Applications of Artificial Intelligence and Machine Learning: Select Proceedings of ICAAAIML 2021

✍ Scribed by Bhuvan Unhelker, Hari Mohan Pandey, Gaurav Raj

• Publisher: Springer
• Year: 2022
• Tongue: English
• Leaves: 792
• Series: Lecture Notes in Electrical Engineering, 925
• Category: Library

✦ Synopsis

The book presents a collection of peer-reviewed articles from the International Conference on Advances and Applications of Artificial Intelligence and Machine Learning―ICAAAIML 2021. The book covers research in the areas of artificial intelligence, machine learning, and deep learning applications in health care, agriculture, business, and security. This book contains research papers from academicians, researchers as well as students. There are also papers on core concepts of computer networks, intelligent system design and deployment, real-time systems, wireless sensor networks, sensors and sensor nodes, software engineering, and image processing. This book is a valuable resource for students, academics, and practitioners in the industry working on AI applications.

✦ Table of Contents

Contents
About the Editors
Firefly Algorithm and Deep Neural Network Approach for Intrusion Detection
1 Introduction
1.1 Research Goals and Contributions
1.2 Structure of the Paper
2 Theoretical Background and Literature Review
3 Proposed Method
3.1 Enhanced FA Metaheuristics
4 The eFA and DNN Framework for IDS Classification Experiments
5 Conclusion
References
Dimensionality Reduction Method for Early Detection of Dementia
1 Introduction
2 Related Works
3 Methodology
3.1 Materials and Subjects
3.2 Pre-processing
3.3 Feature Reduction
4 Result and Discussion
5 Conclusion
References
Prognostication in Retail World: Analysing Using Opinion Mining
1 Introduction
2 Literature Survey
3 Proposed Model
3.1 Sentimental Analysis
3.2 Classification Model
3.3 Techniques and Tools
4 Data
5 Evaluation Outcome
6 Conclusion
References
Impact of Resolution Techniques on Chlorophyll Fluorescence Wheat Images Using Classifier Models to Detect Nitrogen Deficiency
1 Introduction
2 Related Work
3 Experimental Setup
4 Results and Discussions
5 Conclusions
References
Exploring Practical Deep Learning Approaches for English-to-Hindi Image Caption Translation Using Transformers and Object Detectors
1 Background
2 Dataset, Methodology and Experimental Setup
2.1 Dataset
2.2 Experimental Setup
2.3 Pre-processing Dataset
2.4 Run-Time Data Handling
2.5 Training and Evaluation
3 Model Architectures and Configurations Tested
3.1 Class A (Seq2Seq Caption Translation)
3.2 Class B (Transformer Caption Translation)
3.3 Class C (Pre-trained Transformer Caption Translation)
4 Results
5 Comparison with Existing Work
6 Conclusion
References
Saving Patterns and Investment Preferences: Prediction Through Machine Learning Approaches
1 Introduction
2 Review of Literature and Hypothesis Development
3 Data Analysis
3.1 Regression Equation and Data
4 Result Analysis and Discussion
4.1 Effect of Eight Independent Variables on the Saving Patterns
4.2 Effect of Eight Independent Variables on the Investment Preferences
4.3 Discussion
5 Conclusion
References
A Machine Learning Based Approach for Detection of Distributed Denial of Service Attacks
1 Introduction
2 Related Work
3 Proposed Framework for DDoS Attack Detection
3.1 Problem Definition
3.2 The Framework
3.3 Proposed Algorithm
3.4 Metrics for Performance Evaluation
4 Experimental Results
5 Conclusion and Future Work
References
Convolutional Neural Network Based Automatic Speech Recognition for Tamil Language
1 Introduction
2 Literature Review
3 Convolution Neural Network
4 Experimental Setup
4.1 Feature Extraction
4.2 Convolutional Neural Network Model
5 Result and Discussion
6 Conclusion
References
Identification of Wheat and Foreign Matter Using Artificial Neural Network and Genetic Algorithm
1 Introduction
2 Proposed Methodology
2.1 Preparation of Samples
2.2 Image Segmentation
2.3 Feature Extraction
2.4 Detection using ANN
2.5 Selection of Optimal Features Using GA
3 Experimental Results and Discussions
4 Conclusion
References
Efficient Classification of Heart Disease Forecasting by Using Hyperparameter Tuning
1 Introduction
2 Related Works
3 Methodology
3.1 Classification of Heart Disease Prediction Using Neural Network Model with Hyper Parameter Tuning
3.2 Automatic Hyper Parameter Tuning
3.3 Evaluation Metrics
4 Results and Discussion
4.1 Outcome of Data Pre-processing
4.2 Performance Evaluation
4.3 Comparison of Model Performance with and without Hyper Parameter Tuning
5 Conclusion
References
LS-Net: An Improved Deep Generative Adversarial Network for Retinal Lesion Segmentation in Fundus Image
1 Introduction
2 Related Work
3 Methodology
3.1 Conditional GANs
3.2 Image-To-Image Translation Network
3.3 Spectral Normalization
3.4 Loss Function
4 Experimental Setup
4.1 Dataset
4.2 Evaluation Metrics
4.3 Network Training
4.4 Implementation Details
5 Results and Discussion
5.1 Results
5.2 Discussion
6 Conclusion
References
A Novel Approach for Analysis of Air Quality Index Before and After Covid-19 Using Machine Learning
1 Introduction
2 Background and Motivation
3 Proposed Work
4 Multiple Linear Regression
5 Polynomial Regression
6 Experimental Result
6.1 Dataset
6.2 Evaluation Matrix
6.3 Result and Discussion
7 Conclusion
References
Embedding of Q-Learning in Sine Co-Sine Algorithm for Optimal Multi Robot Path Planning
1 Introduction
2 Formulation of the Problem
2.1 Objective Function Creation for Optimized Navigation
2.2 Movement of Mobile Robot
3 Projected Optimization Methods
3.1 Q-Learning Algorithm
3.2 Sine–Cosine Algorithm (SCA)
4 Necessity of Hybridization and Proposed Algorithm for Multi-robot Path Planning
5 Computer Simulation
6 Experiment on E-puck Robot
7 Performance Analysis
8 Conclusion and Future Works
References
Image-Based Number Sign Recognition for Ethiopian Sign Language Using Support Vector Machine
1 Introduction
2 Related Works
3 Ethiopian Sign Language Number System
3.1 Amharic Sign Language System
3.2 Proposed System
3.3 Support Vector Machine Modeling
4 Results and Discussion
4.1 Dataset
4.2 Performance Evaluation
4.3 Test Result
5 Conclusion
References
BIC Algorithm for Exercise Behavior at Customers’ Fitness Center in Ho Chi Minh City, Vietnam
1 Introduction
2 Literature Review
2.1 Exercise Behavior (EB)
2.2 Usefulness (US)
2.3 Ease of Use (EU)
2.4 Barrier (BR)
2.5 Facilities (FAC)
2.6 Price and Promotion (PP)
2.7 Service Quality (SQ)
3 Methodology
3.1 Sample
3.2 Reliability Test and BIC Algorithm
4 Results
4.1 Reliability Test
4.2 BIC Algorithm
4.3 Model Evaluation
5 Conclusions
6 Limitations and Future Scope
References
Medicine Supply Chain Using Ethereum Blockchain
1 Introduction
2 Related Previous Work
3 Proposed Method
3.1 Overview of Drug SCM Procedure
3.2 Three-Layer Architecture
3.3 Detail Architecture of Proposed DSCM System
3.4 Smart Contract of DSCM
3.5 Transactions Execution Procedure in DSCM
4 Stakeholders
4.1 Supplier
4.2 Manufacturer
4.3 Distributor
4.4 Hospitals
4.5 Pharmacies
5 Scope
6 Result and Evaluation
6.1 Deployment Costs
6.2 Price of the Gas Used in deploy the Smart Contract
7 Conclusion and Future Work
References
Human Activity Recognition Using Single Frame CNN
1 Introduction
2 Literature Survey
3 Proposed Methods and Results
3.1 CNN Classification Model
3.2 Compile and Train the Model
3.3 Plot Accuracy Curves and Model’s Loss
4 Conclusion
5 Future Scope
References
Monitoring Pedestrian Social Distance System for COVID-19
1 Introduction
2 Literature Survey
3 Technologies Used
3.1 Python
3.2 OpenCV
3.3 YOLOv3
4 Propounded Monitoring Pedestrian Scheme
4.1 Camera Perspective Transformation
4.2 Pedestrian Detection and Tracking
4.3 Distance Calculation
4.4 Distance Violation with Count
5 Testing and Analysis
6 Conclusion
References
A Study and Comparative Analysis on Different Techniques Used for Predicting Type 2 Diabetes Mellitus
1 Introduction
1.1 Classification of Diabetes Mellitus: There Are Primarily Three Types of Known Diabetes Mellitus
1.2 Possible Reasons for Diabetes
1.3 Possible Problems Due to Diabetes:
2 Existing Predictive Analysis Techniques
2.1 Machine Learning (ML) Algorithms can be broadly classified as
2.2 Deep Learning (DL) Algorithm
2.3 Nature-Inspired Algorithm
3 Performance Analysis of Various Predictive Analysis Techniques
4 Comparison of Techniques Employed for Diabetes Prediction
5 Conclusion and Future Scope
References
RGB Based Secure Share Creation in Steganography with ECC and DNN
1 Introduction
2 Steganographic Techniques
3 Elliptic Curve Cryptography [ECC]
3.1 Proposed Model
3.2 Implementation Specifications
3.3 Modelling of Architecture
3.4 Secure Share Creation Using RGB
3.5 Reconstruction of the Shadow Images
4 Results and Discussion
4.1 Results for Multiple Hidden Secrets
4.2 Splitting of Channels
4.3 Creating Shares or Shadows of the Corresponding Channels
4.4 Encrypting the Generated Shares
4.5 Comparison of Histogram Between the Original Shares and the Encrypted Shares
4.6 Decryption and Stacking of Shares
4.7 Revealed Network
4.8 SSIM of Cover, Container, Secret and Decoded Secret Images
4.9 Complexity of Computation
5 Conclusion
References
Model to Detect and Correct the Grammatical Error in a Sentence Using Pre-trained BERT
1 Introduction
2 Related Work
3 Methodology
4 Results
5 Conclusion
References
Crop Recommendation System for Precision Agriculture Using Fuzzy Clustering Based Ant Colony Optimization
1 Introduction
2 Related Work
3 Proposed Methodology
3.1 Collaborative Filtering
3.2 Ant Colony Optimization (ACO)
3.3 Fuzzy Systems
3.4 Fuzzy Clustering
3.5 Fuzzy Clustering ACO
4 Results and Discussion
4.1 Dataset
4.2 Data Pre-processing
4.3 Evaluation Metrics and Tuning Step
4.4 Graph and Tables
5 Conclusions
References
Classification and Hazards of Arsenic in Varanasi Region Using Machine Learning
1 Introduction
2 Materials and Methods
2.1 Study Area and Sampling
2.2 Implementation of Machine Learning Algorithms
3 Results and Discussion
3.1 Classification of Arsenic Contamination in Groundwater
3.2 Approximation of Number of Population Affected by as Contamination
4 Conclusion
References
Implementing Reinforcement Learning to Design a Game Bot
1 Introduction
1.1 Purpose of Plan
2 A Dynamic Decision Problem—Bellman Equation
2.1 Applying Bellman’s Equation in Reinforcement Learning
3 Markov Decision Process
3.1 Markov Property
3.2 Defining Markov Decision Process
4 Q Learning Algorithm
5 Deep Q Learning
5.1 Need for Deep Q Learning
5.2 Process
5.3 Experience Replay
6 Deep Convolutional Q Learning
6.1 Brief About Deep Convolutional Learning
6.2 Steps Involved in Deep Convolutional Q Learning
7 Results
8 Conclusion and Future Scope
References
Darknet (Tor) Accessing Identification System Using Deep-Wide Cross Network
1 Introduction
2 Review of Literature
3 Proposed Scheme
3.1 Dataset
3.2 Pre-processing
3.3 Feature Selection
3.4 Classification
4 Performance Evaluation
5 Conclusion
References
Energy Efficient Dual Probability-Based Function of Wireless Sensor Network for Internet of Things
1 Introduction
2 Related Work
3 Proposed Methodology
3.1 Dual Probability Function (DPF)
3.2 System Model
3.3 Algorithm 1: DP_E Estimation
3.4 Algorithm 2: DP (Dual Probability)
3.5 Algorithm 3: Integration of Sink Nodes
4 Experimental Results
5 Conclusion and Future Scope
References
OFDMA Based UAVs Communication for Ensuring QoS
1 Introduction
2 System Model
2.1 IEEE 802.11 EDCAF
2.2 Markov Model
2.3 Throughput and PDR Analysis
3 Delay Analysis
4 Simulation Results
5 Conclusion
References
Personalization and Prediction System Based on Learner Assessment Attributes Using CNN in E-learning Environment
1 Introduction
2 Review of Literature
3 Proposed Scheme
3.1 Initial and Collection Phase
3.2 Pre-processing Phase
3.3 Profiling Phase
3.4 Feature Construction Phase
3.5 Identification Phase
4 Result and Discussion
4.1 Environmental Setup
4.2 Evaluation Result
5 Conclusion
References
Prognosis of Clinical Depression with Resting State Functionality Connectivity using Machine Learning
1 Introduction
2 Related Work
3 Proposed Methodology
3.1 Dimensionality Reduction Using Principal Component Analysis
3.2 K-Nearest Neighbor Algorithm for Depression Prediction
4 Experimental Evaluation
4.1 Performance Evaluation Metrics
5 Conclusion
References
Medical Diagnosis Using Image-Based Deep Learning and Supervised Hashing Approach
1 Introduction
1.1 Content Based Medical Image Retrieval (CBMIR)
1.2 Deep Learning with DCNN
2 Methodology
2.1 Proposed Framework
3 Algorithms
3.1 Algorithm 1: Training the Network
3.2 Feature Extraction and Image Retrieval
3.3 Algorithm 2: Implementing Hash Function and Fast Image Retrieval
4 Result and Discussion
4.1 Description of Dataset
5 Experimental Results
6 Conclusion
References
Ontological Representation and Analysis for Smart Education
1 Introduction
2 Literature Survey
2.1 First Generations
2.2 Second Generations
3 Basic Definitions Used
4 Ontological Knowledge Representation
5 Discussion
6 Conclusion
References
Empirical Analysis of Diabetes Prediction Using Machine Learning Techniques
1 Introduction
2 Related Work
3 Application of Techniques
4 Dataset Details
4.1 Understanding the Dataset
4.2 Cleaning and Preprocessing of Dataset
4.3 Training Model Using Different Classifiers
4.4 Evaluation of Classifiers Performance Metrics
5 Results
6 Conclusion and Future Scope
References
An Energy Efficient Smart Street Lamp with Fog-Enabled Machine Learning Based IoT Computing Environments
1 Introduction
2 Related Work
3 Smart Street Lamp
3.1 Energy Conserving Unit
3.2 Communication Network
3.3 Master Light Controller
4 System Architecture
4.1 Street Lamp Sensor Network
4.2 Fog Computing Framework
4.3 Cloud Data Center
5 Design and Implementation
6 Performance Evaluation
7 Conclusion
References
A Comparative Study of Machine Learning and Deep Learning Techniques on X-ray Images for Pneumonia
1 Introduction
2 Related Work
3 Dataset Description
4 Exploratory Data Analysis (EDA) and Data Preprocessing
4.1 Convolution Neural Network
4.2 Multi-layer Perceptron
4.3 MobileNet
4.4 Machine Learning Techniques
5 Application of Techniques
5.1 Deep Learning Models
5.2 Machine Learning Models
6 Results and Discussion
7 Conclusion and Future Scope
References
Analysis of Covid-19 Fake News on Indian Dataset Using Logistic Regression and Decision Tree Classifiers
1 Introduction
2 Literature Review
3 Materials and Methods
3.1 Proposed Framework
3.2 Collecting Data
3.3 Algorithms
4 Datasets
4.1 Dataset Information
4.2 Dataset Analysis
5 Evaluation Metrics
5.1 Recall
5.2 Precision
5.3 F1-score
5.4 Accuracy
6 Results
7 Conclusion
References
A Multilingual iChatbot for Voice Based Conversation
1 Introduction
2 Related Work
3 Dataset Description
3.1 Multi-linguistic Dataset
3.2 Preprocessing with NLP and NLTK
4 Proposed Method
4.1 Deep Neural Network Model
4.2 Speech-to-Text Recognition
4.3 Graphical User Interface
5 Implementation Details
6 Result Analysis
7 Conclusion
References
Analysis and Forecasting of COVID-19 Pandemic on Indian Health Care System During Summers 2021
1 Introduction
2 Literature Review
3 Research Dataset and Methodology
4 Results and Discussion
5 Conclusions
References
A Novel Approach to Image Forgery Detection Techniques in Real World Applications
1 Introduction
2 Literature Survey
3 Proposed Methodology
3.1 Dataset
3.2 VGG-19 Architecture
3.3 VGG-16 Architecture
3.4 EfficientNet
4 Results
4.1 Evaluation Metrics
5 Conclusion
References
Modified Bat Algorithm for Balancing Load of Optimal Virtual Machines in Cloud Computing Environment
1 Introduction
2 Related Work
3 Modified Bat Algorithm for Load Balancing in Cloud Computing
4 Comparative Analysis of Proposed Algorithm
5 Conclusion and Future Work
References
Forecasting Floods Using Classification Based Machine Learning Models
1 Introduction
2 Related Work
3 ML Based Flood Forecasting Model
4 Experimental Results
4.1 Accuracy
4.2 Precision
4.3 Recall
4.4 F-measure
4.5 AUC-ROC
5 Conclusion
References
Multilayer Perceptron Optimization Approaches for Detecting Spam on Social Media Based on Recursive Feature Elimination
1 Introduction
2 Literature Review
3 Methodology
3.1 Data Collection and Description
3.2 Feature Selection
3.3 Multilayer Perceptron
3.4 Evaluation
4 Experimental Results and Evaluation
4.1 Tool Used
4.2 Performance Metrics
4.3 Results
5 Conclusion and Future Scope
References
Convolution Neural Network Based Classification of Plant Leaf Disease Images
1 Introduction
2 Related Work
3 Materials and Methodology
3.1 Materials
3.2 Methodology
4 Proposed Work
4.1 Proposed VGG16 Architecture
5 Experimental Results
5.1 Accuracy, Loss and Execution Time for Different CNN’s Using Various Optimizers
5.2 Performance Analysis of Alex Net, ResNet50 and VGG16 CNN Models in Classification
5.3 Model Validation
5.4 Performance Measure Indices
6 Conclusions
References
Predicting Deflagration and Detonation in Detonation Tube
1 Introduction
2 Literature Review
3 Experiment Description
3.1 Study Limitations
3.2 Preprocessing
3.3 Tools Used in Research
4 Classification Results
4.1 Maximum Velocity
4.2 Maximum Pressure
5 Discussion of the Results
6 Conclusion and Future Work
References
Movie Recommendation Based on Fully Connected Neural Network with Matrix Factorization
1 Introduction
2 Review of Existing Works
3 Proposed Technique
3.1 Dataset Description
3.2 Feature Analysis
3.3 Content-Based Filtering
3.4 Collaborative Filtering (CF)
3.5 Deep Neural Network
4 Performance Analysis
5 Conclusion
References
PropFND: Propagation Based Fake News Detection
1 Introduction
2 Literature Survey
2.1 Text Based Detection
2.2 User Profile-Based Detection
2.3 Propagation Based Detection
3 Classifier Background
3.1 Naive Bayes (NB)
3.2 Support Vector Machine (SVM)
3.3 Random Forest (RF)
3.4 Artificial Neural Network (ANN)
4 Proposed Model
4.1 PropFND Model Algorithm
4.2 PropFND Model Design
5 Implementation and Result
5.1 Experimental Setup
5.2 Dataset
5.3 Performance Metrics
5.4 PropFND Model
5.5 Result
5.6 Comparative Study
6 Conclusion and Future Work
References
Depression Detection Using Spatial Images of Multichannel EEG Data
1 Introduction
2 Materials and Methods
2.1 About Dataset
2.2 EEG Classification System
3 Experimental Results
3.1 Experimental Setup
3.2 Results
3.3 Discussion
4 Conclusion and Future Work
References
Feature Selection for HRV to Optimized Meticulous Presaging of Heart Disease Using LSTM Algorithm
1 Introduction
1.1 HRV Metrics
2 Literature Review
3 Feature Selection Techniques
3.1 Sequential Forward Selection
3.2 Sequential Floating Forward/Backward Selection (SFFS and SFBS)
3.3 SFFS (Sequential Floating Forward Selection)
3.4 Sequential Floating Backward Selection
3.5 Sequential Backward Selection
3.6 LSTM
4 Machine Learning Classifiers
4.1 KNN
4.2 SVM
4.3 Random Forest (RF)
4.4 Gradient Boosting (GB)
4.5 NB
5 Materials and Methods
5.1 Proposed Methodology
6 Results and Discussion
7 Conclusion
References
Determining the Most Effective Machine Learning Techniques for Detecting Phishing Websites
1 Introduction
2 Related Work
3 Proposed Approach
4 Dataset
4.1 Address Bar Based Features
4.2 Abnormal Based Features
4.3 Domain Based Features
5 Result and Analysis
6 Conclusion
References
Performance Analysis of Computational Task Offloading Using Deep Reinforcement Learning
1 Introduction
2 Related Work
3 Overview of Computational Offloading
3.1 Cost of Computation Offloading
3.2 Cost of Local Computing
4 Problem Formulation
5 Computational Offloading Scheme Using Deep Reinforcement Learning
6 Result Analysis
6.1 Energy Consumption Versus the Number of Iteration
6.2 Energy Consumption Versus the Maximum Power
6.3 Welfare Versus Number of Mobile Users
6.4 Welfare Versus Different Request Workload
6.5 Comparative State-Of-Art
7 Conclusion
References
GyanSagAR 1.0: An AR Tool for K-12 Educational Assistance
1 Introduction
1.1 Motivation of Work
1.2 Augmented Reality
2 Literature Review
3 Implementation
3.1 Unity
3.2 AR Foundation
3.3 Sections of GyanSagAR 1.0
3.4 Workflow of GyanSagAR 1.0
4 Comparative Analysis
5 Conclusion and Future Scope
References
Performance Analysis of Energy Efficient Optimization Algorithms for Cluster Based Routing Protocol for Heterogeneous WSN
1 Introduction
2 Related Work
3 Methodology
3.1 Network Model
3.2 Energy Consumption Model
3.3 Bio-inspired Optimization Algorithms
3.4 Parameters for Designing Bio-Inspired Optimization Algorithm
4 Discussion
4.1 Simulation Scenario
4.2 Result Analysis
5 Conclusion
References
Applied Multivariate Regression Model for Improvement of Performance in Labor Demand Forecast
1 Introduction
2 The Proposed Model
2.1 Applied Regression Function to the Proposed Model for Labor Forecast
2.2 Hypothesis of Multivariate Regression Models for Labor Forecast
2.3 Applied the Proposed Model for Labor Forecasting
2.4 Parameter estimation
3 Experimental Results
4 Conclusion
References
Twitter Sentiment Analysis on Oxygen Supply During Covid 19 Outbreak
1 Introduction
2 Literature Review
3 Research Methodology
4 Implementation
4.1 Data Collection
4.2 Pre-processing
4.3 Sentiment Analysis and Classification
5 Experimental Results and Discussion
6 Conclusion
References
Artificial Eye for the Visually Impaired
1 Introduction
2 Fundamentals
3 Related Work
4 Methodology
4.1 Input
4.2 Object Detection
4.3 Estimating Position and Depth and Output
5 Experimentation
6 Dataset Description
7 Computation
7.1 Tensor Processing Unit
8 Training
8.1 Training the Model
9 Experimental Result and Discussion
10 Future Work
References
Blockchain Network: Performance Optimization
1 Introduction
1.1 Types of Blockchain
2 Performance of Blockchain
2.1 Performance Evaluation
2.2 Benchmarking
2.3 Transaction Latency Time
2.4 Transaction Throughput
3 Blockchain Performance Analysis Tool: Hyperledger Caliper
3.1 Hyperledger Fabric Blockchain Architecture
3.2 Performance Analysis on Hyperladger Fabric Blockchain Network
4 Blockchain Performance Impacting Parameters
4.1 Block Size
4.2 Endorsement Policy
4.3 Channel
4.4 Resource Allocation
4.5 Ledger Database
4.6 Other Performance Impacting Parameters
5 Conclusion
References
Abstractive Text Summarization Using Attentive GRU Based Encoder-Decoder
1 Introduction
2 Related Work
3 Methodology
3.1 Data Collection and Pre-processing
3.2 GRU Based Encoder-Decoder with Attention
4 Experiment and Result Analysis
4.1 Sample Output
5 Conclusion and Future Work
References
Object Detection and Foreground Extraction in Thermal Images
1 Introduction
2 Proposed Methodology
3 GrabCut Algorithm
4 Mask RCNN
5 Experimental Results
6 Conclusion
References
STABA: Secure Trust Based Approach for Black-Hole Attack Detection
1 Introduction
2 Background Study
2.1 Black-Hole Attack
3 Literature Review
4 Proposed System
4.1 Concept
4.2 Algorithm Design
5 Simulation
5.1 Simulation Arrangement
5.2 Simulation Scenario
6 Result Analysis
6.1 E to E Delay
6.2 PDR
6.3 Network Throughput
7 Conclusion
References
Wind Speed Prediction in the Region of India Using Artificial Intelligence
1 Introduction
2 Literature Review
3 Methodology
4 Result
4.1 Ultra-Short-Term WSF
4.2 Short-Term WSF
4.3 Medium-Term WSF
4.4 Long-Term WSF
5 Conclusion
6 Future Work
References
Lung Cancer Detection Using Modified Fuzzy C-Means Clustering and Adaptive Neuro-Fuzzy Network
1 Introduction
2 Literature Survey
3 Proposed System
3.1 Image Acquisition
3.2 Wiener Filter
3.3 Modified Fuzzy C-Means Clustering
3.4 Feature Extraction
3.5 Random Forest Adaptive Neuro-Fuzzy Classifier
4 Results and Discussions
4.1 Training Phase
4.2 Testing Phase
5 Conclusion
References
Significance of Preprocessing Techniques on Text Classification Over Hindi and English Short Texts
1 Introduction
2 Related Works
3 Best Preprocessing Strategies for Hindi and English Text
4 Text Classification Experiments
4.1 Datasets and Preprocessing
4.2 Classification Techniques
5 Results and Discussions
6 Conclusion
References
CD-KNN: A Modified K-Nearest Neighbor Classifier with Dynamic K Value
1 Introduction
1.1 Motivation
1.2 Problem Definition
1.3 Contributions
2 Proposed Method
2.1 Conceptual Framework of CD-KNN Method
2.2 How Does CD-KNN Differ from KNN?
2.3 Complexity Analysis
3 Experimental Analysis
3.1 Dataset Description
3.2 Result Analysis on UCI Datasets
4 Conclusion and Future Work
References
Automated Classification of Hyper Spectral Image Using Supervised Machine Learning Approach
1 Introduction
2 Related Work
3 Materials and Methods
4 Results and Discussion
5 Conclusion
References
An Ensemble Model for Network Intrusion Detection Using AdaBoost, Random Forest and Logistic Regression
1 Introduction
2 Literature Review
3 Proposed Methodology
3.1 Dataset for Empirical Evaluation
3.2 Data Preprocessing
3.3 Base Learning Techniques
4 Experimental Setup and Results
4.1 Dataset
4.2 Experiment
4.3 Results
5 Comparative Analysis
6 Conclusion and Future Work
References
Real Time Location Tracking for Performance Enhancement and Services
1 Introduction
2 Background Details and Related Work
3 Proposed Approach
3.1 Data Flow Diagram for the Application
3.2 Deep Learning Using LSTM Model
3.3 Advantages of Time Series Model
4 Results
5 Challenges, Conclusion and Future Scope
References
Enhanced Contrast Pattern Based Classifier for Handling Class Imbalance in Heterogeneous Multidomain Datasets of Alzheimer Disease Detection
1 Introduction
2 Related Work
3 Methodology: Handling Class Imbalance in Alzheimer Detection Using Enhanced Contrast Pattern Based Classifier
3.1 Dataset Description
3.2 Data Preprocessing
3.3 Mutual Information for Feature Elimination
3.4 Pruning Redundant Itemsets
4 Results and Discussions
5 Conclusion
References