Note: Intro -- Preface -- Contents -- Automatic Notes Generation from Lecture Videos -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 4 Procedure -- 4.1 Extraction of Audio and Speech Recognition -- 4.2 Punctuating the Text and Preprocessing -- 4.3 Dividing into Subtopics -- 4.4 Generating PDF and PPT -- 5 Results -- 6 Conclusion and Future Work -- References -- Correlation Between Code Smells for Open Source Java Projects -- 1 Introduction -- 2 Related Study -- 3 Research Methodology -- 3.1 Datasets -- 3.2 Code Smells -- 3.3 Correlation -- 4 Results -- 5 Conclusions and Future Scope -- References -- Throughput Improvement in Energy Efficient Heterogeneous Wireless Sensor Network -- 1 Introduction -- 1.1 Sensor Node -- 1.2 Energy Saving Mechanisms in WSN -- 1.3 Routing Protocols -- 1.4 Energy Efficiency in Mac Protocols in WSN -- 1.5 Motivation -- 2 Literature Review -- 3 Energy Consumption Model -- 4 EEC Network Model -- 4.1 Cluster Formation and Cluster Head Selection -- 5 Proposed Protocol -- 6 Simulation Parameters -- 7 Simulation Results and Discussion -- 7.1 Network Initialization and Neighbour Discovery -- 7.2 Cluster Formation and CH Selection -- 8 Performance Analysis -- 8.1 Energy Graph -- 8.2 Packet Delivery Ratio -- 8.3 Throughput -- 9 Conclusions -- References -- Deep Learning Models for Rubik's Cube with Entropy Modelling -- 1 Introduction -- 2 Related Works -- 3 Proposed Methodology -- 3.1 Data Structure Generation -- 3.2 Data Set Generation Using Standard Algorithms -- 3.3 Deep Learning Models (RL/CNN/LSTM) Implementation -- 3.4 Entropy Modelling Traversal -- 4 Results and Discussion -- 5 Conclusion and Future Work -- References -- Detecting Diabetic Retinopathy Using Deep Learning Technique with Resnet-50 -- 1 Introduction -- 2 Literature Survey -- 3 Proposed System -- 3.1 Feature Extraction in Fundus Image. , 3.2 Fundus Image Classification -- 4 Results -- 4.1 Symptoms Identification -- 4.2 Disease Severity Classification -- 5 Conclusion and Future Scope -- References -- Restoration of Rician Corrupted MR Data Using Improved Hybrid Model -- 1 Introduction -- 2 Background -- 2.1 Rician Distribution in Molecular Imaging -- 2.2 Application of Hybrid Filter in MR Imaging -- 3 Experimental Results -- 3.1 Hybrid Model Applied to Thorax MR Images -- 3.2 Hybrid Model Applied to Brain MR Images -- 4 Conclusion -- References -- Flight Delay Prediction Using Random Forest Classifier -- 1 Introduction -- 2 Related Work -- 2.1 Dataset -- 3 System Implementation and Results -- 4 Conclusion -- 5 Future Enhancement -- References -- A Framework Using Markov-Bayes' Model for Intrusion Detection in Wireless Sensor Network -- 1 Introduction -- 2 Related Research -- 3 The Model -- 4 Hidden Markov and Bayesian Network Model -- 5 Simulation Experiments and Result Analysis -- 6 Conclusion -- References -- Effective Text Comment Classification Using Novel ML Algorithm-Modified Lazy Random Forest -- 1 Introduction -- 2 Literature Review -- 3 System Design -- 3.1 Data Pre-Processing -- 3.2 Training with the Model -- 3.3 SPAM Classification -- 4 Proposed Algorithm -- 5 Experiment and Results -- 6 Results with HOLD-OUT Method: Youtube and SMS Dataset -- 6.1 Hold-Out Method Results on Youtube Dataset -- 6.2 Hold-Out Method Results on SMS Dataset -- 7 Results with K-Fold CV Method: YouTube and SMS Dataset -- 7.1 K-Fold CV Method Results on YouTube Dataset -- 7.2 Lazy Random Forest -- 7.3 Native Bayes -- 8 Conclusion -- References -- Unraveling Deep Learning Performance in Cross-Sensor Iris Recognition -- 1 Introduction -- 2 Proposed Work -- 2.1 Description of Standard CNN Models -- 2.2 Image Augmentation -- 2.3 Feature Extraction -- 2.4 Classification -- 3 Experiments. , 3.1 Dataset Description -- 3.2 Experimental Design -- 4 Experimental Outcomes -- 5 Conclusion -- References -- Travelling Salesman Problem Using GA-ACO Hybrid Approach: A Review -- 1 Introduction -- 2 Travelling Salesman Problem (TSP) -- 3 Approaches to Solve TSP -- 3.1 Genetic Algorithm (GA) -- 3.2 Ant Colony Optimization (ACO) -- 3.3 Hybridization -- 4 Conclusion -- Bibliography -- Efficient and Robust Indian Number Plate Recognition Through Modified and Tuned LPRNet -- 1 Introduction -- 2 Related Work -- 3 Proposed Approach: Modified LPRNet -- 3.1 Existing LPRNet Model -- 3.2 Modified LPRNet Model -- 3.3 Post Processing -- 4 Experiment Setup -- 4.1 Dataset -- 4.2 Training Details -- 5 Results -- 5.1 Synthetic Data Results -- 5.2 Transfer Learning on Real Data -- 5.3 Confusion Matrix and Test Accuracy -- 5.4 Sample Results -- 6 Conclusion and Future Work -- References -- An Improved Machine Learning Prediction Model for Diabetes -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Toolkit -- 3.2 Dataset Description -- 3.3 Proposed Approach -- 3.4 Kmeans Clustering Algorithm -- 3.5 Voting Classifier -- 4 Results -- 5 Conclusions and Future Scope -- References -- University Recommendation System for Higher Studies in USA -- 1 Introduction -- 1.1 Problem Statement -- 1.2 Scope of the Project -- 2 Literature Survey -- 3 Our University Recommendation System -- 4 System Architecture -- 4.1 DataSet -- 4.2 Data Cleaning -- 5 Algorithms Used -- 5.1 Collaborative Filtering -- 5.2 Content Based Filtering -- 5.3 Similarity and Distance -- 5.4 K Nearest Neighbor -- 5.5 Random Forest Classifier -- 6 Result and Analysis -- 7 Conclusion and Future Scope -- References -- Comparison of Performances of Regression Model-Based Prediction of Meteorological Conditions -- 1 Introduction -- 1.1 Linear Regression -- 1.2 Logistic Regression. , 1.3 K-Means Clustering -- 2 Procedure -- 2.1 Dataset Extraction -- 2.2 Linear Regression -- 2.3 Logistic Regression -- 2.4 Clustering -- 3 Flow Chart -- 3.1 Linear Regression -- 3.2 Logistic Regression -- 3.3 Clustering -- 4 Results -- 4.1 Linear Regression -- 4.2 Logistic Regression -- 4.3 Clustering -- 5 Conclusion -- References -- Vocal Source Builds Divergence in Gender Recognition -- 1 Introduction -- 2 Methodology -- 2.1 Multi Layered Perceptron (MLP) -- 2.2 RandomForest -- 2.3 DecisionTree -- 2.4 LogisticRegression -- 3 Procedure -- 3.1 Multi Layered Perceptron (MLP) -- 3.2 Random Forest -- 3.3 Decision Tree -- 3.4 Logistic Regression -- 4 Results -- 4.1 Multi Layered Perceptron(MLP) -- 4.2 Random Forest -- 4.3 Decision Tree -- 4.4 Logistic Regression -- 5 Conclusions -- References -- An Analytical Prediction of Breast Cancer Using Machine Learning -- 1 Introduction -- 2 Methodology -- 2.1 K-Nearest Neighbour -- 2.2 Random Forest -- 2.3 Artificial Neural Network -- 3 Procedure -- 3.1 Data Set and Pre-processing -- 3.2 Decision Tree -- 3.3 Gaussian Naïve Bayes -- 3.4 Artificial Neural Network -- 4 Results -- 4.1 K-Nearest Neighbor Evaluation -- 4.2 Logistic Regression Evaluation -- 4.3 Naïve Bayes Evaluation -- 4.4 SVC Evaluation -- 4.5 Decision Tree Evaluation -- 4.6 Random Forest Evaluatıon -- 5 Conclusion -- References -- A Synopsis of Monocular Depth Estimation -- 1 Introduction -- 2 Datasets -- 2.1 NYU-Depth V2 -- 2.2 KITTI Dataset -- 2.3 Make3D -- 2.4 Gamehook Mod -- 2.5 Synthia Dataset -- 3 Methods -- 3.1 Supervised -- 3.2 Unsupervised -- 3.3 Semi-supervised -- 3.4 Self-supervised -- 4 Prominent Work Done -- 4.1 Intel-ISL MiDaS -- 4.2 Consistent Video Depth Estimation -- 5 Comparative Study -- 6 Scope -- 6.1 3D Reconstruction and Point Cloud -- 6.2 Virtual Effects -- 6.3 Object Trajectory -- 6.4 Absolute Depth -- 6.5 Parallax Simulation. , 6.6 Drawbacks of Traditional Methods -- 7 Conclusion -- References -- Automated Car Parking System Using Deep Convolutional Neural Networks -- 1 Introduction -- 2 Literature Survey -- 3 Methodology Used -- 3.1 Creation of CNN Model -- 3.2 Creation of Training and Test Labelled Dataset -- 3.3 Experimentation -- 4 Result and Discussions -- 5 Conclusion and Future Scope -- References -- Currency Exchange Rate Prediction Using Multi-layer Perceptron -- 1 Introduction -- 2 Acquiring and Preparing Data -- 3 Building the MLP Model with Keras -- 4 Training and Testing of the Model -- 5 Results and Conclusion -- References -- Analysis of Web Application Firewalls, Challenges, and Research Opportunities -- 1 Introduction -- 1.1 Web Application Firewall -- 1.2 Web Application Security Risk -- 2 Related Work -- 2.1 Critcal Analysis of Web Application Firewall -- 2.2 APO Technique -- 2.3 Dataset -- 2.4 ANN based Web Application Firewall -- 3 Comparison of Web Application Firewalls -- 4 Proposed Approaches -- 4.1 Multimodal Networks -- 4.2 Attention-Based Mechanism -- 4.3 Heuristic Based Selection -- 5 Followings Are the Key Finding from Above Survey -- 6 Conclusion -- References -- A Comparative Study for Predicting Burned Areas of a Forest Fire Using Soft Computing Techniques -- 1 Introduction -- 2 Materials and Methods -- 2.1 Description of Dataset -- 2.2 Methods -- 3 Results and Discussion -- 3.1 Data Preparation -- 3.2 Performance Analysis -- 3.3 Computational Execution Time -- 4 Conclusion -- References -- Shill Bidding Detection in Online Auction -- 1 Introduction -- 2 Literature Survey -- 3 Proposal -- 3.1 Patterns Observed in Real Time Online Auctions -- 3.2 Security Perspective -- 4 Result Analysis -- 5 Conclusion -- References -- An Optimal Region Growing Segmentation Algorithm with Decision Tree Tumor Classifier -- 1 Introduction -- 2 Literature Survey. , 3 Proposed Methodology.