Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
Intelligence of Things : The Second International Conference on Intelligence of Things (ICIT 2023), Ho Chi Minh City, Vietnam, October 25-27, 2023, Proceedings, Volume 1
| Intelligence of Things : The Second International Conference on Intelligence of Things (ICIT 2023), Ho Chi Minh City, Vietnam, October 25-27, 2023, Proceedings, Volume 1 |
| Autore | Dao Nhu-Ngoc |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham : , : Springer, , 2023 |
| Descrizione fisica | 1 online resource (452 pages) |
| Altri autori (Persone) |
ThinhTran Ngoc
NguyenNgoc Thanh |
| Collana | Lecture Notes on Data Engineering and Communications Technologies Series |
| ISBN | 3-031-46573-3 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- State-of-the-Art and Theoretical Analyses -- FPGA/AI-Powered Data Security for IoT Edge Computing Platforms: A Survey and Open Issues -- 1 Introduction -- 1.1 Related Work -- 1.2 Contributions -- 1.3 Outline -- 2 Preliminary -- 2.1 IoT Layers and Threats -- 2.2 IoT Security vs. Traditional Security -- 3 FPGA-Based Security for Edge Devices -- 4 AI-Based Security for Edge Devices -- 4.1 Processor-Based AI Approaches -- 4.2 FPGA-Based AI Approaches -- 5 FPGA/AI-Powered Security for Edge Devices: Open Issues -- 6 Conclusion -- References -- A Review in Deep Learning-Based Thyroid Cancer Detection Techniques Using Ultrasound Images -- 1 Introduction -- 2 Deep Learning-Based Thyroid Cancer Detection Using Ultrasound Image -- 2.1 Convolutional Neural Networks - CascadeMaskR-CNN -- 2.2 VGG16, VGG19, and Inception v3 -- 2.3 ThyNet -- 2.4 Generative Adversarial Networks (GANs) -- 3 Discussion -- 4 Conclusion -- References -- Bio-Inspired Clustering: An Ensemble Method for User-Based Collaborative Filtering -- 1 Introduction -- 2 Related Work -- 3 Bio-Inspired Clustering Model for User-Based Collaborative Filtering (BICCF) -- 4 Experiments and Results -- 4.1 Setting -- 4.2 Evaluation -- 5 Conclusions -- References -- Deep Reinforcement Learning-Based Sum-Rate Maximization for Uplink Multi-user SIMO-RSMA Systems -- 1 Introduction -- 2 DRL-Based Sum-Rate Maximization for Uplink Multi-user SIMO-RSMA Framework -- 2.1 System Model and Problem Formulation -- 2.2 Proposed Deep Reinforcement Learning Framework -- 3 Evaluation -- 4 Conclusion -- References -- Multiobjective Logistics Optimization for Automated ATM Cash Replenishment Process -- 1 Introduction -- 2 Research Problem -- 3 Mathematical Model -- 3.1 Problem Statement -- 3.2 Constraints -- 3.3 Mathematical Model -- 4 Methodology -- 5 Testing and Evaluation.
6 Conclusion -- References -- Adaptive Conflict-Averse Multi-gradient Descent for Multi-objective Learning -- 1 Introduction -- 2 Conflict-Averse Methods for MOL -- 2.1 Multi-objective Learning Problems -- 2.2 Conflicting Gradients -- 2.3 Convergence and Learning Rate Issues -- 2.4 AdaCAGrad: Adaptive Conflict-Averse Multi-gradient Descent -- 3 Experiments -- 3.1 Toy Optimization Example -- 3.2 Image Classification -- 4 Conclusion -- References -- Multicriteria Portfolio Selection with Intuitionistic Fuzzy Goals as a Pseudoconvex Vector Optimization -- 1 Introduction -- 2 Multicriteria Portfolio Selection Problem -- 3 Multicriteria Portfolio Selection with Intuitionistic Fuzzy Goals -- 3.1 Intuitionistic Fuzzy Goals -- 3.2 Transformation to Deterministic Model -- 4 Computational Experiment -- 5 Conclusion -- References -- Research and Develop Solutions to Traffic Data Collection Based on Voice Techniques -- 1 Introduction -- 2 Related Work -- 3 Definition of Problem and End-to-End ASR System -- 3.1 Data Collection -- 3.2 Data Preprocessing -- 3.3 Language Modeling -- 3.4 Training End-to-End ASR -- 3.5 Decoding and Transcription -- 4 Experiment -- 4.1 Experimental Setup -- 4.2 Experimental Result -- 4.3 Analysis and Discussion -- 5 Conclusion -- References -- Using Machine Learning Algorithms to Diagnosis Melasma from Face Images -- 1 Introduction -- 2 Diagnostic Data for Melasma -- 3 Machine Learning Algorithm -- 3.1 About YOLO V8 -- 3.2 Anchor-Free Detection -- 3.3 Model for Diagnosing Melasma -- 3.4 Results of Model Evaluation -- 4 Conclusions -- References -- Reinforcement Learning for Portfolio Selection in the Vietnamese Market -- 1 Introduction -- 2 Overview -- 2.1 State-of-the-Art Reinforcement Learning -- 2.2 Related Work -- 3 Method -- 3.1 Modeling the Stock Trading Problem -- 3.2 Environment for Vietnamese Market -- 3.3 Noise Filter. 4 Experimental Evaluation -- 4.1 Data Pre-processing -- 4.2 Experimental Setup -- 4.3 Experimental Results -- 5 Conclusion -- References -- AIoT Technologies -- A Systematic CL-MLP Approach for Online Forecasting of Multiple Key Performance Indicators -- 1 Introduction -- 2 Preliminaries -- 3 Related Works -- 3.1 Time Series Forecasting Models -- 3.2 Online Learning -- 4 CL-MLP -- 4.1 Our Workflow -- 4.2 Model Construction -- 4.3 Online Learning -- 5 Experiment Results -- 5.1 Dataset -- 5.2 Our Results -- 6 Conclusion -- References -- Neutrosophic Fuzzy Data Science and Addressing Research Gaps in Geographic Data and Information Systems -- 1 Introduction -- 2 Neutrosophic Fuzzy Data Sciences -- 3 Neutrosophic Fuzzy GIS- Map -- 4 Neutrosophic Crisp Open in GIS Topology -- 5 Conclusion and Future Work -- References -- Inhibitory Control during Visual Perspective Taking Revealed by Multivariate Analysis of Event-Related Potentials -- 1 Introduction -- 2 Method -- 2.1 Participants -- 2.2 Stimulus -- 2.3 Procedure -- 2.4 Analysis -- 3 Results -- 3.1 Go vs No/Go Condition in the Self and Other Conditions Combined -- 3.2 Go vs No/Go Condition in the Self and Other Perspective Condition -- 4 Discussion -- References -- A Novel Custom Deep Learning Network Combining 1D-Convolution and LSTM for Rapid Wine Quality Detection in Small and Average-Scale Applications -- 1 Introduction -- 2 Material and Methodology -- 2.1 Data Description -- 2.2 Sampling Procedure -- 2.3 Computation Algorithm -- 3 Computation Algorithm -- 4 Validation Strategy -- 5 Result and Discussion -- 6 Conclusion -- References -- IoT-Enabled Wearable Smart Glass for Monitoring Intraoperative Anesthesia Patients -- 1 Introduction -- 1.1 Surgical Patient Monitoring System -- 1.2 Literature Review -- 2 Experimental Setup and Procedure -- 3 Results and Discussions -- 4 Conclusion -- References. Traffic Density Estimation at Intersections via Image-Based Object Reference Method -- 1 Introduction -- 2 Related Work -- 3 Problem Definition and Proposed Solutions -- 3.1 Problem Definition -- 3.2 Proposed Solutions -- 4 Experiment Setup and Result -- 4.1 Overall System Architecture -- 4.2 Automatic Access -- 4.3 Data Setup -- 4.4 Error Rate Calculation -- 4.5 Result and Evaluation -- 5 Conclusion and Future Work -- References -- Improving Automatic Speech Recognition via Joint Training with Speech Enhancement as Multi-task Learning -- 1 Introduction -- 2 Related Work -- 3 ASR-SE: A MTL Approach -- 4 Experiments and Results -- 5 Conclusion -- References -- Solving Feature Selection Problem by Quantum Optimization Algorithm -- 1 Introduction -- 2 Feature Selection Model -- 3 Solving Feature Selection Problems by CVaR-QAOA -- 3.1 Quantum Approximate Optimization Algorithm -- 3.2 CVaR Optimization for QAOA -- 3.3 Apply CVaR-QAOA to Feature Selection Problem -- 4 Numerical Simulation -- 5 Conclusion and Feature Work -- References -- A Methodology of Extraction DC Model for a 65 nm Floating-Gate Transistor -- 1 Introduction -- 2 Floating-Gate Transistor Concepts -- 2.1 Device Structure -- 2.2 DC Operation -- 3 Methodology in Model Extraction -- 4 Result -- 4.1 Drain Current Versus Control Gate Voltage at Initial Condition -- 4.2 Drain Current Versus Control Gate Voltage When VSB Varies -- 4.3 Drain Current Versus Control Gate Voltage When VD Varies -- 4.4 Drain Current Versus Drain Voltage When VCG Varies -- 5 Conclusion -- References -- imMeta: An Incremental Sub-graph Merging for Feature Extraction in Metagenomic Binning -- 1 Introduction -- 2 Methods -- 2.1 Fundamentals and Notations -- 2.2 Algorithms -- 3 Experimental Results -- 3.1 Dataset -- 3.2 Performance Metrics -- 3.3 Results -- 3.4 Parameter Evaluation -- 4 Conclusion -- References. Virtual Sensor to Impute Missing Data Using Data Correlation and GAN-Based Model -- 1 Introduction -- 2 Related Work -- 3 Problem Description -- 4 Virtual Sensor Components -- 4.1 Generator -- 4.2 Discriminator -- 4.3 Data Correlation Arrangement -- 4.4 Hint -- 4.5 Objective -- 5 Algorithm -- 6 Experiments -- 6.1 Performance of the Proposed Virtual Sensor -- 6.2 Virtual Sensor Prediction Accuracy -- 7 Conclusions and Future Work -- References -- An Edge AI-Based Vehicle Tracking Solution for Smart Parking Systems -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 4 Experimental Results -- 4.1 Training Phase -- 4.2 Evaluation -- 5 Conclusion -- References -- Low-Light Image Enhancement Using Quaternion CNN -- 1 Introduction -- 2 Background -- 2.1 Quaternion Algebra -- 2.2 Quaternion Convolutional Neural Network -- 2.3 CNN Approaches for Image Enhancements -- 3 Proposed Quaternion Attention Unet -- 3.1 Quaternion ResUnet -- 3.2 Quaternion Attention Module -- 3.3 The proposed Quaternion Attention Unet model -- 4 Experimental Results -- 4.1 Datasets -- 4.2 Training of Quaternion CNN -- 4.3 Performance Evaluations -- 5 Conclusion and Future Work -- References -- Leverage Deep Learning Methods for Vehicle Trajectory Prediction in Chaotic Traffic -- 1 Introduction -- 1.1 Vehicle Trajectory Prediction -- 1.2 The Challenges in Vietnamese Traffic -- 2 Related Work -- 3 Methods -- 3.1 Vehicle Detection -- 3.2 Vehicle Tracking -- 3.3 Vehicle Trajectory Prediction -- 4 Experiment -- 4.1 Experimental Setup and Implementation -- 4.2 Metrics -- 4.3 Experimental Result -- 5 Conclusion -- References -- AIoT System Architectures -- Wireless Sensor Network to Collect and Forecast Environment Parameters Using LSTM -- 1 Introduction -- 2 Related Work -- 3 Proposing System -- 3.1 System Overview -- 3.2 System Details -- 4 Simulation and Result -- 4.1 Product. 4.2 Training Result. |
| Record Nr. | UNINA-9910754096403321 |
Dao Nhu-Ngoc
|
||
| Cham : , : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Intelligence of Things : The Second International Conference on Intelligence of Things (ICIT 2023), Ho Chi Minh City, Vietnam, October 25-27, 2023, Proceedings, Volume 2
| Intelligence of Things : The Second International Conference on Intelligence of Things (ICIT 2023), Ho Chi Minh City, Vietnam, October 25-27, 2023, Proceedings, Volume 2 |
| Autore | Dao Nhu-Ngoc |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham : , : Springer, , 2023 |
| Descrizione fisica | 1 online resource (368 pages) |
| Altri autori (Persone) |
ThinhTran Ngoc
NguyenNgoc Thanh |
| Collana | Lecture Notes on Data Engineering and Communications Technologies Series |
| ISBN | 3-031-46749-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- AIoT Services and Applications -- Investigating Ensemble Learning Methods for Predicting Water Quality Index -- 1 Introduction -- 2 Methodology -- 2.1 Decision Tree -- 2.2 Bagging (Bootstrapped Aggregating) -- 2.3 Random Forest -- 2.4 Extra Trees -- 2.5 Adaptive Boosting -- 2.6 XGBoost (eXtreme Gradient Boosting) -- 3 Experiments and Results -- 3.1 Data Description -- 3.2 Metrics to Evaluate the Performance of ML Models -- 3.3 The Performance of Ensemble Methods on Predicting the WQI -- 4 Conclusions -- References -- Age-Invariant Face Recognition Based on Self-Supervised Learning -- 1 Introduction -- 2 Related Works -- 2.1 Age-Invariant Face Recognition -- 2.2 Self-Supervised Learning in Face Recognition -- 3 Methods -- 3.1 Data Augmentation -- 3.2 Age-Invariant Face Recognition Models -- 3.3 Self-Supervised Learning -- 4 Experimental Results -- 4.1 Experiment Setup -- 4.2 Experimental Results -- 5 Conclusion -- References -- Detection of Kidney Stone Based on Super Resolution Techniques and YOLOv7 Under Limited Training Samples -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Dataset -- 3.2 Convolutional Block Attention Module -- 3.3 Single Image Super Resolution Techniques -- 3.4 The Proposed Re-Designed YOLOv7 Architecture -- 4 Experimental Results -- 4.1 Environment and Hyperparameters Setup -- 4.2 Evaluation Results -- 5 Conclusion -- References -- Hardware-Based Lane Detection System Architecture for Autonomous Vehicles -- 1 Introduction -- 2 Related Work -- 3 Proposed Hough Transform Hardware Design Architecture -- 4 Proposed Design Verification -- 5 Conclusions -- References -- Video Classification Based on the Behaviors of Children in Pre-school Through Surveillance Cameras -- 1 Introduction -- 2 Related Works -- 3 The BCiPS Dataset -- 3.1 Dataset Creation.
3.2 Dataset Analysis -- 4 Baseline Models -- 4.1 CNN+LSTM (ConvLSTM2D) -- 4.2 CNN+SVM -- 4.3 CNN+Random Forest -- 4.4 TimeSformer -- 4.5 MoViNets -- 4.6 (2+1)D Resnet-18 -- 4.7 EfficientNetB0 -- 5 Results -- 5.1 Results of Baseline Models -- 5.2 Error Analysis -- 6 Conclusion-Future Works -- References -- Land Subsidence Susceptibility Mapping Using Machine Learning in the Google Earth Engine Platform -- 1 Introduction -- 2 Study Area -- 3 Materials and Methods -- 3.1 Methods -- 3.2 Materials -- 4 Results and Discussions -- 5 Conclusions -- References -- Building an AI-Powered IoT App for Fall Detection Using Yolov8 Approach -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Network Architecture -- 3.2 Fall Detection Work Flow -- 3.3 Performance Metrics -- 4 Implementation and Result -- 4.1 Data -- 4.2 Comparison Result of Different YOLOv5 Models over 100 Epochs -- 4.3 Fall Detection Web Application Using Streamlit -- 5 Discussion and Conclusion -- References -- Seam Puckering Level Classification Using AIoT Technology -- 1 Introduction -- 2 Background and Related Works -- 3 Methodology -- 3.1 Framework Architecture -- 3.2 Custom Dataset -- 3.3 Models for Seam Puckering Level Classification -- 3.4 System Implementation -- 4 Result and Evaluation -- 4.1 Result -- 4.2 Evaluation -- 5 Discussion, Conclusion, and Future Works -- References -- Classification of Pneumonia on Chest X-ray Images Using Transfer Learning -- 1 Introduction -- 2 Related Works -- 3 Dataset and Methods -- 3.1 Dataset -- 3.2 Proposed Method -- 4 Experimental Results -- 5 Conclusions -- References -- Bayesian Approach for Static Object Detection and Localization in Unmanned Ground Vehicles -- 1 Introduction -- 2 Methodologies -- 2.1 Detecting Algorithms -- 2.2 Noise Reducing and Navigating Procedures -- 2.3 Sensor's Fusion and Target Localization. 3 Experiment and Prelim Results -- 3.1 Simulation Environment -- 3.2 Onsite Testing -- 4 Conclusion and Future Work -- References -- Diabetic Retinopathy Diagnosis Leveraging Densely Connected Convolutional Networks and Explanation Technique -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Data Preprocessing -- 3.2 Data Augmentation -- 3.3 Architectures for Classification -- 3.4 Grad-CAM for Output Visualization From the Trained Model -- 4 Experimental Results -- 4.1 Datasets -- 4.2 Evaluation Metrics -- 4.3 Scenarios -- 4.4 Result Summary and Comparison with Some Previous Studies -- 5 Conclusion -- References -- Deep Learning Approach for Inundation Area Detection Using Sentinel Data -- 1 Introduction -- 2 Methodology and Dataset -- 2.1 Methodology -- 2.2 Dataset -- 3 Prelim Results -- 4 Conclusion -- References -- Classification of Raisin Grains Based on Ensemble Learning Techniques in Machine Learning -- 1 Introduction -- 2 Problem and Data -- 3 Research Methodology -- 3.1 Existing Methods -- 3.2 Proposed Method -- 3.3 Data Preprocessing -- 3.4 Experimental Settings -- 4 Results -- 5 Conclusion -- References -- An Effective Deep Learning Model for Detecting Plant Diseases Using a Natural Dataset for the Agricultural IoT System -- 1 Introduction -- 2 Related Work -- 3 Background -- 3.1 Data Augmentation Methods -- 3.2 Datasets -- 3.3 CNN Architecture -- 4 The Proposed Model -- 5 Conclusions -- References -- Real-Time Air Quality Monitoring System Using Fog Computing Technology -- 1 Introduction -- 2 Background and Related Works -- 3 Methodology -- 3.1 System Design -- 3.2 Pollution Parameters Selection -- 3.3 Data Acquisition Module -- 3.4 Communication Module -- 3.5 Fog Computing Module -- 4 Implementation and Evaluation -- 4.1 Implementation -- 4.2 Evaluation -- 5 Discussion, Conclusion, and Future Works -- References. An Intelligent Computing Method for Scheduling Projects with Normally Distributed Activity Times -- 1 Introduction -- 2 Project Scheduling with Crisp Activity Duration Times Using Approach Based on Linear Programming -- 2.1 Program Evaluation and Review Technique: Some Fundamental Definitions and Concepts -- 2.2 Scheduling Projects Using Linear Programming -- 3 Schedule Project with Normally Distributed Activity Times Using an Approach Based on Fuzzy Linear Programming -- 3.1 Solving a Class of Stochastic Programming Problems Using Fuzzy Linear Programming -- 3.2 Computing the Project Completion Time when Project Activity Duration Times are Random Variables following Normal Distributions -- 3.3 Finding Critical Activities when Project Activity Duration Times are Random Variables following Normal Distributions -- 4 Concluding Observations -- References -- Security and Privacy -- An Improved Hardware Architecture of Ethereum Blockchain Hashing System -- 1 Introduction -- 2 Proposed Ethash Hardware Architecture -- 2.1 The Architecture of Ethash -- 2.2 The Architecture of Keccak256_2stage -- 2.3 The Architecture of Main_Loop -- 3 Implementation Results -- 3.1 Keccak Implementation Result -- 3.2 Ethash Implementation Result -- 4 Conclusion -- References -- CSS-EM: A Comprehensive, Secured and Sharable Education Management System for Schools -- 1 Introduction -- 2 Blockchain -- 2.1 Overview -- 2.2 Substrate -- 3 Proposed Scorechain System -- 3.1 Scorechain System Overview -- 3.2 A Comprehensive University Management System -- 3.3 High Secure Data Management Through a Hierarchical Role Assignment Mechanism -- 3.4 Multiple Universities' High Secure Privacy and Data-Sharing Platform -- 4 System Implementation -- 5 Discussion -- 6 Conclusion -- References -- A High-Speed Barret-Based Modular Multiplication with Bit-Correction for the CRYSTAL-KYBER Cryptosystem. 1 Introduction -- 2 The Preliminary Background -- 2.1 Barret Reduction Method -- 2.2 K-RED/K2-RED Reduction Method -- 3 The Proposed Design -- 4 Implementation Result -- 5 Conclusion -- References -- Securing Digital Futures: Exploring Decentralised Systems and Blockchain for Enhanced Identity Protection -- 1 Introduction -- 2 Centralized and Decentralized Identity Models -- 2.1 Definition -- 2.2 Process -- 2.3 Practical Applications -- 2.4 Advantages -- 2.5 Disadvantages -- 2.6 Decentralized Identity Model -- 3 Preliminaries of Blockchain-Based Digital Identity Management System -- 3.1 Blockchain Technology -- 3.2 AI and OCR Technologies -- 3.3 Zero-Knowledge Proof and Smart Contracts -- 4 Proposed System Model and Processes for Managing Privacy Attributes -- 4.1 Scheme Overview -- 4.2 User Registration -- 4.3 Identity Verification -- 4.4 Authentication in Digital Identity Decentralized System on Blockchain -- 4.5 Access Control -- 5 Conclusion and Future Work -- 5.1 Conclusion -- 5.2 Future Work -- References -- Enhancing Blockchain Interoperability Through Sidechain Integration and Valid-Time-Key Data Access Control -- 1 Introduction -- 2 Related Works -- 3 Proposed System -- 3.1 Blockchain -- 3.2 Sidechain -- 3.3 Valid Time Key - VTK -- 3.4 Cross-Chain Data Transfer -- 4 Experiments and Results -- 4.1 Performance Evaluation -- 4.2 Security Analysis -- 5 Conclusions and Future Work -- References -- An IoT Attack Detection Framework Leveraging Graph Neural Networks -- 1 Introduction -- 2 Related Work -- 3 Graph Neural Networks (GNNs) -- 4 Data Preparation -- 4.1 Datasets -- 4.2 Data Acquisition and Integration -- 4.3 Data Preprocessing -- 4.4 Feature Selection -- 5 GraphSage-Based Attack Classification Framework -- 6 Performance Evaluation and Discussion -- 7 Conclusion -- References -- Network Attack Detection on IoT Devices Using 2D-CNN Models. 1 Introduction. |
| Record Nr. | UNINA-9910754096603321 |
|
Dao Nhu-Ngoc
|
||
| Cham : , : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||