LEADER 04693nam 22006615 450 001 996418253003316 005 20200706121121.0 010 $a3-030-46943-3 024 7 $a10.1007/978-3-030-46943-6 035 $a(CKB)4100000011343241 035 $a(DE-He213)978-3-030-46943-6 035 $a(MiAaPQ)EBC6268625 035 $a(PPN)269144889 035 $a(EXLCZ)994100000011343241 100 $a20200706d2020 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAdvances in Computational and Bio-Engineering$b[electronic resource] $eProceeding of the International Conference on Computational and Bio Engineering, 2019, Volume 2 /$fedited by S. Jyothi, D. M. Mamatha, Suresh Chandra Satapathy, K. Srujan Raju, Margarita N. Favorskaya 205 $a1st ed. 2020. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2020. 215 $a1 online resource (IX, 506 p. 224 illus., 162 illus. in color.) 225 1 $aLearning and Analytics in Intelligent Systems,$x2662-3447 ;$v16 311 $a3-030-46942-5 327 $aChapter 1: Cloud Computing: A Study On Type of Data Stored in a Cloud and Its Security Mechanisms -- Chapter 2: Smart bag using electromagnetic zipping -- Chapter 3: Analysis on Various Feature Extraction Methods for Medical Image Classification -- Chapter 4: Prediction of Pest Generations based on Future Climate using Big Data Mining -- Chapter 5: Optimizing TCP Congestion Control Techniques for Wireless Sensor Network Architectures -- Chapter 6: Comparative In-silico studies for theolecular basis of lepidopteran insect pestsBio-control using insect?s own enzymes -- Chapter 7: Collaborative Cloud Computing for Resour Sharing Platform in Multiple Clouds -- Chapter 8: Deep Learning of Paradigms: The Outlook -- Chapter 9: Applications of Network Analysis in Bioinformatics -- Chapter 10: Identification of Clinical Variants Present inSkin Melanoma Using Exome Sequencing Data. 330 $aThis book gathers state-of-the-art research in computational engineering and bioengineering to facilitate knowledge exchange between various scientific communities. Computational engineering (CE) is a relatively new discipline that addresses the development and application of computational models and simulations often coupled with high-performance computing to solve complex physical problems arising in engineering analysis and design in the context of natural phenomena. Bioengineering (BE) is an important aspect of computational biology, which aims to develop and use efficient algorithms, data structures, and visualization and communication tools to model biological systems. Today, engineering approaches are essential for biologists, enabling them to analyse complex physiological processes, as well as for the pharmaceutical industry to support drug discovery and development programmes. 410 0$aLearning and Analytics in Intelligent Systems,$x2662-3447 ;$v16 606 $aBiomathematics 606 $aComputational intelligence 606 $aBiomedical engineering 606 $aEngineering mathematics 606 $aMathematical and Computational Biology$3https://scigraph.springernature.com/ontologies/product-market-codes/M31000 606 $aComputational Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/T11014 606 $aBiomedical Engineering and Bioengineering$3https://scigraph.springernature.com/ontologies/product-market-codes/T2700X 606 $aEngineering Mathematics$3https://scigraph.springernature.com/ontologies/product-market-codes/T11030 615 0$aBiomathematics. 615 0$aComputational intelligence. 615 0$aBiomedical engineering. 615 0$aEngineering mathematics. 615 14$aMathematical and Computational Biology. 615 24$aComputational Intelligence. 615 24$aBiomedical Engineering and Bioengineering. 615 24$aEngineering Mathematics. 676 $a004 702 $aJyothi$b S$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aMamatha$b D. 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