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Smart technologies in data science and communication [electronic resource] : proceedings of SMART-DSC 2019 / Jinan Fiaidhi, Debnath Bhattacharyya, N. Thirupathi Rao, editors.

This book features high-quality, peer-reviewed research papers presented at the International Conference on Smart Technologies in Data Science and Communication (Smart-DSC 2019), held at Vignans Institute of Information Technology (Autonomous), Visakhapatnam, Andhra Pradesh, India on 1314 December 2...

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Bibliographic Details
Online Access: Full Text (via Springer)
Corporate Author: International Conference on Smart Technologies in Data Science and Communication Vishakhapatnam, India
Other Authors: Fiaidhi, Jinan, 1955-, Bhattacharyya, Debnath, Rao, N. Thirupathi
Other title:SMART-DSC 2019.
Format: Electronic Conference Proceeding eBook
Language:English
Published: Singapore : Springer, ©2020.
Series:Lecture notes in networks and systems ; v. 105.
Subjects:
Quantitative research > Congresses.
Communication > Technological innovations > Congresses.
Soft computing > Congresses.
Table of Contents:
  • Intro
  • Conference Committee Members
  • Advisory Board
  • Program Chair
  • Finance Committee
  • Local Arrangements Committee
  • Technical Programme Committee
  • Preface
  • Acknowledgements
  • Contents
  • About the Editors
  • Digital Transformation of Seed Distribution Process
  • 1 Introduction
  • 1.1 Problem Definition
  • 2 Data Preparation
  • 2.1 Data Collection
  • 2.2 Data Preprocessing
  • 2.3 Clustering
  • 2.4 Algorithm
  • 3 Model
  • 3.1 Introduction to E-Smart Card/Agri Card
  • 3.2 Agri Smart Card Working Process
  • 3.3 Main Advantages of Smart Seed System with Agri Smart Card.
  • 3.4 Smart Seed System with Agri Card-Implementation Phases
  • 3.5 Insurance Claims Using Smart Seed System with Agri E-Card
  • 4 Results and Conclusion
  • References
  • Detection of Deceptive Phishing Based on Machine Learning Techniques
  • 1 Introduction
  • 2 Related Work
  • 3 Combining the Models of Machine Learning Algorithms
  • 4 Machine Learning Methods
  • 4.1 Holdout Method
  • 4.2 K-Cross-Validation Mechanism
  • 4.3 Bootstrap Sampling
  • 5 Problem Statement
  • 6 Methodology
  • 7 Mathematical Analysis
  • 8 Graphical Analysis
  • 9 Conclusion
  • References.
  • A Shape-Based Model with Zone-Wise Hough Transformation for Handwritten Digit Recognition
  • 1 Introduction
  • 2 Related Works
  • 3 System Description
  • 3.1 Shape Database
  • 3.2 Training
  • 3.3 Testing
  • 4 Result
  • 5 Conclusions
  • References
  • Deducted Sentiment Analysis for Sarcastic Reviews Using LSTM Networks
  • 1 Introduction
  • 2 Related Work
  • 2.1 Deep Learning
  • 2.2 LSTM Layers
  • 2.3 Advantages of Proposed System
  • 3 Problem Deduction
  • 4 Methodology
  • 5 Results and Analysis
  • 6 Conclusion and Future Scope
  • 6.1 Future Scope
  • References.
  • Automatic Identification of Colloid Cyst in Brain Through MRI/CT Scan Images
  • 1 Introduction
  • 2 Literature Survey
  • 2.1 Observations from Previous Works
  • 3 Proposed Work
  • 3.1 Algorithm
  • 3.2 Study of Algorithm
  • 3.3 Flowchart
  • 4 Results
  • 5 Conclusion
  • References
  • A Detailed Review on Big Data Analytics
  • 1 Introduction
  • 1.1 Foundation of Big Data
  • 2 Characteristics of Big Data
  • 3 Benefits of Big Data
  • 4 Modules of Hadoop
  • 4.1 HDFS Concepts
  • 5 Yet Another Resource Manager (YARN)
  • 5.1 Components of Yarn [6]
  • 5.2 Benefits of Yarn [6]
  • 5.3 MapReduce [7]
  • 6 Conclusion
  • References
  • A Review on Datasets and Tools in the Research of Recommender Systems
  • 1 Introduction
  • 2 Research and Datasets
  • 3 An Insight on Recommender Datasets
  • 3.1 Open-Source Datasets for Recommender System
  • 4 Tools of Trade
  • 5 Conclusion and Future Opportunities
  • References
  • Performance Comparison of Different Machine Learning Algorithms for Risk Prediction and Diagnosis of Breast Cancer
  • 1 Introduction
  • 2 Materials and Methods
  • 3 Experiment
  • 3.1 Breast Cancer Dataset (Mammographic Image Analysis Society)
  • 3.2 Simulation Software.

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