Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/356349
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dc.date.accessioned2022-01-18T11:32:31Z-
dc.date.available2022-01-18T11:32:31Z-
dc.identifier.urihttp://hdl.handle.net/10603/356349-
dc.description.abstractThe mobile sales has grown very fast over the past many years. Due to fast technological changes, the Mobile phone, especially smart phones has influenced human life largely. Mobile Phone can almost be counted among the most basic needs of modern human life. It s observed since past that technology has made many things easy for human beings but it comes with some drawbacks as well. With the usage of mobile phones on large scale there comes a question of its recycling, reusing, effect on environment, decomposition etc. Many researchers across the globe have entered this area and have also developed models using different approaches. This research gives a manifold perspective to handle this problem of e-waste (generated due to mobile phones). In this research the Statistical analysis conducted on the data related to usage of mobile phones motivates towards developing a model that can help in recycling and reusing mobile phones. Machine learning algorithms have helped in recent past in developing large number of models to handle the real life problems. In this research also the problem of e-waste is tackled using machine learning algorithms and then also utilizing deep learning to achieve higher efficiency. Moreover the issue of recycling and reusing are handled separately. Recycling is taken care with the help of deep learning algorithm. And an algorithm is developed by customizing the Bankers resource allocation algorithm used by Operating Systems to handle reusing and refurbishment. newline
dc.format.extent
dc.languageEnglish
dc.relation
dc.rightsuniversity
dc.titleDesign of Framework for E waste Recycling and Process Management
dc.title.alternative
dc.creator.researcherSwapnali Khanolkar
dc.subject.keywordComputer Science
dc.subject.keywordComputer Science Software Engineering
dc.subject.keywordEngineering and Technology
dc.description.note
dc.contributor.guideKhunteta, Ajay and Naik, Mahesh
dc.publisher.placeJaipur
dc.publisher.universityPoornima University
dc.publisher.institutionDepartment of Computer Science
dc.date.registered2014
dc.date.completed2021
dc.date.awarded2021
dc.format.dimensions
dc.format.accompanyingmaterialDVD
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Department of Computer Science

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80_recommendation.pdfAttached File7.09 MBAdobe PDFView/Open
abstract.pdf1.63 MBAdobe PDFView/Open
certificate.pdf1.63 MBAdobe PDFView/Open
chapter-1.pdf5.41 MBAdobe PDFView/Open
chapter-2.pdf5.41 MBAdobe PDFView/Open
chapter-3.pdf5.41 MBAdobe PDFView/Open
chapter 4.pdf5.41 MBAdobe PDFView/Open
chapter-5.pdf5.41 MBAdobe PDFView/Open
chapter-6.pdf5.41 MBAdobe PDFView/Open
preliminary pages.pdf1.63 MBAdobe PDFView/Open
referance & publication.pdf5.41 MBAdobe PDFView/Open
title.pdf1.63 MBAdobe PDFView/Open


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