top

  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.

  Info

  • Utilizzare questo link per rimuovere la selezione effettuata.

Biblioteca

MARC Lista (tabellare)
Progress in Artificial Intelligence : 22nd EPIA Conference on Artificial Intelligence, EPIA 2023, Faial Island, Azores, September 5-8, 2023, Proceedings, Part I
Progress in Artificial Intelligence : 22nd EPIA Conference on Artificial Intelligence, EPIA 2023, Faial Island, Azores, September 5-8, 2023, Proceedings, Part I
Autore Moniz Nuno
Edizione [1st ed.]
Pubbl/distr/stampa Cham : , : Springer, , 2024
Descrizione fisica 1 online resource (551 pages)
Altri autori (Persone) ValeZita
CascalhoJosé
SilvaCatarina
SebastiãoRaquel
Collana Lecture Notes in Computer Science Series
ISBN 3-031-49008-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Keynotes -- Machine Learning Algorithms for Brain-Machine Interfaces -- Digital Twins of the Ocean -- On the Use (and Misuse) of Differential Privacy in Machine Learning -- Learning on Graphs -- Contents - Part I -- Contents - Part II -- Ambient Intelligence and Affective Environments -- Simulation-Based Adaptive Interface for Personalized Learning of AI Fundamentals in Secondary School -- 1 Introduction -- 2 Education About AI -- 3 The RoboboITS -- 3.1 RoboboITS Architecture -- 3.2 RoboboITS Operation -- 4 AI Lesson Implemented -- 5 Secondary School Validation -- 6 Conclusions -- References -- Gamified CollectiveEyes: A Gamified Distributed Infrastructure for Collectively Sharing People's Eyes -- 1 Introduction -- 2 Gamified CollectiveEyes -- 2.1 Seeing Several Viewpoints Simultaneously -- 2.2 Navigating Views with Gaze-Focused Gesture -- 2.3 Topic Channels -- 2.4 Thing-Focused and Value-Focused Topic Channel -- 2.5 Gamification Strategies in Gamified CollectiveEyes -- 3 A User Study for Motivation Management -- 3.1 Research Method -- 3.2 Effects of Topic Channels -- 3.3 Effects of Gamification -- 3.4 Effects of Consciousness -- 4 A User Study for Serendipity Management -- 4.1 Research Method -- 4.2 Effects of Serendipity -- 5 Related Work -- 6 Limitation of the Current Study -- 7 Conclusion and Future Work -- References -- Design and Development of Ontology for AI-Based Software Systems to Manage the Food Intake and Energy Consumption of Obesity, Diabetes and Tube Feeding Patients -- 1 Introduction -- 2 Related Works -- 2.1 FoodOn Ontology -- 2.2 Quisper Ontology -- 2.3 Ontology Based Food Recommendation -- 3 Methodology -- 3.1 Diabetes Use Case -- 3.2 Obesity Use Case -- 3.3 Tube Feeding Use Case -- 4 Proposed Ontology -- 5 Discussion -- 6 Conclusions -- References.
A System for Animal Health Monitoring and Emotions Detection -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 4 System Overview -- 5 Experiments -- 6 Results Evaluation -- 7 Future Works -- 8 Conclusion -- References -- Ethics and Responsibility in Artificial Intelligence -- A Three-Way Knot: Privacy, Fairness, and Predictive Performance Dynamics -- 1 Introduction -- 2 Background -- 2.1 Privacy -- 2.2 Fairness -- 2.3 Related Work -- 3 Experimental Study -- 3.1 Data -- 3.2 Methods -- 3.3 Experimental Results -- 4 Discussion -- 5 Conclusion -- References -- A Maturity Model for Industries and Organizations of All Types to Adopt Responsible AI-Preliminary Results -- 1 Introduction -- 1.1 Context and Justification -- 1.2 Why a Maturity Model for Responsible Artificial Intelligence (RAI)? -- 2 Methodology -- 3 The Maturity Model for Responsible AI -- 4 Implementation, Results and Discussion -- 5 Conclusions -- References -- Completeness of Datasets Documentation on ML/AI Repositories: An Empirical Investigation -- 1 Introduction and Motivation -- 2 Documentation Test Sheet from Related Works -- 2.1 Fields of Information -- 2.2 Measurement -- 3 Study Design -- 3.1 Repositories Under Analysis -- 3.2 Datasets Selection -- 4 Results and Discussion -- 4.1 Datasets Level -- 4.2 Sections Level -- 4.3 Test Fields Level -- 5 Threats to Validity and Limitations -- 6 Conclusions -- 7 Future Work -- References -- Navigating the Landscape of AI Ethics and Responsibility -- 1 Introduction -- 2 Research Methodology -- 3 Analysis of the Literature -- 4 Discussion -- 5 Conclusion -- References -- Towards Interpretability in Fintech Applications via Knowledge Augmentation -- 1 Introduction -- 2 Interpretability in Fintech -- 2.1 Interpretability Approaches -- 2.2 Surrogate Models -- 3 Knowledge Extraction and Augmentation -- 3.1 Knowledge Extraction Methods.
3.2 Knowledge Augmentation Methods -- 4 Proposed Approach -- 5 Experimental Setup -- 5.1 Evaluation Metrics -- 5.2 Case Studies -- 6 Analysis of Results -- 7 Conclusions and Future Work -- References -- General Artificial Intelligence -- Revisiting Deep Attention Recurrent Networks -- 1 Introduction -- 2 Related Work -- 2.1 Deep Attention Recurrent Q-Network -- 2.2 Soft Top-Down Spatial Attention -- 2.3 Similarities Between DARQN and STDA -- 3 Experimental Setup -- 3.1 Extensions to the DARQN Architecture -- 3.2 Top-Down Spatial Attention Agent -- 3.3 Training Setup -- 4 Experimental Results -- 4.1 Preliminary Results -- 4.2 Comparative Results (DARAC vs. TDA) -- 4.3 Visualization of the Attention Maps -- 4.4 Discussion -- 5 Conclusion -- References -- Pre-training with Augmentations for Efficient Transfer in Model-Based Reinforcement Learning -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Augmentation Scheme -- 3.2 Pre-training with Augmentations -- 4 Evaluation -- 4.1 Experimental Setup -- 4.2 Pre-training of Model-Based RL Agents -- 4.3 Atari Games -- 5 Conclusions -- References -- DyPrune: Dynamic Pruning Rates for Neural Networks -- 1 Introduction -- 2 Methodology -- 2.1 Dataset -- 2.2 Pruning Weights -- 2.3 Removing Neurons -- 3 Results -- 4 Discussion -- 5 Conclusions -- References -- Robustness Analysis of Machine Learning Models Using Domain-Specific Test Data Perturbation -- 1 Introduction -- 2 Literature Review -- 2.1 Image -- 2.2 Audio -- 2.3 Text -- 3 Experimental Setup -- 4 Results -- 5 Conclusion -- References -- Vocalization Features to Recognize Small Dolphin Species for Limited Datasets -- 1 Introduction and Related Work -- 2 Features -- 2.1 The Spectral Analysis Features -- 2.2 The Contour Analysis Features -- 3 Classification -- 3.1 Data -- 3.2 The Training Phase -- 4 Results and Discussion -- 5 Conclusion -- References.
Covariance Kernel Learning Schemes for Gaussian Process Based Prediction Using Markov Chain Monte Carlo -- 1 Introduction -- 2 Model -- 3 Empirical Illustration -- 3.1 Model for Univariate Case -- 3.2 Model for Multivariate Case -- 3.3 New Nonparametric Kernel -- 4 Results -- 5 Conclusion -- References -- Intelligent Robotics -- A Review on Quadruped Manipulators -- 1 Introduction -- 2 Methodology -- 3 Quadruped Manipulators -- 3.1 Leg-Arm Approaches -- 3.2 Robotic Arm Addition -- 4 Motion Planning -- 4.1 Separate Systems (SS) -- 4.2 Combined Systems (CS) -- 4.3 Discussion -- 5 Kinematic Configuration -- 6 Conclusions -- References -- Knowledge Discovery and Business Intelligence -- Pollution Emission Patterns of Transportation in Porto, Portugal Through Network Analysis -- 1 Introduction -- 2 Related Work -- 3 Data and Methods -- 3.1 Data Pre-processing -- 3.2 Road Transportation and Emission Network -- 4 Experimental Results -- 4.1 Emissions over Porto -- 4.2 Road Network Analysis -- 4.3 Discussion -- 5 Conclusion and Future Work -- References -- Analysis of Dam Natural Frequencies Using a Convolutional Neural Network -- 1 Introduction -- 2 Case Study: Cabril Dam -- 2.1 Dam Description -- 2.2 Continuous Vibration Monitoring System -- 3 Supervised Convolutional Neural Network (CNN) Proposed for the Analysis of Dam Natural Frequencies -- 3.1 Dataset -- 3.2 Main Model -- 3.3 CNN Hyperparameter Tuning -- 4 Results: Analysis of Natural Frequencies of Cabril Dam -- 5 Conclusion and Future Work -- References -- Imbalanced Regression Evaluation Under Uncertain Domain Preferences -- 1 Introduction -- 2 Imbalanced Regression -- 2.1 Relevance Functions -- 2.2 Evaluation -- 3 Sensitivity Evaluation and Relevance Uncertainty -- 4 Experimental Study -- 4.1 Methods -- 4.2 Results -- 5 Conclusions and Future Work -- References.
Studying the Impact of Sampling in Highly Frequent Time Series -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 4 Experimental Setup -- 4.1 Algorithm -- 4.2 Datasets -- 4.3 Missing Data -- 4.4 Evaluation -- 5 Experiments -- 6 Results and Discussion -- 7 Conclusion and Future Work -- References -- Mining Causal Links Between TV Sports Content and Real-World Data -- 1 Introduction -- 2 Literature Review -- 3 Data -- 4 Methods -- 4.1 Granger Causality Test -- 4.2 Causal Analysis of TV Viewership in Liga NOS -- 5 Results and Discussion -- 6 Conclusion -- References -- Hybrid SkipAwareRec: A Streaming Music Recommendation System -- 1 Introduction -- 2 Related Work -- 2.1 Recommendations with Negative Implicit Feedback -- 2.2 Sequential Music Recommendation -- 3 Methodology and Proposed Solution -- 3.1 Action Set Generation -- 3.2 Next Best Action Recommendation -- 3.3 Next Best Items Recommendation -- 4 Experiments and Results -- 4.1 Data Setup and Model Training -- 4.2 Evaluation -- 5 Conclusions and Future Work -- References -- Interpreting What is Important: An Explainability Approach and Study on Feature Selection -- 1 Introduction -- 2 Related Works -- 3 Datasets and Methods -- 3.1 Rossmann Store Sales -- 3.2 Bike Sharing Dataset -- 3.3 Data Exploration -- 3.4 LSTM Hyperparameter Tunning -- 3.5 SHAP Method Implementation -- 4 Experiments, Results, and Discussion -- 4.1 Experimental Setup -- 4.2 Experimental Procedure -- 4.3 Results -- 4.4 Discussion -- 5 Conclusion and Future Work -- References -- Time-Series Pattern Verification in CNC Machining Data -- 1 Introduction -- 2 Background -- 2.1 CNC Machining and Offset Adjustment in Turning -- 2.2 Feature Extraction and Linear Frequency Cepstral Coefficients -- 2.3 One-Class Classification -- 3 Methodology -- 4 Results and Discussion -- 5 Conclusion -- References.
A Comparison of Automated Machine Learning Tools for Predicting Energy Building Consumption in Smart Cities.
Record Nr. UNINA-9910770258303321
Moniz Nuno  
Cham : , : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Progress in Artificial Intelligence : 22nd EPIA Conference on Artificial Intelligence, EPIA 2023, Faial Island, Azores, September 5-8, 2023, Proceedings, Part II
Progress in Artificial Intelligence : 22nd EPIA Conference on Artificial Intelligence, EPIA 2023, Faial Island, Azores, September 5-8, 2023, Proceedings, Part II
Autore Moniz Nuno
Edizione [1st ed.]
Pubbl/distr/stampa Cham : , : Springer, , 2024
Descrizione fisica 1 online resource (606 pages)
Altri autori (Persone) ValeZita
CascalhoJosé
SilvaCatarina
SebastiãoRaquel
Collana Lecture Notes in Computer Science Series
ISBN 3-031-49011-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Keynotes -- Machine Learning Algorithms for Brain-Machine Interfaces -- Digital Twins of the Ocean -- On the Use (and Misuse) of Differential Privacy in Machine Learning -- Learning on Graphs -- Contents - Part II -- Contents - Part I -- Artifical Intelligence, Generation and Creativity -- Erato: Automatizing Poetry Evaluation -- 1 Introduction -- 2 Related Work -- 3 What Characterizes a Good Poem? -- 4 Erato: A Framework for Poetry Evaluation -- 4.1 General Structure -- 4.2 Available Modules -- 4.3 Extending Erato for Specific Purposes -- 5 Case Study: Human and Machine Poetry -- 5.1 Computer-Generated Poetry -- 5.2 Human-Written Poetry -- 5.3 Analysis -- 6 Conclusion and Future Directions -- References -- A Path to Generative Artificial Selves -- 1 Introduction -- 2 Creativity as Restructuring a Manifold -- 3 Selfhood -- 4 Reflexively Autocatalytic Foodset-Derived Networks (RAFs) -- 5 RAF Models of Emergent Cognition -- 6 Discussion -- 6.1 Related Research -- 6.2 Future Work: Experimental Testing and Validation -- 7 Conclusions -- References -- Human+Non-human Creative Identities. Symbiotic Synthesis in Industrial Design Creative Processes -- 1 Technologies and Creative Processes -- 2 AI-Tools and Design Practice -- 3 An Evolving Symbiotic Creative Ecology -- References -- AIGenC: AI Generalisation via Creativity -- 1 Introduction -- 2 Functional Creativity, Concept Space and Affordances -- 3 A Framework for Concept Transfer and Functional Creativity -- 3.1 Deep Reinforcement Learning -- 3.2 Concept Processing Component -- 3.3 Reflective Reasoning Component -- 3.4 Blending Component -- 4 Discussion -- References -- Creativity, Intentions, and Self-Narratives: Can AI Really Be Creative? -- 1 Introduction -- 2 Creativity -- 3 Process Creativity and Intentions -- 4 Intentions and AI.
5 Creativity in the Prompts -- 6 Self-Narratives -- 7 Conclusion -- References -- Evolving Urban Landscapes -- 1 Introduction -- 2 Related Work -- 3 Approach -- 3.1 Visual Grammar -- 3.2 Lexicon -- 3.3 Rules -- 3.4 Implementation -- 4 Assessing Creativity -- 4.1 Definition of Creativity -- 4.2 Creativity in the Context of Our System -- 4.3 Questionnaire -- 4.4 Results Analysis -- 5 Final Remarks -- References -- Emotion4MIDI: A Lyrics-Based Emotion-Labeled Symbolic Music Dataset -- 1 Introduction -- 2 Related Work -- 2.1 Text Emotion Classification -- 2.2 Emotion-Labeled Symbolic Music Datasets -- 3 Methodology -- 3.1 Model -- 3.2 Training -- 3.3 Inference -- 4 Results -- 4.1 Emotion Classification on the GoEmotions Dataset -- 4.2 Labeled MIDI Dataset -- 5 Conclusion and Future Work -- References -- Artificial Intelligence and Law -- On the Assessment of Deep Learning Models for Named Entity Recognition of Brazilian Legal Documents -- 1 Introduction -- 2 Related Works -- 3 Method -- 3.1 Hyperparameters Tuning -- 4 Results and Discussion -- 4.1 Experimental Setup -- 4.2 Hyperparameters Evaluation for LeNER-Br -- 4.3 Hyperparameter Evaluation for PL-Corpus -- 4.4 Comparison and Discussion -- 5 Conclusion and Future Works -- References -- Anonymisation of Judicial Rulings for Legal Analytics Purposes: Ethics, Law, and Compliance -- 1 Introduction -- 2 Advancements and Benefits of Legal Analytics -- 2.1 A Case Study: The Legal Analytics for Italian Law (LAILA) Project -- 3 Anonymisation of Judicial Rulings for Legal Analytics Purposes -- 3.1 The Legal Framework -- 3.2 Anonymisation Measures Taken by Judicial Offices -- 3.3 Anonymisation of Court Decisions in the Context of the LAILA Project -- 4 Conclusions: At the Crossroads of Law and Ethics -- References -- LeSSE-A Semantic Search Engine Applied to Portuguese Consumer Law -- 1 Introduction.
2 Related Work -- 3 Legal Semantic Search Engine -- 3.1 Datasets -- 3.2 System Overview -- 3.3 Semantic Pipeline -- 3.4 Lexical Pipeline -- 3.5 Results Selection and Presentation -- 3.6 Model Training and Optimization -- 4 Performance of LeSSE in Consumer Law -- 5 Performance of LeSSE in the Absence of Manual Annotations -- 6 Conclusions and Future Work -- References -- Does ChatGPT Pass the Brazilian Bar Exam? -- 1 Introduction -- 2 GPT in Law -- 3 Experiment Design -- 4 Results and Discussion -- 5 Conclusions and Further Work -- References -- A Semantic Search System for the Supremo Tribunal de Justiça -- 1 Introduction -- 2 Related Work -- 3 Data -- 4 Semantic Search System Architecture -- 5 Legal Language Model -- 5.1 Domain Adaptation -- 5.2 Semantic Textual Similarity -- 5.3 Natural Language Inference -- 5.4 Multilingual Knowledge Distillation -- 5.5 Metadata Knowledge Distillation -- 6 Evaluation -- 6.1 Language Model Evaluation -- 6.2 Search System Evaluation -- 7 Conclusion -- References -- Artificial Intelligence in Power and Energy Systems -- The AI Act Meets General Purpose AI: The Good, The Bad and The Uncertain -- 1 AI Act: The Regulation of GPAI -- 1.1 Context -- 1.2 Definition: Dimensions of Generality -- 1.3 Regulation: Challenges and Risks -- 2 AIA Draft -- 2.1 AI Requirements and Obligations -- 2.2 Key Elements: Value Chain and Cooperation -- 2.3 Exemptions -- 3 Conclusions -- References -- Rule-Based System for Intelligent Energy Management in Buildings -- 1 Introduction -- 2 Proposed Model -- 2.1 Power Consumption State Ruleset -- 2.2 Air Conditioning System Ruleset -- 2.3 Brightness Ruleset -- 3 Rulesets Evaluation -- 3.1 Consumption State Ruleset -- 3.2 Brightness Ruleset Case Study -- 3.3 Air Conditioning System Ruleset Case Study -- 4 Conclusions -- References.
Production Scheduling for Total Energy Cost and Machine Longevity Optimization Through a Genetic Algorithm -- 1 Introduction -- 2 Related Works -- 3 Proposed Methodology -- 4 Genetic Algorithm Implementation -- 4.1 Initial Population Procedure -- 4.2 Crossover Procedure -- 4.3 Mutation Procedure -- 4.4 Selection Procedure -- 5 Case Study -- 6 Results and Discussion -- 7 Conclusions -- References -- A Novel Federated Learning Approach to Enable Distributed and Collaborative Genetic Programming -- 1 Introduction -- 2 Genetic Programming -- 3 Federated Learning -- 4 Methodology -- 5 Case Study -- 6 Discussion and Results -- 7 Conclusion -- References -- Artificial Intelligence in Medicine -- A Scoping Review of Energy Load Disaggregation -- 1 Introduction -- 2 Methodology -- 3 Results -- 3.1 Applied Domains -- 3.2 Data and Data Sources -- 3.3 Related Methods -- 4 Discussion -- 5 Conclusion -- References -- Deep Learning Survival Model to Predict Atrial Fibrillation From ECGs and EHR Data -- 1 Introduction -- 2 Materials and Methods -- 2.1 Data -- 2.2 Model Development -- 2.3 Experimental Setting -- 2.4 Evaluation Metrics -- 3 Results -- 4 Discussion -- 5 Conclusion -- References -- Generalization Ability in Medical Image Analysis with Small-Scale Imbalanced Datasets: Insights from Neural Network Learning -- 1 Introduction -- 2 Methods -- 2.1 Definition of Neural Network Architecture Components -- 2.2 Generalization Ability -- 2.3 Model Complexity -- 3 Results and Discussion -- 4 Conclusion -- References -- Multi-omics Data Integration and Network Inference for Biomarker Discovery in Glioma -- 1 Introduction -- 2 Materials and Methods -- 2.1 Graphical Lasso -- 2.2 Network Distance -- 2.3 Data Description -- 2.4 Pipeline and Implementation -- 2.5 Network Validation -- 3 Results -- 3.1 Variable Selection -- 3.2 Protein Networks -- 3.3 Validation Outcomes.
4 Discussion -- References -- Better Medical Efficiency by Means of Hospital Bed Management Optimization-A Comparison of Artificial Intelligence Techniques -- 1 Introduction -- 2 Background -- 2.1 Resources Planning in Hospital Settings -- 2.2 Related Work -- 3 Materials and Methods -- 3.1 Methodologies -- 3.2 Tools and Algorithms -- 3.3 Data Sets -- 4 Experiments -- 4.1 Problem Formulation -- 4.2 Data Provided -- 4.3 Data Preparation -- 4.4 Domain and Fitness Function -- 4.5 Optimization Techniques -- 4.6 Evaluation -- 5 Results and Discussion -- 5.1 Algorithm Settings -- 5.2 Results -- 6 Conclusions -- References -- AI-Based Medical Scribe to Support Clinical Consultations: A Proposed System Architecture -- 1 Introduction -- 2 Literature Review -- 2.1 Digital Medical Scribe -- 2.2 Automatic Speech Recognition and Natural Language Processing Algorithms -- 3 System Architecture -- 4 Conclusion and Further Work -- References -- Combining Neighbor Models to Improve Predictions of Age of Onset of ATTRv Carriers -- 1 Introduction -- 2 Background -- 2.1 Ensemble Learning -- 2.2 Related Work -- 3 Single Learning Approach and Combination Strategies -- 3.1 Prediction Problem and Single Learning Approach -- 3.2 Data and Evaluation Strategy -- 3.3 Combination Strategies -- 3.4 Evaluation -- 4 Results and Discussion -- 5 Conclusions and Future Work -- References -- Unravelling Heterogeneity: A Hybrid Machine Learning Approach to Predict Post-discharge Complications in Cardiothoracic Surgery -- 1 Background -- 2 Dataset -- 3 Methodology -- 3.1 Unsupervised Learning Strategy -- 3.2 Supervised Learning Strategy -- 4 Results -- 4.1 Clustering -- 4.2 Classification -- 5 Discussion -- 6 Conclusion -- References -- Leveraging TFR-BERT for ICD Diagnoses Ranking -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Overview -- 3.2 Learning-to-Rank System.
3.3 Fine-Tuned Language Representation Model.
Record Nr. UNINA-9910770269303321
Moniz Nuno  
Cham : , : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Progress in Artificial Intelligence : 22nd EPIA Conference on Artificial Intelligence, EPIA 2023, Faial Island, Azores, September 5-8, 2023, Proceedings, Part I
Progress in Artificial Intelligence : 22nd EPIA Conference on Artificial Intelligence, EPIA 2023, Faial Island, Azores, September 5-8, 2023, Proceedings, Part I
Autore Moniz Nuno
Edizione [1st ed.]
Pubbl/distr/stampa Cham : , : Springer, , 2024
Descrizione fisica 1 online resource (551 pages)
Altri autori (Persone) ValeZita
CascalhoJosé
SilvaCatarina
SebastiãoRaquel
Collana Lecture Notes in Computer Science Series
ISBN 3-031-49008-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Keynotes -- Machine Learning Algorithms for Brain-Machine Interfaces -- Digital Twins of the Ocean -- On the Use (and Misuse) of Differential Privacy in Machine Learning -- Learning on Graphs -- Contents - Part I -- Contents - Part II -- Ambient Intelligence and Affective Environments -- Simulation-Based Adaptive Interface for Personalized Learning of AI Fundamentals in Secondary School -- 1 Introduction -- 2 Education About AI -- 3 The RoboboITS -- 3.1 RoboboITS Architecture -- 3.2 RoboboITS Operation -- 4 AI Lesson Implemented -- 5 Secondary School Validation -- 6 Conclusions -- References -- Gamified CollectiveEyes: A Gamified Distributed Infrastructure for Collectively Sharing People's Eyes -- 1 Introduction -- 2 Gamified CollectiveEyes -- 2.1 Seeing Several Viewpoints Simultaneously -- 2.2 Navigating Views with Gaze-Focused Gesture -- 2.3 Topic Channels -- 2.4 Thing-Focused and Value-Focused Topic Channel -- 2.5 Gamification Strategies in Gamified CollectiveEyes -- 3 A User Study for Motivation Management -- 3.1 Research Method -- 3.2 Effects of Topic Channels -- 3.3 Effects of Gamification -- 3.4 Effects of Consciousness -- 4 A User Study for Serendipity Management -- 4.1 Research Method -- 4.2 Effects of Serendipity -- 5 Related Work -- 6 Limitation of the Current Study -- 7 Conclusion and Future Work -- References -- Design and Development of Ontology for AI-Based Software Systems to Manage the Food Intake and Energy Consumption of Obesity, Diabetes and Tube Feeding Patients -- 1 Introduction -- 2 Related Works -- 2.1 FoodOn Ontology -- 2.2 Quisper Ontology -- 2.3 Ontology Based Food Recommendation -- 3 Methodology -- 3.1 Diabetes Use Case -- 3.2 Obesity Use Case -- 3.3 Tube Feeding Use Case -- 4 Proposed Ontology -- 5 Discussion -- 6 Conclusions -- References.
A System for Animal Health Monitoring and Emotions Detection -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 4 System Overview -- 5 Experiments -- 6 Results Evaluation -- 7 Future Works -- 8 Conclusion -- References -- Ethics and Responsibility in Artificial Intelligence -- A Three-Way Knot: Privacy, Fairness, and Predictive Performance Dynamics -- 1 Introduction -- 2 Background -- 2.1 Privacy -- 2.2 Fairness -- 2.3 Related Work -- 3 Experimental Study -- 3.1 Data -- 3.2 Methods -- 3.3 Experimental Results -- 4 Discussion -- 5 Conclusion -- References -- A Maturity Model for Industries and Organizations of All Types to Adopt Responsible AI-Preliminary Results -- 1 Introduction -- 1.1 Context and Justification -- 1.2 Why a Maturity Model for Responsible Artificial Intelligence (RAI)? -- 2 Methodology -- 3 The Maturity Model for Responsible AI -- 4 Implementation, Results and Discussion -- 5 Conclusions -- References -- Completeness of Datasets Documentation on ML/AI Repositories: An Empirical Investigation -- 1 Introduction and Motivation -- 2 Documentation Test Sheet from Related Works -- 2.1 Fields of Information -- 2.2 Measurement -- 3 Study Design -- 3.1 Repositories Under Analysis -- 3.2 Datasets Selection -- 4 Results and Discussion -- 4.1 Datasets Level -- 4.2 Sections Level -- 4.3 Test Fields Level -- 5 Threats to Validity and Limitations -- 6 Conclusions -- 7 Future Work -- References -- Navigating the Landscape of AI Ethics and Responsibility -- 1 Introduction -- 2 Research Methodology -- 3 Analysis of the Literature -- 4 Discussion -- 5 Conclusion -- References -- Towards Interpretability in Fintech Applications via Knowledge Augmentation -- 1 Introduction -- 2 Interpretability in Fintech -- 2.1 Interpretability Approaches -- 2.2 Surrogate Models -- 3 Knowledge Extraction and Augmentation -- 3.1 Knowledge Extraction Methods.
3.2 Knowledge Augmentation Methods -- 4 Proposed Approach -- 5 Experimental Setup -- 5.1 Evaluation Metrics -- 5.2 Case Studies -- 6 Analysis of Results -- 7 Conclusions and Future Work -- References -- General Artificial Intelligence -- Revisiting Deep Attention Recurrent Networks -- 1 Introduction -- 2 Related Work -- 2.1 Deep Attention Recurrent Q-Network -- 2.2 Soft Top-Down Spatial Attention -- 2.3 Similarities Between DARQN and STDA -- 3 Experimental Setup -- 3.1 Extensions to the DARQN Architecture -- 3.2 Top-Down Spatial Attention Agent -- 3.3 Training Setup -- 4 Experimental Results -- 4.1 Preliminary Results -- 4.2 Comparative Results (DARAC vs. TDA) -- 4.3 Visualization of the Attention Maps -- 4.4 Discussion -- 5 Conclusion -- References -- Pre-training with Augmentations for Efficient Transfer in Model-Based Reinforcement Learning -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Augmentation Scheme -- 3.2 Pre-training with Augmentations -- 4 Evaluation -- 4.1 Experimental Setup -- 4.2 Pre-training of Model-Based RL Agents -- 4.3 Atari Games -- 5 Conclusions -- References -- DyPrune: Dynamic Pruning Rates for Neural Networks -- 1 Introduction -- 2 Methodology -- 2.1 Dataset -- 2.2 Pruning Weights -- 2.3 Removing Neurons -- 3 Results -- 4 Discussion -- 5 Conclusions -- References -- Robustness Analysis of Machine Learning Models Using Domain-Specific Test Data Perturbation -- 1 Introduction -- 2 Literature Review -- 2.1 Image -- 2.2 Audio -- 2.3 Text -- 3 Experimental Setup -- 4 Results -- 5 Conclusion -- References -- Vocalization Features to Recognize Small Dolphin Species for Limited Datasets -- 1 Introduction and Related Work -- 2 Features -- 2.1 The Spectral Analysis Features -- 2.2 The Contour Analysis Features -- 3 Classification -- 3.1 Data -- 3.2 The Training Phase -- 4 Results and Discussion -- 5 Conclusion -- References.
Covariance Kernel Learning Schemes for Gaussian Process Based Prediction Using Markov Chain Monte Carlo -- 1 Introduction -- 2 Model -- 3 Empirical Illustration -- 3.1 Model for Univariate Case -- 3.2 Model for Multivariate Case -- 3.3 New Nonparametric Kernel -- 4 Results -- 5 Conclusion -- References -- Intelligent Robotics -- A Review on Quadruped Manipulators -- 1 Introduction -- 2 Methodology -- 3 Quadruped Manipulators -- 3.1 Leg-Arm Approaches -- 3.2 Robotic Arm Addition -- 4 Motion Planning -- 4.1 Separate Systems (SS) -- 4.2 Combined Systems (CS) -- 4.3 Discussion -- 5 Kinematic Configuration -- 6 Conclusions -- References -- Knowledge Discovery and Business Intelligence -- Pollution Emission Patterns of Transportation in Porto, Portugal Through Network Analysis -- 1 Introduction -- 2 Related Work -- 3 Data and Methods -- 3.1 Data Pre-processing -- 3.2 Road Transportation and Emission Network -- 4 Experimental Results -- 4.1 Emissions over Porto -- 4.2 Road Network Analysis -- 4.3 Discussion -- 5 Conclusion and Future Work -- References -- Analysis of Dam Natural Frequencies Using a Convolutional Neural Network -- 1 Introduction -- 2 Case Study: Cabril Dam -- 2.1 Dam Description -- 2.2 Continuous Vibration Monitoring System -- 3 Supervised Convolutional Neural Network (CNN) Proposed for the Analysis of Dam Natural Frequencies -- 3.1 Dataset -- 3.2 Main Model -- 3.3 CNN Hyperparameter Tuning -- 4 Results: Analysis of Natural Frequencies of Cabril Dam -- 5 Conclusion and Future Work -- References -- Imbalanced Regression Evaluation Under Uncertain Domain Preferences -- 1 Introduction -- 2 Imbalanced Regression -- 2.1 Relevance Functions -- 2.2 Evaluation -- 3 Sensitivity Evaluation and Relevance Uncertainty -- 4 Experimental Study -- 4.1 Methods -- 4.2 Results -- 5 Conclusions and Future Work -- References.
Studying the Impact of Sampling in Highly Frequent Time Series -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 4 Experimental Setup -- 4.1 Algorithm -- 4.2 Datasets -- 4.3 Missing Data -- 4.4 Evaluation -- 5 Experiments -- 6 Results and Discussion -- 7 Conclusion and Future Work -- References -- Mining Causal Links Between TV Sports Content and Real-World Data -- 1 Introduction -- 2 Literature Review -- 3 Data -- 4 Methods -- 4.1 Granger Causality Test -- 4.2 Causal Analysis of TV Viewership in Liga NOS -- 5 Results and Discussion -- 6 Conclusion -- References -- Hybrid SkipAwareRec: A Streaming Music Recommendation System -- 1 Introduction -- 2 Related Work -- 2.1 Recommendations with Negative Implicit Feedback -- 2.2 Sequential Music Recommendation -- 3 Methodology and Proposed Solution -- 3.1 Action Set Generation -- 3.2 Next Best Action Recommendation -- 3.3 Next Best Items Recommendation -- 4 Experiments and Results -- 4.1 Data Setup and Model Training -- 4.2 Evaluation -- 5 Conclusions and Future Work -- References -- Interpreting What is Important: An Explainability Approach and Study on Feature Selection -- 1 Introduction -- 2 Related Works -- 3 Datasets and Methods -- 3.1 Rossmann Store Sales -- 3.2 Bike Sharing Dataset -- 3.3 Data Exploration -- 3.4 LSTM Hyperparameter Tunning -- 3.5 SHAP Method Implementation -- 4 Experiments, Results, and Discussion -- 4.1 Experimental Setup -- 4.2 Experimental Procedure -- 4.3 Results -- 4.4 Discussion -- 5 Conclusion and Future Work -- References -- Time-Series Pattern Verification in CNC Machining Data -- 1 Introduction -- 2 Background -- 2.1 CNC Machining and Offset Adjustment in Turning -- 2.2 Feature Extraction and Linear Frequency Cepstral Coefficients -- 2.3 One-Class Classification -- 3 Methodology -- 4 Results and Discussion -- 5 Conclusion -- References.
A Comparison of Automated Machine Learning Tools for Predicting Energy Building Consumption in Smart Cities.
Record Nr. UNISA-996574259003316
Moniz Nuno  
Cham : , : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Progress in Artificial Intelligence : 22nd EPIA Conference on Artificial Intelligence, EPIA 2023, Faial Island, Azores, September 5-8, 2023, Proceedings, Part II
Progress in Artificial Intelligence : 22nd EPIA Conference on Artificial Intelligence, EPIA 2023, Faial Island, Azores, September 5-8, 2023, Proceedings, Part II
Autore Moniz Nuno
Edizione [1st ed.]
Pubbl/distr/stampa Cham : , : Springer, , 2024
Descrizione fisica 1 online resource (606 pages)
Altri autori (Persone) ValeZita
CascalhoJosé
SilvaCatarina
SebastiãoRaquel
Collana Lecture Notes in Computer Science Series
ISBN 3-031-49011-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Keynotes -- Machine Learning Algorithms for Brain-Machine Interfaces -- Digital Twins of the Ocean -- On the Use (and Misuse) of Differential Privacy in Machine Learning -- Learning on Graphs -- Contents - Part II -- Contents - Part I -- Artifical Intelligence, Generation and Creativity -- Erato: Automatizing Poetry Evaluation -- 1 Introduction -- 2 Related Work -- 3 What Characterizes a Good Poem? -- 4 Erato: A Framework for Poetry Evaluation -- 4.1 General Structure -- 4.2 Available Modules -- 4.3 Extending Erato for Specific Purposes -- 5 Case Study: Human and Machine Poetry -- 5.1 Computer-Generated Poetry -- 5.2 Human-Written Poetry -- 5.3 Analysis -- 6 Conclusion and Future Directions -- References -- A Path to Generative Artificial Selves -- 1 Introduction -- 2 Creativity as Restructuring a Manifold -- 3 Selfhood -- 4 Reflexively Autocatalytic Foodset-Derived Networks (RAFs) -- 5 RAF Models of Emergent Cognition -- 6 Discussion -- 6.1 Related Research -- 6.2 Future Work: Experimental Testing and Validation -- 7 Conclusions -- References -- Human+Non-human Creative Identities. Symbiotic Synthesis in Industrial Design Creative Processes -- 1 Technologies and Creative Processes -- 2 AI-Tools and Design Practice -- 3 An Evolving Symbiotic Creative Ecology -- References -- AIGenC: AI Generalisation via Creativity -- 1 Introduction -- 2 Functional Creativity, Concept Space and Affordances -- 3 A Framework for Concept Transfer and Functional Creativity -- 3.1 Deep Reinforcement Learning -- 3.2 Concept Processing Component -- 3.3 Reflective Reasoning Component -- 3.4 Blending Component -- 4 Discussion -- References -- Creativity, Intentions, and Self-Narratives: Can AI Really Be Creative? -- 1 Introduction -- 2 Creativity -- 3 Process Creativity and Intentions -- 4 Intentions and AI.
5 Creativity in the Prompts -- 6 Self-Narratives -- 7 Conclusion -- References -- Evolving Urban Landscapes -- 1 Introduction -- 2 Related Work -- 3 Approach -- 3.1 Visual Grammar -- 3.2 Lexicon -- 3.3 Rules -- 3.4 Implementation -- 4 Assessing Creativity -- 4.1 Definition of Creativity -- 4.2 Creativity in the Context of Our System -- 4.3 Questionnaire -- 4.4 Results Analysis -- 5 Final Remarks -- References -- Emotion4MIDI: A Lyrics-Based Emotion-Labeled Symbolic Music Dataset -- 1 Introduction -- 2 Related Work -- 2.1 Text Emotion Classification -- 2.2 Emotion-Labeled Symbolic Music Datasets -- 3 Methodology -- 3.1 Model -- 3.2 Training -- 3.3 Inference -- 4 Results -- 4.1 Emotion Classification on the GoEmotions Dataset -- 4.2 Labeled MIDI Dataset -- 5 Conclusion and Future Work -- References -- Artificial Intelligence and Law -- On the Assessment of Deep Learning Models for Named Entity Recognition of Brazilian Legal Documents -- 1 Introduction -- 2 Related Works -- 3 Method -- 3.1 Hyperparameters Tuning -- 4 Results and Discussion -- 4.1 Experimental Setup -- 4.2 Hyperparameters Evaluation for LeNER-Br -- 4.3 Hyperparameter Evaluation for PL-Corpus -- 4.4 Comparison and Discussion -- 5 Conclusion and Future Works -- References -- Anonymisation of Judicial Rulings for Legal Analytics Purposes: Ethics, Law, and Compliance -- 1 Introduction -- 2 Advancements and Benefits of Legal Analytics -- 2.1 A Case Study: The Legal Analytics for Italian Law (LAILA) Project -- 3 Anonymisation of Judicial Rulings for Legal Analytics Purposes -- 3.1 The Legal Framework -- 3.2 Anonymisation Measures Taken by Judicial Offices -- 3.3 Anonymisation of Court Decisions in the Context of the LAILA Project -- 4 Conclusions: At the Crossroads of Law and Ethics -- References -- LeSSE-A Semantic Search Engine Applied to Portuguese Consumer Law -- 1 Introduction.
2 Related Work -- 3 Legal Semantic Search Engine -- 3.1 Datasets -- 3.2 System Overview -- 3.3 Semantic Pipeline -- 3.4 Lexical Pipeline -- 3.5 Results Selection and Presentation -- 3.6 Model Training and Optimization -- 4 Performance of LeSSE in Consumer Law -- 5 Performance of LeSSE in the Absence of Manual Annotations -- 6 Conclusions and Future Work -- References -- Does ChatGPT Pass the Brazilian Bar Exam? -- 1 Introduction -- 2 GPT in Law -- 3 Experiment Design -- 4 Results and Discussion -- 5 Conclusions and Further Work -- References -- A Semantic Search System for the Supremo Tribunal de Justiça -- 1 Introduction -- 2 Related Work -- 3 Data -- 4 Semantic Search System Architecture -- 5 Legal Language Model -- 5.1 Domain Adaptation -- 5.2 Semantic Textual Similarity -- 5.3 Natural Language Inference -- 5.4 Multilingual Knowledge Distillation -- 5.5 Metadata Knowledge Distillation -- 6 Evaluation -- 6.1 Language Model Evaluation -- 6.2 Search System Evaluation -- 7 Conclusion -- References -- Artificial Intelligence in Power and Energy Systems -- The AI Act Meets General Purpose AI: The Good, The Bad and The Uncertain -- 1 AI Act: The Regulation of GPAI -- 1.1 Context -- 1.2 Definition: Dimensions of Generality -- 1.3 Regulation: Challenges and Risks -- 2 AIA Draft -- 2.1 AI Requirements and Obligations -- 2.2 Key Elements: Value Chain and Cooperation -- 2.3 Exemptions -- 3 Conclusions -- References -- Rule-Based System for Intelligent Energy Management in Buildings -- 1 Introduction -- 2 Proposed Model -- 2.1 Power Consumption State Ruleset -- 2.2 Air Conditioning System Ruleset -- 2.3 Brightness Ruleset -- 3 Rulesets Evaluation -- 3.1 Consumption State Ruleset -- 3.2 Brightness Ruleset Case Study -- 3.3 Air Conditioning System Ruleset Case Study -- 4 Conclusions -- References.
Production Scheduling for Total Energy Cost and Machine Longevity Optimization Through a Genetic Algorithm -- 1 Introduction -- 2 Related Works -- 3 Proposed Methodology -- 4 Genetic Algorithm Implementation -- 4.1 Initial Population Procedure -- 4.2 Crossover Procedure -- 4.3 Mutation Procedure -- 4.4 Selection Procedure -- 5 Case Study -- 6 Results and Discussion -- 7 Conclusions -- References -- A Novel Federated Learning Approach to Enable Distributed and Collaborative Genetic Programming -- 1 Introduction -- 2 Genetic Programming -- 3 Federated Learning -- 4 Methodology -- 5 Case Study -- 6 Discussion and Results -- 7 Conclusion -- References -- Artificial Intelligence in Medicine -- A Scoping Review of Energy Load Disaggregation -- 1 Introduction -- 2 Methodology -- 3 Results -- 3.1 Applied Domains -- 3.2 Data and Data Sources -- 3.3 Related Methods -- 4 Discussion -- 5 Conclusion -- References -- Deep Learning Survival Model to Predict Atrial Fibrillation From ECGs and EHR Data -- 1 Introduction -- 2 Materials and Methods -- 2.1 Data -- 2.2 Model Development -- 2.3 Experimental Setting -- 2.4 Evaluation Metrics -- 3 Results -- 4 Discussion -- 5 Conclusion -- References -- Generalization Ability in Medical Image Analysis with Small-Scale Imbalanced Datasets: Insights from Neural Network Learning -- 1 Introduction -- 2 Methods -- 2.1 Definition of Neural Network Architecture Components -- 2.2 Generalization Ability -- 2.3 Model Complexity -- 3 Results and Discussion -- 4 Conclusion -- References -- Multi-omics Data Integration and Network Inference for Biomarker Discovery in Glioma -- 1 Introduction -- 2 Materials and Methods -- 2.1 Graphical Lasso -- 2.2 Network Distance -- 2.3 Data Description -- 2.4 Pipeline and Implementation -- 2.5 Network Validation -- 3 Results -- 3.1 Variable Selection -- 3.2 Protein Networks -- 3.3 Validation Outcomes.
4 Discussion -- References -- Better Medical Efficiency by Means of Hospital Bed Management Optimization-A Comparison of Artificial Intelligence Techniques -- 1 Introduction -- 2 Background -- 2.1 Resources Planning in Hospital Settings -- 2.2 Related Work -- 3 Materials and Methods -- 3.1 Methodologies -- 3.2 Tools and Algorithms -- 3.3 Data Sets -- 4 Experiments -- 4.1 Problem Formulation -- 4.2 Data Provided -- 4.3 Data Preparation -- 4.4 Domain and Fitness Function -- 4.5 Optimization Techniques -- 4.6 Evaluation -- 5 Results and Discussion -- 5.1 Algorithm Settings -- 5.2 Results -- 6 Conclusions -- References -- AI-Based Medical Scribe to Support Clinical Consultations: A Proposed System Architecture -- 1 Introduction -- 2 Literature Review -- 2.1 Digital Medical Scribe -- 2.2 Automatic Speech Recognition and Natural Language Processing Algorithms -- 3 System Architecture -- 4 Conclusion and Further Work -- References -- Combining Neighbor Models to Improve Predictions of Age of Onset of ATTRv Carriers -- 1 Introduction -- 2 Background -- 2.1 Ensemble Learning -- 2.2 Related Work -- 3 Single Learning Approach and Combination Strategies -- 3.1 Prediction Problem and Single Learning Approach -- 3.2 Data and Evaluation Strategy -- 3.3 Combination Strategies -- 3.4 Evaluation -- 4 Results and Discussion -- 5 Conclusions and Future Work -- References -- Unravelling Heterogeneity: A Hybrid Machine Learning Approach to Predict Post-discharge Complications in Cardiothoracic Surgery -- 1 Background -- 2 Dataset -- 3 Methodology -- 3.1 Unsupervised Learning Strategy -- 3.2 Supervised Learning Strategy -- 4 Results -- 4.1 Clustering -- 4.2 Classification -- 5 Discussion -- 6 Conclusion -- References -- Leveraging TFR-BERT for ICD Diagnoses Ranking -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Overview -- 3.2 Learning-to-Rank System.
3.3 Fine-Tuned Language Representation Model.
Record Nr. UNISA-996574259103316
Moniz Nuno  
Cham : , : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui