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Deep Learning has radically transformed the field of Medical Image Analysis by surpassing human performance in several challenging classification tasks and thus has widespread applications in industry and academia. In this work, we employ a Deep Convolutional Neural Network (DCNN) that uses Transfer Learning and is trained using the Open-access Medical Image Repositories and OpenI repository. We use DCNN to assist in a crowdsourced Big Data platform by conducting two crucial classification tasks: (1) Interclass classification of the type of the medical image-MRI, Ultrasound or X-Ray; (2) Intraclass classification of the X-Ray images into chest or abdomen X-Rays. Our approach automates the classification process of medical images, to provide certified medical experts with medical images of individuals on a crowdsourced platform, along with similar medical images of the suspected medical condition for validation, in order to enhance diagnostic effectiveness. In this work, we focus primarily on the classification tasks using DCNN; the elucidation of the privacy-preserving architecture of our cloud-based crowdsourcing platform and classification using conventional clustering approaches in the absence of large training images is deferred to future work.

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Experimental Learning is an Important learning approach in which students learn by doing it. This research analysed effective learning approach for success of graduates in engineering education. For this experiment 168 students of computer science and engineering from college A and B are considered, where college A adopted Experimental Learning and college B adopted Traditional learning approach. The result is significantly difference in success rate of college A than college B. The course delivery in college A has done by project-based learning which concept of course has been implemented by students by doing projects, solving problems, mini projects for real world problems to find solutions and completing course by doing it practically with involvement of latest technologies. This Experience develops problem solving, creative thinking, leadership qualities, teamwork and ready for industry. Students success is measured with semester end exam (SEE) scores and Placements. This shows college A graduates are successes then college B and also a positive change in individual growth and Organizational. A conclusion is done that Experimental Learning Improve Students' performance and can be implemented in other disciplines.