Advances in Data-Driven Computing and Intelligent Systems : Selected Papers from ADCIS 2022, Volume 1 / edited by Swagatam Das, Snehanshu Saha, Carlos A. Coello Coello, Jagdish Chand Bansal.

Format:

Book

Author/Creator:

Das, Swagatam.

Contributor:

Saha, Snehanshu.

Coello Coello, Carlos A.

Bansal, Jagdish Chand.

Series:

Lecture Notes in Networks and Systems, 2367-3389 ; 698

Language:

English

Subjects (All):

Telecommunication.

Electronic circuits.

Cloud computing.

Artificial intelligence.

Signal processing.

Communications Engineering, Networks.

Electronic Circuits and Systems.

Cloud Computing.

Artificial Intelligence.

Signal, Speech and Image Processing.

Local Subjects:

Communications Engineering, Networks.

Electronic Circuits and Systems.

Cloud Computing.

Artificial Intelligence.

Signal, Speech and Image Processing.

Physical Description:

1 online resource (885 pages)

Edition:

1st ed. 2023.

Place of Publication:

Singapore : Springer Nature Singapore : Imprint: Springer, 2023.

Summary:

The volume is a collection of best selected research papers presented at International Conference on Advances in Data-driven Computing and Intelligent Systems (ADCIS 2022) held at BITS Pilani, K K Birla Goa Campus, Goa, India during 23 – 25 September 2022. It includes state-of-the art research work in the cutting-edge technologies in the field of data science and intelligent systems. The book presents data-driven computing; it is a new field of computational analysis which uses provided data to directly produce predictive outcomes. The book will be useful for academicians, research scholars, and industry persons.

Contents:

Intro

Preface

Contents

Editors and Contibutors

Adaptive Volterra Noise Cancellation Using Equilibrium Optimizer Algorithm

1 Introduction

2 Problem Formulation

3 Proposed Equilibrium Optimizer Algorithm-Based Adaptive Volterra Noise Cancellation

3.1 Gbest

3.2 Exploration Stage (F)

3.3 Exploitation Stage (Rate of Generation G)

4 Simulation Outcomes

4.1 Qualitative Performance Analysis

4.2 Quantitative Performance Analysis

5 Conclusion and Scope

References

SHLPM: Sentiment Analysis on Code-Mixed Data Using Summation of Hidden Layers of Pre-trained Model

2 Literature Review

3 Proposed Methodology

3.1 BERT

3.2 RoBERTa

3.3 SHLPM

4 Implementation Details

4.1 Dataset and Pre-processing

4.2 SHLPM-BERT

4.3 SHLPM-XLM-RoBERTa

5 Results and Discussion

6 Conclusion

Comprehensive Analysis of Online Social Network Frauds

1.1 Statistics of Online Social Network Frauds

2 Interrelationship between OSN Frauds, Social Network Threats, and Cybercrime

3 Types of Frauds in OSN

3.1 Social Engineering Frauds (SEF)

3.2 Human-Targeted Frauds (Child/Adults)

3.3 False Identity

3.4 Misinformation

3.5 E-commerce Fraud (Consumer Frauds)

3.6 Case Study for Facebook Security Fraud

4 OSN Frauds Detection Using Machine Learning

4.1 Pros and Cons

5 Conclusion

Electric Vehicle Control Scheme for V2G and G2V Mode of Operation Using PI/Fuzzy-Based Controller

2 Motivation

3 System Description

4 Mathematical Model Equipments Used

4.1 Bidirectional AC-DC Converter

4.2 Bidirectional Buck-Boost Converter

4.3 Battery Modeling

4.4 Control of 1-∅-Based Bidirectional AC-DC Converter Strategy

5 Fuzzy Logic Controller

6 Control Strategy

6.1 Constant Voltage Strategy.

6.2 Constant Current Strategy

7 Results and Discussion

7.1 PI Controller

7.2 Fuzzy Logic Controller

7.3 Comparison of Harmonic Profile

8 Conclusion

Experimental Analysis of Skip Connections for SAR Image Denoising

2 Related Works

2.1 Residual Network

2.2 Existing ResNet-Based Denoising Works

3 Implementation of the Different Patterns of Skip Connections

3.1 Datasets and Pre-processing

3.2 Loss Function

4 Results and Discussions

4.1 Denoising Results on Synthetic Images

4.2 Denoising Results on Real SAR Images

A Proficient and Economical Approach for IoT-Based Smart Doorbell System

3 System Design and Implementation

3.1 System Design

3.2 Implementation

4 Results and Discussion

4.1 Performance Results

4.2 Comparison with an Existing System

4.3 Cost Analysis

5 Limitations

Predicting Word Importance Using a Support Vector Regression Model for Multi-document Text Summarization

2 Related Work

3 Description of Dataset

4 Proposed Methodology

4.1 Preprocessing

4.2 Word Importance Prediction Using Support Vector Regression Model

4.3 Sentence Scoring

4.4 Summary Generation

5 Evaluation, Experiment, and Results

5.1 Evaluation

5.2 Experiment

5.3 Results

6 Conclusion and Future Works

A Comprehensive Survey on Deep Learning-Based Pulmonary Nodule Identification on CT Images

2 Datasets and Experimental Setup

2.1 LIDC/IDRI Dataset

2.2 LUNA16 Dataset

2.3 NLST Dataset

2.4 KAGGLE DATA SCIENCE BOWL (KDSB) Dataset

2.5 VIA/I-ELCAP

2.6 NELSON

2.7 Others

3 CAD System Structure

3.1 Data Acquisition

3.2 Preprocessing

3.3 Lung Segmentation.

3.4 Candidate Nodule Detection

3.5 False Positive Reduction

3.6 Nodule Categorization

4 CNN

4.1 Overview

4.2 CNN Architectures for Medical Imaging

4.3 Unique Characteristics of CNNs

4.4 CNN Software and Hardware Equipment

4.5 CNNs versus Conventional Models

5 Discussion

5.1 Research Trends

5.2 Challenges and Future Directions

Comparative Study on Various CNNs for Classification and Identification of Biotic Stress of Paddy Leaf

2 Materials and Methods

2.1 Dataset

2.2 Proposed Methods

3 Experimental Results

3.1 Hardware Setup

3.2 Time Analysis with respect to GPU and CPU

3.3 Performance Analysis for Keras and PyTorch

3.4 Performance Analysis of CNN Models

3.5 Comparison of the Proposed CNN with Other State-of-the-Art Works

4 Conclusion

Studies on Machine Learning Techniques for Multivariate Forecasting of Delhi Air Quality Index

2 Materials and Methodology

2.1 Delhi AQI Multivariate Data

2.2 Methodology

3 Experimental Setup and Simulation Results

4 Contrast Analysis Considering Dimensionality Reduction

5 Conclusions

Fine-Grained Voice Discrimination for Low-Resource Datasets Using Scalogram Images

3.1 Collection of Voice Dataset

3.2 Preprocessing of Available Dataset to Increase the Trainable Samples

3.3 Classification of Phonemes Using Deep Convolutional Neural Network (DCNN)-Based Image Classifiers

4 Implementation Result and Analysis

5 Conclusion and Future Work

Sign Language Recognition for Indian Sign Language

3 Methodology

3.1 Dataset

3.2 Data Preprocessing

3.3 Data Splitting

3.4 Data Augmentation

3.5 Model Compilation.

3.6 Model Training and Testing

4 Results

5 Novelty and Future Work

Buffering Performance of Optical Packet Switch Consisting of Hybrid Buffer

2 Literature Survey

3 Description of the Optical Packet Switch

4 Simulation Results

4.1 Bernoulli Process

4.2 Results

Load Balancing using Probability Distribution in Software Defined Network

3 Grouping of Controllers in SDN

4 Load Balancing in SDN

4.1 Simulation and Evaluation Result

COVID Prediction Using Different Modality of Medical Imaging

2 Principles of Support Vector Machine (SVM)

2.1 Linear Case

2.2 Nonlinear Case

3 Material and Methods

3.1 CT Image Dataset

3.2 X-Ray Image Dataset

3.3 Ultrasound Image Dataset

4 The Proposed Model

5 Experimental Result

Optimizing Super-Resolution Generative Adversarial Networks

3 Dataset

3.1 Training Dataset

3.2 Test Dataset

5 Performance Metrics

5.1 Peak Signal-to-Noise Ratio (PSNR)

5.2 Structural Similarity Index (SSIM)

6 Results and Discussion

7 Conclusion

Prediction of Hydrodynamic Coefficients of Stratified Porous Structure Using Artificial Neural Network (ANN)

2 Stratified Porous Structure

3 Experimental Setup

4 Artificial Neural Network

4.1 Dataset Used for ANN

4.2 ANN Model

5 Results and Discussions

6 Conclusions

Performance Analysis of Machine Learning Algorithms for Landslide Prediction

3 Methodology of the Performance Analysis Work

3.1 Data Acquisition Layer

3.2 Fog Layer

3.3 Cloud Layer.

4 Performance Analysis and Results

Brain Hemorrhage Classification Using Leaky ReLU-Based Transfer Learning Approach

3 Materials and Method

3.2 Transfer Learning

3.3 ResNet50

4.1 Input Dataset

4.2 Pre-processing

4.3 Network Training

4.4 Transfer Learning-Based Feature Extraction

5 Results

Factors Affecting Learning the First Programming Language of University Students

3.1 Data Collection

3.2 Experimental Design

3.3 Data Analysis

4 Result

4.1 Findings

5 Decision and Conclusion

Nature-Inspired Hybrid Virtual Machine Placement Approach in Cloud

3 Problem Formulation

4 Proposed Framework

4.1 Intelligent Water Drops (IWD) Algorithm

4.2 Water Cycle Algorithm (WCA)

4.3 Intelligent Water Drop Cycle Algorithm (IWDCA)

5 Result

5.1 Experiment Setup

5.2 Simulation Analysis of IWDCA

Segmented ε-Greedy for Solving a Redesigned Multi-arm Bandit Environment

2 Previous Works

Data-Based Time Series Modelling of Industrial Grinding Circuits

2 Formulation

2.1 Grinding Circuit

2.2 Least Square Support Vector Regression

2.3 Proposed Algorithm

3 Results and Discussions

3.1 Results of Proposed Algorithm

3.2 LS-SVR Model Performance

3.3 Comparison with Arbitrarily Selected Model

4 Conclusions

Computational Models for Prognosis of Medication for Cardiovascular Diseases

References.

Develop a Marathi Lemmatizer for Common Nouns and Simple Tenses of Verbs.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

9789819932504

9819932505

OCLC:

1393307354