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1,394 results on '"Sharma, Jai"'

24. An RNA Sequencing Analysis of Glaucoma Genesis in Mice

Author

Sharma, Jai and Bhaskar, Vidhyacharan

Subjects
Quantitative Biology - Genomics
Abstract

Glaucoma is the leading cause of irreversible blindness in people over the age of 60, accounting for 6.6 to 8% of all blindness in 2010, but there is still much to be learned about the genetic origins of the eye disease. With the modern development of Next-Generation Sequencing (NGS) technologies, scientists are starting to learn more about the genetic origins of Glaucoma. This research uses differential expression (DE) and gene ontology (GO) analyses to study the genetic differences between mice with severe Glaucoma and multiple control groups. Optical nerve head (ONH) and retina data samples of genome-wide RNA expression from NCBI (NIH) are used for pairwise comparison experimentation. In addition, principal component analysis (PCA) and dispersion visualization methods are employed to perform quality control tests of the sequenced data. Genes with skewed gene counts are also identified, as they may be marker genes for a particular severity of Glaucoma. The gene ontologies found in this experiment support existing knowledge of Glaucoma genesis, providing confidence that the results were valid. Future researchers can thoroughly study the gene lists generated by the DE and GO analyses to find potential activator or protector genes for Glaucoma in mice to develop drug treatments or gene therapies to slow or stop the progression of the disease. The overall goal is that in the future, such treatments can be made for humans as well to improve the quality of life for human patients with Glaucoma and reduce Glaucoma blindness rates., Comment: 6 pages, 6 figures

Published
2022

25. Longitudinal Assessment of ROX and HACOR Scores to Predict Non-Invasive Ventilation Failure in Patients with SARS-CoV-2 Pneumonia

Author

Anand Abhijeet, Kodamanchili Sai Teja, Joshi Ankur, Joshi Rajnish, Sharma Jai Prakash, Abhishek Goyal, Pakhare Abhijit P, Niwariya Yogesh, Panda Rajesh, Karna Sunaina T, Khurana Alkesh K, and Saigal Saurabh

Subjects
non-invasive ventilation, hacor, rox, covid-19, ards, Medical emergencies. Critical care. Intensive care. First aid, RC86-88.9
Abstract

NIV (Non-invasive ventilation) and HFNC (High Flow nasal cannula) are being used in patients with acute respiratory failure. HACOR score has been exclusively calculated for patients on NIV, on other hand ROX index is being used for patients on HFNC. This is first study where ROX index has been used in patients on NIV to predict failure.

Published
2024
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27. A Deep Learning Ensemble Framework for Off-Nadir Geocentric Pose Prediction

Author

Sun, Christopher, Sharma, Jai, and Maiti, Milind

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Computational methods to accelerate natural disaster response include change detection, map alignment, and vision-aided navigation. Current software functions optimally only on near-nadir images, though off-nadir images are often the first sources of information following a natural disaster. The use of off-nadir images for the aforementioned tasks requires the computation of geocentric pose, which is an aerial vehicle's spatial orientation with respect to gravity. This study proposes a deep learning ensemble framework to predict geocentric pose using 5,923 near-nadir and off-nadir RGB satellite images of cities worldwide. First, a U-Net Fully Convolutional Neural Network predicts the pixel-wise above-ground elevation mask of the RGB images. Then, the elevation masks are concatenated with the RGB images to form four-channel inputs fed into a second convolutional model, which predicts orientation angle and magnification scale. A performance accuracy of R2=0.917 significantly outperforms previous methodologies. In addition, outlier removal is performed through supervised interpolation, and a sensitivity analysis of elevation masks is conducted to gauge the usefulness of data features, motivating future avenues of feature engineering. The high-accuracy software built in this study contributes to mapping and navigation procedures for effective disaster response to save lives., Comment: 2022 5th International Conference on Pattern Recognition and Artificial Intelligence (PRAI)

Published
2022

28. Abstract 4142390: The LAI-OLS registry: Unveiling crucial insights into the challenges of managing LDL cholesterol in Indian patients with CAD

Author

Mahajan, Kunal, Gupta, Ashu, Batra, Aditya, Rana, Vivek, Kumar, Mukul, Gawalkar, Atit, Bhatia, Tanuj, Yadav, Rahul, Kumar, Dhananjay, Sharma, Jai Bharat, Theja, Pavan, Yadav, Ashwani, dev, munish, Himral, Surender, Thakur, Priyanka, Khandelwal, Sakshi, Pratap, Akshay, Khan, Aziz, Agarwala, Rajeev, and Puri, Raman

Published
2024
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34. Surveillance of ventilator associated pneumonia in a network of indian hospitals using modified definitions: a pilot study

Author

Mathur, Purva, Ningombam, Aparna, Soni, Kapil Dev, Aggrawal, Richa, Singh, Kumari Vandana, Samanta, Projoyita, Gupta, Stuti, Srivastava, Smriti, Behera, Bijayini, Tripathy, Swagata, Ray, Pallab, Biswal, Manisha, Rodrigues, Camilla, Bhattacharya, Sanjay, Mukherjee, Sudipta, Mukherjee, Satyam, Venkatesh, Vimala, Verma, Sheetal, Arshad, Zia, Tak, Vibhor, Bhatia, Pradeep Kumar, Nag, Vijaylakshmi, Karuna, Tadepalli, Saigal, Sourabh, Sharma, Jai Prakash, Singh, Sanjeev, Mukhopadhyay, Chiranjay, KE, Vandana, Varma, Muralidhar, Majumdar, Tapan, Deotale, Vijayshree, Attal, Ruchita, Iravane, Jyoti, Harbade, Mangala, Omkari, Amruta, and Walia, Kamini

Published
2024
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41. Investigating the Relationship Between Dropout Regularization and Model Complexity in Neural Networks

Author

Sun, Christopher, Sharma, Jai, and Maiti, Milind

Subjects
Computer Science - Machine Learning
Abstract

Dropout Regularization, serving to reduce variance, is nearly ubiquitous in Deep Learning models. We explore the relationship between the dropout rate and model complexity by training 2,000 neural networks configured with random combinations of the dropout rate and the number of hidden units in each dense layer, on each of the three data sets we selected. The generated figures, with binary cross entropy loss and binary accuracy on the z-axis, question the common assumption that adding depth to a dense layer while increasing the dropout rate will certainly enhance performance. We also discover a complex correlation between the two hyperparameters that we proceed to quantify by building additional machine learning and Deep Learning models which predict the optimal dropout rate given some hidden units in each dense layer. Linear regression and polynomial logistic regression require the use of arbitrary thresholds to select the cost data points included in the regression and to assign the cost data points a binary classification, respectively. These machine learning models have mediocre performance because their naive nature prevented the modeling of complex decision boundaries. Turning to Deep Learning models, we build neural networks that predict the optimal dropout rate given the number of hidden units in each dense layer, the desired cost, and the desired accuracy of the model. Though, this attempt encounters a mathematical error that can be attributed to the failure of the vertical line test. The ultimate Deep Learning model is a neural network whose decision boundary represents the 2,000 previously generated data points. This final model leads us to devise a promising method for tuning hyperparameters to minimize computational expense yet maximize performance. The strategy can be applied to any model hyperparameters, with the prospect of more efficient tuning in industrial models.

Published
2021

46. Vibrations Signal Analysis of Cantilever Beam Using Machine Learning

Author

Sharma, Lali, Sharma, Jai Kumar, Khatri, Pallavi, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Tomar, Ranjeet Singh, editor, Verma, Shekhar, editor, Chaurasia, Brijesh Kumar, editor, Singh, Vrijendra, editor, Abawajy, Jemal H., editor, Akashe, Shyam, editor, Hsiung, Pao-Ann, editor, and Prasad, Ramjee, editor

Published
2023
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47. Impact of Phase-Locked Loop on the Control of TCSC

Author

Singh, Gaurav Kumar, Sharma, Jai Prakash, Gupta, Om Hari, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Namrata, Kumari, editor, Priyadarshi, Neeraj, editor, Bansal, Ramesh C., editor, and Kumar, Jitendra, editor

Published
2023
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48. Control and Operation of Microgrid Integrated with Solar PV and Wind Power (DFIG)

Author

Venkatesh, Paluru, Sharma, Jai Prakash, Ansari, Salauddin, Gupta, Om Hari, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Namrata, Kumari, editor, Priyadarshi, Neeraj, editor, Bansal, Ramesh C., editor, and Kumar, Jitendra, editor

Published
2023
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50. Comparative study on complications and difficulties in laparoscopy in female genital tuberculosis cases versus non-tuberculosis cases

Author

Sharma, Jai, Dharmendra, Sona, Rapaka, Gawri, Singh, Urvashi, Kriplani, Alka, Kumar, Sunesh, Dash, N., and Nayyer, Rishi

Subjects
World Health Organization, Diseases, Complications and side effects, Research, Laparoscopy -- Research, Tinidazole -- Complications and side effects -- Research, Tuberculosis -- Complications and side effects -- Research, Laparoscopic surgery -- Research
Published
2024

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