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Advances in computational and bio-engineeringproceeding of the International Conference on Computational and Bio Engineering, 2019.Volume 1 /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Advances in computational and bio-engineeringedited by S. Jyothi ... [et al.].
Reminder of title:	proceeding of the International Conference on Computational and Bio Engineering, 2019.
other author:	Jyothi, S.
corporate name:
Published:	Cham :Springer International Publishing :2020.
Description:	x, 667 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Computer science
Online resource:	https://doi.org/10.1007/978-3-030-46939-9
ISBN:	9783030469399$q(electronic bk.)

Advances in computational and bio-engineeringproceeding of the International Conference on Computational and Bio Engineering, 2019.Volume 1 /
Advances in computational and bio-engineeringproceeding of the International Conference on Computational and Bio Engineering, 2019.Volume 1 /[electronic resource] :edited by S. Jyothi ... [et al.]. - Cham :Springer International Publishing :2020. - x, 667 p. :ill., digital ;24 cm. - Learning and analytics in intelligent systems,v.152662-3447 ;. - Learning and analytics in intelligent systems ;v.1..

Chapter 1: Sequential Pattern Mining for U.S. presidential elections using Google Cloud Platform (GCP) -- Chapter 2: An evolutionary optimization methodology for analysing breast canr gene sequens using MSAPSO and MSADE -- Chapter 3: Performing Image Compression and Decompression Using Matrix Substitution Technique -- Chapter 4: Classification of Cotton Crop Pests using Big Data Analytics -- Chapter 5: Effect Of Formulation Variables on Optimization of Gastroretentive in Situ Rafts of Bosentan Monohydrate HCL by 32 Factorial Design -- Chapter 6: Performan Analysis of Apache Spark ML lib Clustering on Batch Data Stored in Cassandra -- Chapter 7: A study on Opinion of B.Sc Nursing studentson Health Informatics and EMR to included in Nursing Education -- Chapter 8: A Comprehensive Hybrid Ensemble Method with Feature Selection Techniques -- Chapter 9: DNA based Quick Response (QR) code for Screening of Potential Parents for Evolving new Silkworm Ras of high Productivity -- Chapter 10: Big Data Analysis for Land Use Classification Using Machine Learning Algorithms.

This book gathers state-of-the-art research in computational engineering and bioengineering to facilitate knowledge exchange between various scientific communities. Computational engineering (CE) is a relatively new discipline that addresses the development and application of computational models and simulations often coupled with high-performance computing to solve complex physical problems arising in engineering analysis and design in the context of natural phenomena. Bioengineering (BE) is an important aspect of computational biology, which aims to develop and use efficient algorithms, data structures, and visualization and communication tools to model biological systems. Today, engineering approaches are essential for biologists, enabling them to analyse complex physiological processes, as well as for the pharmaceutical industry to support drug discovery and development programmes.

ISBN: 9783030469399$q(electronic bk.)

Standard No.: 10.1007/978-3-030-46939-9doiSubjects--Topical Terms:

252805
Computer science

LC Class. No.: QA75.5

Dewey Class. No.: 004

Advances in computational and bio-engineeringproceeding of the International Conference on Computational and Bio Engineering, 2019.Volume 1 /
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505 0 $a Chapter 1: Sequential Pattern Mining for U.S. presidential elections using Google Cloud Platform (GCP) -- Chapter 2: An evolutionary optimization methodology for analysing breast canr gene sequens using MSAPSO and MSADE -- Chapter 3: Performing Image Compression and Decompression Using Matrix Substitution Technique -- Chapter 4: Classification of Cotton Crop Pests using Big Data Analytics -- Chapter 5: Effect Of Formulation Variables on Optimization of Gastroretentive in Situ Rafts of Bosentan Monohydrate HCL by 32 Factorial Design -- Chapter 6: Performan Analysis of Apache Spark ML lib Clustering on Batch Data Stored in Cassandra -- Chapter 7: A study on Opinion of B.Sc Nursing studentson Health Informatics and EMR to included in Nursing Education -- Chapter 8: A Comprehensive Hybrid Ensemble Method with Feature Selection Techniques -- Chapter 9: DNA based Quick Response (QR) code for Screening of Potential Parents for Evolving new Silkworm Ras of high Productivity -- Chapter 10: Big Data Analysis for Land Use Classification Using Machine Learning Algorithms.
520 $a This book gathers state-of-the-art research in computational engineering and bioengineering to facilitate knowledge exchange between various scientific communities. Computational engineering (CE) is a relatively new discipline that addresses the development and application of computational models and simulations often coupled with high-performance computing to solve complex physical problems arising in engineering analysis and design in the context of natural phenomena. Bioengineering (BE) is an important aspect of computational biology, which aims to develop and use efficient algorithms, data structures, and visualization and communication tools to model biological systems. Today, engineering approaches are essential for biologists, enabling them to analyse complex physiological processes, as well as for the pharmaceutical industry to support drug discovery and development programmes.
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