

MARC Lista (tabellare)
Current Trends in Analysis, its Applications and Computation [[electronic resource] ] : Proceedings of the 12th ISAAC Congress, Aveiro, Portugal, 2019 / / edited by Paula Cerejeiras, Michael Reissig, Irene Sabadini, Joachim Toft
Current Trends in Analysis, its Applications and Computation [[electronic resource] ] : Proceedings of the 12th ISAAC Congress, Aveiro, Portugal, 2019 / / edited by Paula Cerejeiras, Michael Reissig, Irene Sabadini, Joachim Toft
Edizione [1st ed. 2022.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Birkhäuser, , 2022
Descrizione fisica 1 online resource (662 pages)
Disciplina 515
Collana Research Perspectives
Soggetto topico Mathematical analysis
Analysis
Anàlisi matemàtica
Processament de dades
Soggetto genere / forma Congressos
Llibres electrònics
ISBN 3-030-87502-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Foreword -- Contributions on: Applications of dynamical systems theory in biology -- Complex Analysis and Partial Differential Equations -- Complex Geometry -- Complex Variables and Potential Theory -- Constructive Methods in the Theory of Composite and Porous Media -- Function Spaces and Applications -- Generalized Functions and Applications -- Geometric & Regularity Properties of Solutions to Elliptic and Parabolic PDEs -- Geometries Defined by Differential Forms -- Partial Differential Equations on Curved Spacetimes -- Partial Differential Equations with Nonstandard Growth -- Quaternionic and Clifford Analysis -- Recent Progress in Evolution Equations -- Wavelet theory and its Related Topics.
Record Nr. UNISA-996495171803316
Cham : , : Springer International Publishing : , : Imprint : Birkhäuser, , 2022
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Current Trends in Analysis, its Applications and Computation : Proceedings of the 12th ISAAC Congress, Aveiro, Portugal, 2019 / / edited by Paula Cerejeiras, Michael Reissig, Irene Sabadini, Joachim Toft
Current Trends in Analysis, its Applications and Computation : Proceedings of the 12th ISAAC Congress, Aveiro, Portugal, 2019 / / edited by Paula Cerejeiras, Michael Reissig, Irene Sabadini, Joachim Toft
Edizione [1st ed. 2022.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Birkhäuser, , 2022
Descrizione fisica 1 online resource (662 pages)
Disciplina 515
Collana Research Perspectives
Soggetto topico Mathematical analysis
Analysis
Anàlisi matemàtica
Processament de dades
Soggetto genere / forma Congressos
Llibres electrònics
ISBN 3-030-87502-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Foreword -- Contributions on: Applications of dynamical systems theory in biology -- Complex Analysis and Partial Differential Equations -- Complex Geometry -- Complex Variables and Potential Theory -- Constructive Methods in the Theory of Composite and Porous Media -- Function Spaces and Applications -- Generalized Functions and Applications -- Geometric & Regularity Properties of Solutions to Elliptic and Parabolic PDEs -- Geometries Defined by Differential Forms -- Partial Differential Equations on Curved Spacetimes -- Partial Differential Equations with Nonstandard Growth -- Quaternionic and Clifford Analysis -- Recent Progress in Evolution Equations -- Wavelet theory and its Related Topics.
Record Nr. UNINA-9910616211203321
Cham : , : Springer International Publishing : , : Imprint : Birkhäuser, , 2022
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Data analysis and classification : methods and applications / / edited by Krzysztof Jajuga, Krzysztof Najman, and Marek Walesiak
Data analysis and classification : methods and applications / / edited by Krzysztof Jajuga, Krzysztof Najman, and Marek Walesiak
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (346 pages)
Disciplina 330.015195
Collana Studies in Classification, Data Analysis, and Knowledge Organization
Soggetto topico Economics - Statistical methods
Statistics - Data processing
Economia
Estadística
Processament de dades
Soggetto genere / forma Congressos
Llibres electrònics
ISBN 3-030-75190-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 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.
4.2 Classification Algorithms Used Per Study -- 4.3 Cybersecurity Incidents Examined -- 4.4 Highly Cited Studies -- 4.5 Challenges in Classification Algorithms Application to the Information Security -- 5 Conclusions and Future Research Directions -- References -- 5 Outlier Detection with the Use of Isolation Forests -- Abstract -- 1 The Essence of Outliers in Cluster Analysis -- 2 Introduction to Isolation Forests and Extended Isolation Forests -- 3 The Impact of Algorithm Parameters on the method's Effectiveness -- 4 The Impact of Dataset Characteristics on the Anomaly Score Values -- 5 Discussion of the Empirical Research Results -- 6 Final Conclusions -- References -- Application in Finance -- 6 Propositions of Transformations of Asymmetrical Nominants into Stimulants on the Example of Chosen Financial Ratios -- Abstract -- 1 Introduction -- 2 Previous Proposition of Modification of Minimum and Maximum -- 3 Proposals of Nonlinear Transformation of Nominant into Stimulants Normalized in the Range [0 -- 1] -- 4 Data and Empirical Results -- 5 Conclusions -- References -- 7 Gini Regression in the Capital Investment Risk Assessment-Sensitivity Risk Measures in Portfolio Analysis -- Abstract -- 1 Introduction -- 2 Systematic Risk-Estimation Beta -- 3 Gini Regression-Multiple Regressions Model -- 4 Application of Gini Regression in Portfolio Analysis -- 5 Discussion and Conclusion -- References -- Application in Economics -- 8 Enterprise Dark Data -- Abstract -- 1 Introduction -- 2 Data Classification in Enterprises -- 2.1 Data Visibility -- 2.2 Data Quality -- 2.3 Data Availability -- 3 Dark Data Definitions-Literature Overview -- 4 Propositions and Results -- 4.1 Location of Dark Data in Enterprise -- 5 Conclusions -- References -- 9 The Significance of Medical Science Issues in Research Papers Published in the Field of Economics -- Abstract.
1 Introduction -- 2 Interaction of Economic and Medical Sciences -- 3 Description of Classifications -- 4 Research Methodology -- 4.1 Research Scope and Goals -- 4.2 Identification of Topics Occurring in Abstracts and Related to Main Subareas of Economics and Medical Science -- 4.3 Projection of Identified Topics into Main Concepts from JEL and MeSH Ontologies -- 4.4 Analysis of Relationships Between Concepts Related to Economics and Medical Science -- 5 The Analysis of the Contribution of Medical Science Issues in Research Papers Published in the Field of Economics -- 6 Conclusions -- Acknowledgements -- References -- 10 Application of Duration Analysis Methods in the Study of the Exit of a Real Estate Sale Offer from the Offer Database System -- Abstract -- 1 Introduction -- 2 Data Used in the Study -- 3 Time on the Market-Censored Data -- 4 Duration Analysis of the Real Estate Offer -- 5 Empirical Research -- 6 Conclusions -- References -- 11 Is Society Ready for Long-Term Investments?-Profiles of Electricity Users in Silesia -- Abstract -- 1 Introduction -- 2 Study of Energy Consumers' Behaviours and Their Impact on Shaping Pro-ecological Attitudes -- 3 Characteristics of the Surveyed Electricity Users and Description of the Methods Applied in the Study -- 4 Results and Discussion -- 4.1 Characteristics of the Short-Term and Long-Term Investor Classes -- 4.2 Profiling of the Short-Term and Long-Term Investor Classes -- 5 Conclusions -- Acknowledgments -- References -- 12 The Use of the Spatial Taxonomic Measure of Development to Assess the Tourist Attractiveness of Districts of the Lesser Poland Province -- Abstract -- 1 Introduction -- 2 Methods -- 2.1 Linear Ordering -- 2.2 Hellwig's Method -- 2.3 Spatial Taxonomy Measure -- 3 Dataset and Results -- 3.1 Dataset -- 3.2 Empirical Study -- 4 Conclusions -- References.
Application in Social Issues -- 13 Models of Competing Events in Assessing the Effects of the Transition of Unemployed People Between the States of Registration and De-Registration -- Abstract -- 1 Introduction -- 2 Literature Review -- 3 Research Methodology -- 4 Data Used in the Study -- 5 Empirical Results -- 6 Conclusions -- References -- 14 Direct Adjusted Survival Probabilities in the Analysis of Finding a Job by the Unemployed Depending on Their Individual Characteristics -- Abstract -- 1 Introduction -- 2 Research Method -- 3 Empirical Data and the Estimation of the Models -- 4 Conclusions -- References -- 15 Europe 2020 Strategy-Objective Evaluation of Realization and Subjective Assessment by Seniors as Beneficiaries of Social Assumptions -- Abstract -- 1 Introduction -- 2 Research Background and Literature Review -- 3 Data and Methods -- 4 Taxonomic Measure of Good Oldness -- 5 Europe 2020 Strategy in the Seniors' Opinion -- 6 Conclusions and Discussion -- References -- 16 Do Seniors Get to the Disco by Bike or in a Taxi?-Classification of Seniors According to Their Preferred Means of Transport -- Abstract -- 1 Introduction -- 2 Literature Review: Seniors and Their Transport Needs. Attempts at Segmentation -- 3 Methodology: Segmentations Rationale and Data Collection -- 3.1 Expert Segmentation -- 3.2 Segmentation Using Taxonomic Methodology -- 4 Results and Discussion -- 4.1 Main Findings of the Expert Segmentation -- 4.2 Main Findings of the Segmentation Using Taxonomic Methodology -- 4.3 Comparison of the Two Segmentations -- 5 Conclusions -- References -- Application with COVID-19 Data -- 17 The Impact of the COVID-19 Pandemic on the Economies of European Countries in the Period January-September 2020 Based on Economic Indicators -- Abstract -- 1 Introduction -- 2 SARS-CoV-2 and Economies -- 3 Literature Review -- 4 Economic Indicators.
5 Methodology -- 6 Economic Situation in European Countries and COVID-19 -- 6.1 First Quarter -- 6.2 Second Quarter -- 6.3 Third Quarter -- 6.4 January-September 2020 -- 7 Conclusions -- References -- 18 Modelling the Risk of Foreign Divestment in the Visegrad Group Countries During the COVID-19 Pandemic -- Abstract -- 1 Introduction -- 2 Review of Literature -- 3 Research Methodology -- 4 Results of Empirical Research -- 4.1 Modelling of the Risk of Insignificant Foreign Divestment -- 4.2 Modelling of the Risk of Moderate Foreign Divestment -- 4.3 Modelling of the Risk of Considerable Foreign Divestment -- 5 Conclusions -- Acknowledgements -- References -- 19 Analysis of COVID-19 Dynamics in EU Countries Using the Dynamic Time Warping Method and ARIMA Models -- Abstract -- 1 Introduction -- 2 Research Methodology -- 3 Empirical Data -- 4 The Results of the DTW Method -- 5 The Results of the ARIMA Modeling -- 6 Conclusions -- References.
Record Nr. UNISA-996466397503316
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Data analysis and classification : methods and applications / / edited by Krzysztof Jajuga, Krzysztof Najman, and Marek Walesiak
Data analysis and classification : methods and applications / / edited by Krzysztof Jajuga, Krzysztof Najman, and Marek Walesiak
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (346 pages)
Disciplina 330.015195
Collana Studies in Classification, Data Analysis, and Knowledge Organization
Soggetto topico Economics - Statistical methods
Statistics - Data processing
Economia
Estadística
Processament de dades
Soggetto genere / forma Congressos
Llibres electrònics
ISBN 3-030-75190-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 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.
4.2 Classification Algorithms Used Per Study -- 4.3 Cybersecurity Incidents Examined -- 4.4 Highly Cited Studies -- 4.5 Challenges in Classification Algorithms Application to the Information Security -- 5 Conclusions and Future Research Directions -- References -- 5 Outlier Detection with the Use of Isolation Forests -- Abstract -- 1 The Essence of Outliers in Cluster Analysis -- 2 Introduction to Isolation Forests and Extended Isolation Forests -- 3 The Impact of Algorithm Parameters on the method's Effectiveness -- 4 The Impact of Dataset Characteristics on the Anomaly Score Values -- 5 Discussion of the Empirical Research Results -- 6 Final Conclusions -- References -- Application in Finance -- 6 Propositions of Transformations of Asymmetrical Nominants into Stimulants on the Example of Chosen Financial Ratios -- Abstract -- 1 Introduction -- 2 Previous Proposition of Modification of Minimum and Maximum -- 3 Proposals of Nonlinear Transformation of Nominant into Stimulants Normalized in the Range [0 -- 1] -- 4 Data and Empirical Results -- 5 Conclusions -- References -- 7 Gini Regression in the Capital Investment Risk Assessment-Sensitivity Risk Measures in Portfolio Analysis -- Abstract -- 1 Introduction -- 2 Systematic Risk-Estimation Beta -- 3 Gini Regression-Multiple Regressions Model -- 4 Application of Gini Regression in Portfolio Analysis -- 5 Discussion and Conclusion -- References -- Application in Economics -- 8 Enterprise Dark Data -- Abstract -- 1 Introduction -- 2 Data Classification in Enterprises -- 2.1 Data Visibility -- 2.2 Data Quality -- 2.3 Data Availability -- 3 Dark Data Definitions-Literature Overview -- 4 Propositions and Results -- 4.1 Location of Dark Data in Enterprise -- 5 Conclusions -- References -- 9 The Significance of Medical Science Issues in Research Papers Published in the Field of Economics -- Abstract.
1 Introduction -- 2 Interaction of Economic and Medical Sciences -- 3 Description of Classifications -- 4 Research Methodology -- 4.1 Research Scope and Goals -- 4.2 Identification of Topics Occurring in Abstracts and Related to Main Subareas of Economics and Medical Science -- 4.3 Projection of Identified Topics into Main Concepts from JEL and MeSH Ontologies -- 4.4 Analysis of Relationships Between Concepts Related to Economics and Medical Science -- 5 The Analysis of the Contribution of Medical Science Issues in Research Papers Published in the Field of Economics -- 6 Conclusions -- Acknowledgements -- References -- 10 Application of Duration Analysis Methods in the Study of the Exit of a Real Estate Sale Offer from the Offer Database System -- Abstract -- 1 Introduction -- 2 Data Used in the Study -- 3 Time on the Market-Censored Data -- 4 Duration Analysis of the Real Estate Offer -- 5 Empirical Research -- 6 Conclusions -- References -- 11 Is Society Ready for Long-Term Investments?-Profiles of Electricity Users in Silesia -- Abstract -- 1 Introduction -- 2 Study of Energy Consumers' Behaviours and Their Impact on Shaping Pro-ecological Attitudes -- 3 Characteristics of the Surveyed Electricity Users and Description of the Methods Applied in the Study -- 4 Results and Discussion -- 4.1 Characteristics of the Short-Term and Long-Term Investor Classes -- 4.2 Profiling of the Short-Term and Long-Term Investor Classes -- 5 Conclusions -- Acknowledgments -- References -- 12 The Use of the Spatial Taxonomic Measure of Development to Assess the Tourist Attractiveness of Districts of the Lesser Poland Province -- Abstract -- 1 Introduction -- 2 Methods -- 2.1 Linear Ordering -- 2.2 Hellwig's Method -- 2.3 Spatial Taxonomy Measure -- 3 Dataset and Results -- 3.1 Dataset -- 3.2 Empirical Study -- 4 Conclusions -- References.
Application in Social Issues -- 13 Models of Competing Events in Assessing the Effects of the Transition of Unemployed People Between the States of Registration and De-Registration -- Abstract -- 1 Introduction -- 2 Literature Review -- 3 Research Methodology -- 4 Data Used in the Study -- 5 Empirical Results -- 6 Conclusions -- References -- 14 Direct Adjusted Survival Probabilities in the Analysis of Finding a Job by the Unemployed Depending on Their Individual Characteristics -- Abstract -- 1 Introduction -- 2 Research Method -- 3 Empirical Data and the Estimation of the Models -- 4 Conclusions -- References -- 15 Europe 2020 Strategy-Objective Evaluation of Realization and Subjective Assessment by Seniors as Beneficiaries of Social Assumptions -- Abstract -- 1 Introduction -- 2 Research Background and Literature Review -- 3 Data and Methods -- 4 Taxonomic Measure of Good Oldness -- 5 Europe 2020 Strategy in the Seniors' Opinion -- 6 Conclusions and Discussion -- References -- 16 Do Seniors Get to the Disco by Bike or in a Taxi?-Classification of Seniors According to Their Preferred Means of Transport -- Abstract -- 1 Introduction -- 2 Literature Review: Seniors and Their Transport Needs. Attempts at Segmentation -- 3 Methodology: Segmentations Rationale and Data Collection -- 3.1 Expert Segmentation -- 3.2 Segmentation Using Taxonomic Methodology -- 4 Results and Discussion -- 4.1 Main Findings of the Expert Segmentation -- 4.2 Main Findings of the Segmentation Using Taxonomic Methodology -- 4.3 Comparison of the Two Segmentations -- 5 Conclusions -- References -- Application with COVID-19 Data -- 17 The Impact of the COVID-19 Pandemic on the Economies of European Countries in the Period January-September 2020 Based on Economic Indicators -- Abstract -- 1 Introduction -- 2 SARS-CoV-2 and Economies -- 3 Literature Review -- 4 Economic Indicators.
5 Methodology -- 6 Economic Situation in European Countries and COVID-19 -- 6.1 First Quarter -- 6.2 Second Quarter -- 6.3 Third Quarter -- 6.4 January-September 2020 -- 7 Conclusions -- References -- 18 Modelling the Risk of Foreign Divestment in the Visegrad Group Countries During the COVID-19 Pandemic -- Abstract -- 1 Introduction -- 2 Review of Literature -- 3 Research Methodology -- 4 Results of Empirical Research -- 4.1 Modelling of the Risk of Insignificant Foreign Divestment -- 4.2 Modelling of the Risk of Moderate Foreign Divestment -- 4.3 Modelling of the Risk of Considerable Foreign Divestment -- 5 Conclusions -- Acknowledgements -- References -- 19 Analysis of COVID-19 Dynamics in EU Countries Using the Dynamic Time Warping Method and ARIMA Models -- Abstract -- 1 Introduction -- 2 Research Methodology -- 3 Empirical Data -- 4 The Results of the DTW Method -- 5 The Results of the ARIMA Modeling -- 6 Conclusions -- References.
Record Nr. UNINA-9910488712803321
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Data Analysis with Machine Learning for Psychologists : Crash Course to Learn Python 3 and Machine Learning in 10 hours / / by Chandril Ghosh
Data Analysis with Machine Learning for Psychologists : Crash Course to Learn Python 3 and Machine Learning in 10 hours / / by Chandril Ghosh
Autore Ghosh Chandril
Edizione [1st ed. 2022.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022
Descrizione fisica 1 online resource (169 pages)
Disciplina 780
004.02415
Soggetto topico Psychology
Business - Data processing
Cognitive science
Mental health
Social sciences - Statistical methods
Psychology - Methodology
Behavioral Sciences and Psychology
Business Analytics
Cognitive Science
Mental Health
Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy
Psychological Methods
Psicologia
Processament de dades
Investigació
Metodologia de les ciències socials
Soggetto genere / forma Llibres electrònics
ISBN 9783031146343
9783031146336
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Introduction -- Step 1:Python Programming -- Step 2:Data Pre-Processing -- Step 3: Data Analysis with Machine Learning -- End Note. Python Programming -- Step 2:Data Pre-Processing -- Step 3: Data Analysis with Machine Learning -- End Note. Python Programming -- Step 2:Data Pre-Processing -- Step 3: Data Analysis with Machine Learning -- End Note. Python Programming -- Step 2:Data Pre-Processing -- Step 3: Data Analysis with Machine Learning -- End Note. Python Programming -- Step 2:Data Pre-Processing -- Step 3: Data Analysis with Machine Learning -- End Note. Python Programming -- Step 2:Data Pre-Processing -- Step 3: Data Analysis with Machine Learning -- End Note. Python Programming -- Step 2:Data Pre-Processing -- Step 3: Data Analysis with Machine Learning -- End Note. Python Programming -- Step 2:Data Pre-Processing -- Step 3: Data Analysis with Machine Learning -- End Note. Python Programming -- Step 2:Data Pre-Processing -- Step 3: Data Analysis with Machine Learning -- End Note. Python Programming -- Step 2:Data Pre-Processing -- Step 3: Data Analysis with Machine Learning -- End Note. Python Programming -- Step 2:Data Pre-Processing -- Step 3: Data Analysis with Machine Learning -- End Note. Python Programming -- Step 2:Data Pre-Processing -- Step 3: Data Analysis with Machine Learning -- End Note. Python Programming -- Step 2:Data Pre-Processing -- Step 3: Data Analysis with Machine Learning -- End Note. Python Programming -- Step 2:Data Pre-Processing -- Step 3: Data Analysis with Machine Learning -- End Note. Python Programming -- Step 2:Data Pre-Processing -- Step 3: Data Analysis with Machine Learning -- End Note. Python Programming -- Step 2:Data Pre-Processing -- Step 3: Data Analysis with Machine Learning -- End Note. Python Programming -- Step 2:Data Pre-Processing -- Step 3: Data Analysis with Machine Learning -- End Note. Python Programming -- Step 2:Data Pre-Processing -- Step 3: Data Analysis with Machine Learning -- End Note. .
Record Nr. UNINA-9910619273603321
Ghosh Chandril  
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Data analytics and artificial intelligence for inventory and supply chain management / / edited by Dinesh K. Sharma, Madhu Jain
Data analytics and artificial intelligence for inventory and supply chain management / / edited by Dinesh K. Sharma, Madhu Jain
Pubbl/distr/stampa Singapore : , : Springer, , [2022]
Descrizione fisica 1 online resource (293 pages)
Disciplina 260
Collana Inventory Optimization
Soggetto topico Business logistics - Data processing
Logística industrial
Processament de dades
Soggetto genere / forma Llibres electrònics
ISBN 981-19-6337-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Foreword -- Preface -- Acknowledgements -- About This Book -- Contents -- Editors and Contributors -- 1 Markov Decision Processes of a Two-Tier Supply Chain Inventory System -- 1.1 Markov Decision Processes of a Supply Chain -- 1.2 M/M1 + M2/1 /K-Rule/f1-policy Queues + Inventory Model with Backorders -- 1.2.1 The Stable M/M1 + M/1 /K-rule/f1-policy Model -- 1.3 Performance Measures for the Inventory-Queueing System -- 1.4 Results for the SCM Attached to M/M/1 Queues with Zero Lead Time -- 1.5 SCM Attached M/M1 + M2/1/K-rule/f2-Policy with Dissatisfied Customers -- 1.5.1 Optimum Order Quantity "Q*" -- 1.6 Conclusion -- References -- 2 Nature-Inspired Optimization for Inventory Models with Imperfect Production -- 2.1 Introduction -- 2.2 An Imperfect Production Inventory Model -- 2.3 Inventory Production Systems with Process Reliability -- 2.4 Nature-Inspired Optimization at a Glance -- 2.5 Important Contributions on Nature-Inspired Optimization for Inventory Control -- 2.6 Economic Production Quantity (EPQ) Models and NIO Algorithms -- 2.7 Conclusions -- References -- 3 A Multi-objective Mathematical Model for Socially Responsible Supply Chain Inventory Planning -- 3.1 Introduction -- 3.2 Literature Survey -- 3.3 Assumptions and Notation -- 3.4 Multi-objective Model -- 3.4.1 Objective Functions -- 3.4.2 Constraints Sets -- 3.5 Solution Methodology and Result -- 3.6 Conclusions -- References -- 4 Artificial Intelligence Computing and Nature-Inspired Optimization Techniques for Effective Supply Chain Management -- 4.1 Introduction -- 4.2 Basic Concepts of AI -- 4.2.1 Categorization of AI -- 4.3 Nature-Inspired Optimization (NIO) -- 4.4 Supply Chain Management -- 4.4.1 Two Echelon Supply Chain Inventory Model -- 4.5 Role of AI and NIO Algorithm in SCM -- 4.5.1 Artificial Neural Network -- 4.5.2 Adaptive Neuro-Fuzzy Inference System (ANFIS).
4.5.3 Inventory Control and Planning -- 4.5.4 Transportation Network Design -- 4.5.5 Purchasing and Supply Management -- 4.5.6 e-Synchronized SCM -- 4.6 Adapted Model Related to Operational Decisions in Supply Chain (SC) Network -- 4.7 Literature Survey on AI, NIO, and Supply Chain Management (SCM) -- 4.8 Research Directions for the Future and Closing Remarks -- References -- 5 An EPQ Model for Imperfect Production System with Deteriorating Items, Price-Dependent Demand, Rework and Lead Time Under Markdown Policy -- 5.1 Introduction -- 5.2 Literature Survey -- 5.3 Assumptions and Notations -- 5.3.1 Notations -- 5.3.2 Assumptions -- 5.4 Mathematical Model -- 5.5 Numerical Illustration -- 5.6 Conclusions -- References -- 6 Retrial Inventory-Queueing Model with Inspection Processes and Imperfect Production -- 6.1 Introduction -- 6.2 Model Description -- 6.3 Joint Probability Distributions -- 6.3.1 Governing Equations -- 6.3.2 Derivation of Joint Probability Distribution Function -- 6.4 System Performance Indices -- 6.5 Cost Optimization -- 6.6 Numerical Illustration and Sensitivity Analysis -- 6.7 Conclusions -- References -- 7 Inventory Model for Growing Items and Its Waste Management -- 7.1 Introduction -- 7.1.1 Literature Survey -- 7.1.2 Motivation -- 7.2 Mathematical Model and Analysis -- 7.3 Profit Function -- 7.4 Profit from Waste Management -- 7.5 Conclusions -- References -- 8 Pavement Cracks Inventory Survey with Machine Deep Learning Models -- 8.1 Introduction -- 8.2 Literature Survey -- 8.3 Technical Background -- 8.3.1 Convolution -- 8.3.2 Activation -- 8.3.3 Max Pooling -- 8.3.4 Flatten Layer -- 8.3.5 Fully Connected Layers -- 8.3.6 Classifcation -- 8.4 Experimental Work -- 8.5 Observations on the Results -- 8.6 Conclusion -- References -- 9 Decarbonisation Through Production of Rhino Bricks From the Waste Plastics: EPQ Model.
9.1 Introduction -- 9.2 Motivation and Problem Description -- 9.3 Notations -- 9.4 Assumptions -- 9.5 Model Formulation -- 9.6 Solution Procedure -- 9.7 Numerical Illustration -- 9.8 Sensitivity Analysis -- 9.9 Managerial Implications -- 9.10 Conclusions -- References -- 10 Cost Analysis of Supply Chain Model for Deteriorating Inventory Items with Shortages in Fuzzy Environment -- 10.1 Introduction -- 10.2 Assumptions and Notations -- 10.3 Development and Analysis of the Model in Crisp Form -- 10.4 Developing Model and Computing Its Solution by Using FP -- 10.5 System of Non-Linear Equations and Its Solution -- 10.6 Numerical Computing and Sensitivity Analysis -- 10.7 Conclusions -- References -- 11 Multi-echelon Inventory Planning in Supply Chain -- 11.1 Introduction -- 11.2 Literature Survey -- 11.3 Model Description -- 11.4 Expected Lead Time -- 11.5 Optimal Policy -- 11.6 Some Special Cases -- 11.7 Cost Minimization Analysis -- 11.8 Numerical Results -- 11.9 Conclusions -- References -- 12 Impact of Renewable Energy on a Flexible Production System Under Preorder and Online Payment Discount Facility -- 12.1 Introduction -- 12.2 Review of Literature -- 12.3 Notations and Assumptions -- 12.3.1 Notations -- 12.3.2 Assumptions -- 12.4 Mathematical Modeling -- 12.5 Solution Methodology -- 12.6 Numerical Illustration -- 12.7 Concavity -- 12.8 Sensitivity Analysis -- 12.9 Observation -- 12.10 Conclusion -- References -- 13 Impact of Preservation Technology Investment and Order Cost Reduction on an Inventory Model Under Different Carbon Emission Policies -- 13.1 Introduction -- 13.2 Literature Review -- 13.3 Notations and Assumptions -- 13.3.1 Notations -- 13.3.2 Assumptions -- 13.4 Mathematical Modeling -- 13.4.1 Profit Function Under Different Carbon Tax Regulations -- 13.5 Numerical Illustration -- 13.6 Concavity -- 13.7 Sensitivity Analysis.
13.8 Observations -- 13.9 Conclusion -- References -- 14 The Impact of Corporate Credibility on Inventory Management Decisions -- 14.1 Introduction -- 14.2 Literature Review -- 14.3 Objective of Study -- 14.4 Research Methodology -- 14.5 Discussion -- 14.5.1 Genetic Algorithm (NSGA-II) -- 14.5.2 Neural Algorithm -- 14.6 Conclusion -- References -- 15 A Bidirectional Neural Network Dynamic Inventory Control Model for Reservoir Operation -- 15.1 Introduction -- 15.2 Basics of Dynamic Inventory Control and Dynamic Reservoir Operations -- 15.3 Structure of the Bidirectional Recurrent Neural Network-Based Dynamic Inventory Control Model -- 15.4 Design of Neuro-Fuzzy Irrigation Reservoir Operation Using Bidirectional Recurrent Neural Network (BRNN) -- 15.4.1 Input Layer: Water Demand and Supply Analysis -- 15.4.2 Output Layer -- 15.4.3 Fuzzy Interface -- 15.4.4 Hidden Layer -- 15.5 Training and Validation of the Irrigation Model Using Data -- 15.5.1 Training -- 15.5.2 Evaluation of Model Performance -- 15.6 Conclusion -- References.
Record Nr. UNISA-996499871103316
Singapore : , : Springer, , [2022]
Materiale a stampa
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Data analytics and artificial intelligence for inventory and supply chain management / / edited by Dinesh K. Sharma, Madhu Jain
Data analytics and artificial intelligence for inventory and supply chain management / / edited by Dinesh K. Sharma, Madhu Jain
Pubbl/distr/stampa Singapore : , : Springer, , [2022]
Descrizione fisica 1 online resource (293 pages)
Disciplina 260
Collana Inventory Optimization
Soggetto topico Business logistics - Data processing
Logística industrial
Processament de dades
Soggetto genere / forma Llibres electrònics
ISBN 981-19-6337-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Foreword -- Preface -- Acknowledgements -- About This Book -- Contents -- Editors and Contributors -- 1 Markov Decision Processes of a Two-Tier Supply Chain Inventory System -- 1.1 Markov Decision Processes of a Supply Chain -- 1.2 M/M1 + M2/1 /K-Rule/f1-policy Queues + Inventory Model with Backorders -- 1.2.1 The Stable M/M1 + M/1 /K-rule/f1-policy Model -- 1.3 Performance Measures for the Inventory-Queueing System -- 1.4 Results for the SCM Attached to M/M/1 Queues with Zero Lead Time -- 1.5 SCM Attached M/M1 + M2/1/K-rule/f2-Policy with Dissatisfied Customers -- 1.5.1 Optimum Order Quantity "Q*" -- 1.6 Conclusion -- References -- 2 Nature-Inspired Optimization for Inventory Models with Imperfect Production -- 2.1 Introduction -- 2.2 An Imperfect Production Inventory Model -- 2.3 Inventory Production Systems with Process Reliability -- 2.4 Nature-Inspired Optimization at a Glance -- 2.5 Important Contributions on Nature-Inspired Optimization for Inventory Control -- 2.6 Economic Production Quantity (EPQ) Models and NIO Algorithms -- 2.7 Conclusions -- References -- 3 A Multi-objective Mathematical Model for Socially Responsible Supply Chain Inventory Planning -- 3.1 Introduction -- 3.2 Literature Survey -- 3.3 Assumptions and Notation -- 3.4 Multi-objective Model -- 3.4.1 Objective Functions -- 3.4.2 Constraints Sets -- 3.5 Solution Methodology and Result -- 3.6 Conclusions -- References -- 4 Artificial Intelligence Computing and Nature-Inspired Optimization Techniques for Effective Supply Chain Management -- 4.1 Introduction -- 4.2 Basic Concepts of AI -- 4.2.1 Categorization of AI -- 4.3 Nature-Inspired Optimization (NIO) -- 4.4 Supply Chain Management -- 4.4.1 Two Echelon Supply Chain Inventory Model -- 4.5 Role of AI and NIO Algorithm in SCM -- 4.5.1 Artificial Neural Network -- 4.5.2 Adaptive Neuro-Fuzzy Inference System (ANFIS).
4.5.3 Inventory Control and Planning -- 4.5.4 Transportation Network Design -- 4.5.5 Purchasing and Supply Management -- 4.5.6 e-Synchronized SCM -- 4.6 Adapted Model Related to Operational Decisions in Supply Chain (SC) Network -- 4.7 Literature Survey on AI, NIO, and Supply Chain Management (SCM) -- 4.8 Research Directions for the Future and Closing Remarks -- References -- 5 An EPQ Model for Imperfect Production System with Deteriorating Items, Price-Dependent Demand, Rework and Lead Time Under Markdown Policy -- 5.1 Introduction -- 5.2 Literature Survey -- 5.3 Assumptions and Notations -- 5.3.1 Notations -- 5.3.2 Assumptions -- 5.4 Mathematical Model -- 5.5 Numerical Illustration -- 5.6 Conclusions -- References -- 6 Retrial Inventory-Queueing Model with Inspection Processes and Imperfect Production -- 6.1 Introduction -- 6.2 Model Description -- 6.3 Joint Probability Distributions -- 6.3.1 Governing Equations -- 6.3.2 Derivation of Joint Probability Distribution Function -- 6.4 System Performance Indices -- 6.5 Cost Optimization -- 6.6 Numerical Illustration and Sensitivity Analysis -- 6.7 Conclusions -- References -- 7 Inventory Model for Growing Items and Its Waste Management -- 7.1 Introduction -- 7.1.1 Literature Survey -- 7.1.2 Motivation -- 7.2 Mathematical Model and Analysis -- 7.3 Profit Function -- 7.4 Profit from Waste Management -- 7.5 Conclusions -- References -- 8 Pavement Cracks Inventory Survey with Machine Deep Learning Models -- 8.1 Introduction -- 8.2 Literature Survey -- 8.3 Technical Background -- 8.3.1 Convolution -- 8.3.2 Activation -- 8.3.3 Max Pooling -- 8.3.4 Flatten Layer -- 8.3.5 Fully Connected Layers -- 8.3.6 Classifcation -- 8.4 Experimental Work -- 8.5 Observations on the Results -- 8.6 Conclusion -- References -- 9 Decarbonisation Through Production of Rhino Bricks From the Waste Plastics: EPQ Model.
9.1 Introduction -- 9.2 Motivation and Problem Description -- 9.3 Notations -- 9.4 Assumptions -- 9.5 Model Formulation -- 9.6 Solution Procedure -- 9.7 Numerical Illustration -- 9.8 Sensitivity Analysis -- 9.9 Managerial Implications -- 9.10 Conclusions -- References -- 10 Cost Analysis of Supply Chain Model for Deteriorating Inventory Items with Shortages in Fuzzy Environment -- 10.1 Introduction -- 10.2 Assumptions and Notations -- 10.3 Development and Analysis of the Model in Crisp Form -- 10.4 Developing Model and Computing Its Solution by Using FP -- 10.5 System of Non-Linear Equations and Its Solution -- 10.6 Numerical Computing and Sensitivity Analysis -- 10.7 Conclusions -- References -- 11 Multi-echelon Inventory Planning in Supply Chain -- 11.1 Introduction -- 11.2 Literature Survey -- 11.3 Model Description -- 11.4 Expected Lead Time -- 11.5 Optimal Policy -- 11.6 Some Special Cases -- 11.7 Cost Minimization Analysis -- 11.8 Numerical Results -- 11.9 Conclusions -- References -- 12 Impact of Renewable Energy on a Flexible Production System Under Preorder and Online Payment Discount Facility -- 12.1 Introduction -- 12.2 Review of Literature -- 12.3 Notations and Assumptions -- 12.3.1 Notations -- 12.3.2 Assumptions -- 12.4 Mathematical Modeling -- 12.5 Solution Methodology -- 12.6 Numerical Illustration -- 12.7 Concavity -- 12.8 Sensitivity Analysis -- 12.9 Observation -- 12.10 Conclusion -- References -- 13 Impact of Preservation Technology Investment and Order Cost Reduction on an Inventory Model Under Different Carbon Emission Policies -- 13.1 Introduction -- 13.2 Literature Review -- 13.3 Notations and Assumptions -- 13.3.1 Notations -- 13.3.2 Assumptions -- 13.4 Mathematical Modeling -- 13.4.1 Profit Function Under Different Carbon Tax Regulations -- 13.5 Numerical Illustration -- 13.6 Concavity -- 13.7 Sensitivity Analysis.
13.8 Observations -- 13.9 Conclusion -- References -- 14 The Impact of Corporate Credibility on Inventory Management Decisions -- 14.1 Introduction -- 14.2 Literature Review -- 14.3 Objective of Study -- 14.4 Research Methodology -- 14.5 Discussion -- 14.5.1 Genetic Algorithm (NSGA-II) -- 14.5.2 Neural Algorithm -- 14.6 Conclusion -- References -- 15 A Bidirectional Neural Network Dynamic Inventory Control Model for Reservoir Operation -- 15.1 Introduction -- 15.2 Basics of Dynamic Inventory Control and Dynamic Reservoir Operations -- 15.3 Structure of the Bidirectional Recurrent Neural Network-Based Dynamic Inventory Control Model -- 15.4 Design of Neuro-Fuzzy Irrigation Reservoir Operation Using Bidirectional Recurrent Neural Network (BRNN) -- 15.4.1 Input Layer: Water Demand and Supply Analysis -- 15.4.2 Output Layer -- 15.4.3 Fuzzy Interface -- 15.4.4 Hidden Layer -- 15.5 Training and Validation of the Irrigation Model Using Data -- 15.5.1 Training -- 15.5.2 Evaluation of Model Performance -- 15.6 Conclusion -- References.
Record Nr. UNINA-9910629299303321
Singapore : , : Springer, , [2022]
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Data analytics for cultural heritage : current trends and concepts / / Abdelhak Belhi [and three others] editors
Data analytics for cultural heritage : current trends and concepts / / Abdelhak Belhi [and three others] editors
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (288 pages)
Disciplina 363.69
Soggetto topico Cultural property - Data processing
Patrimoni cultural
Digitalització
Processament de dades
Aprenentatge automàtic
Soggetto genere / forma Llibres electrònics
ISBN 3-030-66777-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Foreword -- Preface -- Acknowledgment -- Contents -- About the Editors -- NoisyArt: Exploiting the Noisy Web for Zero-shot Classification and Artwork Instance Recognition -- 1 Introduction -- 2 Related Work -- 3 The NoisyArt Dataset -- 3.1 Data Sources -- 3.2 Data Collection -- 3.3 Discussion -- 4 Webly-Supervised Artwork Recognition -- 4.1 Baseline Classifier Model -- 4.2 Labelflip Noise -- 4.3 Entropy Scaling for Outlier Mitigation -- 4.4 Gradual Bootstrapping -- 4.5 Domain Shift Mitigation and L2 Normalization -- 5 Zero-Shot Artwork Recognition -- 5.1 Compatibility Models -- 5.2 Zero-shot Learning with Webly-Labeled Data -- 6 Experimental Results: Artwork Instance Recognition -- 6.1 Datasets -- 6.2 Webly-Supervised Classification -- 6.3 Identifying Problem Classes -- 7 Experimental Results: Zero-Shot Recognition -- 7.1 Zero-shot Recognition with Webly-Labeled Data -- 8 Conclusions and Future Work -- References -- Cultural Heritage Image Classification -- 1 Introduction -- 1.1 Artificial Neural Networks -- 2 CNN Architectures -- 3 Data and Methodology -- 3.1 Data -- 3.2 Methodology -- 3.3 Model Configuration -- 4 Results and Discussion -- References -- Study and Evaluation of Pre-trained CNN Networks for Cultural Heritage Image Classification -- 1 Introduction -- 2 Related Work -- 2.1 Feature Extraction Approaches -- 2.2 Feature Learning Approaches -- 3 The Cultural Heritage Image Classification Problem -- 3.1 Architectural Heritage Elements Dataset (AHE) -- 3.2 The WikiArt Dataset -- 4 The CNN-Based Pre-trained Networks -- 4.1 The Oxford Visual Geometry Group Models (VGG16 and VGG19) -- 4.2 Residual Networks -- 4.3 The Inception-V3 Model -- 5 Transfer Learning of the Pre-trained Networks to CH Image Classification -- 6 The Experimental Study -- 6.1 Experimental Setup -- 6.2 Experimental Results -- 6.3 Discussion -- 7 Conclusion.
References -- Visual Classification of Intangible Cultural Heritage Images in the Mekong Delta -- 1 Background and Purpose -- 2 Approach -- 2.1 Data Collection of Intangible Cultural Heritage Images -- 2.2 Visual Approaches for Classifying Intangible Cultural Heritage Images -- 3 Results -- 3.1 Tuning Parameters -- 3.2 Classification Results for 17 ICH Categories -- 4 Conclusions -- References -- Digital Image Inpainting Techniques for Cultural Heritage Preservation and Restoration -- 1 Introduction -- 1.1 The Importance of Inpainting in Cultural Heritage -- 1.2 The Image Inpainting Problem -- 2 Interpolation -- 3 Digital Image Inpainting Methods -- 3.1 Diffusion-Based Methods -- 3.2 Texture Synthesis-Based Inpainting -- 3.3 Exemplar-Based Methods -- 3.4 Hybrid Inpainting Methods -- 3.5 Semiautomatic and Fast Inpainting Technique -- 3.6 Deep Learning-Based Technique -- 3.6.1 CNN-Based Inpainting Method -- 3.6.2 GAN-Based Inpainting Method -- 4 A Two-Stage Method for CH Digital Image Inpainting -- 5 Results and Comparisons -- 6 Conclusion -- References -- Crowd Source Framework for Indian Digital Heritage Space -- 1 Introduction -- 2 Crowd Source Framework for IHDS -- 3 Data Preprocessing -- 3.1 Redundancy Removal -- 3.2 Blur Removal -- 3.3 Super-Resolution -- 3.3.1 GAN Network Architecture -- 3.3.2 Generator Network -- 3.3.3 Discriminator Network -- 3.3.4 Perceptual Loss Function -- 4 Classification -- 4.1 Deep Neural Network -- 4.2 MobileNet Architecture -- 4.3 Transfer Learning -- 5 Results -- 5.1 IHDS Dataset -- 5.2 Blur Removal -- 5.3 Super-Resolution -- 5.3.1 Training Details -- 5.4 Transfer Learning Classification Results -- 5.5 Screenshots of Framework Working (GUI) -- 6 Conclusions -- References -- A Robust Method for Text, Line, and Word Segmentation for Historical Arabic Manuscripts -- 1 Introduction -- 2 Related Works.
2.1 Text Segmentation Methods -- 2.2 Line Segmentation Methods -- 2.3 Word Segmentation Methods -- 3 Proposed Method -- 3.1 Texture Component Extraction -- 3.2 Encoder-Decoder Architecture -- 3.3 Line Segmentation -- 3.3.1 Smoothing -- 3.4 Word Segmentation -- 3.4.1 The Smoothed Generalized Chamfer Distance -- 3.4.2 Classification of Inter/intra-Word Distances -- 3.5 Classification of Beginning and Ending of Words -- 3.6 Classification of First and Last Characters -- 4 Experimental Results -- 4.1 Datasets -- 4.2 Metrics -- 4.3 Analysis -- 5 Conclusion -- References -- Aesthetical Issues with Stochastic Evaluation -- 1 Introduction -- 1.1 Aesthetical Issues and Mathematics -- 1.2 Aesthetical Issues and Stochastic Analysis -- 2 Methodology -- 2.1 Stochastic Analysis in 2D -- 2.2 Illustration of Stochastic Analysis in 2D -- 3 Examples of Stochastic Analysis -- 3.1 Range of Fluctuations in Groups of Images -- 3.1.1 Data Analysis -- 3.1.2 Evaluation -- 3.2 Evaluation of Urban and Natural Landscapes Transformed by Technological and Civil Infrastructure through Climacogram Subtraction -- 3.2.1 Data Analysis -- 3.2.2 Evaluation -- 3.3 Qualitative Evaluation Aspect of Climacogram Curves -- 3.3.1 Data Analysis -- 4 Conclusions -- References -- 3D Visual Interaction for Cultural Heritage Sector -- 1 Introduction -- 2 Human-Computer Interaction -- 3 Visual Interaction in Cultural Heritage -- 4 Human-Computer Gesture Recognition -- 5 Hand Gesture Visual Processing Techniques -- 5.1 Hand Detection -- 5.1.1 3D Modelling -- 5.1.2 Pixel Values -- 5.1.3 Shape -- 5.1.4 Skin Colour -- 5.2 Hand Tracking -- 5.2.1 Estimation Based -- 5.2.2 Template Based -- 5.3 Gesture Recognition -- 6 Product Markets of Vision-Based Sensing Devices -- 6.1 Microsoft Kinect -- 6.2 Leap Motion Controller -- 7 Software Development Environments -- 7.1 Unity 3D -- 7.2 OpenCV.
8 Proposed Approach -- 8.1 Data Acquisition -- 8.2 Data Pre-processing -- 8.2.1 Motion Interpolation -- 8.2.2 Super-Resolution -- 8.3 Photogrammetry -- 8.4 3D Model Adaptation -- 8.5 3D Model Visualisation -- 8.6 3D Interaction -- 9 Evaluation Work and Discussion -- 9.1 Evaluation Methodology -- 9.2 Results and Discussions -- 10 Summary and Conclusions -- References -- Retrieving Visually Linked Digitized Paintings -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 4 Experiment -- 4.1 Time Period Classification -- 4.2 Link Retrieval -- 5 Conclusion -- References -- Named Entity Recognition for Cultural Heritage Preservation -- 1 Introduction -- 1.1 Natural Language Processing in Cultural Heritage Domain -- 2 Named Entity Recognition -- 2.1 NER Process -- 2.2 NER Approaches -- 2.2.1 Rule-Based Approaches -- 2.2.2 Machine Learning Approaches -- 2.2.3 Deep Learning Approaches -- 2.3 Pre-trained NER Tools -- 2.4 Performance Measures for NER -- 3 Named Entity Recognition in Cultural Heritage Domain and Historical Texts -- 4 Discussion -- 4.1 NLP Challenges in Cultural Heritage Domain -- 4.1.1 Lack of Consistent Orthography -- 4.1.2 Solution Methods -- 5 Conclusion -- References -- Index.
Record Nr. UNINA-9910484619103321
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
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Data cultures in higher education : emergent practices and the challenge ahead / / Juliana E. Raffaghelli and Albert Sangrà
Data cultures in higher education : emergent practices and the challenge ahead / / Juliana E. Raffaghelli and Albert Sangrà
Autore Raffaghelli Juliana E.
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham, Switzerland : , : Springer International Publishing, , [2023]
Descrizione fisica 1 online resource (389 pages)
Disciplina 378.17344678
Collana Higher Education Dynamics
Soggetto topico Education, Higher - Data processing
Education, Higher - Planning
Educació superior
Processament de dades
Soggetto genere / forma Llibres electrònics
ISBN 3-031-24193-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto INTRODUCTION -- Chap 1. Data Cultures in higher education: acknowledging complexity -- Chap 2. Data, Society and the University: facets of a complex problem -- FIRST PART -- Exploring reactive data epistemologies in HE and the Society -- Chap 3. Fair learning analytics: design, participation and trans-discipline in the techno-structure -- Chap 4. Beyond just metrics: for a renewed approach to assessment in higher education -- Chap 5. “We used to have fun but then data came into play...”: Social media at the crossroads between big data and digital literacy issues -- SECOND PART: -- Exploring proactive data epistemologies in HE and the Society -- Chap 6. Why does open data get underused? A focus on the role of (open) data literacy -- Chap 7. Responsible Educational Technology Research: From Open Science and Open Data to Ethics and Trustworthy Learning Analytics -- Chap 8. Exploring possible worlds: open and participatory tools for critical data literacy and fairer data culture -- THIRD PART -- The challenge ahead -- Chap 9. Toward an ethics of classroom tools: Educating educators for data literacy -- Chap 10. How to integrate data culture in HE: A teaching experience in a Digital competence course -- Chap 11. Teaching Data That Matters: History and Practice -- Chap 12. Critical data literacy in higher education: teaching and research for data ethics and justice -- Chap 13. How stakeholders’ data literacy contributes to quality in higher education: a goal-oriented analysis -- Chap 14. Data centres in the university. From tools to symbols of power and transformation -- Chap 15. Conclusion: Building Fair Data Cultures in Higher Education -- AFTERWORD -- Chap 16. For: Data Cultures in Higher Education: Emergent Practices and the Challenge Ahead.
Record Nr. UNINA-9910682588603321
Raffaghelli Juliana E.  
Cham, Switzerland : , : Springer International Publishing, , [2023]
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Data Driven Model Learning for Engineers : With Applications to Univariate Time Series / / by Guillaume Mercère
Data Driven Model Learning for Engineers : With Applications to Univariate Time Series / / by Guillaume Mercère
Autore Mercère Guillaume
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (X, 212 p. 93 illus., 54 illus. in color.)
Disciplina 519.55
620.00151955
Soggetto topico Time-series analysis
Machine learning
Statistics
Time Series Analysis
Statistical Learning
Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences
Enginyeria
Models matematics
Processament de dades
Anàlisi de sèries temporals
Soggetto genere / forma Llibres electrònics
ISBN 3-031-31636-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910741194703321
Mercère Guillaume  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Materiale a stampa
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