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[null,"1.","Record Nr.",null,"UNISA990002404100203316"]
[null,null,"Autore",null,"VILLANI, Vinicio"]
[null,null,"Titolo",null,"Cominciamo da zero : domande, risposte e commenti per saperne di più sui perchè della matematica (Aritmetica e Algebra) / Vinicio Villani"]
[null,null,"Pubbl/distr/stampa",null,"Bologna : Pitagora, 2003"]
[null,null,"ISBN",null,"88-371-1406-0"]
[null,null,"Descrizione fisica",null,"III, 216 p. ; 20 cm"]
[null,null,"Collana",null,"Complementi di matematica per l'indirizzo didattico ; 12"]
[null,null,"Disciplina",null,"510"]
[null,null,"Soggetti",null,"Matematica - Testi per l'insegnamento"]
[null,null,"Collocazione",null,"510 VIL"]
[null,null,"Lingua di pubblicazione",null,"Italiano"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,"2.","Record Nr.",null,"UNISA996574259003316"]
[null,null,"Autore",null,"Moniz Nuno"]
[null,null,"Titolo",null,"Progress in Artificial Intelligence : 22nd EPIA Conference on Artificial Intelligence, EPIA 2023, Faial Island, Azores, September 5-8, 2023, Proceedings, Part I"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer, , 2024"]
[{"$nulls":4},"©2023"]
[null,null,"ISBN",null,"3-031-49008-8"]
[null,null,"Edizione",null,"[1st ed.]"]
[null,null,"Descrizione fisica",null,"1 online resource (551 pages)"]
[null,null,"Collana",null,"Lecture Notes in Computer Science Series ; ; v.14115"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"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 "]
[{"$nulls":4},"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."]
[{"$nulls":4},"A System for Animal Health Monitoring and Emotions Detection -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 4 System Overview -- 5 Experiments -- 6 Results Evaluation -- 7 Future Works -- 8 Conclusion -- References -- Ethics and Responsibility in Artificial Intelligence -- A Three-Way Knot: Privacy, Fairness, and Predictive Performance Dynamics -- 1 Introduction -- 2 Background -- 2.1 Privacy -- 2.2 Fairness -- 2.3 Related Work -- 3 Experimental Study -- 3.1 Data -- 3.2 Methods -- 3.3 Experimental Results -- 4 Discussion -- 5 Conclusion -- References -- A Maturity Model for Industries and Organizations of All Types to Adopt Responsible AI-Preliminary Results -- 1 Introduction -- 1.1 Context and Justification -- 1.2 Why a Maturity Model for Responsible Artificial Intelligence (RAI)? -- 2 Methodology -- 3 The Maturity Model for Responsible AI -- 4 Implementation, Results and Discussion -- 5 Conclusions -- References -- Completeness of Datasets Documentation on ML/AI Repositories: An Empirical Investigation -- 1 Introduction and Motivation -- 2 Documentation Test Sheet from Related Works -- 2.1 Fields of Information -- 2.2 Measurement -- 3 Study Design -- 3.1 Repositories Under Analysis -- 3.2 Datasets Selection -- 4 Results and Discussion -- 4.1 Datasets Level -- 4.2 Sections Level -- 4.3 Test Fields Level -- 5 Threats to Validity and Limitations -- 6 Conclusions -- 7 Future Work -- References -- Navigating the Landscape of AI Ethics and Responsibility -- 1 Introduction -- 2 Research Methodology -- 3 Analysis of the Literature -- 4 Discussion -- 5 Conclusion -- References -- Towards Interpretability in Fintech Applications via Knowledge Augmentation -- 1 Introduction -- 2 Interpretability in Fintech -- 2.1 Interpretability Approaches -- 2.2 Surrogate Models -- 3 Knowledge Extraction and Augmentation -- 3.1 Knowledge Extraction Methods."]
[{"$nulls":4},"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 "]
[{"$nulls":4},"-- 2.1 The Spectral Analysis Features -- 2.2 The Contour Analysis Features -- 3 Classification -- 3.1 Data -- 3.2 The Training Phase -- 4 Results and Discussion -- 5 Conclusion -- References."]
[{"$nulls":4},"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."]
[{"$nulls":4},"Studying the Impact of Sampling in Highly Frequent Time Series -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 4 Experimental Setup -- 4.1 Algorithm -- 4.2 Datasets -- 4.3 Missing Data -- 4.4 Evaluation -- 5 Experiments -- 6 Results and Discussion -- 7 Conclusion and Future Work -- References -- Mining Causal Links Between TV Sports Content and Real-World Data -- 1 Introduction -- 2 Literature Review -- 3 Data -- 4 Methods -- 4.1 Granger Causality Test -- 4.2 Causal Analysis of TV Viewership in Liga NOS -- 5 Results and Discussion -- 6 Conclusion -- References -- Hybrid SkipAwareRec: A Streaming Music Recommendation System -- 1 Introduction -- 2 Related Work -- 2.1 Recommendations with Negative Implicit Feedback -- 2.2 Sequential Music Recommendation -- 3 Methodology and Proposed Solution -- 3.1 Action Set Generation -- 3.2 Next Best Action Recommendation -- 3.3 Next Best Items Recommendation -- 4 Experiments and Results -- 4.1 Data Setup and Model Training -- 4.2 Evaluation -- 5 Conclusions and Future Work -- References -- Interpreting What is Important: An Explainability Approach and Study on Feature Selection -- 1 Introduction -- 2 Related Works -- 3 Datasets and Methods -- 3.1 Rossmann Store Sales -- 3.2 Bike Sharing Dataset -- 3.3 Data Exploration -- 3.4 LSTM Hyperparameter Tunning -- 3.5 SHAP Method Implementation -- 4 Experiments, Results, and Discussion -- 4.1 Experimental Setup -- 4.2 Experimental Procedure -- 4.3 Results -- 4.4 Discussion -- 5 Conclusion and Future Work -- References -- Time-Series Pattern Verification in CNC Machining Data -- 1 Introduction -- 2 Background -- 2.1 CNC Machining and Offset Adjustment in Turning -- 2.2 Feature Extraction and Linear Frequency Cepstral Coefficients -- 2.3 One-Class Classification -- 3 Methodology "]
[{"$nulls":4},"-- 4 Results and Discussion -- 5 Conclusion -- References."]
[{"$nulls":4},"A Comparison of Automated Machine Learning Tools for Predicting Energy Building Consumption in Smart Cities."]