Proceedings of International Conference on Artificial Intelligence and Applications : Icaia 2020.

Detaylı Bibliyografya
Yazar: Bansal, Poonam
Diğer Yazarlar: Tushir, Meena, Balas, Valentina Emilia, Srivastava, Rajeev
Materyal Türü: e-Kitap
Dil:İngilizce
Baskı/Yayın Bilgisi: Singapore : Springer Singapore Pte. Limited, 2020.
Edisyon:1st ed.
Seri Bilgileri:Advances in Intelligent Systems and Computing Series
Konular:
Artificial intelligence, Congresses.
Electronic books.
Online Erişim:Full-text access
İçindekiler:
  • Intro
  • Organization
  • ICAIA 2020 Organizing Committee
  • Advisory Committee
  • Technical Committee
  • ICAIA 2020 Keynote Speaker
  • ICAIA 2020 Invited Speakers
  • Preface
  • Contents
  • About the Editors
  • Evolving Machine Learning and Deep Learning Models for Computer Vision
  • Analysis of Breast Cancer Detection Techniques Using RapidMiner
  • 1 Introduction
  • 2 Related Work
  • 3 Comparative Study of Machine Learning Algorithms
  • 3.1 Decision Trees
  • 3.2 k-NN
  • 3.3 Neural Networks
  • 3.4 Linear Regression
  • 3.5 Support Vector Machines
  • 4 Results and Discussions
  • 5 Conclusion and Future Scope
  • References
  • Software Cost Estimation Using LSTM-RNN
  • 1 Introduction
  • 2 Related Work
  • 3 Recurrent Neural Network (RNN)
  • 4 Proposed Method
  • 5 Experimental Outcomes
  • 6 Conclusion
  • References
  • Artificial Neural Network (ANN) to Design Microstrip Transmission Line
  • 1 Introduction
  • 2 ANN Model for MTL
  • 3 Methodology
  • 4 Results and Discussion
  • 5 Conclusion
  • References
  • Classifying Breast Cancer Based on Machine Learning
  • 1 Introduction
  • 2 Methods
  • 2.1 Logistic Regression (LR)
  • 2.2 Support Vector Machines (SVMs)
  • 2.3 K-Nearest Neighbour (KNN)
  • 3 Experiments and Methodology
  • 3.1 Data Preparation and Analysis
  • 3.2 Implementation
  • 3.3 Training Method of Class of Breast Cancer Using SVM
  • 4 Results Analysis
  • 5 Conclusions
  • References
  • Comparison of Various Statistical Techniques Used in Meta-analysis
  • 1 Introduction
  • 2 Pooling Effect Sizes
  • 2.1 Forest Plots
  • 2.2 Moderator Variables and Subgroup Analysis
  • 2.3 Meta-regression
  • 3 Popular Algorithms
  • 3.1 Mantel Haenszel Method
  • 3.2 DerSimonian and Laird Approach
  • 3.3 Comparison
  • 4 Heterogeneity
  • 4.1 Cochran's Q
  • 4.2 Higgins and Thompson's I2
  • 4.3 H2 Test
  • 4.4 Identifying Best Measure of Heterogeneity
  • 5 Conclusion.
  • References
  • Stress Prediction Model Using Machine Learning
  • 1 Introduction
  • 2 Research Methodology
  • 2.1 Data Cleaning
  • 2.2 Data Transformation
  • 2.3 Data Reduction
  • 3 Data Visualization
  • 4 Application of Machine Learning Algorithm
  • 5 Results, Discussion and Conclusion
  • References
  • Finger Vein Recognition Using Deep Learning
  • 1 Introduction
  • 2 Literature Review
  • 3 Database Description
  • 4 Methodology
  • 4.1 Convolutional Neural Network
  • 4.2 One-Shot Learning (Triplet Loss Network)
  • 5 Proposed Architecture
  • 5.1 Convolutional Neural Network
  • 5.2 Triplet Loss Network
  • 6 Results and Discussion
  • 6.1 CNN Classification Model
  • 6.2 Triplet Loss Network One-Shot Learning Model
  • 7 Conclusion
  • References
  • Machine Learning Applications in Cyber Security and Cryptography
  • Secure Communication: Using Double Compound-Combination Hybrid Synchronization
  • 1 Introduction
  • 2 Problem Formulation
  • 3 System Description
  • 3.1 Fractional Order Hyper-Chaotic Xling Systems
  • 3.2 Fractional Order Hyper-Chaotic Vanderpol System
  • 3.3 Fractional Order Hyper-Chaotic Rabinovich System
  • 3.4 Fractional Order Hyper-Chaotic Rikitake System
  • 3.5 Complex Fractional Order Lorenz Chaotic System
  • 3.6 Complex Fractional Order T Chaotic System
  • 3.7 Complex Fractional Order Lu Chaotic System
  • 3.8 Complex Fractional Order Chen Chaotic System
  • 4 Double Compound-Combination Hybrid Synchronization on Eight Fractional Order Chaotic Systems
  • 5 Application in Secure Communication
  • 6 Conclusion
  • References
  • Fractional Inverse Matrix Projective Combination Synchronization with Application in Secure Communication
  • 1 Introduction
  • 2 Preliminaries
  • 2.1 Definitions
  • 3 Problem Formulation
  • 4 System Description
  • 5 Numerical Simulations and Discussion
  • 6 Illustration in Secure Communication
  • 7 Conclusions.
  • References
  • Cryptosystem Based on Hybrid Chaotic Structured Phase Mask and Hybrid Mask Using Gyrator Transform
  • 1 Introduction
  • 2 Theoretical Background
  • 2.1 Gyrator Transform
  • 2.2 Hybrid Chaotic Structured Phase Mask
  • 2.3 Hybrid Mask
  • 3 Proposed Work
  • 4 Results
  • 5 Conclusion
  • References
  • PE File-Based Malware Detection Using Machine Learning
  • 1 Introduction
  • 1.1 Static Analysis
  • 1.2 Dynamic Analysis
  • 2 Related Work
  • 3 Discussion
  • 4 Conclusion
  • References
  • Intelligence Graphs for Threat Intelligence and Security Policy Validation of Cyber Systems
  • 1 Logical Vulnerability, Threats and Risks in Cyber Security
  • 2 Ontologies, Knowledge Graphs and Process Workflows
  • 3 Ontology of Transactions Under Security Threats
  • 3.1 Logical Foundations of the Ontological Modelling
  • 3.2 Situations, Events, Threats and Items
  • 3.3 Actions
  • 3.4 Parametrization
  • 4 Heuristic Level and Security Policies
  • 4.1 Security Policies as Heuristics
  • 4.2 Types of Heuristics
  • 4.3 Examples of Heuristic Rules
  • 5 Workflow Level and Intelligence Graphs
  • 5.1 Transaction Flow as a Graph
  • 5.2 Framework Validation
  • 6 Process Level, Implementation and Future Work
  • References
  • Anomaly Detection Using Federated Learning
  • 1 Introduction
  • 2 Related Work
  • 2.1 Federated Learning
  • 2.2 Anomaly Detection
  • 2.3 Deep Learning
  • 2.4 Artificial Neutral Network
  • 2.5 Autoencoder
  • 3 Experiment
  • 4 Result
  • 5 Conclusion
  • References
  • Enhanced Digital Image Encryption Using Sine Transformed Complex Chaotic Sequence
  • 1 Introduction
  • 1.1 Chaotic Theory
  • 2 Proposed Encryption Strategy
  • 2.1 Surrounding Pixel Matrix Using SHA-256
  • 2.2 STLS
  • 2.3 Image Matrix Permutation
  • 2.4 Hybrid Rotation
  • 2.5 Diffusion
  • 3 Simulation Example
  • 4 Results
  • 4.1 Security Analysis of Secret Key.
  • 4.2 Analysis of Sensitivity of Algorithm to Plaintext
  • 4.3 Analysis of Image Pixel Correlation
  • 4.4 Analysis of Image Information Entropy
  • 5 Conclusion
  • References
  • Advances in Signal Processing and Learning Methods
  • A Low-Power Ring Voltage-Controlled Oscillator with MOS Resistor Tuning for Wireless Application
  • 1 Introduction
  • 2 VCO Design Methodology
  • 3 Results and Discussion
  • 4 Conclusion
  • References
  • Fuzzy Logic Control D-STATCOM Technique
  • 1 Introduction
  • 2 Modeling of D-STATCOM
  • 3 Synchronous Reference Frame Theory
  • 4 Design of Fuzzy Logic Controller
  • 5 Results and Discussions
  • 5.1 Performance Under Linear Load and Nonlinear Loads
  • 5.2 Performance Under Unbalanced Linear Load
  • 5.3 Comparison Analysis of Fuzzy Controller and PI Controller
  • 6 Conclusion
  • Appendix
  • References
  • Comparative Study on Machine Learning Classifiers for Epileptic Seizure Detection in Reference to EEG Signals
  • 1 Introduction
  • 2 Proposed Approach
  • 3 Dataset
  • 4 Classification Algorithms
  • 4.1 Na ive Bayes
  • 4.2 Logistic Regression
  • 4.3 k-NN
  • 4.4 Support Vector Machines
  • 4.5 Decision Trees
  • 4.6 Random Forest
  • 4.7 Neural Network
  • 5 Evaluation and Metrics
  • 6 Conclusion
  • References
  • Design Fundamentals: Iris Waveguide Filters Versus Substrate Integrated Waveguide (SIW) Bandpass Filters
  • 1 Introduction
  • 2 Design of Waveguide Iris Bandpass Filter
  • 2.1 Simulated Response of Filter
  • 3 The Substrate Integrated Waveguide Filter Design
  • 3.1 Simulated Response of SIW Bandpass Filter
  • 4 Conclusion
  • References
  • FPGA Implementation of Recursive Algorithm of DCT
  • 1 Introduction
  • 2 Proposed DCT-II Algorithm
  • 2.1 Derivation
  • 2.2 DCT-II Algorithm for N = 8
  • 3 Hardware Implementation of DCT Algorithm
  • 3.1 Architecture
  • 3.2 Verilog Program
  • 4 Results
  • 5 Conclusion
  • References.
  • Classification of EEG Signals for Hand Gripping Motor Imagery and Hardware Representation of Neural States Using Arduino-Based LED Sensors
  • 1 Introduction
  • 2 Literature Review
  • 3 Methodology
  • 3.1 Data Acquisition
  • 3.2 Data Preprocessing
  • 3.3 Feature Extraction
  • 3.4 Classification
  • 3.5 Hardware Implementation
  • 4 Results
  • 5 Discussion
  • References
  • Bandwidth and Gain Enhancement Techniques of DRA Antenna
  • 1 Introduction
  • 2 DRA Mathematical Modeling
  • 3 Antenna Designs
  • 4 Results and Discussion
  • 5 Conclusion
  • References
  • Social Intelligence and Sustainability
  • TODD: Time-Aware Opinion Dynamics Diffusion Model for Online Social Networks
  • 1 Introduction
  • 2 Existing Diffusion Benchmarks
  • 3 Proposed TODD Algorithmic Framework
  • 4 Discussion
  • 5 Conclusion
  • References
  • Spectral Graph Theory-Based Spatio-spectral Filters for Motor Imagery Brain-Computer Interface
  • 1 Introduction
  • 2 Proposed Approach: Graph Theory-Based Common Spatial Patterns (GBCSP)
  • 3 Experimental Results
  • 4 Conclusions
  • References
  • Discovering Mutated Motifs in DNA Sequences: A Comparative Analysis
  • 1 Introduction
  • 2 Problem Definition
  • 3 Literature Survey
  • 4 Algorithmic Analysis and Evaluation
  • 4.1 Graph-Based Algorithm
  • 4.2 Anchor-Based Clustering Algorithm
  • 4.3 Speed-up Technique
  • 4.4 Heuristic Algorithm Using Topic Models
  • 4.5 Using Genetic Algorithm
  • 4.6 MCES Algorithm for Large Dataset
  • 5 Comparative Analysis
  • 6 Conclusion
  • References
  • Classification of S&amp
  • P 500 Stocks Based on Correlating Market Trends
  • 1 Introduction
  • 2 Related Work
  • 3 Research Methodology
  • 3.1 Dataset Collection and Preprocessing
  • 3.2 Data Visualization
  • 3.3 Classifier Modeling and Implementation
  • 4 Results
  • 5 Conclusion and Future Scope
  • References.
  • Blockchain and Industrial Internet of Things: Applications for Industry 4.0.

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