Advances in computational and bio-engineering : proceeding of the International Conference on Computational and Bio Engineering, 2019. Volume 1 - Jyothi, S. (Springer, 2020)
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