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217 results on '"Rawat, Seema"'

9. 5G Revolution Transforming the Delivery in Healthcare

Author

Singh, Shivam, Chowdhary, Sunil Kumar, Rawat, Seema, Acharya, Biswa Mohan, Howlett, Robert J., Series Editor, Jain, Lakhmi C., Series Editor, Swarnkar, Tripti, editor, Patnaik, Srikanta, editor, Mitra, Pabitra, editor, Misra, Sanjay, editor, and Mishra, Manohar, editor

Published
2023
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11. Trisodium 2-Hydroxypropane-1,2,3-Tricarboxylate Encapsulated Nanocontainer-Based Template-Free Electrochemical Synthesis of Multidimensional Copper/Copper Oxide Nanoparticles

Author

Saini, Mona, Rani, Nutan, Mushtaq, Asifa, Singh, Rini, Rawat, Seema, Kumar, Manoj, saini, Kalawati, Ghosh, Arindam, Series Editor, Chua, Daniel, Series Editor, de Souza, Flavio Leandro, Series Editor, Aktas, Oral Cenk, Series Editor, Han, Yafang, Series Editor, Gong, Jianghong, Series Editor, Jawaid, Mohammad, Series Editor, Mudali, U. Kamachi, editor, Aruna, S. T., editor, Nagaswarupa, H. P., editor, and Rangappa, Dinesh, editor

Published
2022
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18. Software as a Service for Upcoming Industries

Author

Chaudhary, Divyansh, Kumar, Praveen, Rawat, Seema, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Hassanien, Aboul Ella, editor, Bhattacharyya, Siddhartha, editor, Chakrabati, Satyajit, editor, Bhattacharya, Abhishek, editor, and Dutta, Soumi, editor

Published
2021
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24. Examining the nexus between learning modalities and scholarly performance in 1st-year medical students.

Author

Rathod, Niraj Mansukhlal, Panchal, Amar, Rawat, Seema, and Makwana, Komal K.

Subjects
AUDITORY learning, COGNITIVE styles, VISUAL learning, MEDICAL students, EXPERIENTIAL learning
Abstract

Background: The visual-aural-read/write-kinesthetic (VARK) questionnaire is a pre-eminent, accessible, and rigorously validated instrument that facilitates students in discerning their learning predilections. Nonetheless, the interrelation between VARK learning styles and scholastic achievement remains largely uncharted. Visual learners excel with diagrams, graphs, and flowcharts; auditory learners prefer aural information; read/write learners engage with textual material; and kinesthetic learners thrive through experiential learning and practical applications. This investigation endeavors to elucidate the correlation between predominant learning styles and the academic performance of 1st-year medical students in both theoretical and practical contexts. Aims and Objectives: The aims and objectives of the study are to scrutinize the correlation between distinct learning modalities (VARK) and academic performance among 1st-year medical students at GMERS Medical College. Materials and Methods: Subsequent to ethical sanction, 1st-year MBBS students from the 2021 cohort were solicited to partake in this cross-sectional, educational institution-based, temporally constrained study. Students who withheld consent were excluded. The investigation was executed in three phases. In the initial phase, the VARK 8.1 questionnaire was disseminated to 189 students to ascertain their learning styles, concomitant with the collection of demographic data. The VARK questionnaire encompasses 16 multiple-choice questions, each corresponding to a specific sensory learning modality. The modality with the highest score was designated as the student's preferred learning style. In the second phase, preliminary examination scores (theoretical and practical) for physiology, anatomy, and biochemistry were recorded. In the third phase, direct, in-depth interviews were conducted to rectify any data discrepancies or ambiguities regarding learning style preferences. Results: Among the participants, 61 out of 104 males and 51 out of 85 females exhibited a predilection for the kinesthetic learning style as their unimodal preference. The second most prevalent preference among males was visual, whereas females favored aural learning. Merely two males and no females identified as read/write learners. Correlation coefficient analysis revealed a robust association between visual learning scores and academic performance across both genders. High achievers predominantly favored the visual modality. Conversely, the aural and read/write modalities exhibited weak or negligible correlation with academic performance. Despite the prevalence of the kinesthetic modality among both male and female students, it only demonstrated a tenuous association with biochemistry scores. For male students, a moderate correlation was observed in anatomy and biochemistry. Conclusion: This study intimates that the preponderance of students prefers the kinesthetic learning style. Nevertheless, there exists a significant correlation between visual learning styles and academic performance in both male and female students. [ABSTRACT FROM AUTHOR]

Published
2024
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29. Analyzing Balancing of Heterogeneous Load on Cluster-Based Web Server

Author

Kumar, Praveen, Singhal, Garvit, Rawat, Seema, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Kotenko, Igor, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Batra, Usha, editor, Roy, Nihar Ranjan, editor, and Panda, Brajendra, editor

Published
2020
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32. Deep learning based COVID and pneumonia detection using chest X-ray.

Author

Kumar, Praveen, Rakhimzhanova, Mira, Rawat, Seema, Orynbek, Alibek, and Kamra, Vikas

Subjects
X-rays, DEEP learning, CONVOLUTIONAL neural networks, COVID-19 pandemic, COVID-19, SARS-CoV-2
Abstract

Since the outbreak, the novel coronavirus (COVID-19) has infected more than 180 million people and has taken a toll of 3.91 million lives globally as of June 2021. This virus causes symptoms like fever, cold, and fatigue, and can develop into Pneumonia which can be detected using chest X-rays (CXRs). Therefore, early detection of COVID-19 can help get early medical attention. However, a sudden rise in the number of cases in many countries caused by COVID waves increases the burden on their testing facilities. As a result, they sometimes fail to perform enough testing to contain the spread. This work proposes a deep learning model to detect COVID-19 and Pneumonia based on CXRs. The dataset for our COVID model contains a total of 3,400 CXRs images of COVID-19 patients and 3,400 normal CXRs. The dataset for our Pneumonia model contains 1,300 CXR images of Pneumonia patients and 1,300 normal CXRs. We use convolutional neural network provided by TensorFlow to build our model, which gave 94.17% and 93.55% accuracy for COVID model and Pneumonia model, respectively. Finally, we deployed our model on the web and added a web tracker, which gives us the cases, deaths, and recoveries state-wise and nationwide. [ABSTRACT FROM AUTHOR]

Published
2024
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33. A Critical and Statistical Analysis of Air Pollution Using Data Analytics

Author

Kumar, Praveen, Lalwani, Paras, Rathore, Karan, Rawat, Seema, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Rathore, Vijay Singh, editor, Worring, Marcel, editor, Mishra, Durgesh Kumar, editor, Joshi, Amit, editor, and Maheshwari, Shikha, editor

Published
2019
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40. Detection and Removal of Security Attacks Using ALARM Protocol in WSN Environment

Author

Rawat, Seema, Kumar, Praveen, Dhruv, Bhawna, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Bokhari, M. U., editor, Agrawal, Namrata, editor, and Saini, Dharmendra, editor

Published
2018
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41. Analytical Planning and Implementation of Big Data Technology Working at Enterprise Level

Author

Pant, Pooja, Kumar, Praveen, Alam, Irshad, Rawat, Seema, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Bhateja, Vikrant, editor, Nguyen, Bao Le, editor, Nguyen, Nhu Gia, editor, Satapathy, Suresh Chandra, editor, and Le, Dac-Nhuong, editor

Published
2018
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42. Eco-Friendly Green Computing Approaches for Next-Generation Power Consumption

Author

Rawat, Seema, Mishra, Richa, Kumar, Praveen, Kacprzyk, Janusz, Series editor, Pal, Nikhil R., Advisory editor, Bello Perez, Rafael, Advisory editor, Corchado, Emilio S., Advisory editor, Hagras, Hani, Advisory editor, Kóczy, László T., Advisory editor, Kreinovich, Vladik, Advisory editor, Lin, Chin-Teng, Advisory editor, Lu, Jie, Advisory editor, Melin, Patricia, Advisory editor, Nedjah, Nadia, Advisory editor, Nguyen, Ngoc Thanh, Advisory editor, Wang, Jun, Advisory editor, Bhalla, Subhash, editor, Bhateja, Vikrant, editor, Chandavale, Anjali A., editor, Hiwale, Anil S., editor, and Satapathy, Suresh Chandra, editor

Published
2018
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43. A Proposed Maturity Model for Himachal Pradesh Government e-Services

Author

Kakkar, Alpana, Rawat, Seema, Gupta, Piyush, Khatri, Sunil Kumar, Kacprzyk, Janusz, Series editor, Pal, Nikhil R., Advisory editor, Bello Perez, Rafael, Advisory editor, Corchado, Emilio S., Advisory editor, Hagras, Hani, Advisory editor, Kóczy, László T., Advisory editor, Kreinovich, Vladik, Advisory editor, Lin, Chin-Teng, Advisory editor, Lu, Jie, Advisory editor, Melin, Patricia, Advisory editor, Nedjah, Nadia, Advisory editor, Nguyen, Ngoc Thanh, Advisory editor, Wang, Jun, Advisory editor, Bhalla, Subhash, editor, Bhateja, Vikrant, editor, Chandavale, Anjali A., editor, Hiwale, Anil S., editor, and Satapathy, Suresh Chandra, editor

Published
2018
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