Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
Advances in artificial intelligence-based technologies . Volume 1 : selected papers in honour of Professor Nikolaos G. Bourbakis / / Maria Virvou [and three others]
| Advances in artificial intelligence-based technologies . Volume 1 : selected papers in honour of Professor Nikolaos G. Bourbakis / / Maria Virvou [and three others] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (241 pages) |
| Disciplina | 006.3 |
| Collana | Learning and Analytics in Intelligent Systems |
| Soggetto topico |
Artificial intelligence
Artificial intelligence - Mathematical models |
| ISBN | 3-030-80571-9 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Foreword -- Preface -- Contents -- 1 Introduction to Advances in Artificial Intelligence-Based Technologies -- References -- Part I Advances in Artificial Intelligence Tools and Methodologies -- 2 Synthesizing 2D Ground Images for Maps Creation and Detecting Texture Patterns -- 2.1 Introduction -- 2.2 Synthesizing 2D Consecutive Region-Images for Space Map Generation -- 2.3 Texture Paths Detection -- 2.4 Simulated Case Study and Comparison with Other Methods -- 2.5 Discussion -- References -- 3 Affective Computing: An Introduction to the Detection, Measurement, and Current Applications -- 3.1 Introduction -- 3.2 Background -- 3.3 Detection and Measurement Devices for Affective Computing -- 3.3.1 Brain Computer Interfaces (BCIs) -- 3.3.2 Facial Expression and Eye Tracking Technologies -- 3.3.3 Galvanic Skin Response -- 3.3.4 Multimodal Input Devices -- 3.3.5 Emotional Speech Recognition and Natural Language Processing -- 3.4 Application Examples -- 3.4.1 Entertainment -- 3.4.2 Chatbots -- 3.4.3 Medical Applications -- 3.5 Conclusions -- References -- 4 A Database Reconstruction Approach for the Inverse Frequent Itemset Mining Problem -- 4.1 Introduction -- 4.2 Related Work -- 4.3 Problem Definition -- 4.3.1 Frequent Itemset Hiding Problem -- 4.3.2 Inverse Frequent Itemset Hiding Problem -- 4.4 Hiding Approach -- 4.5 Conclusion and Future Steps -- References -- 5 A Rough Inference Software System for Computer-Assisted Reasoning -- 5.1 Introduction -- 5.2 Basic Concepts -- 5.2.1 Rough Sets -- 5.2.2 Information System -- 5.2.3 Decision System -- 5.2.4 Indiscernibility Relation -- 5.3 The Approximate Algorithms for Information Systems -- 5.3.1 The Approximate Algorithm for Attribute Reduction -- 5.3.2 The Algorithm for Approximate Rule Generation -- 5.4 Implementation of the Rough Inference System.
5.5 An Application in Electrical Engineering-A Case Study -- 5.6 Conclusions -- References -- Part II Advances in Artificial Intelligence-based Applications and Services -- 6 Context Representation and Reasoning in Robotics-An Overview -- 6.1 Introduction -- 6.2 Context -- 6.2.1 Definitions of Context -- 6.2.2 Context Aware Systems -- 6.2.3 Context Representation -- 6.3 Context Reasoning -- 6.3.1 Reasoning Approaches and Techniques -- 6.3.2 Reasoning Tools -- 6.4 Conclusions and Future Work -- References -- 7 Smart Tourism and Artificial Intelligence: Paving the Way to the Post-COVID-19 Era -- 7.1 Introduction -- 7.2 Methodology and Research Approach -- 7.3 Artificial Intelligence and Smart Tourism -- 7.3.1 Artificial Intelligence -- 7.3.2 AI Smart Tourism Recommender Systems -- 7.3.3 Deep Learning -- 7.3.4 Augmented Reality In tourism -- 7.3.5 AI Autonomous Agents -- 7.4 Smart Tourism in COVID-19 Pandemic -- 7.5 Conclusions and Future Directions -- References -- 8 Challenges and AI-Based Solutions for Smart Energy Consumption in Smart Cities -- 8.1 Introduction -- 8.2 Smart Energy in Smart Cities -- 8.3 Energy Consumption Challenges and AI Solutions -- 8.3.1 End-User Consumers in Smart Cities -- 8.3.2 Demand Forecasting -- 8.3.3 Prosumers Management -- 8.3.4 Consumption Privacy -- 8.4 Discussion -- References -- 9 How to Make Different Thinking Profiles Visible Through Technology: The Potential for Log File Analysis and Learning Analytics -- 9.1 Introduction -- 9.2 The Development of Log File Analysis and Learning Analytics -- 9.3 Analysing Log File Data in Researching Dynamic Problem-Solving -- 9.4 Extracting, Structuring and Analysing Log File Data to Make Different Thinking Profiles Visible -- 9.4.1 Aims -- 9.4.2 Methods -- 9.5 Participants -- 9.6 Instruments -- 9.7 Procedures -- 9.8 Results -- 9.9 Discussion -- 9.10 Conclusions and Limitations. References -- 10 AI in Consumer Behavior -- 10.1 Introduction -- 10.2 Literature Review -- 10.3 Artificial Intelligence (AI) in Consumer Behavior -- 10.3.1 Artificial Intelligence -- 10.3.2 Consumer Behavior -- 10.3.3 AI in Consumer Behavior -- 10.3.4 AI and Ethics -- 10.4 Conclusion -- References -- Part III Theoretical Advances in Computation and System Modeling -- 11 Coupled Oscillator Networks for von Neumann and Non-von Neumann Computing -- 11.1 Introduction -- 11.2 Basic Unit, Network Architecture and Computational Principle -- 11.3 Nonlinear Oscillator Networks and Phase Equation -- 11.3.1 Example -- 11.4 Oscillator Networks for Boolean Logic -- 11.4.1 Registers -- 11.4.2 Logic Gates -- 11.5 Conclusions -- References -- 12 Design and Implementation in a New Approach of Non-minimal State Space Representation of a MIMO Model Predictive Control Strategy-Case Study and Performance Analysis -- 12.1 Introduction -- 12.2 Centrifugal Chiller-System Decomposition -- 12.2.1 Centrifugal Chiller Dynamic Model Description -- 12.2.2 Centrifugal Chiller Dynamic MIMO ARMAX Model Description -- 12.2.3 Centrifugal Chiller Open Loop MIMO ARMAX Discrete-Time Model -- 12.2.4 Centrifugal Chiller Dynamic MIMO ARMAX Model Nonminimal State Space Description -- 12.3 MISO MPC Strategy Design in a Minimal State Space Realization -- 12.3.1 MIMO MPC Optimization Problem Formulation -- 12.3.2 MIMO MPC Parameters Design -- 12.3.3 MIMO MPC MATLAB SIMULINK Simulation Results -- 12.4 MIMO MPC Strategy Design in a Nonminimal State Space Realization -- 12.5 Conclusions -- References. |
| Record Nr. | UNINA-9910523901603321 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in Assistive Technologies : Selected Papers in Honour of Professor Nikolaos G. Bourbakis - Vol. 3
| Advances in Assistive Technologies : Selected Papers in Honour of Professor Nikolaos G. Bourbakis - Vol. 3 |
| Autore | Tsihrintzis George A |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing AG, , 2022 |
| Descrizione fisica | 1 online resource (317 pages) |
| Altri autori (Persone) |
VirvouMaria
EspositoAnna JainLakhmi C |
| Collana | Learning and Analytics in Intelligent Systems Ser. |
| Soggetto genere / forma | Electronic books. |
| ISBN |
9783030871321
9783030871314 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910512310203321 |
Tsihrintzis George A
|
||
| Cham : , : Springer International Publishing AG, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in Bioinformatics, Multimedia, and Electronics Circuits and Signals [[electronic resource] ] : Proceedings of GUCON 2019 / / edited by Lakhmi C. Jain, Maria Virvou, Vincenzo Piuri, Valentina E. Balas
| Advances in Bioinformatics, Multimedia, and Electronics Circuits and Signals [[electronic resource] ] : Proceedings of GUCON 2019 / / edited by Lakhmi C. Jain, Maria Virvou, Vincenzo Piuri, Valentina E. Balas |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (xix, 262 pages) : illustrations |
| Disciplina | 004 |
| Collana | Advances in Intelligent Systems and Computing |
| Soggetto topico |
Electronic circuits
Signal processing Bioinformatics Multimedia systems Electronic Circuits and Systems Signal, Speech and Image Processing Computational and Systems Biology Multimedia Information Systems |
| ISBN | 981-15-0339-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910366604503321 |
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in Core Computer Science-Based Technologies [[electronic resource] ] : Papers in Honor of Professor Nikolaos Alexandris / / edited by George A. Tsihrintzis, Maria Virvou
| Advances in Core Computer Science-Based Technologies [[electronic resource] ] : Papers in Honor of Professor Nikolaos Alexandris / / edited by George A. Tsihrintzis, Maria Virvou |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 |
| Descrizione fisica | 1 online resource (449 pages) |
| Disciplina | 004 |
| Collana | Learning and Analytics in Intelligent Systems |
| Soggetto topico |
Engineering mathematics
Computer simulation Engineering Mathematics Simulation and Modeling |
| ISBN | 3-030-41196-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1: This is Just Metadata: From no Communication Content to User Profiling, Surveillance and Exploitation -- Chapter 2: A fuzzy task scheduling method -- Chapter 3: A Bimodal System for Emotion Recognition via Computer of Known or Unknown Persons in Normal or Fatigue Situations -- Chapter 4: Homeodynamic modelling of complex abnormal biological processes -- Chapter 5: Engaging Students in Basic Cybersecurity Concepts Using Digital Game-Based Learning: Computer Games as Virtual Learning Environments. |
| Record Nr. | UNINA-9910483468103321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in Machine Learning/Deep Learning-Based Technologies : Selected Papers in Honour of Professor Nikolaos G. Bourbakis - Vol. 2
| Advances in Machine Learning/Deep Learning-Based Technologies : Selected Papers in Honour of Professor Nikolaos G. Bourbakis - Vol. 2 |
| Autore | Tsihrintzis George A |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing AG, , 2021 |
| Descrizione fisica | 1 online resource (237 pages) |
| Altri autori (Persone) |
VirvouMaria
JainLakhmi C |
| Collana | Learning and Analytics in Intelligent Systems Ser. |
| Soggetto genere / forma | Electronic books. |
| ISBN | 3-030-76794-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Advances in Machine Learning/Deep Learning-Based Technologies |
| Record Nr. | UNINA-9910497094003321 |
|
Tsihrintzis George A
|
||
| Cham : , : Springer International Publishing AG, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in machine learning/deep learning-based technologies Selected papers in honour of Professor Nikolaos G. Bourbakis . Volume 2 / / George A. Tsihrintzis, Maria Virvou, Lakhmi C. Jain, editors
| Advances in machine learning/deep learning-based technologies Selected papers in honour of Professor Nikolaos G. Bourbakis . Volume 2 / / George A. Tsihrintzis, Maria Virvou, Lakhmi C. Jain, editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (237 pages) |
| Disciplina | 006.31 |
| Collana | Learning and Analytics in Intelligent Systems |
| Soggetto topico | Machine learning |
| ISBN | 3-030-76794-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910523796803321 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in Personalized Web-Based Education [[electronic resource] /] / by Konstantina Chrysafiadi, Maria Virvou
| Advances in Personalized Web-Based Education [[electronic resource] /] / by Konstantina Chrysafiadi, Maria Virvou |
| Autore | Chrysafiadi Konstantina |
| Edizione | [1st ed. 2015.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
| Descrizione fisica | 1 online resource (171 p.) |
| Disciplina |
006.3
006.7 371.33 620 |
| Collana | Intelligent Systems Reference Library |
| Soggetto topico |
Computational intelligence
Artificial intelligence Educational technology Multimedia information systems Computational Intelligence Artificial Intelligence Educational Technology Multimedia Information Systems |
| ISBN | 3-319-12895-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Student Modeling for Personalized Education: A Review of the Literature -- Student Modeling for Personalized Education: A Review of the Literature -- A Novel Hybrid Student Model for Personalized Education -- Evaluation -- Conclusions. |
| Record Nr. | UNINA-9910299706103321 |
|
Chrysafiadi Konstantina
|
||
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in selected artificial intelligence areas : world outstanding women in artificial intelligence / / Maria Virvou, George A. Tsihrintzis, Lakhmi C. Jain, editors
| Advances in selected artificial intelligence areas : world outstanding women in artificial intelligence / / Maria Virvou, George A. Tsihrintzis, Lakhmi C. Jain, editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (363 pages) |
| Disciplina | 006.3 |
| Collana | Learning and Analytics in Intelligent Systems |
| Soggetto topico | Artificial intelligence |
| ISBN | 3-030-93052-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910548164903321 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in Social Networking-based Learning [[electronic resource] ] : Machine Learning-based User Modelling and Sentiment Analysis / / by Christos Troussas, Maria Virvou
| Advances in Social Networking-based Learning [[electronic resource] ] : Machine Learning-based User Modelling and Sentiment Analysis / / by Christos Troussas, Maria Virvou |
| Autore | Troussas Christos |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (xii, 176 pages) |
| Disciplina | 371.334 |
| Collana | Intelligent Systems Reference Library |
| Soggetto topico |
Computational intelligence
Artificial intelligence Educational technology Computational Intelligence Artificial Intelligence Technology and Digital Education |
| ISBN | 3-030-39130-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Related Work -- Intelligent, Adaptive and social e-learning in POLYGLOT. . |
| Record Nr. | UNINA-9910484947303321 |
|
Troussas Christos
|
||
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Handbook on artificial intelligence-empowered applied software engineering . Volume 1 Novel methodologies to engineering smart software systems / / Maria Virvou [and three others] editors
| Handbook on artificial intelligence-empowered applied software engineering . Volume 1 Novel methodologies to engineering smart software systems / / Maria Virvou [and three others] editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (342 pages) |
| Disciplina | 006.3 |
| Collana | Artificial intelligence-enhanced software and systems engineering |
| Soggetto topico |
Artificial intelligence - Industrial applications
Software engineering |
| ISBN | 3-031-08202-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Foreword -- Preface -- Contents -- 1 Introduction to Handbook on Artificial Intelligence-Empowered Applied Software Engineering-VOL.1: Novel Methodologies to Engineering Smart Software Systems -- 1.1 Editorial Note -- 1.2 Book Summary and Future Volumes -- Bibliography for Further Reading -- Part I Survey of Recent Relevant Literature -- 2 Synergies Between Artificial Intelligence and Software Engineering: Evolution and Trends -- 2.1 Introduction -- 2.2 Methodology -- 2.3 The Evolution of AI in Software Engineering -- 2.4 Top Authors and Topics -- 2.5 Trends in AI Applications to Software Engineering -- 2.5.1 Machine Learning and Data Mining -- 2.5.2 Knowledge Representation and Reasoning -- 2.5.3 Search and Optimisation -- 2.5.4 Communication and Perception -- 2.5.5 Cross-Disciplinary Topics -- 2.6 AI-Based Tools -- 2.7 Conclusion -- References -- Part II Artificial Intelligence-Assisted Software Development -- 3 Towards Software Co-Engineering by AI and Developers -- 3.1 Introduction -- 3.2 Software Development Support and Automation Level by Machine Learning -- 3.2.1 Project Planning: Team Composition -- 3.2.2 Requirements Engineering: Data-Driven Persona -- 3.2.3 Design: Detection of Design Patterns -- 3.2.4 Categorization of Initiative and Level of Automation -- 3.3 Quality of AI Application Systems and Software -- 3.3.1 Metamorphic Testing -- 3.3.2 Improving Explainability -- 3.3.3 Systems and Software Architecture -- 3.3.4 Integration of Goals, Strategies, and Data -- 3.4 Towards Software Co-Engineering by AI and Developers -- 3.5 Conclusion -- References -- 4 Generalizing Software Defect Estimation Using Size and Two Interaction Variables -- 4.1 Introduction -- 4.2 Background -- 4.3 A Proposed Approach -- 4.3.1 Selection of Sample Projects -- 4.3.2 Data Collection -- 4.3.3 The Scope and Decision to Go with 'Interaction' Variables.
4.3.4 Data Analysis and Results Discussion -- 4.3.5 The Turning Point -- 4.3.6 Models Performance-Outside Sample -- 4.4 Conclusion and Limitations -- 4.5 Future Research Directions -- 4.6 Annexure-Model Work/Details -- References -- 5 Building of an Application Reviews Classifier by BERT and Its Evaluation -- 5.1 Background -- 5.2 The Process of Building a Machine Learning Model -- 5.3 Dataset -- 5.4 Preprocessing -- 5.5 Feature Engineering -- 5.5.1 Bag of Words (BoW) [4] -- 5.5.2 FastText [5, 6] -- 5.5.3 Bidirectional Encoder Representations from Transformers (BERT) Embedding [7] -- 5.6 Machine-Learning Algorithms -- 5.6.1 Naive Bayes -- 5.6.2 Logistic Regression -- 5.6.3 BERT -- 5.7 Training and Evaluation Methods -- 5.8 Results -- 5.9 Discussion -- 5.9.1 Comparison of Classifier Performances -- 5.9.2 Performance of the Naive Bayes Classifiers -- 5.9.3 Performance of the Logistic Regression Classifiers -- 5.9.4 Visualization of Classifier Attention Using the BERT -- 5.10 Threats to Validity -- 5.10.1 Labeling Dataset -- 5.10.2 Parameter Tuning -- 5.11 Summary -- References -- 6 Harmony Search-Enhanced Software Architecture Reconstruction -- 6.1 Introduction -- 6.2 Related Work -- 6.3 HS Enhanced SAR -- 6.3.1 SAR Problem -- 6.3.2 HS Algorithm -- 6.3.3 Proposed Approach -- 6.4 Experimentation -- 6.4.1 Test Problems -- 6.4.2 Competitor approaches -- 6.5 Results and Discussion -- 6.6 Conclusion and Future Work -- References -- 7 Enterprise Architecture-Based Project Model for AI Service System Development -- 7.1 Introduction -- 7.2 Related Work -- 7.3 AI Servie System and Enterprise Architecture -- 7.3.1 AI Service System -- 7.3.2 Enterprise Architecture and AI Service System -- 7.4 Modeling Business IT Alignment for AI Service System -- 7.4.1 Generic Business-AI Alignment Model -- 7.4.2 Comparison with Project Canvas Model. 7.5 Business Analysis Method for Constructing Domain Specific Business-AI Alignment Model -- 7.5.1 Business Analysis Tables -- 7.5.2 Model Construction Method -- 7.6 Practice -- 7.6.1 Subject Project -- 7.6.2 Result -- 7.7 Discussion -- 7.8 Conclusion -- References -- Part III Software Engineering Tools to Develop Artificial Intelligence Applications -- 8 Requirements Engineering Processes for Multi-agent Systems -- 8.1 Introduction -- 8.2 Background -- 8.2.1 Agents, Multiagent Systems, and the BDI Model -- 8.2.2 Requirements Engineering -- 8.3 Techniques and Process of Requirements Engineering for Multiagent Systems -- 8.3.1 Elicitation Requirements Techniques for Multiagent Systems -- 8.3.2 Requirements Engineering Processes for Multiagent Systems -- 8.3.3 Requirements Validation -- 8.4 Conclusion -- References -- 9 Specific UML-Derived Languages for Modeling Multi-agent Systems -- 9.1 Introduction -- 9.2 Backgroud -- 9.2.1 UML -- 9.2.2 Agents, Multiagent Systems, and the BDI Model -- 9.2.3 BDI Models -- 9.3 AUML-Agent UML -- 9.4 AORML-Agent-Object-Relationship Modeling Language -- 9.4.1 Considerations About AORML -- 9.5 AML-Agent Modeling Language -- 9.5.1 Considerations About AML -- 9.6 MAS-ML-Multiagent System Modeling Language -- 9.6.1 Considerations About MAS-ML -- 9.7 SEA-ML-Semantic Web Enabled Agent Modeling Language -- 9.7.1 Considerations -- 9.8 MASRML-A Domain-Specific Modeling Language for Multi-agent Systems Requirements -- 9.8.1 Considerations -- References -- 10 Methods for Ensuring the Overall Safety of Machine Learning Systems -- 10.1 Introduction -- 10.2 Related Work -- 10.2.1 Safety of Machine Learning Systems -- 10.2.2 Conventional Safety Model -- 10.2.3 STAMP and Its Related Methods -- 10.2.4 Standards for Software Lifecycle Processes and System Lifecycle Processes -- 10.2.5 Social Technology Systems and Software Engineering. 10.2.6 Software Layer Architecture -- 10.2.7 Assurance Case -- 10.2.8 Autonomous Driving -- 10.3 Safety Issues in Machine Learning Systems -- 10.3.1 Eleven Reasons Why We Cannot Release Autonomous Driving Cars -- 10.3.2 Elicitation Method -- 10.3.3 Eleven Problems on Safety Assessment for Autonomous Driving Car Products -- 10.3.4 Validity to Threats -- 10.3.5 Safety Issues of Automatic Operation -- 10.3.6 Task Classification -- 10.3.7 Unclear Assurance Scope -- 10.3.8 Safety Assurance of the Entire System -- 10.3.9 Machine Learning and Systems -- 10.4 STAMP S& -- S Method -- 10.4.1 Significance of Layered Modeling of Complex Systems -- 10.4.2 STAMP S& -- S and Five Layers -- 10.4.3 Scenario -- 10.4.4 Specification and Standard -- 10.5 CC-Case -- 10.5.1 Definition of CC-Case -- 10.5.2 Technical Elements of CC-Case -- 10.6 Measures for Autonomous Driving -- 10.6.1 Relationship Between Issues and Measures Shown in This Section -- 10.6.2 Measure 1: Analyze Various Quality Attributes in Control Action Units -- 10.6.3 Measure 2: Modeling the Entire System -- 10.6.4 Measure 3: Scenario Analysis and Specification -- 10.6.5 Measure 4: Socio-Technical System -- 10.7 Considerations in Level 3 Autonomous Driving -- 10.7.1 Example of Autonomous Driving with the 5-layered Model of STAMP S& -- S -- 10.8 Conclusion -- References -- 11 MEAU: A Method for the Evaluation of the Artificial Unintelligence -- 11.1 Introduction -- 11.2 Machine Learning and Online Unintelligence: Improvisation or Programming? -- 11.3 The New Paradigm of Information from Digital Media and Social Networks -- 11.4 Numbers, Images and Texts: Sources of Errors, Misinformation and Unintelligence -- 11.5 MEAU: A Method for the Evaluation of the Artificial Unintelligence -- 11.6 Results -- 11.7 Lessons Learned -- 11.8 Conclusions -- Appendix 1 -- Appendix 2 -- Appendix 3 -- Appendix 4. References -- 12 Quantum Computing Meets Artificial Intelligence: Innovations and Challenges -- 12.1 Introduction -- 12.1.1 Benefits of Quantum Computing for AI -- 12.2 Quantum Computing Motivations -- 12.2.1 What Does ``Quantum'' Mean? -- 12.2.2 The Wave-Particle Duality -- 12.2.3 Qubit Definition -- 12.2.4 The Schrödinger Equation -- 12.2.5 Superposition -- 12.2.6 Interference -- 12.2.7 Entanglement -- 12.2.8 Gate-Based Quantum Computing -- 12.3 Quantum Machine Learning -- 12.3.1 Variational Quantum Algorithms -- 12.3.2 Data Encoding -- 12.3.3 Quantum Neural Networks -- 12.3.4 Quantum Support Vector Machine -- 12.3.5 Variational Quantum Generator -- 12.4 Quantum Computing Limitations and Challenges -- 12.4.1 Scalability and Connectivity -- 12.4.2 Decoherence -- 12.4.3 Error Correction -- 12.4.4 Qubit Control -- 12.5 Quantum AI Software Engineering -- 12.5.1 Hybrid Quantum-Classical Frameworks -- 12.5.2 Friction-Less Development Environment -- 12.5.3 Quantum AI Software Life Cycle -- 12.6 A new Problem Solving Approach -- 12.6.1 Use Case 1: Automation and Transportation Sector -- 12.6.2 Use Case 2: Food for the Future World -- 12.6.3 Use Case 3: Cheaper Reliable Batteries -- 12.6.4 Use Case 4: Cleaner Air to Breathe -- 12.6.5 Use Case 5: AI-Driven Financial Solutions -- 12.7 Summary and Conclusion -- References. |
| Record Nr. | UNINA-9910591037803321 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
