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AI Assisted Business Analytics : Techniques for Reshaping Competitiveness / / by Joseph Boffa
| AI Assisted Business Analytics : Techniques for Reshaping Competitiveness / / by Joseph Boffa |
| Autore | Boffa Joseph |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (133 pages) |
| Disciplina |
300.727
658.4012 |
| Soggetto topico |
Statistics
Stochastic models Multivariate analysis Statistics in Business, Management, Economics, Finance, Insurance Stochastic Modelling in Statistics Multivariate Analysis Planificació empresarial Planificació estratègica Processament de dades Intel·ligència artificial Aplicacions industrials Competència econòmica |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-031-40821-7 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Business Prosperity -- Analytics Case Studies -- Statistical Audit Design -- The Sales Tax Audit -- Forensic Accounting Using Benford Formula -- Financial Projections -- Planning Expenses and Investments -- Market Research. |
| Record Nr. | UNINA-9910755079503321 |
Boffa Joseph
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Bayesian Network Modeling of Corrosion / / edited by Narasi Sridhar
| Bayesian Network Modeling of Corrosion / / edited by Narasi Sridhar |
| Autore | Sridhar Narasi |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (343 pages) |
| Disciplina | 620.11223 |
| Altri autori (Persone) | Sridhar |
| Soggetto topico |
Corrosion and anti-corrosives
Statistics Stochastic models Surfaces (Technology) Thin films Coatings Corrosion Bayesian Network Stochastic Modelling in Statistics Surfaces, Interfaces and Thin Film |
| ISBN | 9783031561283 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter1. Introduction: Risk Assessment -- Chapter.2. Bayesian Network Basics -- Chaoter.3. Corrosion Models -- Chapter.4. Statistical Models: Propagation of Uncertainty and Monte Carlo modeling -- Chapter.5. Corrosion Risk Assessment in Pipelines -- Chapter.6. Oil and Gas Production Systems -- Chapter.7.Nuclear Energy -- Chapter.8. Localized Corrosion in Saline Environments -- Chapter.9. BN for reinforced concrete structures -- Chapter.10.Coatings -- Chapter.11.Summary and Future. |
| Record Nr. | UNINA-9910869156003321 |
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Sridhar Narasi
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Closure Properties for Heavy-Tailed and Related Distributions : An Overview / / by Remigijus Leipus, Jonas Šiaulys, Dimitrios Konstantinides
| Closure Properties for Heavy-Tailed and Related Distributions : An Overview / / by Remigijus Leipus, Jonas Šiaulys, Dimitrios Konstantinides |
| Autore | Leipus Remigijus |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (99 pages) |
| Disciplina | 519.24 |
| Altri autori (Persone) |
SiaulysJonas
KonstantinidesDimitrios |
| Collana | SpringerBriefs in Statistics |
| Soggetto topico |
Probabilities
Distribution (Probability theory) Stochastic models Actuarial science Applied Probability Distribution Theory Probability Theory Stochastic Modelling in Statistics Actuarial Mathematics Distribució (Teoria de la probabilitat) |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-031-34553-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Acronyms -- 1 Introduction -- 1.1 An Overview of the Book -- 1.2 Notations and Definitions -- 2 Heavy-Tailed and Related Classes of Distributions -- 2.1 Heavy-Tailed Distributions -- 2.2 Regularly Varying Distributions -- 2.3 Consistently Varying Distributions -- 2.4 Dominatedly Varying Distributions -- 2.5 Long-Tailed Distributions -- 2.6 Exponential-Like-Tailed Distributions -- 2.7 Generalized Long-Tailed Distributions -- 2.8 Subexponential Distributions -- 2.9 Strong Subexponential Distributions -- 2.10 Convolution Equivalent Distributions -- 2.11 Generalized Subexponential Distributions -- 2.12 Bibliographical Notes -- 3 Closure Properties Under Tail-Equivalence, Convolution, Finite Mixing, Maximum, and Minimum -- 3.1 Ruin Probability in the Cramér-Lundberg Risk Model in the Case of Heavy-Tailed Claims -- 3.2 Convolution Closure and Max-Sum Equivalence -- 3.3 Closure Properties for Heavy-Tailed Class of Distributions -- 3.4 Closure Properties for Regularly Varying Class of Distributions -- 3.5 Closure Properties for Consistently Varying Class of Distributions -- 3.6 Closure Properties for Dominatedly Varying Class of Distributions -- 3.7 Closure Properties for Long-Tailed Class of Distributions -- 3.8 Closure Properties for Exponential-Like-Tailed Class of Distributions -- 3.9 Closure Properties for Generalized Long-Tailed Class of Distributions -- 3.10 Closure Properties for Subexponential Class of Distributions -- 3.11 Closure Properties for Strong Subexponential Class of Distributions -- 3.12 Closure Properties for Convolution Equivalent Class of Distributions -- 3.13 Closure Properties for Generalized Subexponential Class of Distributions -- 3.14 Bibliographical Notes -- 4 Convolution-Root Closure -- 4.1 Distribution Classes Closed Under Convolution Roots.
4.2 Distribution Classes Not Closed Under Convolution Roots -- 4.3 Bibliographical Notes -- 5 Product-Convolution of Heavy-Tailed and Related Distributions -- 5.1 Product-Convolution -- 5.2 From Light Tails to Heavy Tails Through Product-Convolution -- 5.3 Product-Convolution Closure Properties for Heavy-Tailed Class of Distributions -- 5.4 Product-Convolution Closure Properties for Regularly Varying Class of Distributions -- 5.5 Product-Convolution Closure Properties for Consistently Varying Class of Distributions -- 5.6 Product-Convolution Closure Properties for Dominatedly Varying Class of Distributions -- 5.7 Product-Convolution Closure Properties for Exponential-Like-Tailed Distributions -- 5.8 Product-Convolution Closure Properties for Generalized Long-Tailed Class of Distributions -- 5.9 Product-Convolution Closure Properties for Convolution Equivalent Class of Distributions -- 5.10 Product-Convolution Closure Properties for Generalized Subexponential Class of Distributions -- 5.11 Some Extensions -- 5.12 Bibliographical Notes -- 6 Summary of Closure Properties -- References -- Index. |
| Record Nr. | UNINA-9910746099003321 |
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Leipus Remigijus
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Practical Applications of Stochastic Modelling [[electronic resource] ] : 11th International Workshop, PASM 2022, Alicante, Spain, September 23, 2022, Revised Selected Papers / / edited by Matthew Forshaw, Katja Gilly, William Knottenbelt, Nigel Thomas
| Practical Applications of Stochastic Modelling [[electronic resource] ] : 11th International Workshop, PASM 2022, Alicante, Spain, September 23, 2022, Revised Selected Papers / / edited by Matthew Forshaw, Katja Gilly, William Knottenbelt, Nigel Thomas |
| Autore | Forshaw Matthew |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (140 pages) |
| Disciplina | 519.2 |
| Collana | Communications in Computer and Information Science |
| Soggetto topico |
Stochastic models
Stochastic processes Application software Stochastic Modelling in Statistics Stochastic Modelling Stochastic Networks Computer and Information Systems Applications |
| ISBN | 3-031-44053-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Performance modelling of attack graphs -- Towards Calculating the Resilience of a Urban Transport Network under Attack -- Analysis of the Battery Level in Complex Wireless Sensor Networks using a Two Time Scales Second Order Fluid Model -- To Confine or not to Confine: A Mean Field Game Analysis of the End of an Epidemic -- Data Center Organization and Optimization Strategy as a k-ary n-cube Topology -- Towards energy-aware management of shared printers -- Modelling Performance and Fairness of Frame Bursting in IEEE 802.11n using PEPA. |
| Record Nr. | UNISA-996558570603316 |
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Forshaw Matthew
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Practical Applications of Stochastic Modelling : 11th International Workshop, PASM 2022, Alicante, Spain, September 23, 2022, Revised Selected Papers / / edited by Matthew Forshaw, Katja Gilly, William Knottenbelt, Nigel Thomas
| Practical Applications of Stochastic Modelling : 11th International Workshop, PASM 2022, Alicante, Spain, September 23, 2022, Revised Selected Papers / / edited by Matthew Forshaw, Katja Gilly, William Knottenbelt, Nigel Thomas |
| Autore | Forshaw Matthew |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (140 pages) |
| Disciplina | 519.2 |
| Collana | Communications in Computer and Information Science |
| Soggetto topico |
Stochastic models
Stochastic processes Application software Stochastic Modelling in Statistics Stochastic Modelling Stochastic Networks Computer and Information Systems Applications |
| ISBN | 3-031-44053-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Performance modelling of attack graphs -- Towards Calculating the Resilience of a Urban Transport Network under Attack -- Analysis of the Battery Level in Complex Wireless Sensor Networks using a Two Time Scales Second Order Fluid Model -- To Confine or not to Confine: A Mean Field Game Analysis of the End of an Epidemic -- Data Center Organization and Optimization Strategy as a k-ary n-cube Topology -- Towards energy-aware management of shared printers -- Modelling Performance and Fairness of Frame Bursting in IEEE 802.11n using PEPA. |
| Record Nr. | UNINA-9910746965903321 |
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Forshaw Matthew
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Statistical Modeling and Simulation for Experimental Design and Machine Learning Applications [[electronic resource] ] : Selected Contributions from SimStat 2019 and Invited Papers / / edited by Jürgen Pilz, Viatcheslav B. Melas, Arne Bathke
| Statistical Modeling and Simulation for Experimental Design and Machine Learning Applications [[electronic resource] ] : Selected Contributions from SimStat 2019 and Invited Papers / / edited by Jürgen Pilz, Viatcheslav B. Melas, Arne Bathke |
| Autore | Pilz Jürgen |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (265 pages) |
| Disciplina | 519.57 |
| Altri autori (Persone) |
MelasViatcheslav B
BathkeArne |
| Collana | Contributions to Statistics |
| Soggetto topico |
Statistics
Mathematical statistics - Data processing Experimental design Machine learning Stochastic models Statistical Theory and Methods Statistics and Computing Design of Experiments Machine Learning Applied Statistics Stochastic Modelling in Statistics |
| ISBN | 3-031-40055-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Part I Invited Papers -- 1 Likelihood Ratios in Forensics: What They Are and What They Are Not -- 1.1 Introduction -- 1.2 Lindley's Likelihood Ratio (LLR) -- 1.2.1 Notations -- 1.2.2 A Frequentist Framework for Lindley's Likelihood Ratio (LLR) -- 1.3 Score-Based Likelihood Ratio (SLR) -- 1.3.1 The Expression of the SLR -- 1.3.2 The Glass Example -- 1.4 Discussion -- References -- 2 MANOVA for Large Number of Treatments -- 2.1 Introduction -- 2.2 Notations and Model Setup -- 2.3 Simulations -- 2.3.1 MANOVA Tests for Large g -- 2.3.2 Special Case: ANOVA for Large g -- 2.4 Discussion and Outlook -- References -- 3 Pollutant Dispersion Simulation by Means of a Stochastic Particle Model and a Dynamic Gaussian Plume Model -- 3.1 Introduction -- 3.2 Meteorological Monitoring Network -- 3.3 Wind Field Modeling -- 3.3.1 Mass Correction of the Wind Field -- 3.3.2 Plume Rise -- 3.4 Stochastic Particle Model -- 3.4.1 Deposition -- 3.4.2 Implementation -- 3.5 Dynamic Gaussian Plume Model -- 3.6 Implementation on the Server -- 3.7 A Real-World Example with Application to an Alpine Valley -- 3.8 Conclusions and Outlook -- References -- 4 On an Alternative Trigonometric Strategy for StatisticalModeling -- 4.1 Introduction -- 4.2 The Alternative Sine Distribution -- 4.2.1 Presentation -- 4.2.2 Moment Properties -- 4.2.3 Parametric Extensions -- 4.3 AS Generated Family -- 4.3.1 Definition -- 4.3.2 Series Expansions -- 4.3.3 Example: The ASE Exponential Distribution -- 4.3.4 Moment Properties -- 4.4 Application to a Famous Cancer Data -- 4.5 Conclusion -- References -- Part II Design of Experiments -- 5 Incremental Construction of Nested Designs Basedon Two-Level Fractional Factorial Designs -- 5.1 Introduction -- 5.2 Greedy Coffee-House Design -- 5.3 Two-Level Fractional Factorial Designs -- 5.3.1 Half Fractions: m=1.
5.3.2 Several Generators -- 5.3.2.1 Defining Relations -- 5.3.2.2 Resolution -- 5.3.2.3 Word Length Pattern -- 5.3.3 Minimum Size -- 5.4 Two-Level Factorial Designs and Error-Correcting Codes -- 5.4.1 Definitions and Properties -- 5.4.2 Examples -- 5.5 Maximin Distance Properties of Two-Level Factorial Designs -- 5.5.1 Neighbouring Pattern and Distant Site Pattern -- 5.5.2 Optimal Selection of Generators by Simulated Annealing -- 5.5.2.1 SA Algorithm for the Maximisation of ρH -- 5.6 Covering Properties of Two-Level Factorial Designs -- 5.6.1 Bounds on CRH(Xn) -- 5.6.2 Calculation of CRH(Xn) -- 5.6.2.1 Algorithmic Construction of a Lower Bound on CRH(Xn) -- 5.7 Greedy Constructions Based on Fractional Factorial Designs -- 5.7.1 Base Designs -- 5.7.2 Rescaled Designs -- 5.7.3 Projection Properties -- 5.8 Summary and Future Work -- Appendix -- References -- 6 A Study of L-Optimal Designs for the Two-Dimensional Exponential Model -- 6.1 Introduction -- 6.2 Equivalence Theorem for L-Optimal Designs -- 6.3 General Case -- 6.4 Excess and Saturated Designs -- References -- 7 Testing for Randomized Block Single-Case Designsby Combined Permutation Tests with Multivariate Mixed Data -- 7.1 Introduction -- 7.2 Randomized Block Single-Case Designs and NPC -- 7.3 Simulation Study -- 7.4 A Real Case Study -- 7.5 Conclusions -- References -- 8 Adaptive Design Criteria Motivated by a Plug-In Percentile Estimator -- 8.1 Introduction -- 8.2 Problem Formulation and Background -- 8.2.1 Problem Formulation -- 8.2.2 Background -- 8.3 The Plug-In Estimator -- 8.4 Adaptive ``Plug-In'' Criteria -- 8.4.1 Monte Carlo Approximation -- 8.4.2 Monte Carlo Approximation Assuming Independency -- 8.4.3 Assuming Independency and Neglecting Uncertainty -- 8.4.4 Using SUR Design Criterion for Exceedance Probability -- 8.5 Numerical Implementation -- 8.6 Numerical Study. 8.6.1 Comparison Study -- 8.6.2 Methodology -- 8.6.2.1 Case Studies -- 8.6.2.2 Performance Indicators -- 8.6.3 Numerical Results -- 8.6.3.1 Estimators Performance -- 8.6.3.2 Implementation -- 8.6.3.3 Criteria -- 8.7 Conclusions -- Appendix 1 -- Posterior Mean and Variance of f Under the Gaussian Process Assumption -- SUR Design Criteria for Exceedance Probability Estimation -- Appendix 2 -- References -- Part III Queueing and Inventory Analysis -- 9 On a Parametric Estimation for a Convolutionof Exponential Densities -- 9.1 Introduction -- 9.2 Convolution of the Exponential Densities -- 9.3 ML Estimation of the Parameters -- 9.4 Parameter's Estimation by the Moments' Method -- 9.5 Approximation of the Density -- 9.6 Experimental Study -- 9.7 Application to a Single Queueing System M/G/1/k -- 9.8 Conclusions -- References -- 10 Statistical Estimation with a Known Quantileand Its Application in a Modified ABC-XYZ Analysis -- 10.1 Introduction -- 10.2 Methods -- 10.2.1 Statistical Estimation with a Known Quantile -- 10.2.2 ABC-XYZ Analysis -- 10.3 ABC-XYZ Analysis Modified with a Known Quantile -- 10.4 Conclusions -- References -- Part IV Machine Learning and Applications -- 11 A Study of Design of Experiments and Machine Learning Methods to Improve Fault Detection Algorithms -- 11.1 Introduction -- 11.2 Design of Experiments and Machine Learning Modelling -- 11.3 Application to Fault Detection -- 11.3.1 Design of Experiments Step -- 11.3.2 Machine Learning Modelling Step -- 11.3.2.1 Refrigerant Undercharge: Fault Detection -- 11.3.2.2 Condenser Fouling: Fault Detection -- 11.4 Conclusions -- References -- 12 Microstructure Image Segmentation Using Patch-Based Clustering Approach -- 12.1 Introduction -- 12.2 Input Data -- 12.3 Previous Work -- 12.4 Grain Segmentation -- 12.4.1 Seeded Region Growing (SRG) -- 12.4.2 Image Denoising and Patch Determination. 12.4.3 Feature Extraction -- 12.4.4 Patch Clustering -- 12.4.5 Implementation -- 12.5 Results -- 12.6 Conclusion and Outlook -- References -- 13 Clustering and Symptom Analysis in Binary Datawith Application -- 13.1 Introduction -- 13.2 The Symptom Analysis -- 13.2.1 The Symptom and Syndrome Definition -- 13.2.2 Impulse Vector and Super-symptoms -- 13.2.3 Prefigurations of Super-symptom -- 13.2.4 The Super-symptom Recovery by Vector β -- 13.2.5 Clustering in Dichotomous Space and Symptom Analysis -- 13.3 The Medical Application of the Clustering and Symptom Analysis in Binary Data -- 13.3.1 Dataset -- 13.3.2 Result and Discussion -- 13.4 Conclusion -- References -- 14 Big Data for Credit Risk Analysis: Efficient Machine Learning Models Using PySpark -- 14.1 Introduction -- 14.2 Data Processing -- 14.2.1 Data Treatment -- 14.2.2 Data Storage and Distribution -- 14.2.3 Munge Data -- 14.2.4 Creating New Measures -- 14.2.5 Missing Values Imputation and Outliers Treatment -- 14.2.6 One-Hot Code and Dummy Variables -- 14.2.7 Final Dataset -- 14.3 Method and Models -- 14.3.1 Method -- 14.3.2 Model Building -- 14.4 Results and Credit Scorecard Conversion -- 14.5 Conclusion -- Appendix 1 -- Appendix 2 -- References. |
| Record Nr. | UNINA-9910754092903321 |
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Pilz Jürgen
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Stochastic Dynamic Response and Stability of Ships and Offshore Platforms / / by Yingguang Wang
| Stochastic Dynamic Response and Stability of Ships and Offshore Platforms / / by Yingguang Wang |
| Autore | Wang Yingguang |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (368 pages) |
| Disciplina | 799 |
| Collana | Ocean Engineering & Oceanography |
| Soggetto topico |
Mechanics, Applied
Mechanical engineering Stochastic models Engineering Mechanics Mechanical Engineering Stochastic Modelling in Statistics |
| ISBN | 981-9958-53-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1 Introduction -- Chapter 2 State of the art -- Chapter 3 The Monte Carlo simulation method -- Chapter 4 The numerical path integral solution method -- Chapter 5 The global geometric method -- Chapter 6 The first passage theory -- Chapter 7 Concluding remarks. |
| Record Nr. | UNINA-9910760300203321 |
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Wang Yingguang
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| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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