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Aligned carbon nanotubes : physics, concepts, fabrication and devices / / Zhifeng Ren, Yucheng Lan, Yang Wang
| Aligned carbon nanotubes : physics, concepts, fabrication and devices / / Zhifeng Ren, Yucheng Lan, Yang Wang |
| Autore | Ren Zhifeng |
| Edizione | [1st ed. 2013.] |
| Pubbl/distr/stampa | Berlin, : Springer, 2013 |
| Descrizione fisica | 1 online resource (309 p.) |
| Disciplina | 620.5 |
| Altri autori (Persone) |
LanYucheng
WangYang |
| Collana | Nanoscience and technology |
| Soggetto topico |
Carbon
Nanotubes Nanostructured materials |
| ISBN |
1-283-63032-X
9786613942777 3-642-30490-7 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction to Carbon -- Introduction to Carbon Nanotubes -- Growth Techniques of Carbon Nanotubes -- Chemical Vapor Deposition of Carbon Nanotubes -- Physics of Direct Current Plasma-Enhanced Chemical Vapor Deposition -- Technologies to Achieve Carbon Nanotube Alignment -- Measurement Techniques of Aligned Carbon Nanotubes -- Properties and Applications of Aligned Carbon Nanotube Arrays -- Potential Applications of Carbon Nanotube Arrays. |
| Record Nr. | UNINA-9910437822403321 |
Ren Zhifeng
|
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| Berlin, : Springer, 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Data science . Part I : 8th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2022, Chengdu, China, August 19-22, 2022 : proceedings / / Yang Wang [and five others], editors
| Data science . Part I : 8th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2022, Chengdu, China, August 19-22, 2022 : proceedings / / Yang Wang [and five others], editors |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (455 pages) |
| Disciplina | 005.7 |
| Collana | Communications in Computer and Information Science |
| Soggetto topico |
Big data
Data mining |
| ISBN | 981-19-5194-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- Big Data Mining and Knowledge Management -- Self-attention Based Multimodule Fusion Graph Convolution Network for Traffic Flow Prediction -- 1 Introduction -- 2 Spatiotemporal Prediction in Deep Learning -- 2.1 Time Correlation Research -- 2.2 Time Correlation Research -- 3 Prediction Model of Traffic Flow Based on Multi-module Fusion -- 3.1 Model Frame Diagram -- 3.2 Space-Time Decoupling -- 3.3 Spatial Convolution -- 3.4 Spatial Self-attention -- 3.5 Temporal Convolution -- 3.6 Time Self-attention -- 3.7 Information Fusion and GRU -- 4 Experimental Analysis -- 4.1 Dataset -- 4.2 Analysis of Results -- 5 Conclusion -- References -- Data Analyses and Parallel Optimization of the Tropical-Cyclone Coupled Numerical Model -- 1 Introduction -- 1.1 A Subsection Sample -- 2 Model Setup -- 2.1 Atmospheric Model Setup -- 2.2 Hydrodynamic Model Setup -- 2.3 Ocean Wave Model Setup -- 2.4 HPC Facilities -- 2.5 Coupled Variables -- 3 Scaling Experiments -- 3.1 Parallel Tests Analysis -- 3.2 SWAN Model Parallel Algorithm Optimization -- 3.3 Ocean Model Grid Optimization -- 4 Parallel Test Results -- 5 Model Results Discussion -- 6 Conclusion -- References -- Factorization Machine Based on Bitwise Feature Importance for CTR Prediction -- 1 Introduction -- 2 Related Work -- 3 Our Approach -- 3.1 Embedding Layer -- 3.2 Learning -- 4 Experiments -- 4.1 Experimental Settings -- 4.2 Hyperparameter Study -- 4.3 Ablation Study -- 4.4 Performance Comparison -- 5 Conclusion -- References -- Focusing on the Importance of Features for CTR Prediction -- 1 Introduction -- 2 ECABiNet Model -- 2.1 Sparse Input and Embedding Layer -- 2.2 Layer Norm -- 2.3 ECANET Layer -- 2.4 Feature Cross Layer -- 2.5 DNN Layer -- 2.6 Output -- 3 Experiment -- 3.1 Experimental Setup.
3.2 LayerNorm Effect Comparison -- 3.3 Comparison of the Effects of Different Attention Modules -- 3.4 Comparison of the Classic Model -- 3.5 Study HyperParameter -- 4 Related Work -- 5 Conclusions -- References -- Active Anomaly Detection Technology Based on Ensemble Learning -- 1 Introduction -- 2 Problem Statement -- 3 Proposed Model -- 3.1 Supervised Ensemble Learning Model -- 3.2 Human Participation -- 3.3 Model Self-training -- 3.4 Experiment -- 3.5 Conclusion -- References -- Automatic Generation of Graduation Thesis Comments Based on Multilevel Analysis -- 1 Introduction -- 2 Technical Principle -- 2.1 BERT Model Introduced -- 2.2 Basic Structure of the BERT Model -- 2.3 Comparison with Other Algorithms -- 3 Project Analysis -- 3.1 Technical Route -- 3.2 Technical Analysis -- 4 Project Implementation -- 4.1 Database Established Modification -- 4.2 Student Information Input -- 4.3 Neural Network Training -- 4.4 Automatically Generate Comments -- 5 Conclusion -- References -- A Survey of Malware Classification Methods Based on Data Flow Graph -- 1 Introduction -- 2 Data Flow Graph -- 2.1 Basic Concepts of the Data Flow Graph -- 2.2 Data Flow Graph Corresponding to Common APIs -- 2.3 Extension of Data Flow Graphs -- 3 Malware Classification Based on Data Flow Graph -- 3.1 User-Defined Data Flow Graph Feature-based Malware Classification -- 3.2 Data Flow Graph Similarity-Based Malware Classification -- 3.3 Graph Neural Network-Based Malware Classification -- 4 Discussion -- 5 Conclusion -- References -- Anomaly Detection of Multivariate Time Series Based on Metric Learning -- 1 Introduction -- 2 Preliminaries -- 3 Proposed Model -- 3.1 Preprocessing -- 3.2 Encoder for High-Dimensional Time Series Data -- 3.3 Attentional Center Learning -- 3.4 Loss Function -- 3.5 Semisupervised Learning -- 4 Experiments -- 4.1 Dataset -- 4.2 Setup -- 4.3 Result. 5 Conclusion -- References -- Social Network Analysis of Coauthor Networks in Inclusive Finance in China -- 1 Introduction and Motivation -- 2 Data Collection and Preprocessing -- 3 Results -- 3.1 General Characteristics of the Coauthor Network -- 3.2 Ego Characteristics of the Coauthor Network -- 3.3 The Evolution of Cohesive Subgroups in the Coauthor Network -- 4 Conclusions -- References -- Multirelationship Aware Personalized Recommendation Model -- 1 Introduction -- 2 Preliminary Preparation -- 2.1 Problem Definition -- 2.2 Data Preprocessing -- 2.3 User Relationship Graphs -- 3 Modeling and Training -- 3.1 MrAPR Model -- 3.2 Model Training -- 4 Experiment -- 4.1 Dataset -- 4.2 Baselines and Evaluation Metrics -- 4.3 Parameter Settings -- 4.4 Ablation Experiments -- 5 Conclusion -- References -- Machine Learning for Data Science -- Preliminary Study on Adapting ProtoPNet to Few-Shot Learning Using MAML -- 1 Introduction -- 2 Related Work -- 2.1 Few-Shot Learning -- 2.2 Interpretability -- 3 Proposed Methods -- 3.1 Adapting ProtoPNet to MAML -- 3.2 Evaluating Models -- 4 Experiments -- 4.1 Datasets -- 4.2 Experiment 1: Omniglot Few-Shot Classification -- 4.3 Experiment 2: MiniImagenet Few-Shot Classification -- 4.4 Experiment 3: Interpretability Analysis on Omngilot -- 4.5 Experiment 4: Preliminary Interpretability Analysis on MiniImagenet -- 5 Conclusion and Future Work -- References -- A Preliminary Study of Interpreting CNNs Using Soft Decision Trees -- 1 Introduction -- 2 Related Work -- 3 Proposed Methods -- 3.1 Model Foundations -- 3.2 Using Normal/Soft Decision Trees to Interpret CNNs -- 3.3 Evaluating Interpretability -- 4 Experiments -- 4.1 Dataset and Experimental Setup -- 4.2 Experiment 1: Classification Performance -- 4.3 Experiment 2: Visualization of Normal/Soft Decision Trees' Top Features. 4.4 Experiment 3: Interpretability Performance -- 4.5 Experiment 4: Scores of Human Experts on Tag Clarity -- 5 Conclusion and Future Work -- References -- Deep Reinforcement Learning with Fuse Adaptive Weighted Demonstration Data -- 1 Introduction -- 2 Related Work -- 2.1 Deep Reinforcement Learning -- 2.2 Multiagent Reinforcement Learning -- 3 Methods -- 4 Experimental Results and Analysis -- 4.1 Experimental Environment and Data -- 4.2 Results and Analysis -- 5 Discussion -- References -- DRIB: Interpreting DNN with Dynamic Reasoning and Information Bottleneck -- 1 Introduction -- 2 Related Works -- 2.1 Explain the Existing Deep Learning Models -- 2.2 Construction of Interpretable Deep Learning Models -- 3 Method -- 3.1 Dynamic Reasoning Decision Module -- 3.2 Information Bottleneck Verification Module -- 4 Experiments -- 4.1 Experimental Settings -- 4.2 Interpretability of Calculation in Dynamic Reasoning Decision -- 4.3 Explainability of Attribution in the Information Bottleneck -- 4.4 Visualization of Understandability -- 5 Conclusion -- References -- Multimedia Data Management and Analysis -- Advanced Generative Adversarial Network for Image Superresolution -- 1 Introduction -- 2 Related Work -- 3 GAN and SRGAN -- 4 Proposed Method -- 4.1 Generator Network Structure -- 4.2 Discriminator Network Structure -- 4.3 Loss Function -- 5 Experiment Results and Analysis -- 5.1 Implementation Details -- 5.2 Datasets and Evaluation Metrics -- 5.3 Experimental Results and Analysis -- 5.4 Ablation Study -- 6 Conclusions -- References -- Real-World Superresolution by Using Deep Degradation Learning -- 1 Introduction -- 2 Related Work -- 2.1 Real-World Superresolution -- 2.2 Contrastive Learning -- 3 PurPosed Method -- 3.1 Overview of the Unsupervised Framework -- 3.2 Degradation Model -- 3.3 Reconstruction Model -- 4 Experiments -- 4.1 Training Data. 4.2 Training Details -- 4.3 Training Details -- 5 Conclusion -- References -- Probability Loop Closure Detection with Fisher Kernel Framework for Visual SLAM -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Fisher Vector Generation -- 3.2 Probability Visual Vocabulary -- 3.3 Loop Closure Detection -- 4 Results and Discussion -- 4.1 Dataset and Preprocessing -- 4.2 Evaluation Metrics -- 4.3 2D Motion -- 4.4 3D Motion -- 4.5 Bidirectional Loops -- 4.6 Ablation Study -- 5 Conclusions -- References -- A Complex Background Image Registration Method Based on the Optical Flow Field Algorithm -- 1 Introduction -- 2 The Proposed Method -- 3 Evaluation Functions -- 4 Experimental Results -- 5 Conclusion -- References -- Collaborative Learning Method for Natural Image Captioning -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 P2PM: Pix2Pix Inverting Module -- 3.2 NLGM: Natural Language Generation Module -- 3.3 Collaborative Learning Framework -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Main Results -- 5 Conclusion -- References -- Visual Analysis of the National Characteristics of the COVID-19 Vaccine Based on Knowledge Graph -- 1 Introduction -- 2 Related Studies -- 3 Construction of the COVID-19 Vaccine Knowledge Graph -- 3.1 Data Acquisition -- 3.2 Entity Extraction to Construct a Relational Model -- 3.3 Knowledge Graph Establishment -- 4 Visual Analysis of the National Characteristics of the COVID-19 Vaccine -- 5 Conclusions and Recommendations -- References -- Speech Recognition for Parkinson's Disease Based on Improved Genetic Algorithm and Data Enhancement Technology -- 1 Introduction -- 2 The Proposed Methods -- 2.1 Method -- 3 Speech Recognition and Diagnosis -- 3.1 Data Preprocessing -- 3.2 Improved GA-SVM Model -- 3.3 Speech Recognition Algorithm -- 4 Experiment and Evaluation -- 4.1 Experiment Setup. 4.2 Comparison and Analysis of Results. |
| Record Nr. | UNINA-9910586578803321 |
| Singapore : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Data science . Part I : 8th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2022, Chengdu, China, August 19-22, 2022 : proceedings / / Yang Wang [and five others], editors
| Data science . Part I : 8th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2022, Chengdu, China, August 19-22, 2022 : proceedings / / Yang Wang [and five others], editors |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (455 pages) |
| Disciplina | 005.7 |
| Collana | Communications in Computer and Information Science |
| Soggetto topico |
Big data
Data mining |
| ISBN | 981-19-5194-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- Big Data Mining and Knowledge Management -- Self-attention Based Multimodule Fusion Graph Convolution Network for Traffic Flow Prediction -- 1 Introduction -- 2 Spatiotemporal Prediction in Deep Learning -- 2.1 Time Correlation Research -- 2.2 Time Correlation Research -- 3 Prediction Model of Traffic Flow Based on Multi-module Fusion -- 3.1 Model Frame Diagram -- 3.2 Space-Time Decoupling -- 3.3 Spatial Convolution -- 3.4 Spatial Self-attention -- 3.5 Temporal Convolution -- 3.6 Time Self-attention -- 3.7 Information Fusion and GRU -- 4 Experimental Analysis -- 4.1 Dataset -- 4.2 Analysis of Results -- 5 Conclusion -- References -- Data Analyses and Parallel Optimization of the Tropical-Cyclone Coupled Numerical Model -- 1 Introduction -- 1.1 A Subsection Sample -- 2 Model Setup -- 2.1 Atmospheric Model Setup -- 2.2 Hydrodynamic Model Setup -- 2.3 Ocean Wave Model Setup -- 2.4 HPC Facilities -- 2.5 Coupled Variables -- 3 Scaling Experiments -- 3.1 Parallel Tests Analysis -- 3.2 SWAN Model Parallel Algorithm Optimization -- 3.3 Ocean Model Grid Optimization -- 4 Parallel Test Results -- 5 Model Results Discussion -- 6 Conclusion -- References -- Factorization Machine Based on Bitwise Feature Importance for CTR Prediction -- 1 Introduction -- 2 Related Work -- 3 Our Approach -- 3.1 Embedding Layer -- 3.2 Learning -- 4 Experiments -- 4.1 Experimental Settings -- 4.2 Hyperparameter Study -- 4.3 Ablation Study -- 4.4 Performance Comparison -- 5 Conclusion -- References -- Focusing on the Importance of Features for CTR Prediction -- 1 Introduction -- 2 ECABiNet Model -- 2.1 Sparse Input and Embedding Layer -- 2.2 Layer Norm -- 2.3 ECANET Layer -- 2.4 Feature Cross Layer -- 2.5 DNN Layer -- 2.6 Output -- 3 Experiment -- 3.1 Experimental Setup.
3.2 LayerNorm Effect Comparison -- 3.3 Comparison of the Effects of Different Attention Modules -- 3.4 Comparison of the Classic Model -- 3.5 Study HyperParameter -- 4 Related Work -- 5 Conclusions -- References -- Active Anomaly Detection Technology Based on Ensemble Learning -- 1 Introduction -- 2 Problem Statement -- 3 Proposed Model -- 3.1 Supervised Ensemble Learning Model -- 3.2 Human Participation -- 3.3 Model Self-training -- 3.4 Experiment -- 3.5 Conclusion -- References -- Automatic Generation of Graduation Thesis Comments Based on Multilevel Analysis -- 1 Introduction -- 2 Technical Principle -- 2.1 BERT Model Introduced -- 2.2 Basic Structure of the BERT Model -- 2.3 Comparison with Other Algorithms -- 3 Project Analysis -- 3.1 Technical Route -- 3.2 Technical Analysis -- 4 Project Implementation -- 4.1 Database Established Modification -- 4.2 Student Information Input -- 4.3 Neural Network Training -- 4.4 Automatically Generate Comments -- 5 Conclusion -- References -- A Survey of Malware Classification Methods Based on Data Flow Graph -- 1 Introduction -- 2 Data Flow Graph -- 2.1 Basic Concepts of the Data Flow Graph -- 2.2 Data Flow Graph Corresponding to Common APIs -- 2.3 Extension of Data Flow Graphs -- 3 Malware Classification Based on Data Flow Graph -- 3.1 User-Defined Data Flow Graph Feature-based Malware Classification -- 3.2 Data Flow Graph Similarity-Based Malware Classification -- 3.3 Graph Neural Network-Based Malware Classification -- 4 Discussion -- 5 Conclusion -- References -- Anomaly Detection of Multivariate Time Series Based on Metric Learning -- 1 Introduction -- 2 Preliminaries -- 3 Proposed Model -- 3.1 Preprocessing -- 3.2 Encoder for High-Dimensional Time Series Data -- 3.3 Attentional Center Learning -- 3.4 Loss Function -- 3.5 Semisupervised Learning -- 4 Experiments -- 4.1 Dataset -- 4.2 Setup -- 4.3 Result. 5 Conclusion -- References -- Social Network Analysis of Coauthor Networks in Inclusive Finance in China -- 1 Introduction and Motivation -- 2 Data Collection and Preprocessing -- 3 Results -- 3.1 General Characteristics of the Coauthor Network -- 3.2 Ego Characteristics of the Coauthor Network -- 3.3 The Evolution of Cohesive Subgroups in the Coauthor Network -- 4 Conclusions -- References -- Multirelationship Aware Personalized Recommendation Model -- 1 Introduction -- 2 Preliminary Preparation -- 2.1 Problem Definition -- 2.2 Data Preprocessing -- 2.3 User Relationship Graphs -- 3 Modeling and Training -- 3.1 MrAPR Model -- 3.2 Model Training -- 4 Experiment -- 4.1 Dataset -- 4.2 Baselines and Evaluation Metrics -- 4.3 Parameter Settings -- 4.4 Ablation Experiments -- 5 Conclusion -- References -- Machine Learning for Data Science -- Preliminary Study on Adapting ProtoPNet to Few-Shot Learning Using MAML -- 1 Introduction -- 2 Related Work -- 2.1 Few-Shot Learning -- 2.2 Interpretability -- 3 Proposed Methods -- 3.1 Adapting ProtoPNet to MAML -- 3.2 Evaluating Models -- 4 Experiments -- 4.1 Datasets -- 4.2 Experiment 1: Omniglot Few-Shot Classification -- 4.3 Experiment 2: MiniImagenet Few-Shot Classification -- 4.4 Experiment 3: Interpretability Analysis on Omngilot -- 4.5 Experiment 4: Preliminary Interpretability Analysis on MiniImagenet -- 5 Conclusion and Future Work -- References -- A Preliminary Study of Interpreting CNNs Using Soft Decision Trees -- 1 Introduction -- 2 Related Work -- 3 Proposed Methods -- 3.1 Model Foundations -- 3.2 Using Normal/Soft Decision Trees to Interpret CNNs -- 3.3 Evaluating Interpretability -- 4 Experiments -- 4.1 Dataset and Experimental Setup -- 4.2 Experiment 1: Classification Performance -- 4.3 Experiment 2: Visualization of Normal/Soft Decision Trees' Top Features. 4.4 Experiment 3: Interpretability Performance -- 4.5 Experiment 4: Scores of Human Experts on Tag Clarity -- 5 Conclusion and Future Work -- References -- Deep Reinforcement Learning with Fuse Adaptive Weighted Demonstration Data -- 1 Introduction -- 2 Related Work -- 2.1 Deep Reinforcement Learning -- 2.2 Multiagent Reinforcement Learning -- 3 Methods -- 4 Experimental Results and Analysis -- 4.1 Experimental Environment and Data -- 4.2 Results and Analysis -- 5 Discussion -- References -- DRIB: Interpreting DNN with Dynamic Reasoning and Information Bottleneck -- 1 Introduction -- 2 Related Works -- 2.1 Explain the Existing Deep Learning Models -- 2.2 Construction of Interpretable Deep Learning Models -- 3 Method -- 3.1 Dynamic Reasoning Decision Module -- 3.2 Information Bottleneck Verification Module -- 4 Experiments -- 4.1 Experimental Settings -- 4.2 Interpretability of Calculation in Dynamic Reasoning Decision -- 4.3 Explainability of Attribution in the Information Bottleneck -- 4.4 Visualization of Understandability -- 5 Conclusion -- References -- Multimedia Data Management and Analysis -- Advanced Generative Adversarial Network for Image Superresolution -- 1 Introduction -- 2 Related Work -- 3 GAN and SRGAN -- 4 Proposed Method -- 4.1 Generator Network Structure -- 4.2 Discriminator Network Structure -- 4.3 Loss Function -- 5 Experiment Results and Analysis -- 5.1 Implementation Details -- 5.2 Datasets and Evaluation Metrics -- 5.3 Experimental Results and Analysis -- 5.4 Ablation Study -- 6 Conclusions -- References -- Real-World Superresolution by Using Deep Degradation Learning -- 1 Introduction -- 2 Related Work -- 2.1 Real-World Superresolution -- 2.2 Contrastive Learning -- 3 PurPosed Method -- 3.1 Overview of the Unsupervised Framework -- 3.2 Degradation Model -- 3.3 Reconstruction Model -- 4 Experiments -- 4.1 Training Data. 4.2 Training Details -- 4.3 Training Details -- 5 Conclusion -- References -- Probability Loop Closure Detection with Fisher Kernel Framework for Visual SLAM -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Fisher Vector Generation -- 3.2 Probability Visual Vocabulary -- 3.3 Loop Closure Detection -- 4 Results and Discussion -- 4.1 Dataset and Preprocessing -- 4.2 Evaluation Metrics -- 4.3 2D Motion -- 4.4 3D Motion -- 4.5 Bidirectional Loops -- 4.6 Ablation Study -- 5 Conclusions -- References -- A Complex Background Image Registration Method Based on the Optical Flow Field Algorithm -- 1 Introduction -- 2 The Proposed Method -- 3 Evaluation Functions -- 4 Experimental Results -- 5 Conclusion -- References -- Collaborative Learning Method for Natural Image Captioning -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 P2PM: Pix2Pix Inverting Module -- 3.2 NLGM: Natural Language Generation Module -- 3.3 Collaborative Learning Framework -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Main Results -- 5 Conclusion -- References -- Visual Analysis of the National Characteristics of the COVID-19 Vaccine Based on Knowledge Graph -- 1 Introduction -- 2 Related Studies -- 3 Construction of the COVID-19 Vaccine Knowledge Graph -- 3.1 Data Acquisition -- 3.2 Entity Extraction to Construct a Relational Model -- 3.3 Knowledge Graph Establishment -- 4 Visual Analysis of the National Characteristics of the COVID-19 Vaccine -- 5 Conclusions and Recommendations -- References -- Speech Recognition for Parkinson's Disease Based on Improved Genetic Algorithm and Data Enhancement Technology -- 1 Introduction -- 2 The Proposed Methods -- 2.1 Method -- 3 Speech Recognition and Diagnosis -- 3.1 Data Preprocessing -- 3.2 Improved GA-SVM Model -- 3.3 Speech Recognition Algorithm -- 4 Experiment and Evaluation -- 4.1 Experiment Setup. 4.2 Comparison and Analysis of Results. |
| Record Nr. | UNISA-996485669903316 |
| Singapore : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Data science . Part II : 8th international conference of pioneering computer scientists, engineers and educators, ICPCSEE 2022, Chengdu, China, August 19-22, 2022, proceedings / / Yang Wang [and five others], editors
| Data science . Part II : 8th international conference of pioneering computer scientists, engineers and educators, ICPCSEE 2022, Chengdu, China, August 19-22, 2022, proceedings / / Yang Wang [and five others], editors |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (520 pages) |
| Disciplina | 005.7 |
| Collana | Communications in Computer and Information Science |
| Soggetto topico |
Big data
Data mining |
| ISBN | 981-19-5209-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents - Part II -- Contents - Part I -- Big Data Management and Applications -- Research on the Realization Path and Application of a Data Governance System Based on Data Architecture -- 1 Introduction -- 2 Research Status and Development of Data Governance -- 3 Functional Composition of Data Architecture -- 3.1 The Method of Integrating Heterogeneous Data with Internal and External Centralized Data Management -- 3.2 Data Security Classification, Data Right Confirmation and Authorization Methods -- 3.3 Basic Composition and Form of the Data Architecture -- 3.4 Data Governance System Supported by Data Architecture -- 4 Understanding the Data Architecture Supporting the Data Governance System -- 4.1 The Impact of Data on Human Civilization - Recognizing the Importance of Data -- 4.2 Comparison Between Data and Material - Similarity and Particularity of Data and Material -- 4.3 Comparison of Data and Information - the Difference Between Data and Information Determines the Difference in Research Data Governance Methods -- 4.4 The Relationship Between Data and Applications - the Systematicness, Integrity, Relevance and Essence of Data -- 5 Implementation Path of the Data Governance System Supported by the Data Architecture -- 5.1 Distinguish the Information System and Data System, and Develop the Data System by Using the Data-Oriented Software Engineering Method -- 5.2 Unify the Database of the Existing Information System, Build a Data System and Crack the "Data Island" -- 5.3 The Separation of Data Management and Use is Adopted to Simplify the Complexity of Data and Business -- 5.4 The Public Key Infrastructure of the Domestic Commercial Key Algorithm is Used to Realize Data Right Confirmation, Data Ownership Authorization and Data Protection.
5.5 Data Architecture Supports the Construction of a Data Governance System and Solves Data Governance Problems in a Package -- 5.6 Application Example of Data Governance System Based on Data Architecture in County New Smart City -- 6 Conclusion -- References -- Data Quality Identification Model for Power Big Data -- 1 Introduction -- 2 Background and Related Works -- 2.1 Related Works -- 2.2 Related Technologies -- 3 Problem Definition -- 4 Proposed Approach -- 4.1 Data Quality Identification Architecture -- 4.2 Data Preprocessing and Grouping -- 4.3 Data Augmentation -- 4.4 Tri-Training Based Detection -- 5 Experiments -- 5.1 Training Data and Baselines -- 5.2 Analysis -- 6 Conclusion -- References -- Data Security and Privacy -- Effective and Lightweight Defenses Against Website Fingerprinting on Encrypted Traffic -- 1 Introduction -- 2 Background and Related Work -- 2.1 WF Attacks -- 2.2 WF Defense -- 3 Threat Model -- 4 The Propose TED -- 4.1 Overview of TED -- 4.2 Similar Scale Traces Clustering -- 4.3 Interconversion -- 4.4 Key Feature Extraction -- 5 Performance Evaluation -- 5.1 Preliminary -- 5.2 Performance Metrics -- 5.3 Parameter Tuning -- 5.4 Evaluation -- 6 Conclusion -- References -- Data Hiding in the Division Domain: Simultaneously Achieving Robustness to Scaling and Additive Attacks -- 1 Introduction -- 2 Preliminaries -- 2.1 QIM -- 2.2 Related Work on Resisting Scaling Attacks -- 3 Proposed Method -- 3.1 Division Domain for Data Hiding -- 3.2 D-QIM -- 3.3 Theoretical Analysis for D-QIM -- 4 Simulations -- 5 Conclusions -- References -- BMSC: A Novel Anonymous Trading Scheme Based on Zero-Knowledge Proof in Ethereum -- 1 Introduction -- 2 Related Works -- 3 Zreo-Knowledge Proof -- 4 BMSC: Anonymous Transaction Scheme -- 4.1 Groth16 -- 4.2 Scheme Construction -- 5 Analysis of Anonymity and Security -- 5.1 Analysis of Anonymity. 5.2 Hide Account Balances and Transaction Amounts -- 5.3 Hide the Transfer Relationships -- 5.4 Analysis of Security -- 5.5 Overspending Attack -- 5.6 Double-Spending Attack -- 6 Conclusion -- References -- Research on the Design and Education of Serious Network Security Games -- 1 Introduction -- 2 Related Work -- 3 Feasibility Analysis -- 3.1 Educational Dilemma -- 3.2 Education Status -- 4 Theoretical Basis -- 4.1 Constructivist Theory -- 4.2 Situational Cognition -- 5 Teaching Design -- 5.1 Design Principle -- 5.2 Design Principle -- 6 Game Design -- 6.1 Game Theme -- 6.2 Game Components -- 6.3 Rules of the Game -- 6.4 Hands-On Game -- 7 Conclusion -- References -- KPH: A Novel Blockchain Privacy Preserving Scheme Based on Paillier and FO Commitment -- 1 Introduction -- 2 Related Works -- 3 Preliminaries -- 3.1 Paillier Cryptosystem -- 3.2 Chinese Remainder Theorem -- 3.3 CRT-Based Paillier Cryptosystem -- 3.4 An Optimized Paillier Cryptosystem -- 3.5 Fujisaki-Okamoto Commitment -- 3.6 Blockchain Data Sharing Model -- 4 Privacy Protection Model for Blockchain Data Sharing -- 4.1 Hidden Amount -- 4.2 Transaction Verification -- 4.3 Update Account Balance -- 4.4 Performance Analysis -- 5 Conclusion -- References -- Blockchain Access Control Scheme Based on Multi-authority Attribute-Based Encryption -- 1 Introduction -- 2 Related Works -- 3 Preliminaries -- 3.1 Bilinear Mapping -- 3.2 Access Control Structure -- 3.3 Linear Secret Sharing Scheme -- 4 Blockchain Access Control Scheme Based on MA-ABE -- 4.1 Scheme Overview -- 4.2 Autonomous Identity Management -- 4.3 Selection of Attribute Authorities -- 4.4 Hierarchical Linear Secret Sharing Scheme -- 4.5 Blockchain Access Control Algorithm -- 5 Scheme Analysis -- 5.1 Security Analysis -- 5.2 Comparison of Scheme Cost -- 6 Conclusion -- References -- Applications of Data Science. Study on the Intelligent Control Model of a Greenhouse Flower Growing Environment -- 1 Introduction -- 2 Problem Scenario -- 2.1 A Floral Growth Factor Analysis -- 2.2 Fuzzy Neural Network -- 2.3 Practice Site and Flowers -- 3 Methods -- 3.1 Framework -- 3.2 Fuzzy Neural Network Model -- 3.3 Design Implementation -- 4 Experimental Results and Analysis -- 4.1 Simulation Analysis -- 4.2 Field Site Experiments -- 4.3 Model Evaluation -- 5 Conclusion and Discussion -- References -- A Multi-event Extraction Model for Nursing Records -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Dataset Annotation -- 3.2 Dataset Analysis -- 3.3 Model -- 4 Experiments -- 4.1 Experiment Settings -- 4.2 Comparison Methods -- 4.3 Main Results -- 4.4 Analysis on the Multi-event Argument Attribution Problem -- 5 Discussion -- 5.1 Analysis on High Score Performance -- 5.2 Application of Missing Item Detection -- 6 Conclusion -- References -- Cuffless Blood Pressure Estimation Based on Both Artificial and Data-Driven Features from Plethysmography -- 1 Introduction -- 2 Related Work -- 3 Proposed Model -- 3.1 Empirical Feature Extracting Branch -- 3.2 Data-Driven Feature Extracting Branch Based on LSTM -- 3.3 Feature Gathering and Multichannel Output Module -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Competing Methods -- 4.3 Results and Analysis -- 5 Conclusions -- References -- User Attribute Prediction Method Based on Stacking Multimodel Fusion -- 1 Introduction -- 2 Related Machine Learning Algorithms -- 3 Multimodel-LightGBM -- 3.1 Stacking Algorithm -- 3.2 Multimodel-LightGBM -- 4 Experiment and Result Analysis -- 4.1 Dataset -- 4.2 Feature Engineering -- 4.3 Evaluation Metrics -- 4.4 Experimental Results -- 5 Conclusion -- References -- How is the Power of the Baidu Index for Forecasting Hotel Guest Arrivals? -A Case Study of Guilin -- 1 Introduction. 2 Literature Review -- 2.1 Baidu Index and Tourism Research -- 2.2 Tourism Forecasting with Big Data -- 3 Data -- 3.1 Data Collection -- 3.2 Keyword Selection for the Baidu Search -- 3.3 Data Preprocessing -- 4 Variable Test and Metrics -- 4.1 Unit Root -- 4.2 Granger Casualty Test -- 4.3 Metrics -- 5 Model Fitting and Performance Evaluation -- 5.1 Forecasting Model Without Any Baidu Index -- 5.2 Autoregressive Distributed Lag Model Establishment with Univariate Baidu Index -- 5.3 Autoregressive Distributed Lag Model Establishment with Multiple Baidu Indexes -- 5.4 Summary -- 6 Conclusions, Limitations, and Future Work -- 6.1 Conclusions -- 6.2 Limitations -- 6.3 Future Work -- References -- A Facial Size Automatic Measurement and Analysis Technology -- 1 Introduction -- 2 Facial Data Acquisition -- 3 Facial Morphology Analysis System -- 3.1 Feature Point Recognition -- 3.2 Location of Three-Dimensional Facial Feature Points -- 3.3 Facial Morphology Analysis -- 3.4 Output Module -- 4 Experimental Comparison -- 5 Conclusion -- References -- Intelligent Industrial Auxiliary System Based on AR Technology -- 1 Introduction -- 2 System Design and Implementation -- 2.1 Real-Time Display -- 2.2 Human-Computer Interaction -- 2.3 Perception and Positioning -- 2.4 Scene Switch -- 3 Example Display -- 4 Summary and Outlook -- References -- Infrastructure for Data Science -- Industry-Oriented Cloud Edge Intelligent Assembly Guidance System -- 1 Introduction -- 2 Method -- 2.1 Instance Segmentation -- 2.2 Pose Estimation -- 2.3 Cloud-Edge Joint Technology -- 3 Experiment and Analysis -- 3.1 Experimental Setup -- 3.2 Experimental Results -- 4 Conclusion -- References -- An Intelligent Data Routing Scheme for Multi-UAV Avionics System Based on Integrated Communication Effectiveness -- 1 Introduction -- 2 Proposed Integrated Communication Effectiveness Metric. 2.1 Link Effectiveness. |
| Record Nr. | UNISA-996485670003316 |
| Singapore : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Data science . Part II : 8th international conference of pioneering computer scientists, engineers and educators, ICPCSEE 2022, Chengdu, China, August 19-22, 2022, proceedings / / Yang Wang [and five others], editors
| Data science . Part II : 8th international conference of pioneering computer scientists, engineers and educators, ICPCSEE 2022, Chengdu, China, August 19-22, 2022, proceedings / / Yang Wang [and five others], editors |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (520 pages) |
| Disciplina | 005.7 |
| Collana | Communications in Computer and Information Science |
| Soggetto topico |
Big data
Data mining |
| ISBN | 981-19-5209-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents - Part II -- Contents - Part I -- Big Data Management and Applications -- Research on the Realization Path and Application of a Data Governance System Based on Data Architecture -- 1 Introduction -- 2 Research Status and Development of Data Governance -- 3 Functional Composition of Data Architecture -- 3.1 The Method of Integrating Heterogeneous Data with Internal and External Centralized Data Management -- 3.2 Data Security Classification, Data Right Confirmation and Authorization Methods -- 3.3 Basic Composition and Form of the Data Architecture -- 3.4 Data Governance System Supported by Data Architecture -- 4 Understanding the Data Architecture Supporting the Data Governance System -- 4.1 The Impact of Data on Human Civilization - Recognizing the Importance of Data -- 4.2 Comparison Between Data and Material - Similarity and Particularity of Data and Material -- 4.3 Comparison of Data and Information - the Difference Between Data and Information Determines the Difference in Research Data Governance Methods -- 4.4 The Relationship Between Data and Applications - the Systematicness, Integrity, Relevance and Essence of Data -- 5 Implementation Path of the Data Governance System Supported by the Data Architecture -- 5.1 Distinguish the Information System and Data System, and Develop the Data System by Using the Data-Oriented Software Engineering Method -- 5.2 Unify the Database of the Existing Information System, Build a Data System and Crack the "Data Island" -- 5.3 The Separation of Data Management and Use is Adopted to Simplify the Complexity of Data and Business -- 5.4 The Public Key Infrastructure of the Domestic Commercial Key Algorithm is Used to Realize Data Right Confirmation, Data Ownership Authorization and Data Protection.
5.5 Data Architecture Supports the Construction of a Data Governance System and Solves Data Governance Problems in a Package -- 5.6 Application Example of Data Governance System Based on Data Architecture in County New Smart City -- 6 Conclusion -- References -- Data Quality Identification Model for Power Big Data -- 1 Introduction -- 2 Background and Related Works -- 2.1 Related Works -- 2.2 Related Technologies -- 3 Problem Definition -- 4 Proposed Approach -- 4.1 Data Quality Identification Architecture -- 4.2 Data Preprocessing and Grouping -- 4.3 Data Augmentation -- 4.4 Tri-Training Based Detection -- 5 Experiments -- 5.1 Training Data and Baselines -- 5.2 Analysis -- 6 Conclusion -- References -- Data Security and Privacy -- Effective and Lightweight Defenses Against Website Fingerprinting on Encrypted Traffic -- 1 Introduction -- 2 Background and Related Work -- 2.1 WF Attacks -- 2.2 WF Defense -- 3 Threat Model -- 4 The Propose TED -- 4.1 Overview of TED -- 4.2 Similar Scale Traces Clustering -- 4.3 Interconversion -- 4.4 Key Feature Extraction -- 5 Performance Evaluation -- 5.1 Preliminary -- 5.2 Performance Metrics -- 5.3 Parameter Tuning -- 5.4 Evaluation -- 6 Conclusion -- References -- Data Hiding in the Division Domain: Simultaneously Achieving Robustness to Scaling and Additive Attacks -- 1 Introduction -- 2 Preliminaries -- 2.1 QIM -- 2.2 Related Work on Resisting Scaling Attacks -- 3 Proposed Method -- 3.1 Division Domain for Data Hiding -- 3.2 D-QIM -- 3.3 Theoretical Analysis for D-QIM -- 4 Simulations -- 5 Conclusions -- References -- BMSC: A Novel Anonymous Trading Scheme Based on Zero-Knowledge Proof in Ethereum -- 1 Introduction -- 2 Related Works -- 3 Zreo-Knowledge Proof -- 4 BMSC: Anonymous Transaction Scheme -- 4.1 Groth16 -- 4.2 Scheme Construction -- 5 Analysis of Anonymity and Security -- 5.1 Analysis of Anonymity. 5.2 Hide Account Balances and Transaction Amounts -- 5.3 Hide the Transfer Relationships -- 5.4 Analysis of Security -- 5.5 Overspending Attack -- 5.6 Double-Spending Attack -- 6 Conclusion -- References -- Research on the Design and Education of Serious Network Security Games -- 1 Introduction -- 2 Related Work -- 3 Feasibility Analysis -- 3.1 Educational Dilemma -- 3.2 Education Status -- 4 Theoretical Basis -- 4.1 Constructivist Theory -- 4.2 Situational Cognition -- 5 Teaching Design -- 5.1 Design Principle -- 5.2 Design Principle -- 6 Game Design -- 6.1 Game Theme -- 6.2 Game Components -- 6.3 Rules of the Game -- 6.4 Hands-On Game -- 7 Conclusion -- References -- KPH: A Novel Blockchain Privacy Preserving Scheme Based on Paillier and FO Commitment -- 1 Introduction -- 2 Related Works -- 3 Preliminaries -- 3.1 Paillier Cryptosystem -- 3.2 Chinese Remainder Theorem -- 3.3 CRT-Based Paillier Cryptosystem -- 3.4 An Optimized Paillier Cryptosystem -- 3.5 Fujisaki-Okamoto Commitment -- 3.6 Blockchain Data Sharing Model -- 4 Privacy Protection Model for Blockchain Data Sharing -- 4.1 Hidden Amount -- 4.2 Transaction Verification -- 4.3 Update Account Balance -- 4.4 Performance Analysis -- 5 Conclusion -- References -- Blockchain Access Control Scheme Based on Multi-authority Attribute-Based Encryption -- 1 Introduction -- 2 Related Works -- 3 Preliminaries -- 3.1 Bilinear Mapping -- 3.2 Access Control Structure -- 3.3 Linear Secret Sharing Scheme -- 4 Blockchain Access Control Scheme Based on MA-ABE -- 4.1 Scheme Overview -- 4.2 Autonomous Identity Management -- 4.3 Selection of Attribute Authorities -- 4.4 Hierarchical Linear Secret Sharing Scheme -- 4.5 Blockchain Access Control Algorithm -- 5 Scheme Analysis -- 5.1 Security Analysis -- 5.2 Comparison of Scheme Cost -- 6 Conclusion -- References -- Applications of Data Science. Study on the Intelligent Control Model of a Greenhouse Flower Growing Environment -- 1 Introduction -- 2 Problem Scenario -- 2.1 A Floral Growth Factor Analysis -- 2.2 Fuzzy Neural Network -- 2.3 Practice Site and Flowers -- 3 Methods -- 3.1 Framework -- 3.2 Fuzzy Neural Network Model -- 3.3 Design Implementation -- 4 Experimental Results and Analysis -- 4.1 Simulation Analysis -- 4.2 Field Site Experiments -- 4.3 Model Evaluation -- 5 Conclusion and Discussion -- References -- A Multi-event Extraction Model for Nursing Records -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Dataset Annotation -- 3.2 Dataset Analysis -- 3.3 Model -- 4 Experiments -- 4.1 Experiment Settings -- 4.2 Comparison Methods -- 4.3 Main Results -- 4.4 Analysis on the Multi-event Argument Attribution Problem -- 5 Discussion -- 5.1 Analysis on High Score Performance -- 5.2 Application of Missing Item Detection -- 6 Conclusion -- References -- Cuffless Blood Pressure Estimation Based on Both Artificial and Data-Driven Features from Plethysmography -- 1 Introduction -- 2 Related Work -- 3 Proposed Model -- 3.1 Empirical Feature Extracting Branch -- 3.2 Data-Driven Feature Extracting Branch Based on LSTM -- 3.3 Feature Gathering and Multichannel Output Module -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Competing Methods -- 4.3 Results and Analysis -- 5 Conclusions -- References -- User Attribute Prediction Method Based on Stacking Multimodel Fusion -- 1 Introduction -- 2 Related Machine Learning Algorithms -- 3 Multimodel-LightGBM -- 3.1 Stacking Algorithm -- 3.2 Multimodel-LightGBM -- 4 Experiment and Result Analysis -- 4.1 Dataset -- 4.2 Feature Engineering -- 4.3 Evaluation Metrics -- 4.4 Experimental Results -- 5 Conclusion -- References -- How is the Power of the Baidu Index for Forecasting Hotel Guest Arrivals? -A Case Study of Guilin -- 1 Introduction. 2 Literature Review -- 2.1 Baidu Index and Tourism Research -- 2.2 Tourism Forecasting with Big Data -- 3 Data -- 3.1 Data Collection -- 3.2 Keyword Selection for the Baidu Search -- 3.3 Data Preprocessing -- 4 Variable Test and Metrics -- 4.1 Unit Root -- 4.2 Granger Casualty Test -- 4.3 Metrics -- 5 Model Fitting and Performance Evaluation -- 5.1 Forecasting Model Without Any Baidu Index -- 5.2 Autoregressive Distributed Lag Model Establishment with Univariate Baidu Index -- 5.3 Autoregressive Distributed Lag Model Establishment with Multiple Baidu Indexes -- 5.4 Summary -- 6 Conclusions, Limitations, and Future Work -- 6.1 Conclusions -- 6.2 Limitations -- 6.3 Future Work -- References -- A Facial Size Automatic Measurement and Analysis Technology -- 1 Introduction -- 2 Facial Data Acquisition -- 3 Facial Morphology Analysis System -- 3.1 Feature Point Recognition -- 3.2 Location of Three-Dimensional Facial Feature Points -- 3.3 Facial Morphology Analysis -- 3.4 Output Module -- 4 Experimental Comparison -- 5 Conclusion -- References -- Intelligent Industrial Auxiliary System Based on AR Technology -- 1 Introduction -- 2 System Design and Implementation -- 2.1 Real-Time Display -- 2.2 Human-Computer Interaction -- 2.3 Perception and Positioning -- 2.4 Scene Switch -- 3 Example Display -- 4 Summary and Outlook -- References -- Infrastructure for Data Science -- Industry-Oriented Cloud Edge Intelligent Assembly Guidance System -- 1 Introduction -- 2 Method -- 2.1 Instance Segmentation -- 2.2 Pose Estimation -- 2.3 Cloud-Edge Joint Technology -- 3 Experiment and Analysis -- 3.1 Experimental Setup -- 3.2 Experimental Results -- 4 Conclusion -- References -- An Intelligent Data Routing Scheme for Multi-UAV Avionics System Based on Integrated Communication Effectiveness -- 1 Introduction -- 2 Proposed Integrated Communication Effectiveness Metric. 2.1 Link Effectiveness. |
| Record Nr. | UNINA-9910586578103321 |
| Singapore : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Digital parenting burdens in China : online homework, parent chats and punch-In culture
| Digital parenting burdens in China : online homework, parent chats and punch-In culture |
| Autore | Lim Sun Sun |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Leeds : , : Emerald Publishing Limited, , 2024 |
| Descrizione fisica | 1 online resource (109 pages) |
| Disciplina | 306.8 |
| Altri autori (Persone) | WangYang |
| Collana | Emerald Points Series |
| Soggetto topico |
Digital media
Parenting |
| ISBN |
9781837977574
1837977577 9781837977550 1837977550 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Intro -- Halftitle Page -- Endorsements -- Title Page -- Copyright Page -- Contents -- List of Figures -- Acknowledgements -- 1: Digital Parenting: Why the Chinese Experience Matters -- Digital Parenting with Chinese Characteristics -- Family Life and Parenting Priorities in China -- Why the Chinese Experience Matters -- 2: Digitalisation of Family Life in China -- Devices, Super Apps, and Mini-Programmes -- Parent Chat Groups -- Online Discussion Forums and Social Media Accounts -- Parent-Teacher Communication and Edtech Platforms -- Online Education During Covid-19 -- Research Questions and Method -- 3: Parental Accountability and Punch-In Culture -- Origins, Manifestations, and Norms of Punch-In Culture -- Punch-In Culture During the Covid-19 Pandemic -- Punch-In Culture Ecosystem and Its Reward-Punishment Regime -- Implications of Punch-In Culture for Parents and Children -- Note -- 4: Performative Parenting and Peer Pressure -- Rules, Norms, and Roles on Parenting's 'Front Stage' -- Peer Pressure: Perceived, Experienced, and Imposed -- Emotion Work and Context Collapse -- Note -- 5: Digital Parenting Burdens and Family Wellbeing -- Growing Digitalisation of Family Life -- Global Perspectives on Digital Parenting -- Wellbeing Through Policy and Design -- Concluding Thoughts -- About the Authors -- Glossary of Chinese Terms -- References -- Index. |
| Record Nr. | UNINA-9910864291603321 |
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Lim Sun Sun
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| Leeds : , : Emerald Publishing Limited, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Generative AI Security : Theories and Practices / / edited by Ken Huang, Yang Wang, Ben Goertzel, Yale Li, Sean Wright, Jyoti Ponnapalli
| Generative AI Security : Theories and Practices / / edited by Ken Huang, Yang Wang, Ben Goertzel, Yale Li, Sean Wright, Jyoti Ponnapalli |
| Autore | Huang Ken |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (367 pages) |
| Disciplina | 005.8 |
| Altri autori (Persone) |
WangYang
GoertzelBen LiYale WrightSean PonnapalliJyoti |
| Collana | Future of Business and Finance |
| Soggetto topico |
Business information services
Financial risk management Data protection Artificial intelligence Information technology - Moral and ethical aspects IT in Business Risk Management Data and Information Security Artificial Intelligence Information Ethics |
| ISBN |
9783031542527
3031542525 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Foundations of Generative AI -- Navigating the GenAI Security -- AI Regulations -- Build Your Security Program for GenAI -- GenAI Data Security -- GenAI Model Security -- GenAI Application Level Security -- From LLMOps to DevSecOps for GenAI -- Utilizing Prompt Engineering to Operationalize Cyber Security -- Use GenAI Tools to Boost Your Security Posture. |
| Record Nr. | UNINA-9910847580503321 |
|
Huang Ken
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||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Intermediate spoken Chinese practice essentials : a wealth of activities to enhance your spoken Mandarin / / Cornelius C. Kubler & Yang Wang
| Intermediate spoken Chinese practice essentials : a wealth of activities to enhance your spoken Mandarin / / Cornelius C. Kubler & Yang Wang |
| Autore | Kubler Cornelius C. |
| Pubbl/distr/stampa | Clarendon, Vermont : , : Tuttle, , 2013 |
| Descrizione fisica | 1 online resource (223 pages) |
| Disciplina | 495.182421 |
| Soggetto topico |
Chinese language - English
Chinese language Chinese language - Spoken Chinese |
| Soggetto genere / forma | Electronic books. |
| ISBN | 1-4629-1545-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910465293803321 |
|
Kubler Cornelius C.
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| Clarendon, Vermont : , : Tuttle, , 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Intermediate spoken Chinese practice essentials : a wealth of activities to enhance your spoken Mandarin / / Cornelius C. Kubler & Yang Wang
| Intermediate spoken Chinese practice essentials : a wealth of activities to enhance your spoken Mandarin / / Cornelius C. Kubler & Yang Wang |
| Autore | Kubler Cornelius C. |
| Pubbl/distr/stampa | Clarendon, Vermont : , : Tuttle, , 2013 |
| Descrizione fisica | 1 online resource (223 pages) |
| Disciplina | 495.182421 |
| Soggetto topico |
Chinese language - English
Chinese language Chinese language - Spoken Chinese |
| ISBN | 1-4629-1545-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910798597303321 |
|
Kubler Cornelius C.
|
||
| Clarendon, Vermont : , : Tuttle, , 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Intermediate spoken Chinese practice essentials : a wealth of activities to enhance your spoken Mandarin / / Cornelius C. Kubler & Yang Wang
| Intermediate spoken Chinese practice essentials : a wealth of activities to enhance your spoken Mandarin / / Cornelius C. Kubler & Yang Wang |
| Autore | Kubler Cornelius C. |
| Pubbl/distr/stampa | Clarendon, Vermont : , : Tuttle, , 2013 |
| Descrizione fisica | 1 online resource (223 pages) |
| Disciplina | 495.182421 |
| Soggetto topico |
Chinese language - English
Chinese language Chinese language - Spoken Chinese |
| ISBN | 1-4629-1545-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910808890203321 |
|
Kubler Cornelius C.
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||
| Clarendon, Vermont : , : Tuttle, , 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
