http://13.232.72.61:8080/jspui/handle/123456789/8387 2025-12-23T02:38:16Z http://13.232.72.61:8080/jspui/handle/123456789/8390 Title: Synthesis, characterization of Zinc oxide and assessment of electrical DC conductivity properties Authors: Sathish Kumar, K B Abstract: Polymer composites are widely used in electrical devices, sensor materials, electromagnetic interference (EMI) shielding, and other applications. Composites may be customized for any intended application by changing the ratios of the polymeric components. Polyaniline (PANI) is not as sensitive as metal oxides toward gasoline species, and its negative solubility in organic solvents limits its packages, however it's miles suitable as a matrix for instruction of engaging in polymer nanocomposites. Therefore, there has been increasing hobby of the researchers for the education of Nano composites based totally on PANI The fuel for the production of nanometal oxide comes from naturally occurring sources. The weight percentages of such generated metal oxides are altered during chemical polymerization with polyaniline. Composites of polyaniline cellulose and varying weight ratios of Zinc oxide (ZnO) are produced. In synthesised Polyaniline cellulose/ZnO composites, the formation of polymers and their interactions with metal oxides are investigated using Ultraviolet (UV)-vis, Fourier-transform infrared spectroscopy (FTIR), and X Ray Diffraction. The surface morphology of the composites is studied using Scanning electron Microscopy. The characteristics of the specified composites are investigated using electrical dc conductivity electrical conductivity. 2023-01-01T00:00:00Z http://13.232.72.61:8080/jspui/handle/123456789/8389 Title: A Novel Functional Machine Learning Approaches on Prostate Cancer Authors: K.Ramakrishna Reddy and Dr.G.N.K.Suresh Babu Abstract: Cancer registries are collections of curated data about malignant tumor diseases. The amount of data processed by cancer registries increases every year, making manual registration more and more tedious.This research work finds Bayes Net classifier gives an optimal results. The Sequential Minimal Optimization of functional machine learning approach is having highest accuracy level which is 85% of accuracy level. The Sequential Minimal Optimization of functional machine learning approach is having highest precision level which is 0.85 of precision level. The least precision value is 0.80 of precision value which is having Quadratic Discriminant Analysis of functional machine learning classifier approach. The Sequential Minimal Optimization of functional machine learning approach is having highest recall level which is 0.85 of recall level. The least recall value is 0.79 which is produced by Quadratic Discriminant Analysis functional machine learning classification approach. The Sequential Minimal Optimization of functional machine learning approach is having highest F- Measure level which is 0.85 of F-Measure level. The Fisher’s Discriminant Analysis algorithm of functional machine learning classifier and Linear Discriminant Analysis classification algorithm of functional machine learning classifier are having same receiver operating characteristic curve value which is 0.90 of receiver operating characteristic curve value.The maximum precision recall curve value is 0.90 of precision recall curve value which is produced by Linear Discriminant Analysis of functional machine learning classifier. This system recommends that the Sequential Minimal Optimization of functional machine learning approach produces optimal results compare with other models. 2022-04-01T00:00:00Z http://13.232.72.61:8080/jspui/handle/123456789/8388 Title: Statistical Machine Learning Classifications On Prostate Cancer Dataset Authors: K.Ramakrishna Reddy and Dr.G.N.K.Suresh Babu Abstract: Cancer is the second prominent cause of death worldwide. Per annum around 6, 50,000 death cases in this current situation due to Prostate cancer. Need to improve determination the causal factors of prostate cancer. In this research work considers a medical dataset containing clinical information on 100 prostate cancer patients by using the inductive learning algorithms. This research work finds Bayes Net classifier gives an optimal results. The Bayes classifier has highest accuracy level which is 84% of accuracy. The lowest accuracy level is 62% of accuracy which is produced by Naïve Bayes Multinomial Text classifier of Bayes classifier. The Bayes classifier has highest precision level which is 0.85 of precision level. The lowest precision level is 0.62 of precision level which is produced by Naïve Bayes Multinomial Text classifier of Bayes classifier. The Bayes classifier has highest recall level which is 0.84 of recall level. The lowest precision level is 0.62 of recall level which is produced by Naïve Bayes Multinomial Text classifier of Bayes classifier. The Bayes classifier has highest F-Measure level which is 0.84 of F-Measure level. The lowest F-Measure level is 0.76 of F-Measure level which is produced by Naïve Bayes Multinomial Text classifier of Bayes classifier. The Bayes classifier has highest ROC value level which is 0.93 of ROC level. The lowest ROC level is 0.46 of ROC level which is produced by Naïve Bayes Multinomial Text classifier of Bayes classifier. The Bayes classifier has highest PRC value level which is 0.92 of ROC level. The lowest ROC level is 0.51 of PRC level which is produced by Naïve Bayes Multinomial Text classifier of Bayes classifier. 2022-02-01T00:00:00Z