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[null,"1.","Record Nr.",null,"UNINA990008400370403321"]
[null,null,"Autore",null,"Nizza, Sebastiano"]
[null,null,"Titolo",null,"Ciò che sopravvive al 1. giugno 1950 nella legge tributaria sulle successioni : prontuario delle imposte di successione e sul valore globale : contenzioso tributario ... [etc.] / Sebastiano Nizza"]
[null,null,"Pubbl/distr/stampa",null,"Roma : Casa editrice Stamperia nazionale già Stamperia reale, 1950"]
[null,null,"Descrizione fisica",null,"134 p. ; 22 cm"]
[null,null,"Locazione",null,"FGBC"]
[null,null,"Collocazione",null,"XIV Z 11"]
[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,"UNISA996565862603316"]
[null,null,"Autore",null,"Tiwari Sanju"]
[null,null,"Titolo",null,"Artificial Intelligence : First International Conference, AI4S 2023, Pune, India, September 4-5, 2023, Proceedings"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer International Publishing AG, , 2023"]
[{"$nulls":4},"©2023"]
[null,null,"ISBN",null,"3-031-47997-1"]
[null,null,"Edizione",null,"[1st ed.]"]
[null,null,"Descrizione fisica",null,"1 online resource (234 pages)"]
[null,null,"Collana",null,"Communications in Computer and Information Science Series ; ; v.1907"]
[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 -- Keynote Abstracts -- Data Analytics for Sustainable Global Supply Chains -- Building Trustworthy Neuro-Symbolic AI Systems with Explainability and Safety: Knowledge is the Key -- Contents -- An Approach Towards Mitigation of Renewable Energy Curtailment -- 1 Introduction -- 2 Test Case Modifications and Assumptions -- 2.1 Test Case and Modifications -- 2.2 Assumptions -- 3 Solution Methodologies and Cases -- 3.1 Solution Methodology -- 3.2 Configuration of Cases -- 4 Results and Discussion -- 4.1 Results -- 4.2 Discussion -- 5 Conclusion and Future Scope -- References -- ESG and IoT: Ensuring Sustainability and Social Responsibility in the Digital Age -- 1 Introduction -- 2 Overview of ESG and Sustainability -- 2.1 Environmental, Social and Governance Impacts of IoT -- 2.2 The Contribution of Artificial Intelligence to ESG -- 2.3 Industry 4.0 and Its Potential Impact on ESG -- 3 Proposed Approach -- 3.1 Proposed Architecture -- 3.2 SAS® Intelligent Monitoring: Product Overview -- 4 Possible Applications -- 5 Future Work -- 6 Conclusion -- References -- AI and Assistive Technologies for Persons with Disabilities - Worldwide Trends in the Scientific Production Using Bibliometrix R Tool -- 1 Introduction -- 1.1 Background -- 1.2 Problem Statement -- 2 Methodology -- 2.1 Data Collection -- 2.2 Analysis -- 3 Results and Discussion -- 3.1 Production -- 3.2 Sources -- 3.3 Authors -- 3.4 Documents -- 4 Conclusion -- 4.1 Limitations and Future Research Directions -- Appendix A: -- References -- Leaf Disease Detection Using Transfer Learning -- 1 Introduction -- 2 Related Work -- 3 Model Architecture and Design -- 3.1 ResNet -- 3.2 MobileNet -- 3.3 VGG16 -- 3.4 "]
[{"$nulls":4},"Design Consideration -- 4 Dataset Preparation and Training -- 4.1 Kaggle Dataset: Potato, Tomato, and Pepper Black Diseases -- 4.2 Training the Models."]
[{"$nulls":4},"5 Results -- 5.1 VGG16 Model -- 5.2 ResNet Model -- 5.3 MobileNet Model -- 5.4 Performance Comparison -- 6 Conclusion -- References -- Automated Scene Recognition for Environmental Monitoring: A Cluster Analysis Approach using Intel Image Classification Dataset -- 1 Introduction -- 2 Literature Review -- 3 Data Preprocessing and EDA -- 3.1 About the Dataset -- 3.2 Data Transformation -- 3.3 Dimensionality Reduction with PCA for Improved Clustering Efficiency -- 4 Clustering Methods for Scene Recognition -- 4.1 K Means Clustering Technique -- 4.2 Agglomerative Clustering -- 4.3 BIRCH (Balanced Iterative Reducing and Clustering Using Hierarchies) -- 4.4 DBSCAN (Density Based Spatial Clustering of Applications with  Noise) -- 4.5 Spectral -- 5 Evaluation of Clustering Algorithms -- 5.1 Silhouette Score -- 5.2 Davis-Bouldin Score -- 5.3 Calinski-Harabasz Score -- 6 Conclusion and Future Scope -- References -- Unveiling the Potentials of Deep Learning Techniques for Accurate Alzheimer's Disease Neuro Image Classification -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 4 The Proposed Bi-LSTM-AJSO Model Development -- 5 Experimentation -- 5.1 Datasets Used and Model Training and Testing -- 5.2 Comparison with Other Machine and Deep Learning Approaches -- 5.3 Execution Time Comparisons -- 5.4 Interpretability Analysis and Significance -- 6 Conclusion and Future Directions -- References -- Food Composition Knowledge Extraction from Scientific Literature -- 1 Introduction -- 2 Food Composition Knowledge -- 3 Food Composition Knowledge Extraction from Scientific Papers -- 3.1 Knowledge Sources -- 3.2 Knowledge Extraction -- 4 Knowledge Validation -- 4.1 Matching to Existing Vocabularies -- 5 Conclusion -- References -- Design and Analysis of an Algorithm Based on Biometric Block Chain for Efficient data sharing in VANET -- 1 Introduction."]
[{"$nulls":4},"2 Literature Review -- 3 Proposed Work -- 4 Experimental Result -- 5 Conclusion -- References -- An Improved Deep Learning Model Implementation for Pest Species Detection -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Dataset -- 3.2 Deep Learning -- 3.3 Data Augmentation -- 3.4 Model Architecture -- 3.5 Classification -- 4 Results -- 5 Conclusion -- References -- Identification of Diseases Affecting Mango Leaves Using Deep Learning Models -- 1 Introduction -- 2 Literature Survey -- 2.1 Disease Affecting Mango Leaves -- 2.2 Factor Influencing Fungal Diseases -- 3 Dataset Description -- 4 Methodology -- 4.1 Feature Extraction -- 4.2 Classification -- 4.3 Model Evaluation -- 4.4 Prediction -- 5 Results and Discussion -- 6 Conclusion -- References -- RWNR: Radial Basis Feed Forward Neural Network Driven Semantically Inclined Strategy for Web 3.0 Compliant News Recommendation -- 1 Introduction -- 2 Related Works -- 3 Proposed Architecture -- 4 Implementation -- 5 Results and Performance Evaluation -- 6 Conclusion -- References -- WDNRegClass - A Hybrid ANN + Bayesian Learning Model to Reduce Temporal Predictive In-Variance Towards Mitigation of WDN Revenue Losses -- 1 Introduction -- 2 Literature Study -- 2.1 Leak Identification Using Hydraulic Model Parameters: -- 2.2 Data-Driven Approaches with Sequential or Temporal Data: -- 2.3 The Integration of Bayesian Belief Propagation: -- 3 Proposed Work -- 4 Result and Discussion -- 5 Conclusion -- References -- Real-Time Birds Shadow Detection for Autonomous UAVs -- 1 Introduction -- 2 Related Work -- 3 Proposed Approach -- 3.1 Acquiring a Sample Dataset -- 3.2 Shadow Generation -- 3.3 Data Cleaning -- 3.4 Post-processing -- 3.5 "]
[{"$nulls":4},"Detection Model Training -- 4 Results and Discussion -- 5 Conclusion -- References."]
[{"$nulls":4},"Knowledge Graph for Fraud Detection: Case of Fraudulent Transactions Detection in Kenyan SACCOs -- 1 Introduction -- 2 Related Work -- 3 Proposed Approach -- 4 Results -- 4.1 Sample Fraudulent Funds Movement Detection -- 5 Conclusion and Future Work -- References -- Conceptual Framework for Representing Knowledge in the Energy Sector -- 1 Introduction -- 2 State of the Art -- 3 Methodology for Semantic Data Model Design and Construction -- 3.1 Step 1: Ontology Requirements Specification -- 3.2 Step 2: Ontology Analysis -- 3.3 Step 3: Overview of Ontological Modules -- 3.4 Step 4: Interaction with Stakeholders and Ontology Formalization -- 4 Overview of Main Pilots' Topics -- 5 Methodology Application -- 5.1 Application of Step 1 - Ontology Requirements Specification -- 5.2 Application of Step 2 - Ontology Analysis -- 5.3 Application of Step 3 - Overview of Ontological Model -- 5.4 Application of Step 4 - Formalization of Semantic Data Models -- 5.5 Use Case Instantiation with an Illustrative Example -- 6 Discussion -- 7 Conclusion -- References -- Semantic Carbon Footprint of Food Supply Chain Management -- 1 Introduction -- 2 Ontology Methodology -- 2.1 Ontology Requirements Specification -- 2.2 Competency Questions -- 2.3 Users -- 2.4 Intended Use -- 3 Ontology Design -- 3.1 Data Sources -- 3.2 Evaluation -- 4 Conclusion -- References -- Author Index."]
[null,"3.","Record Nr.",null,"UNINA9910814106803321"]
[null,null,"Autore",null,"Berger Stephen A."]
[null,null,"Titolo",null,"Crimean-Congo Hemorrhagic Fever : Global Status / / Stephen A. Berger"]
[null,null,"Pubbl/distr/stampa",null,"Los Angeles : , : Gideon Informatics, Inc, , 2021"]
[null,null,"ISBN",null,"1-4988-3244-X"]
[null,null,"Descrizione fisica",null,"1 online resource (77 pages)"]
[null,null,"Disciplina",null,"616.157"]
[null,null,"Soggetti",null,"Hemorrhagic fever"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]