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   <subfield code="a">Advances in computational and bio-engineering :</subfield>
   <subfield code="b">proceeding of the International Conference on Computational and Bio Engineering, 2019. Volume 1 /</subfield>
   <subfield code="c">S. Jyothi, D. M. Mamatha, Suresh Chandra Satapathy, K. Srujan Raju, Margarita N. Favorskaya, editors.</subfield>
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   <subfield code="c">2020.</subfield>
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   <subfield code="a">667 σ. ;</subfield>
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   <subfield code="a">Learning and Analytics in Intelligent Systems ;</subfield>
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   <subfield code="a">Contents: Intro -- Contents -- Polycystic Ovarian Follicles Segmentation Using GA -- 1 Introduction -- 2 Image Segmentation -- 2.1 Edge Detection with Sobel Operator -- 2.2 Edge Detection with Canny Operator -- 2.3 Genetic Algorithm for Edge Detection -- 3 Result and Discussions -- 4 Conclusion -- References -- An Evolutionary Optimization Methodology for Analyzing Breast Cancer Gene Sequences Using MSAPSO and MSADE -- 1 Introduction -- 2 Soft Computing Techniques for Gene Sequence Analysis -- 2.1 Particle Swarm Optimization (PSO) -- 2.2 Differential Evolution (DE) -- 3 MSA for Gene Sequence Analysis Contents: 4 Proposed Evolutionary Methodology -- 4.1 Implementation of Evolutionary Methodologies MSAPSO and MSADE -- 4.2 Algorithm for MSAPSO -- 4.3 Algorithm for MSADE -- 4.4 Flow Chart for MSAPSO -- 4.5 Flow Chart for MSADE -- 5 Result Analysis -- 5.1 Representation of Resultant Values in a Table Using Hybridized Algorithm MSAPSO -- 5.2 Representation of Resultant Values in a Table Using Hybridized Algorithm MSADE -- 6 Conclusion -- References -- Performing Image Compression and Decompression Using Matrix Substitution Technique -- 1 Introduction -- 2 Compression of an Image Contents: 3 Decompression of an Image -- 4 Computational Results -- 4.1 Different Compression Ratios of an Image -- 4.2 Output Results -- 4.3 Error Measurement -- 4.4 Comparison of Results -- 5 Conclusion -- References -- Classification of Cotton Crop Pests Using Big Data Analytics -- 1 Introduction -- 2 Literature Survey -- 3 Problem Domain -- 3.1 Description of Cotton Pests Dataset -- 4 Methodology -- 4.1 Big Data Analytics -- 4.2 Classification of Cotton Crop Pests -- 4.3 Machine Learning -- 5 Experimental Results -- 5.1 Decision Tree Classifier for Pest Classification -- 5.2 Test Results and Analysis Contents: 6 Conclusion -- References -- Effect of Formulation Variables on Optimization of Gastroretentive In Situ Rafts of Bosentan Monohydrate HCl by 32 Factorial Design -- 1 Introduction -- 2 Experimental -- 2.1 Materials -- 2.2 Optimization of Variables Using 32 Factorial Design -- 2.3 Method of Preparation -- 2.4 Methods of Evaluation -- 2.5 Drug Content -- 2.6 Overall Desirability (OD) Factor -- 2.7 Drug-Excipient Compatibility Studies -- 2.8 In-Vivo Studies -- 2.9 Short Term Stability Studies -- 3 Results and Discussion -- 3.1 Effect of Polymer Ratio (X1) on Y1-Y4 Contents: 3.2 Effect of Quantity of Effervescent (X2) on Y1-Y4 -- 3.3 Comparison of Effect of X1 and X2 -- 3.4 Other Parameters -- 3.5 Characterization of the Best Selected Formulation -- 3.6 Compatibility Studies -- 3.7 In Vivo Studies -- 3.8 Stability Studies -- 4 Conclusion -- References -- Performance Analysis of Apache Spark MLlib Clustering on Batch Data Stored in Cassandra -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Apache Spark Machine Learning Library -- 3.2 Clustering Models -- 3.3 Apache Cassandra -- 3.4 Spark Cassandra Integration -- 4 Proposed System</subfield>
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   <subfield code="a">Learning and analytics in intelligent systems ;</subfield>
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