https://dr.ddn.upes.ac.in//xmlui/handle/123456789/3062 Wed, 13 May 2026 10:44:41 GMT 2026-05-13T10:44:41Z https://dr.ddn.upes.ac.in//xmlui/handle/123456789/4490 Title: Blended learning tools and practices: a comprehensive analysis Authors: Kumar, Adarsh et. al. Abstract: Petroleum and Energy Studies, India, and Jaypee Institute of InformaBlended learning incorporates online learning experiences and helps students for meaningful learning through exible online information and communication technologies, reduced overcrowded classroom presence, and planned teaching and learning experience. This study has conducted surveys of various tools, techniques, frameworks, and models useful for blended learning. This article has prepared a comprehensive survey of student, teacher, and management experiences in blended learning courses during COVID-19 and pre-COVID-19 times. The survey will be useful to faculty members, students, and management to adopt new tools and mindsets for positive outcomes. This work reports on implementing and assessing blended learning at two different universities (University of tion Technology, Noida, India). The assessments prepare the benefts and challenges of learning (by students) and teaching (by faculty) blended learning courses with different online learning tools. Additionally, student performance in the traditional and blended learning courses was compared to list the concerns about effectively shifting the face-to-face courses to a blended learning model in emergencies like COVID-19. As a result, it has been observed that blended learning is helpful for school, university, and professional training. A large set of online and e-learning platforms are developed in recent times that can be used in blended learning to improve the learner's abilities. The use of similar tools (Blackboard, CodeTantra, and g suite) has fulfilled the requirements of the two universities, and timely conducted and completed all academic activities during pandemic times. Description: The article received on April 26, 2021, accepted May 23, 2021, date of publication June 3, 2021, date of current version June 18, 2021 Thu, 03 Jun 2021 00:00:00 GMT https://dr.ddn.upes.ac.in//xmlui/handle/123456789/4490 2021-06-03T00:00:00Z https://dr.ddn.upes.ac.in//xmlui/handle/123456789/4152 Title: Evolutionary framework for designing adaptive convolutional neural network Authors: Mishra, Vidyanand; Kane, Lalit Description: Published in the Expert systems with applications Journal, 224 (2023) | doi: https://doi.org/10.1016/j.eswa.2023.120032 Wed, 05 Apr 2023 00:00:00 GMT https://dr.ddn.upes.ac.in//xmlui/handle/123456789/4152 2023-04-05T00:00:00Z