Vai al contenuto principale della pagina

Progress in Artificial Intelligence : 22nd EPIA Conference on Artificial Intelligence, EPIA 2023, Faial Island, Azores, September 5-8, 2023, Proceedings, Part II



(Visualizza in formato marc)    (Visualizza in BIBFRAME)

Autore: Moniz Nuno Visualizza persona
Titolo: Progress in Artificial Intelligence : 22nd EPIA Conference on Artificial Intelligence, EPIA 2023, Faial Island, Azores, September 5-8, 2023, Proceedings, Part II Visualizza cluster
Pubblicazione: Cham : , : Springer, , 2024
©2023
Edizione: 1st ed.
Descrizione fisica: 1 online resource (606 pages)
Altri autori: ValeZita  
CascalhoJosé  
SilvaCatarina  
SebastiãoRaquel  
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.
Titolo autorizzato: Progress in Artificial Intelligence  Visualizza cluster
ISBN: 3-031-49011-8
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 996574259103316
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Serie: Lecture Notes in Computer Science Series