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[null,"1.","Record Nr.",null,"UNICAMPANIASUN0013526"]
[null,null,"Titolo",null,"Nozione, formazione e interpretazione del diritto 4"]
[null,null,"Pubbl/distr/stampa",null,"Napoli : Jovene, 1997"]
[null,null,"ISBN",null,"88-243-1231-4"]
[null,null,"Descrizione fisica",null,"673 p. ; 24 cm."]
[null,null,"Disciplina",null,"340"]
[null,null,"Soggetti",null,"Diritto - Studi"]
[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,"UNINA9910631098803321"]
[null,null,"Titolo",null,"Trends on Construction in the Digital Era : Proceedings of ISIC 2022 / / edited by António Gomes Correia, Miguel Azenha, Paulo J. S. Cruz, Paulo Novais, Paulo Pereira"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023"]
[null,null,"ISBN",null,"3-031-20241-4"]
[null,null,"Edizione",null,"[1st ed. 2023.]"]
[null,null,"Descrizione fisica",null,"1 online resource (556 pages)"]
[null,null,"Collana",null,"Lecture Notes in Civil Engineering, , 2366-2565 ; ; 306"]
[null,null,"Disciplina",null,"720"]
[null,null,"Soggetti",null,"Buildings - Design and construction"]
[{"$nulls":4},"Automatic control"]
[{"$nulls":4},"Robotics"]
[{"$nulls":4},"Automation"]
[{"$nulls":4},"Computational intelligence"]
[{"$nulls":4},"Artificial intelligence"]
[{"$nulls":4},"Sampling (Statistics)"]
[{"$nulls":4},"Building Construction and Design"]
[{"$nulls":4},"Control, Robotics, Automation"]
[{"$nulls":4},"Computational Intelligence"]
[{"$nulls":4},"Intelligence Infrastructure"]
[{"$nulls":4},"Survey Methodology"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Intro -- Preface -- Organization -- Organizing Committee -- Co-Organizing Committee -- National Technical Committee -- Technical Oversight Committee -- International Advisory Committee -- International Scientific Committee -- Contents -- Artificial Intelligence for Design and Built Environment -- A WGAN Approach to Synthetic TBM Data Generation -- 1 Introduction -- 2 (Deep) Generative Adversarial Network Architecture -- 2.1 Generative Adversarial Networks -- 2.2 Deep Convolutional Neural Network-Based GAN (DCGAN) -- 2.3 Optimization of GANs by Wasserstein Distance Minimization -- 3 Methods -- 3.1 Data Description and Pre-processing -- 3.2 WGAN Architecture and Training Process -- 3.3 Experimental Setup -- 3.4 Evaluation Methods -- 4 Results -- 4.1 Results "]
[{"$nulls":4},"of the Training Process -- 4.2 Demand for Conformity -- 4.3 Demand for Originality -- 5 Conclusions and Outlook -- References -- Digital Construction Strategy for Project Management Optimization in a Building Renovation Site: Machine Learning and Big Data Analysis -- 1 Introduction -- 2 State of the Art -- 2.1 Case Studies Analysis -- 3 Methodology -- 3.1 Lean Construction -- 3.2 Management of Cost, Time and Quality -- 3.3 Operational Aspects of Lean Construction Delivery -- 3.4 BIM-Based Real-Time Construction Management -- 4 Application Case -- 4.1 BIM-Based Digital Framework -- 5 Results and Discussions -- 6 Conclusions -- References -- Disruptive Innovation in AEC: The Case of Artificial Intelligence Applied to Project Management -- 1 Background -- 2 Sustaining Innovation vs Disruptive Innovation -- 3 The Case of Project Management and Artificial Intelligence -- 4 Case Study: Queensland Transport and Main Roads -- 5 A Path Towards Disruptive Innovation -- 6 Conclusion -- References."]
[{"$nulls":4},"Neural Network-Based Model to Predict Permanent Deformation Induced in the Subgrade by the Passage of the Trains -- 1 Introduction -- 2 Numerical Modelling -- 2.1 Short-Term Performance: Numerical Model of the Train-Track-Ground System -- 2.2 Long-Term Performance: Permanent Deformation Modelling -- 2.3 Case Study: Finite Element-Based Knowledge Database Development -- 3 Neural Network-Based on Permanent Deformation Response Predicted Models for Railway Structures -- 3.1 Neural Network Algorithm -- 3.2 Neural Network Model and Predictions -- 4 Results and Discussion -- 4.1 Model Development and Evaluation -- 4.2 Validation of the Results -- 4.3 Sensitivity Analysis - Importance of Variables -- 5 Conclusions -- References -- Prediction of Airport Pavement Moduli by Machine Learning Methodology Using Non-destructive Field Testing Data Augmentation -- 1 Introduction -- 2 Materials and Methods -- 2.1 In Situ Investigation -- 2.2 Backcalculation Process -- 3 Methodology -- 3.1 Neural Modelling -- 3.2 Bayesian Regularization -- 3.3 k-Fold Cross-Validation -- 3.4 Data Augmentation -- 4 Results and Discussion -- 5 Conclusions -- References -- Prediction of Geological Conditions Ahead of the Tunnel Face: Comparing the Accuracy of Machine Learning Models Trained on Real and Synthetic Data -- 1 Introduction -- 2 Methodology -- 2.1 Data Collection and Preprocessing -- 2.2 Oversampling and Synthetic Data Generation -- 2.3 Ensemble ML Methods -- 3 Results -- 3.1 Input Variables Selection -- 3.2 Oversampling -- 3.3 Unsupervised Clustering -- 3.4 Supervised Classification -- 4 Conclusion and Outlook -- References -- Predictions of Root Tensile Strength for Different Vegetation Species Using Individual and Ensemble Machine Learning Models -- 1 Introduction -- 2 Background -- 3 Methodology -- 3.1 Experimental Analysis."]
[{"$nulls":4},"3.2 Selection of Critical Parameters (Affecting Root Tensile Strength) Using Feature Engineering -- 3.3 Machine Learning Models -- 3.4 Optimization of Model Parameters -- 4 Results -- 4.1 Feature Selection -- 4.2 Root Tensile Strength -- 4.3 Optimized Hyperparameters -- 4.4 Model Validation -- 5 Discussion and Conclusions -- References -- Towards the Development of a Budget Categorisation Machine Learning Tool: A Review -- 1 Introduction -- 1.1 Artificial Neural Networks in Cost Estimation -- 1.2 Natural Language Processing in Budget Categorisation -- 2 Research Methodology -- 3 AI and Its Use in AEC for Cost Management and Budgeting -- 3.1 Main Techniques -- 3.2 Practical Application of the Algorithms -- 3.3 The Importance of Data Collection -- 3.4 Algorithm Performance and Impact on Task Improvement -- 4 Conclusions -- References -- Transforming Construction Entities from Traditional Management to Autonomous "]
[{"$nulls":4},"Management Using Blockchain -- 1 Introduction -- 2 Construction Industry Transformation -- 3 Blockchain, Smart Contracts and DAOs -- 3.1 Establishing a DAO -- 4 Construction Governance DAO -- 5 Conclusion -- References -- Building Information Modelling (BIM), Construction Automation and Robotics -- A Toolbox for the Automatic Interpretation of Bender Element Tests in Geomechanics -- 1 Introduction -- 2 Description of the GeoHyTE Platform -- 2.1 Background -- 2.2 Computational Architecture -- 3 Validation Using International Parallel Test Benchmarks -- 3.1 Description of the Experimental Campaign -- 3.2 Statistical Analysis of the Results -- 4 Conclusions -- References -- Additive Manufactured (3D-Printed) Connections for Thermoplastic Facades -- 1 Introduction -- 2 Methodology -- 2.1 Design Criteria -- 2.2 Fabrication -- 3 Experiments and Results -- 3.1 Monomaterial Approach -- 3.2 Hybrid Connection Study -- 3.3 Facade Connections."]
[{"$nulls":4},"4 Conclusion and Outlook -- References -- Auto(mated)nomous Assembly -- 1 Introduction -- 1.1 Intelligent Construction and Automation -- 2 State of the Art -- 3 SL Blocks for Architectural Design and Construction -- 3.1 Hierarchical Design Strategy -- 3.2 Automate Generation of SL-Strands -- 3.3 Towards Fully Autonomous Construction - from Shape Input to Robotic Assembly -- 4 Conclusion and Future Work -- References -- BIM-to-FEM: Development of a Software Tool to Increase the Operational Efficiency of Dam Construction Projects -- 1 Introduction -- 2 Review on BIM-to-FEM Applications -- 3 BIM-to-FEM: Integration of Design and Numerical Analysis -- 3.1 Status Quo of Original Tool -- 3.2 Numerical Analysis Workflow -- 3.3 Human-Centered Data Integration Methodology -- 3.4 Numerical Modelling -- 3.5 Output, Visualization and Reporting -- 3.6 Capabilities and Outlook -- 4 Conclusion -- References -- Converting Algorithms into Tangible Solutions -- 1 Introduction -- 2 Methodology -- 3 Making the Digital Real -- 3.1 New Manufacturing Strategies -- 3.2 Fabricating Through Algorithms -- 4 Algorithmic Framework -- 5 Evaluation -- 5.1 Design Intent -- 5.2 Geometric Exploration -- 5.3 Manufacturing-Related Information -- 5.4 Design Prototyping -- 5.5 Aesthetical Consideration -- 6 Discussion -- 7 Conclusion -- References -- Development of a BIM Model for Facility Management with Virtual/Augmented Reality Interaction -- 1 Introduction -- 2 FEHST Case Study Project Requirements -- 2.1 Information Requirements, Purposes and BIM Uses -- 2.2 Functional and Nonfunctional Project Requirements -- 2.3 Level of Information Need Definition -- 3 BIM Model from Laser Scanner Survey -- 3.1 Point Cloud of the Case Study Region -- 3.2 Development of the BIM Model -- 4 Adding Complex Machinery into the Model -- 4.1 Simplification of the Machines."]
[{"$nulls":4},"4.2 Adding the Simplified Machines to the BIM Model -- 4.3 Export and Delivery for FM Database and Virtual/Augmented Reality -- 5 Conclusion -- References -- Improv-Structure: Exploring Improvisation in Collective Human-Robot Construction -- 1 Introduction -- 2 State of the Art -- 2.1 Improvisation and Robotics -- 2.2 Segregation Between Design and Construction -- 2.3 Human-Robot Interaction and Immersive/Participatory Design Using Robots -- 2.4 Collective Human-Robot Construction (CHRC) -- 3 Methodology -- 3.1 Combining the Strengths of Robots and Humans -- 3.2 Distributing Design Decision-Making -- 4 Results -- 5 Discussion, Limitation, and Outlook -- 5.1 Discussion -- 5.2 Limitations -- 5.3 Outlook -- 6 Image Credits -- References -- Sustainable Construction -- An Exploration of Graph-Based FEM Optimization for Construction Industry -- 1 Research Background -- 1.1 Objectified Design -- 1.2 "]
[{"$nulls":4},"Objectified Data Structure -- 1.3 The Objectified Design Dilemma of Structural Profession -- 1.4 Specific Manifestations of the Dilemma -- 1.5 Certification Issues for New Structural Materials Caused by FEM -- 2 Research Content -- 2.1 Basic Concepts and Principles of This Research -- 2.2 Research Work and Technical Path -- 2.3 Data Format Interpretation for Plug-In -- 2.4 Assembly Case Introduction -- 2.5 Initial-Split-Graph -- 2.6 Analysis of Damage-Path -- 2.7 FEM Analysis for Components and Mechanics Approximation -- 3 Summary -- References -- Assessing Hazardous Spills Impact on Road Surface Performances by 3D High Resolution Surveying Techniques -- 1 Introduction -- 2 Geomatic Methods for High Resolution 3D Modelling -- 3 Experimental Program -- 3.1 Test Preparation and Spill Procedure -- 3.2 Photogrammetric Survey and Data Processing -- 4 Results -- 5 Conclusion -- References."]
[{"$nulls":4},"Integrating Smart and Sustainable Construction: A Review of Present Status, and Possible Opportunities."]
[null,null,null,"Sommario/riassunto","These proceedings address the latest developments in the broad area of intelligent construction integrated in the mission of the International Society for Intelligent Construction (ISIC) which aims to promote intelligent construction technologies applications from the survey, design, construction, operation, and maintenance/rehabilitation by adapting to changes of environments and minimizing risks. Its goals are to improve the quality of construction, cost-saving, and safety, exploring fundamental issues related to the application and use of Artificial Intelligence (AI) and Machine Learning techniques and technology. ISIC 2022 is the 3rd ISIC international conference, held in Guimarães, Portugal on September 6–9, 2022, and follows the previous successful instalments of the conference series in China (2019) and USA (2017). It took a holistic approach to integrate civil engineering, construction machinery, electronic sensor technology, survey/testing technologies, information technology/computing, and other related fields in the broad area of intelligent construction. The respective contributions cover the following topics: Artificial Intelligence for Design and the Built Environment, Building Information Modelling (BIM) and Construction Automation and Robotics, Intelligent Construction, Sustainable Construction, and Sustainable and Smart Infrastructures. Given its broad range of coverage, the book will benefit students, educators, researchers and professionals practitioners alike, encouraging these readers to help the intelligent construction community into the digital era and with a vision on societal issues."]