Kooperativer Bibliotheksverbund

UID:

Format: XV, 440 p. 192 illus., 167 illus. in color. , online resource.

Edition: 1st ed. 2023.

ISBN: 9783031465734

Series Statement: Lecture Notes on Data Engineering and Communications Technologies, 187

Content: This book aims to provide state-of-the-art knowledge in the field of Intelligence of Things to both academic and industrial readers. In particular, undergraduate, graduate, and researchers may find valuable information to drive their future research. This book is considered a reference for numerous courses such as Artificial Intelligence, Internet of Things, Intelligent Systems, and Mobile Networks. In the industrial area, this book provides information on recent studies in applying AI to IoT developments, which help to align and shorten R&D processes to introduce new classes of intelligent IoT products. This book provides a technical reference for interdisciplinary studies which utilize machine learning and IoT as tools in their fields such as constructional management, smart agriculture, Earth sciences and geo-spatial analysis, intelligent business, and digital transformation in education.

Note: FPGA/AI-Powered Data Security for IoT Edge Computing Platforms: A Survey and Open Issues -- A Review in Deep Learning-Based Thyroid Cancer Detection Techniques Using Ultrasound Images -- Bio-Inspired Clustering: An Ensemble Method for User-Based Collaborative Filtering -- Deep Reinforcement Learning-Based Sum-Rate Maximization for Uplink Multi-User SIMO-RSMA Systems -- Multiobjective Logistics Optimization for Automated ATM Cash Replenishment Process -- Adaptive Conflict-Averse Multi-Gradient Descent for Multi-Objective Learning -- Multicriteria Portfolio Selection with Intuitionistic Fuzzy Goals as a Pseudoconvex Vector Optimization -- Research and Develop Solutions to Traffic Data Collection Based on Voice Techniques -- Using Machine Learning Algorithms to Diagnosis Melasma from Face Images -- Reinforcement Learning for Solving Portfolio Selection Problems in the Vietnamese Market -- Towards a Smart Parking System with the Jetson Xavier Edge Computing Platform -- AlPicoSoC: A Low-Power RISC-V Based System on Chip for Edge Devices with a Deep Learning Accelerator -- A Transparent Scalable E-Voting Protocol Based on Open Vote Network Protocol and Zk-STARKs -- DarkMDE: Excavating Synthetic Images for Nighttime Depth Estimation Using Cross-Domain Supervision.

In: Springer Nature eBook

Additional Edition: Printed edition: ISBN 9783031465727

Additional Edition: Printed edition: ISBN 9783031465741

Language: English

DOI: 10.1007/978-3-031-46573-4

URL: https://doi.org/10.1007/978-3-031-46573-4

URL: Volltext  (URL des Erstveröffentlichers)

UID:

Format: 1 online resource (452 pages)

Edition: 1st ed.

ISBN: 9783031465734 , 3031465733

Series Statement: Lecture Notes on Data Engineering and Communications Technologies Series ; v.187

Content: This book contains the proceedings from the Second International Conference on Intelligence of Things (ICIT 2023) held in Ho Chi Minh City, Vietnam. It explores the integration of artificial intelligence (AI) with the Internet of Things (IoT) to form the AIoT, a technology aimed at enhancing IoT operations through intelligent adaptations. The volume consists of selected papers presenting cutting-edge research and applications in AIoT, emphasizing the advancements in data engineering and technologies. The book is intended for scholars, researchers, and professionals interested in the latest developments in AIoT and data technologies.

Note: 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.

Additional Edition: Print version: Dao, Nhu-Ngoc Intelligence of Things: Technologies and Applications Cham : Springer,c2023 ISBN 9783031465727

Language: English