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Advances in Crowdfunding : Research and Practice / / edited by Rotem Shneor, Liang Zhao, Bjørn-Tore Flåten
| Advances in Crowdfunding : Research and Practice / / edited by Rotem Shneor, Liang Zhao, Bjørn-Tore Flåten |
| Autore | Shneor Rotem |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Springer Nature, 2020 |
| Descrizione fisica | 1 online resource (XXVI, 531 p. 32 illus.) |
| Disciplina |
658.421
650 |
| Soggetto topico |
New business enterprises
Venture capital Business enterprises - Finance Finance Small business Electronic commerce Start-Ups and Venture Capital Corporate Finance Financial Economics Small Business E-Business |
| ISBN |
9783030463090
3030463095 |
| Classificazione | BUS017000BUS017030BUS027000BUS060000BUS090000 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1. Introduction: From Fundamentals to Advances in Crowdfunding Research and Practice -- 2. Crowdfunding Models, Strategies, and Choices Between Them -- 3. The Global Status of the Crowdfunding Industry -- 4. Lending Crowdfunding: Principles and Market Development -- 5. Equity Crowdfunding: Principles and Investor Behaviour -- 6. Reward-based Crowdfunding Research and Practice -- 7. Donation Crowdfunding: Principles and Donor Behaviour -- 8. Ethical Considerations in Crowdfunding -- 9. Legal Institutions, Social Capital, and Financial Crowdfunding: A Multilevel Perspective -- 10. History of Crowdfunding in the Context of Ever-Changing Modern Financial Markets -- 11. The Fintech Industry: Crowdfunding in Context -- 12. Crowdfunding in China: Turmoil of Global Leadership -- 13. Crowdfunding Prospects in New Emerging Markets: The Cases of India and Bangladesh -- 14. Crowdfunding in Africa: Opportunities and Challenges -- 15. Israeli Crowdfunding: A Reflection of its Entrepreneurial Culture -- 16. Crowdfunding in Europe: Between Fragmentation and Harmonisation -- 17. Crowdfunding Sustainability -- 18. Crowdfunding in the Cultural Industries -- 19. Civic Crowdfunding: Four perspectives on the definition of civic crowdfunding -- 20. Crowdfunding Education: Objectives, Content, Pedagogy, and Assessment -- 21. The Future of Crowdfunding Research and Practice. |
| Record Nr. | UNINA-9910416122303321 |
Shneor Rotem
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| Springer Nature, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery : Volume 2 / / edited by Yong Liu, Lipo Wang, Liang Zhao, Zhengtao Yu
| Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery : Volume 2 / / edited by Yong Liu, Lipo Wang, Liang Zhao, Zhengtao Yu |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (xxv, 1,119 pages) : illustrations |
| Disciplina |
006
006.38 |
| Collana | Advances in Intelligent Systems and Computing |
| Soggetto topico |
Computational intelligence
Expert systems (Computer science) Computational Intelligence Knowledge Based Systems |
| ISBN | 3-030-32591-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910484228803321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery : Volume 1 / / edited by Yong Liu, Lipo Wang, Liang Zhao, Zhengtao Yu
| Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery : Volume 1 / / edited by Yong Liu, Lipo Wang, Liang Zhao, Zhengtao Yu |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (1,006 pages) |
| Disciplina | 006 |
| Collana | Advances in Intelligent Systems and Computing |
| Soggetto topico |
Computational intelligence
Expert systems (Computer science) Computational Intelligence Knowledge Based Systems |
| ISBN | 3-030-32456-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910484316103321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Autonomous Marine Vehicles Planning and Control
| Autonomous Marine Vehicles Planning and Control |
| Autore | Bai Yong |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Newark : , : John Wiley & Sons, Incorporated, , 2025 |
| Descrizione fisica | 1 online resource (505 pages) |
| Disciplina | 623.82/06 |
| Altri autori (Persone) | ZhaoLiang |
| Soggetto topico | Automated vehicles - Design and construction |
| ISBN |
1-394-35507-6
1-394-35505-X 9781394355051 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Series Page -- Title Page -- Copyright Page -- Contents -- Preface -- Chapter 1 Introduction -- 1.1 Overview -- 1.2 System Structure -- 1.3 Mathematical Model of a USV -- 1.4 Maritime Applications -- 1.5 Motivation of this Book -- References -- Chapter 2 Automatic Control Module -- 2.1 Origin and Development -- 2.2 Common Control System Development -- 2.2.1 Dynamic Positioning and Position Mooring Systems -- 2.2.1.1 Dynamic Positioning Control System -- 2.2.1.2 Position Mooring Control System -- 2.2.2 Waypoint Tracking and Path-Following Control Systems -- 2.2.2.1 Waypoint Tracking Control System -- 2.2.2.2 Path-Following Control System -- 2.3 Advanced Control System Development -- 2.3.1 Linear Quadratic Optimal Control -- 2.3.2 State Feedback Linearization -- 2.3.2.1 Decoupling in the BODY Frame (Velocity Control) -- 2.3.2.2 Decoupling in the NED Frame (Position and Attitude Control) -- 2.3.3 Integrator Backstepping Control -- 2.3.4 Sliding-Mode Control -- 2.3.4.1 SISO Sliding-Mode Control -- 2.3.4.2 Sliding-Mode Control Using the Eigenvalue Decomposition -- References -- Chapter 3 Perception and Sensing Module -- 3.1 Low-Pass and Notch Filtering -- 3.1.1 Low-Pass Filtering -- 3.1.2 Cascaded Low-Pass and Notch Filtering -- 3.2 Fixed Gain Observer Design -- 3.2.1 Observability -- 3.2.2 Luenberger Observer -- 3.2.3 Case Study: Luenberger Observer for Heading Autopilots Using Only Compass Measurements -- 3.3 Kalman Filter Design -- 3.3.1 Discrete-Time Kalman Filter -- 3.3.2 Continuous-Time Kalman Filter -- 3.3.3 Extended Kalman Filter -- 3.3.4 Corrector-Predictor Representation for Nonlinear Observers -- 3.3.5 Case Study: Kalman Filter for Heading Autopilots Using Only Compass Measurements -- 3.3.5.1 Heading Sensors Overview -- 3.3.5.2 System Model for Heading Autopilot Observer Design.
3.3.6 Case Study: Kalman Filter for Dynamic Positioning Systems Using GNSS and Compass Measurements -- 3.4 Nonlinear Passive Observer Designs -- 3.4.1 Case Study: Passive Observer for Dynamic Positioning Using GNSS and Compass Measurements -- 3.4.2 Case Study: Passive Observer for Heading Autopilots Using only Compass Measurements -- 3.4.3 Case Study: Passive Observer for Heading Autopilots Using Both Compass and Rate Measurements -- 3.5 Integration Filters for IMU and Global Navigation Satellite Systems -- 3.5.1 Integration Filter for Position and Linear Velocity -- 3.5.2 Accelerometer and Compass Aided Attitude Observer -- 3.5.3 Attitude Observer Using Gravitational and Magnetic Field Directions -- References -- Chapter 4 Model Predictive Control for Autonomous Marine Vehicles: A Review -- 4.1 Introduction -- 4.1.1 Object Introduction -- 4.1.2 Previous Reviews -- 4.2 Fundamental Models and a General Picture -- 4.2.1 Model of AMVs -- 4.2.1.1 6-DOF Model -- 4.2.1.2 3-DOF Model -- 4.2.2 Model Predictive Control -- 4.2.3 Literature Search -- 4.3 Methodology -- 4.3.1 MPC Applications of AMVs -- 4.3.1.1 Real-Coded Chromosome -- 4.3.1.2 Path Following -- 4.3.1.3 Trajectory Tracking -- 4.3.1.4 Cooperative Control/Formation Control -- 4.3.1.5 Collision Avoidance -- 4.3.1.6 Energy Management -- 4.3.1.7 Other Topics -- 4.4 Discussion -- 4.4.1 Limitations of Existing Techniques and Challenges in Developing MPC -- 4.4.1.1 Uncertainties of AMV Motion Models -- 4.4.1.2 Stability and Security of the New MPC Method -- 4.4.1.3 The Balance Between Effectiveness and Efficiency of the Methods -- 4.4.1.4 The Practical Application Scenario of the MPC and the Discussion of the Working Conditions -- 4.4.1.5 Challenges Posed by the Marine Environment Affect MPC Development for AMVs -- 4.4.2 Trends in the Technology Development for MPC in AMV. 4.4.2.1 More Cooperative Control with MPC -- 4.4.2.2 Rigorous Theoretical Derivation and Experimental Verification -- 4.4.2.3 Real-Time MPC for AMVs Applications -- 4.4.2.4 The Combination of Machine Learning/Neural Networks and MPC for AMVs Applications -- 4.4.2.5 Address the Challenges Posed by the Marine Environment -- 4.4.2.6 Potential Interdisciplinary Approaches that Combine MPC with Other Innovative Fields -- 4.5 Conclusion -- Acknowledgement -- References -- Chapter 5 Controller-Consistent Path Planning for Unmanned Surface Vehicles -- 5.1 Introduction -- 5.2 Problem Formulation -- 5.3 Methodology -- 5.3.1 Improved Artificial Fish Swarm Algorithm -- 5.3.1.1 Prey Behavior -- 5.3.1.2 Follow Behavior -- 5.3.1.3 Swarm Behavior -- 5.3.1.4 Random Behavior -- 5.3.1.5 Adaptive Visual and Step -- 5.3.2 Expanding Technique -- 5.3.3 Node Cutting and Path Smoother -- 5.3.4 Establishment of USV Model -- 5.4 Simulation -- 5.4.1 Monte Carlo Simulation -- 5.4.2 Path Quality Test -- 5.4.3 Simulation Using USV Control Model in Practical Environment -- 5.5 Conclusion -- References -- Chapter 6 Nonlinear Model Predictive Control and Routing for USV-Assisted Water Monitoring -- 6.1 Introduction -- 6.2 Problem Formulation -- 6.2.1 Heterogeneous Global Path Planning Problem -- 6.2.1.1 USV Model -- 6.2.1.2 Task Model -- 6.2.1.3 Problem Statement -- 6.2.2 Problem Analysis -- 6.2.3 Path Following Problem -- 6.2.3.1 Basic Assumptions -- 6.2.3.2 Vessel Model -- 6.2.3.3 Problem Description -- 6.3 Methodology -- 6.3.1 Greedy Partheno Genetic Algorithm -- 6.3.1.1 Dual-Coded Chromosome -- 6.3.1.2 Fitness Function -- 6.3.1.3 Greedy Randomized Initialization -- 6.3.1.4 Local Exploration -- 6.3.1.5 Mutation Operators -- 6.3.1.6 Algorithm Flow -- 6.3.2 Nonlinear Model Predictive Control -- 6.3.2.1 State Space Model -- 6.3.2.2 NMPC Design -- 6.3.2.3 Solver -- 6.3.2.4 Stability. 6.4 Results and Discussion -- 6.4.1 Simulation: Global Task Planning -- 6.4.1.1 Convergence Test -- 6.4.1.2 Heterogeneous Task Planning -- 6.4.2 Simulation: NMPC Control Performance -- 6.4.2.1 Test 1: Simulation Under Different Model Uncertainties -- 6.4.2.2 Test 2: Comparative Study with Other Methods -- 6.4.3 Simulation Verification of the Framework -- 6.5 Conclusion -- References -- Chapter 7 Global-Local Hierarchical Framework for USV Trajectory Planning -- 7.1 Introduction -- 7.2 Problem Formulation -- 7.2.1 Marine Environment -- 7.2.2 Dynamic Obstacles -- 7.2.3 Effects of Currents -- 7.2.4 USV Model and Constraints -- 7.2.5 Protocol Constraints -- 7.2.6 Objective Functions -- 7.2.6.1 The Minimum Cruising Time -- 7.2.6.2 The Minimum Variation of Heading Angle -- 7.2.6.3 The Safest Path -- 7.2.7 Problem Statement -- 7.3 Methodology -- 7.3.1 Adaptive-Elite GA with Fuzzy Inference (AEGAfi) -- 7.3.1.1 Real-Coded Chromosome -- 7.3.1.2 Initialization Based on Adaptive Random Testing (ART) -- 7.3.1.3 Adaptive Elite Selection -- 7.3.1.4 Double-Functioned Crossover -- 7.3.1.5 Mutation Operators -- 7.3.1.6 Fuzzy-Based Probability Choice -- 7.3.1.7 Fitness Function Design -- 7.3.2 Replanning Strategy Based on Sensory Vector -- 7.3.2.1 Sensory Vector Structure -- 7.3.2.2 Formulation of Vs -- 7.3.2.3 Formulation of Gap Vector Vg Based on COLREGs -- 7.3.2.4 Formulation of Transition Path -- 7.4 Simulation Study -- 7.4.1 Convergence Benchmark Analysis -- 7.4.2 Simulation Under Static Environment -- 7.4.3 Simulation Under Time-Varying Environment -- 7.4.4 Simulation on Real-World Geography -- 7.5 Conclusion -- Appendix -- List of Abbreviations -- Acknowledgements -- References -- Chapter 8 Reinforcement Learning for USV-Assisted Wireless Data Harvesting -- 8.1 Introduction -- 8.2 Fundamental Models -- 8.2.1 Environment Model. 8.2.2 Sensor Node and Communication Model -- 8.2.3 USV Model -- 8.2.3.1 Kinematic Model -- 8.2.3.2 Sensing Module -- 8.3 Methodology -- 8.3.1 Brief States on Q-Learning -- 8.3.2 Interactive Learning -- 8.3.2.1 Heuristic Reward Design -- 8.3.2.2 Design of Value-Iterated Global Cost Matrix -- 8.3.2.3 Local Cost Matrix and Path Generation -- 8.3.2.4 USV Actions with Discrete Precise Clothoid Path -- 8.3.3 Summary of the Path Planning Algorithm -- 8.3.4 Time Complexity -- 8.4 Results and Discussion -- 8.4.1 Performance Indicators -- 8.4.2 Hyper-Parameter Analysis -- 8.4.3 Comparative Study with State of the Art -- 8.5 Conclusion -- Appendix -- References -- Chapter 9 Achieving Optimal Dynamic Path Planning for Unmanned Surface Vehicles: A Rational Multi-Objective Approach and a Sensory-Vector Re-Planner -- 9.1 Introduction -- 9.2 Problem Formulation -- 9.2.1 Environment Modeling -- 9.2.1.1 Motion Area -- 9.2.1.2 Effects of Currents -- 9.2.2 Dynamic Obstacles -- 9.2.3 Motion Constraints -- 9.2.4 Objective Functions -- 9.2.4.1 Path Length -- 9.2.4.2 Path Smoothness -- 9.2.4.3 Energy Consumption -- 9.2.4.4 The Safest Path -- 9.2.5 Optimization Problem Statement -- 9.3 Methodology -- 9.3.1 Framework of NSGA-II -- 9.3.2 AENSGA-II -- 9.3.2.1 Real-Coded Representation -- 9.3.2.2 Initialization Using Candidate Set Adaptive Random Testing (CSART) -- 9.3.2.3 Adaptive Crowding Distance (ACD) Strategy -- 9.3.2.4 Improved Binary Tournament Selection -- 9.3.3 Fuzzy Satisfactory Degree -- 9.3.4 Replanning Strategy Based on Sensory Vector -- 9.3.4.1 Sensory Vector Structure -- 9.3.4.2 Formulation of Gap Vector Vg Based on COLREGs -- 9.3.4.3 Formulation of Transition Path -- 9.4 Results and Discussion -- 9.4.1 Convergence and Diversity Analysis -- 9.4.2 Implementation in Static Environment -- 9.4.2.1 Fixed Currents -- 9.4.2.2 Time-Varying Currents. 9.4.3 Simulation Under Dynamic Environment. |
| Record Nr. | UNINA-9911034469103321 |
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Bai Yong
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| Newark : , : John Wiley & Sons, Incorporated, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Effect of Protein and Peptide Supplementation on Physical Performance and Health Status
| Effect of Protein and Peptide Supplementation on Physical Performance and Health Status |
| Autore | Zhao Lei |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2024 |
| Descrizione fisica | 1 online resource |
| Soggetto topico |
Mathematics and Science
Biology, life sciences |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910870887003321 |
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Zhao Lei
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| MDPI - Multidisciplinary Digital Publishing Institute, 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Fourth International Conference on Natural Computation : proceedings : ICNC 2008 : 18-20 October 2008, Jinan, China
| Fourth International Conference on Natural Computation : proceedings : ICNC 2008 : 18-20 October 2008, Jinan, China |
| Pubbl/distr/stampa | [Place of publication not identified], : IEEE Computer Society, 2008 |
| Disciplina | 006.3/5 |
| Soggetto topico |
Natural computation
Engineering & Applied Sciences Computer Science |
| ISBN | 1-5090-7601-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996198146403316 |
| [Place of publication not identified], : IEEE Computer Society, 2008 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Fourth International Conference on Natural Computation : proceedings : ICNC 2008 : 18-20 October 2008, Jinan, China
| Fourth International Conference on Natural Computation : proceedings : ICNC 2008 : 18-20 October 2008, Jinan, China |
| Pubbl/distr/stampa | [Place of publication not identified], : IEEE Computer Society, 2008 |
| Disciplina | 006.3/5 |
| Soggetto topico |
Natural computation
Engineering & Applied Sciences Computer Science |
| ISBN |
9781509076017
1509076018 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910140032103321 |
| [Place of publication not identified], : IEEE Computer Society, 2008 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Knowledge Science, Engineering and Management : 17th International Conference, KSEM 2024, Birmingham, UK, August 16–18, 2024, Proceedings, Part V / / edited by Cungeng Cao, Huajun Chen, Liang Zhao, Junaid Arshad, Taufiq Asyhari, Yonghao Wang
| Knowledge Science, Engineering and Management : 17th International Conference, KSEM 2024, Birmingham, UK, August 16–18, 2024, Proceedings, Part V / / edited by Cungeng Cao, Huajun Chen, Liang Zhao, Junaid Arshad, Taufiq Asyhari, Yonghao Wang |
| Autore | Cao Cungeng |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (341 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
ChenHuajun
ZhaoLiang ArshadJunaid AsyhariTaufiq WangYonghao |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Computer engineering Computer networks Computers Information technology - Management Social sciences - Data processing Application software Artificial Intelligence Computer Engineering and Networks Computing Milieux Computer Application in Administrative Data Processing Computer Application in Social and Behavioral Sciences Computer and Information Systems Applications |
| ISBN |
9789819754892
9819754895 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | -- Special Track. -- Adversary and Attention Guided Knowledge Graph Reasoning based on Reinforcement Learning. -- Evaluating GPT’s Programming Capability through CodeWars’ Katas. -- An Online Portfolio Selection Algorithm with Dynamic Coreset Construction. -- Interval-valued Fuzzy Portfolio decision Model with Transaction Cost and Liquidity Constraint. -- Active Learning for Low-Resource Project-Specific Code Summarization. -- A Survey of Game-Theoretic Methods for Controlling COVID-19. -- ComPAT: a Compiler Principles course AssisTant. -- Tram Air Conditioning Fault Prediction Using Machine learning. -- Lexicon Graph Adapter based BERT Model For Chinese Named Entity Recognition. -- Insider Threat Defense Strategies: Survey and Knowledge Integration. -- GA-MEPS: Multiple Experts Portfolio Selection Based on Genetic Algorithm. -- Deep Learning and Machine Learning-Based Approaches to Inferring Social Media Network Users’ Interests from a Missing Data Issus. -- Customer Segmentation for Telecommunication using Machine Learning. -- DP-MFRNN: Difficulty Prediction for Examination Questions Based on Neural Network Framework. -- Causal Relationship Extraction Combined Boundary Detection and Information Interaction. -- Profit Maximization in Edge-enabled Multimedia Data Market: A Game-based Pricing Approach. -- Reinforcement learning for scientific application: A survey. -- Zunna: A New Browser Extension for Protecting Personal Data. -- HRTC:A Triple Joint Extraction Model Based on Cyber Threat Intelligence. -- Personalized Image Aesthetics Assessment based onTheme and Personality. -- A Spatio-temporal Neural Network for Medical Insurance Fraud Detection. -- Exploring Language Diversity to Improve Neural Text Generation. -- Diffusion Review-based Recommendation. -- IntellectSeeker: A Personalized Literature Management System with the Probabilistic Model and Large Language Model. -- A novel network intrusion detection method for unbalanced data in open scenarios. -- Explainable Knowledge-Based Learning For Online Medical Question Answering. -- Energy consumption prediction method for refrigeration systems based on adversarial networks and Transformer networks. -- P-Vit: A simplified Vision Transformer model based on FFN and Simple Attention. |
| Record Nr. | UNINA-9910878046903321 |
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Cao Cungeng
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| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Knowledge Science, Engineering and Management : 17th International Conference, KSEM 2024, Birmingham, UK, August 16–18, 2024, Proceedings, Part III / / edited by Cungeng Cao, Huajun Chen, Liang Zhao, Junaid Arshad, Taufiq Asyhari, Yonghao Wang
| Knowledge Science, Engineering and Management : 17th International Conference, KSEM 2024, Birmingham, UK, August 16–18, 2024, Proceedings, Part III / / edited by Cungeng Cao, Huajun Chen, Liang Zhao, Junaid Arshad, Taufiq Asyhari, Yonghao Wang |
| Autore | Cao Cungeng |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (438 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
ChenHuajun
ZhaoLiang ArshadJunaid AsyhariTaufiq WangYonghao |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Computer engineering Computer networks Computers Information technology - Management Social sciences - Data processing Application software Artificial Intelligence Computer Engineering and Networks Computing Milieux Computer Application in Administrative Data Processing Computer Application in Social and Behavioral Sciences Computer and Information Systems Applications |
| ISBN | 981-9754-98-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | -- Knowledge Management with Optimization and Security (KMOS). -- Knowledge Enhanced Zero-Shot Visual Relationship Detection. -- WGGAL: A Practical Time Series Forecasting Framework for Dynamic Cloud Environments. -- Dynamic Splitting of Diffusion Models for Multivariate Time Series Anomaly Detection in A JointCloud Environment. -- VulCausal: Robust Vulnerability Detection Using Neural Network Models from a Causal Perspective. -- LLM-Driven Ontology Learning to Augment Student Performance Analysis in Higher Education. -- DA-NAS: Learning Transferable Architecture for Unsupervised Domain Adaptation. -- Optimize rule mining based on constraint learning in knowledge graph. -- GC-DAWMAR: A Global-Local Framework for Long-Term Time Series Forecasting. -- An improved YOLOv7 based prohibited item detection model in X-ray images. -- Invisible Backdoor Attacks on Key Regions Based on Target Neurons in Self-Supervised Learning. -- Meta learning based Rumor Detection by Awareness of Social Bot. -- Financial FAQ Question-Answering System Based on Question Semantic Similarity. -- An illegal website family discovery method based on association graph clustering. -- Different Attack and Defense Types for AI Cybersecurity. .-An Improved Ultra-Scalable Spectral Clustering Assessment with Isolation Kernel. -- A Belief Evolution Model with Non-Axiomatic Logic. -- Lurking in the Shadows: Imperceptible Shadow Black-Box Attacks against Lane Detection Models. -- Multi-mode Spatial-Temporal Data Modeling with Fully Connected Networks. -- KEEN: Knowledge Graph-enabled Governance System for Biological Assets. -- Cop: Continously Pairing of Heterogeneous Wearable Devices based on Heartbeat. -- DFDS: Data-Free Dual Substitutes Hard-Label Black-Box Adversarial Attack. -- Logits Poisoning Attack in Federated Distillation. -- DiVerFed: Distribution-Aware Vertical Federated Learning for Missing Information. -- Prompt Based CVAE Data Augmentation for Few-shot Intention Detection. -- Reentrancy Vulnerability Detection Based On Improved Attention Mechanism. -- Knowledge-Driven Backdoor Removal in Deep Neural Networks via Reinforcement Learning. -- AI in Healthcare Data Privacy-preserving: Enhanced Trade-off between Security and Utility. -- Traj-MergeGAN: A Trajectory Privacy Preservation Model Based on Generative Adversarial Network. -- Adversarial examples for Preventing Diffusion Models from Malicious Image Edition. -- ReVFed: Representation-based Privacy-preserving Vertical Federated Learning with Heterogeneous Models. -- Logit Adjustment with Normalization and Augmentation in Few-shot Named Entity Recognition. -- New Indicators and Optimizations for Zero-Shot NAS Based on Feature Maps. |
| Record Nr. | UNINA-9910878063003321 |
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Cao Cungeng
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| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Knowledge Science, Engineering and Management : 17th International Conference, KSEM 2024, Birmingham, UK, August 16–18, 2024, Proceedings, Part IV / / edited by Cungeng Cao, Huajun Chen, Liang Zhao, Junaid Arshad, Taufiq Asyhari, Yonghao Wang
| Knowledge Science, Engineering and Management : 17th International Conference, KSEM 2024, Birmingham, UK, August 16–18, 2024, Proceedings, Part IV / / edited by Cungeng Cao, Huajun Chen, Liang Zhao, Junaid Arshad, Taufiq Asyhari, Yonghao Wang |
| Autore | Cao Cungeng |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (465 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
ChenHuajun
ZhaoLiang ArshadJunaid AsyhariTaufiq WangYonghao |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Computer engineering Computer networks Computers Information technology - Management Social sciences - Data processing Application software Artificial Intelligence Computer Engineering and Networks Computing Milieux Computer Application in Administrative Data Processing Computer Application in Social and Behavioral Sciences Computer and Information Systems Applications |
| ISBN | 981-9755-01-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | -- Emerging Technology. -- Integrated geologic terms and dual model for Chinese geological word segmentation. -- Random Virtual Embeddings Bootstrap High-degree Item Diffusion for Recommendation. -- Contrastive Learning for Money Laundering Detection: Node- Subgraph-Node Method with Context Aggregation and Enhancement Strategy. -- GCCR: GAT-Based Category-aware Course Recommendation. -- Exploring Word Composition Knowledge In Language Usages. -- L2R-Nav: A Large Language Model-Enhanced Framework for Robotic Navigation. -- Adversarial attacks on Large Language Models. -- Enhancing Question Embedding with Relation Chain for Multi-hop KGQA. -- IIU: Independent Inference Units for Knowledge-based Visual Question Answering. -- Research on Blockchain-Based Trustworthy Data Sharing and Privacy Data Protection Mechanism. -- A Hierarchical Neural Task Scheduling Algorithm in The Operating System of Neuromorphic Computers. -- Efficient Data Asset Right Provenance for Data Asset Trading Based on Blockchain. -- CGCL: A Novel Collaborative Graph Contrastive Learning Network for Chinese NER. -- Scalable attack on graph data by important nodes. -- WaveSegNet: Wavelet Transform and Multi-Scale Focusing Network for Scrap Steel Segmentation. -- Recommendation Algorithm Based on Refined Knowledge Graphs and Contrastive Learning. -- Enhancing Pet Health Record Security through RSA-Encrypted NFTs and Smart Contracts on the Blockchain. -- A Blockchain-Based Secure ADS-B System. -- An Emotion-Aware Human-Computer Negotiation Model Powered by Pretrained Language Model. -- Feature Re-enhanced Meta-Contrastive Learning for Recommendation. -- ANGCN:Adaptive Neighborhood-awareness for Recommendation. -- The study of named entity identification in Chinese electronic medical records based on multi-tasking. -- A Comparative Study of Different Pre-trained Language Models for Sentiment Analysis of Human-Computer Negotiation Dialogue. -- Integrating Blockchain and RSA-Encrypted NFTs for Enhanced Digital Knowledge Management. -- An Effective RSP Data Sampling Algorithm. -- Rationality of Thought Improves Reasoning in Large Language Models. -- NFTMosaic: Piecing Together Assets in a Unified Blockchain Token. -- Global Context Enhanced Multi-Granularity Intent Networks for Session-based Recommendation. -- Enhancing Electoral Integrity: A Comprehensive Study of Blockchain-Enabled Voting on EVM Platforms. -- AutoLabel: Automated Textual Data Annotation Method based on Active Learning and Large Language Model. -- KDTSS: A Blockchain-based Scheme for Knowledge Data Traceability and Secure Sharing. -- A Joint Client-Server Watermarking Framework for Federated Learning. -- Robust Representation Learning for Image Clustering. |
| Record Nr. | UNINA-9910878060703321 |
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Cao Cungeng
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| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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