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Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries [[electronic resource] ] : 7th International Workshop, BrainLes 2021, Held in Conjunction with MICCAI 2021, Virtual Event, September 27, 2021, Revised Selected Papers, Part I / / edited by Alessandro Crimi, Spyridon Bakas
| Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries [[electronic resource] ] : 7th International Workshop, BrainLes 2021, Held in Conjunction with MICCAI 2021, Virtual Event, September 27, 2021, Revised Selected Papers, Part I / / edited by Alessandro Crimi, Spyridon Bakas |
| Autore | Crimi Alessandro |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham, : Springer Nature, 2022 |
| Descrizione fisica | 1 online resource (XXI, 489 p. 171 illus., 134 illus. in color.) |
| Disciplina | 006.37 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Computer vision
Artificial intelligence Computer engineering Computer networks Application software Computer Vision Artificial Intelligence Computer Engineering and Networks Computer and Information Systems Applications |
| Soggetto non controllato |
artificial intelligence
bioinformatics computer science computer systems computer vision education image analysis image processing image segmentation learning machine learning medical images neural networks pattern recognition segmentation methods software design software engineering software quality validation verification and validation |
| ISBN | 3-031-08999-5 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Supervoxel Merging towards Brain Tumor Segmentation -- Challenging Current Semi-Supervised Anomaly Segmentation Methods for Brain MRI -- Modeling multi-annotator uncertainty as multi-class segmentation problem -- Modeling multi-annotator uncertainty as multi-class segmentation problem -- Adaptive unsupervised learning with enhanced feature representation for intra-tumor partitioning and survival prediction for glioblastoma -- Predicting isocitrate dehydrogenase mutation status in glioma using structural brain networks and graph neural networks -- Optimization of Deep Learning based Brain Extraction in MRI for Low Resource Environments. Reciprocal Adversarial Learning for Brain Tumor Segmentation: A Solution to BraTS Challenge 2021 Segmentation Task -- Unet3D with Multiple Atrous Convolutions Attention Block for Brain Tumor Segmentation -- BRATS2021: exploring each sequence in multi-modal input for baseline U-net performance -- Automatic Brain Tumor Segmentation using Multi-scale Features and Attention Mechanism -- Simple and Fast Convolutional Neural Network applied to median cross sections for predicting the presence of MGMT promoter methylation in FLAIR MRI scans -- MSViT: Multi Scale Vision Transformer forBiomedical Image Segmentation -- Unsupervised Multimodal -- HarDNet-BTS: A Harmonic Shortcut Network for Brain Tumor Segmentation -- Multimodal Brain Tumor Segmentation Algorithm -- Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images -- Multi-plane UNet++ Ensemble for Glioblastoma Segmentation -- Multimodal Brain Tumor Segmentation using Modified UNet Architecture -- A video data based transfer learning approach for classification of MGMT status in brain tumor MR images -- Multimodal Brain Tumor Segmentation Using a 3D ResUNet in BraTS 2021 -- 3D MRI brain tumour segmentation with autoencoder regularization and Hausdorff distance loss function -- 3D CMM-Net with Deeper Encoder for Semantic Segmentation of Brain Tumors in BraTS2021 Challenge -- Cascaded training pipeline for 3D brain tumor segmentation -- nnU-Net with Region-based Training and Loss Ensembles for Brain Tumor Segmentation -- Brain Tumor Segmentation Using Attention Activated U-Net with Positive Mining -- Automatic segmentation of brain tumor using 3D convolutional neural networks -- Hierarchical and Global Modality Interaction for Brain Tumor Segmentation -- Ensemble Outperforms Single Models in Brain Tumor Segmentation -- Brain Tumor Segmentation using UNet-Context Encoding Network -- Ensemble CNN Networks for GBM Tumors Segmentation using Multi-parametric MRI. |
| Record Nr. | UNISA-996483157303316 |
Crimi Alessandro
|
||
| Cham, : Springer Nature, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries : 7th International Workshop, BrainLes 2021, Held in Conjunction with MICCAI 2021, Virtual Event, September 27, 2021, Revised Selected Papers, Part I / / edited by Alessandro Crimi, Spyridon Bakas
| Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries : 7th International Workshop, BrainLes 2021, Held in Conjunction with MICCAI 2021, Virtual Event, September 27, 2021, Revised Selected Papers, Part I / / edited by Alessandro Crimi, Spyridon Bakas |
| Autore | Crimi Alessandro |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham, : Springer Nature, 2022 |
| Descrizione fisica | 1 online resource (XXI, 489 p. 171 illus., 134 illus. in color.) |
| Disciplina |
006.37
616.8 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Computer vision
Artificial intelligence Computer engineering Computer networks Application software Computer Vision Artificial Intelligence Computer Engineering and Networks Computer and Information Systems Applications |
| Soggetto non controllato |
artificial intelligence
bioinformatics computer science computer systems computer vision education image analysis image processing image segmentation learning machine learning medical images neural networks pattern recognition segmentation methods software design software engineering software quality validation verification and validation |
| ISBN | 3-031-08999-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Supervoxel Merging towards Brain Tumor Segmentation -- Challenging Current Semi-Supervised Anomaly Segmentation Methods for Brain MRI -- Modeling multi-annotator uncertainty as multi-class segmentation problem -- Modeling multi-annotator uncertainty as multi-class segmentation problem -- Adaptive unsupervised learning with enhanced feature representation for intra-tumor partitioning and survival prediction for glioblastoma -- Predicting isocitrate dehydrogenase mutation status in glioma using structural brain networks and graph neural networks -- Optimization of Deep Learning based Brain Extraction in MRI for Low Resource Environments. Reciprocal Adversarial Learning for Brain Tumor Segmentation: A Solution to BraTS Challenge 2021 Segmentation Task -- Unet3D with Multiple Atrous Convolutions Attention Block for Brain Tumor Segmentation -- BRATS2021: exploring each sequence in multi-modal input for baseline U-net performance -- Automatic Brain Tumor Segmentation using Multi-scale Features and Attention Mechanism -- Simple and Fast Convolutional Neural Network applied to median cross sections for predicting the presence of MGMT promoter methylation in FLAIR MRI scans -- MSViT: Multi Scale Vision Transformer forBiomedical Image Segmentation -- Unsupervised Multimodal -- HarDNet-BTS: A Harmonic Shortcut Network for Brain Tumor Segmentation -- Multimodal Brain Tumor Segmentation Algorithm -- Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images -- Multi-plane UNet++ Ensemble for Glioblastoma Segmentation -- Multimodal Brain Tumor Segmentation using Modified UNet Architecture -- A video data based transfer learning approach for classification of MGMT status in brain tumor MR images -- Multimodal Brain Tumor Segmentation Using a 3D ResUNet in BraTS 2021 -- 3D MRI brain tumour segmentation with autoencoder regularization and Hausdorff distance loss function -- 3D CMM-Net with Deeper Encoder for Semantic Segmentation of Brain Tumors in BraTS2021 Challenge -- Cascaded training pipeline for 3D brain tumor segmentation -- nnU-Net with Region-based Training and Loss Ensembles for Brain Tumor Segmentation -- Brain Tumor Segmentation Using Attention Activated U-Net with Positive Mining -- Automatic segmentation of brain tumor using 3D convolutional neural networks -- Hierarchical and Global Modality Interaction for Brain Tumor Segmentation -- Ensemble Outperforms Single Models in Brain Tumor Segmentation -- Brain Tumor Segmentation using UNet-Context Encoding Network -- Ensemble CNN Networks for GBM Tumors Segmentation using Multi-parametric MRI. |
| Record Nr. | UNINA-9910585786203321 |
|
Crimi Alessandro
|
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| Cham, : Springer Nature, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
C++ Programming Fundamentals
| C++ Programming Fundamentals |
| Autore | Malhotra D |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | New York : , : Mercury Learning & Information, , 2022 |
| Descrizione fisica | 1 online resource (289 pages) |
| Disciplina | 005.133 |
| Altri autori (Persone) | MalhotraN |
| Soggetto topico | COMPUTERS / Programming Languages / C++ |
| Soggetto non controllato |
AI
arrays computer science developers embedded systems file handling game design pointers polymorphism programming video game |
| ISBN |
1-68392-974-8
1-68392-975-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Title -- Copyright -- Contents -- Preface -- Acknowledgments -- Chapter 1 C++ and Beyond -- Introduction -- 1.1 The Origin of C++ -- 1.2 Why Use C++? -- 1.3 Various Programming Paradigms -- 1.3.1 Structural Programming -- 1.3.2 Procedural Programming -- 1.3.3 Object Oriented Programming -- 1.4 C++ Basics -- 1.4.1 Variables -- 1.4.2 Data Types -- 1.4.3 Data Modifiers -- 1.t C++ Execution Flow -- Summary -- Exercises -- Theory Questions -- MCQ-Based -- Practical Application -- References -- Books -- Websites -- Chapter 2 Basic Play in C++ -- 2.1 Literals, Constants, and Qualifiers -- 2.2 Stream-Based IO -- 2.3 Comments -- 2.4 Operators and Types -- 2.4.1 Types of Operators in C++ -- 2.5 Type Conversion -- 2.6 Keywords -- 2.7 Loops in C++ -- 2.9 Control Statements -- 2.9 Defining Functions -- 2.9.1 Why Use Functions? -- 2.10 C vs. C++ -- Summary -- Exercises -- Theory Questions -- MCQ-Based -- Practical Questions -- References -- Books -- Websites -- Chapter 3 Arrays and Strings -- 3.1 What is an Array? -- 3.1.1 Ways to Declare Arrays -- 3.1.2 Ways to Access Array Members -- 3.1.3 Traversing a 1D Array -- 3.2 Operations on an Array -- 3.2.1 Passing an Array to Functions -- 3.2.2 Finding the Length -- 3.2.3 Enum in C++ -- 3.2.4 Searching -- 3.3 Multi-Dimensional Array -- 3.4 Strings -- 3.5 String Functions -- Summary -- Exercises -- Theory Questions -- MCQ-Based -- Practical Questions -- References -- Books -- Websites -- Chapter 4 Pointers in C++ -- 4.1 Introduction -- 4.2 Pointers: Declaration and Initialization -- 4.3 Casting and Passing Pointers -- 4.3.1 Typecasting -- 4.3.2 Passing -- 4.4 Using Pointers with Arrays -- 4.5 Pointer Use -- Summary -- Exercises -- Theory Questions -- Practical Questions -- MCQ-Based -- References -- Books -- Websites -- Chapter 5 Classes in C++ -- 5.1 Class Making.
5.2 Constructors and Destructors -- 5.3 The This Pointer -- 5.4 Class Methods -- 5.5 The static Keyword -- 5.6 Memory Management and Garbage Collection in C++ -- Summary -- Exercises -- Theory Questions -- Practical Questions -- MCQ-Based -- References -- Books -- Websites -- Chapter 6 Inheritance -- 6.1 Introduction -- 6.2 Inheritance -- 6.2.1 Access Specifiers -- 6.2.2 Inheritance Modes -- 6.3 Types of Inheritance -- 6.4 Constructor Calling -- 6.5 Implementing Inheritance -- Summary -- Exercises -- Theory Questions -- Practial Questions -- MCQ-Based -- References -- Books -- Websites -- Chapter 7 Polymorphism -- 7.1 Introduction -- 7.2 Dynamic vs. Static Binding -- 7.3 Interface and Implementation -- 7.4 Function Overriding and Overloading -- 7.5 Friend and Generic Functions -- 7.5.1 Friend Functions -- 7.5.2 Generic Functions -- 7.6 Namespaces -- Summary -- Exercises -- Theory Questions -- Practical Questions -- MCQ-Based -- References -- Books -- Websites -- Chapter 8 Operator Overloading -- 8.1 Basics -- 8.2 How to Overload an Operator? -- 8.3 Overloading Unary Operators -- 8.4 Overloading Binary Operators -- 8.5 Overloading by Friend Function -- Summary -- Exercises -- Theory Questions -- Practical Questions -- MCQ-Based -- References -- Books -- Websites -- Chapter 9 Structure and Union -- 9.1 Structure: Declaration and Definition -- 9.2 Accessing a Structure -- 9.3 Union -- 9.4 Differences Between Structure and Union -- 9.5 Enum in C++ -- Summary -- Exercises -- Theory Questions -- Practical Questions -- MCQ-Based -- References -- Books -- Websites -- Chapter 10 Exception Handling -- 10.1 Errors and Exceptions -- 10.2 Exception Handling -- 10.3 Various Exceptions -- 10.4 Custom Exceptions in C++ -- Summary -- Exercises -- Theory Questions -- Practical Questions -- MCQ-Based -- References -- Books -- Websites -- Chapter 11 File Handling. 11.1 Files and Streams -- 11.2 File Operations -- 11.3 Random Access and Object Serialization -- Summary -- Exercises -- Theory Questions -- Practical Questions -- MCQ-Based -- References -- Books -- Websites -- Index. |
| Record Nr. | UNINA-9910838375803321 |
|
Malhotra D
|
||
| New York : , : Mercury Learning & Information, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Computer aided verification : 34th International Conference, CAV 2022, Haifa, Israel, August 7-10, 2022, proceedings . Part II. / / editors, Sharon Shoham, Yakir Vizel
| Computer aided verification : 34th International Conference, CAV 2022, Haifa, Israel, August 7-10, 2022, proceedings . Part II. / / editors, Sharon Shoham, Yakir Vizel |
| Autore | Shoham Sharon |
| Pubbl/distr/stampa | Cham, : Springer Nature, 2022 |
| Descrizione fisica | 1 online resource (560 pages) : illustrations (black and white) |
| Altri autori (Persone) | VizelYakir |
| Collana | Lecture notes in computer science |
| Soggetto topico | Computer software - Verification |
| Soggetto non controllato |
architecting
architecture verification and validation artificial intelligence computer programming computer science computer systems databases distributed computer systems embedded systems engineering formal languages formal logic linguistics mathematics model checking software architecture software design software engineering software quality theoretical computer science |
| ISBN | 3-031-13188-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910586580503321 |
|
Shoham Sharon
|
||
| Cham, : Springer Nature, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Computer aided verification : 34th International Conference, CAV 2022, Haifa, Israel, August 7-10, 2022, proceedings . Part II. / / editors, Sharon Shoham, Yakir Vizel
| Computer aided verification : 34th International Conference, CAV 2022, Haifa, Israel, August 7-10, 2022, proceedings . Part II. / / editors, Sharon Shoham, Yakir Vizel |
| Autore | Shoham Sharon |
| Pubbl/distr/stampa | Cham, : Springer Nature, 2022 |
| Descrizione fisica | 1 online resource (560 pages) : illustrations (black and white) |
| Altri autori (Persone) | VizelYakir |
| Collana | Lecture notes in computer science |
| Soggetto topico | Computer software - Verification |
| Soggetto non controllato |
architecting
architecture verification and validation artificial intelligence computer programming computer science computer systems databases distributed computer systems embedded systems engineering formal languages formal logic linguistics mathematics model checking software architecture software design software engineering software quality theoretical computer science |
| ISBN | 3-031-13188-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996485664103316 |
|
Shoham Sharon
|
||
| Cham, : Springer Nature, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Computer aided verification : 34th International Conference, CAV 2022, Haifa, Israel, August 7-10, 2022, proceedings . Part I. / / editors, Sharon Shoham, Yakir Vizel
| Computer aided verification : 34th International Conference, CAV 2022, Haifa, Israel, August 7-10, 2022, proceedings . Part I. / / editors, Sharon Shoham, Yakir Vizel |
| Autore | Shoham Sharon |
| Pubbl/distr/stampa | Cham, : Springer Nature, 2022 |
| Descrizione fisica | 1 online resource (563 pages) : illustrations (black and white) |
| Disciplina | 005.14 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico | Computer software - Verification |
| Soggetto non controllato |
architecting
architecture verification and validation artificial intelligence computer programming computer science computer systems distributed computer systems distributed systems embedded systems formal logic mathematics model checking programming languages software architecture software design software engineering software quality theoretical computer science verification verification and validation |
| ISBN | 3-031-13185-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996485664203316 |
|
Shoham Sharon
|
||
| Cham, : Springer Nature, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Computer aided verification : 34th International Conference, CAV 2022, Haifa, Israel, August 7-10, 2022, proceedings . Part I. / / editors, Sharon Shoham, Yakir Vizel
| Computer aided verification : 34th International Conference, CAV 2022, Haifa, Israel, August 7-10, 2022, proceedings . Part I. / / editors, Sharon Shoham, Yakir Vizel |
| Autore | Shoham Sharon |
| Pubbl/distr/stampa | Cham, : Springer Nature, 2022 |
| Descrizione fisica | 1 online resource (563 pages) : illustrations (black and white) |
| Disciplina | 005.14 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico | Computer software - Verification |
| Soggetto non controllato |
architecting
architecture verification and validation artificial intelligence computer programming computer science computer systems distributed computer systems distributed systems embedded systems formal logic mathematics model checking programming languages software architecture software design software engineering software quality theoretical computer science verification verification and validation |
| ISBN | 3-031-13185-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910586580203321 |
|
Shoham Sharon
|
||
| Cham, : Springer Nature, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Computer Science and Engineering Education for Pre-collegiate Students and Teachers
| Computer Science and Engineering Education for Pre-collegiate Students and Teachers |
| Autore | Burrows Andrea |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (142 p.) |
| Soggetto non controllato |
secondary science
STEM outreach mathematics (STEM) education environmental radioactivity learner analysis coaching learner-centered pedagogy preservice teacher beliefs computer science education laboratory activity science education challenge-based learning engineering K–12 teacher literature review pre-collegiate teacher scintillator detector computing outreach science computer science application pre-college engineering activities K-12 teachers engineering design process ?-ray spectroscopy student engagement in-situ measurements conceptual assessment items engineering education Web-GIS platform K–12 computer science engineering outreach online professional development training pre-college STEM activities Android app students’ alternative conceptions technology inquiry-based science and technology computer science integration assessment tool perceptions pre-college computing activities nuclear engineering experiment conceptual change NGSS physics education engineering design technology |
| ISBN | 3-03897-941-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910346689903321 |
|
Burrows Andrea
|
||
| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Data Science for IoT Engineers : A Systems Analytics Approach
| Data Science for IoT Engineers : A Systems Analytics Approach |
| Autore | Madhavan P. G |
| Pubbl/distr/stampa | Bloomfield : , : Mercury Learning & Information, , 2021 |
| Descrizione fisica | 1 online resource (170 pages) |
| Disciplina | 006.312024004678 |
| Soggetto topico | COMPUTERS / Desktop Applications / Presentation Software |
| Soggetto non controllato |
IOT
MATLAB computer science data analytics engineering mathematics physics |
| ISBN |
1-68392-640-4
1-68392-641-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Frontmatter -- Contents -- Preface -- About the Author -- PART I Machine Learning from Multiple Perspectives -- CHAPTER 1 Overview of Data Science -- CHAPTER 2 Introduction to Machine Learning -- CHAPTER 3 Systems Theory, Linear Algebra, and Analytics Basics -- CHAPTER 4 “Modern” Machine Learning -- PART II Systems Analytics -- CHAPTER 5 Systems Theory Foundations of Machine Learning -- CHAPTER 6 State Space Model and Bayes Filter -- CHAPTER 7 The Kalman Filter for Adaptive Machine Learning -- CHAPTER 8 The Need for Dynamical Machine Learning: The Bayesian Exact Recursive Estimation -- CHAPTER 9 Digital Twins -- Epilogue A New Random Field Theory -- Index |
| Record Nr. | UNINA-9910795555703321 |
|
Madhavan P. G
|
||
| Bloomfield : , : Mercury Learning & Information, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Data Science for IoT Engineers : A Systems Analytics Approach
| Data Science for IoT Engineers : A Systems Analytics Approach |
| Autore | Madhavan P. G |
| Pubbl/distr/stampa | Bloomfield : , : Mercury Learning & Information, , 2021 |
| Descrizione fisica | 1 online resource (170 pages) |
| Disciplina | 006.312024004678 |
| Soggetto topico | COMPUTERS / Desktop Applications / Presentation Software |
| Soggetto non controllato |
IOT
MATLAB computer science data analytics engineering mathematics physics |
| ISBN |
1-68392-640-4
1-68392-641-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Frontmatter -- Contents -- Preface -- About the Author -- PART I Machine Learning from Multiple Perspectives -- CHAPTER 1 Overview of Data Science -- CHAPTER 2 Introduction to Machine Learning -- CHAPTER 3 Systems Theory, Linear Algebra, and Analytics Basics -- CHAPTER 4 “Modern” Machine Learning -- PART II Systems Analytics -- CHAPTER 5 Systems Theory Foundations of Machine Learning -- CHAPTER 6 State Space Model and Bayes Filter -- CHAPTER 7 The Kalman Filter for Adaptive Machine Learning -- CHAPTER 8 The Need for Dynamical Machine Learning: The Bayesian Exact Recursive Estimation -- CHAPTER 9 Digital Twins -- Epilogue A New Random Field Theory -- Index |
| Record Nr. | UNINA-9910810050903321 |
|
Madhavan P. G
|
||
| Bloomfield : , : Mercury Learning & Information, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
