Search

Your search keyword '"Kumar, Sahil"' showing total 465 results
Start Over Author "Kumar, Sahil"
465 results on '"Kumar, Sahil"'

4. Vision Transformer Segmentation for Visual Bird Sound Denoising

Author

Kumar, Sahil, Li, Jialu, and Zhang, Youshan

Subjects
Computer Science - Sound, Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

Audio denoising, especially in the context of bird sounds, remains a challenging task due to persistent residual noise. Traditional and deep learning methods often struggle with artificial or low-frequency noise. In this work, we propose ViTVS, a novel approach that leverages the power of the vision transformer (ViT) architecture. ViTVS adeptly combines segmentation techniques to disentangle clean audio from complex signal mixtures. Our key contributions encompass the development of ViTVS, introducing comprehensive, long-range, and multi-scale representations. These contributions directly tackle the limitations inherent in conventional approaches. Extensive experiments demonstrate that ViTVS outperforms state-of-the-art methods, positioning it as a benchmark solution for real-world bird sound denoising applications. Source code is available at: https://github.com/aiai-4/ViVTS., Comment: INTERSPEECH 2024

Published
2024

11. Comparative Study of MPPT and Parameter Estimation of PV cells

Author

Kumar, Sahil, Gupta, Sahitya, Pratik, Vajayant, and Brunet, Pascal

Subjects
Computer Science - Machine Learning
Abstract

The presented work focuses on utilising machine learning techniques to accurately estimate accurate values for known and unknown parameters of the PVLIB model for solar cells and photovoltaic modules.Finding accurate model parameters of circuits for photovoltaic (PV) cells is important for a variety of tasks. An Artificial Neural Network (ANN) algorithm was employed, which outperformed other metaheuristic and machine learning algorithms in terms of computational efficiency. To validate the consistency of the data and output, the results were compared against other machine learning algorithms based on irradiance and temperature. A Bland Altman test was conducted that resulted in more than 95 percent accuracy rate. Upon validation, the ANN algorithm was utilised to estimate the parameters and their respective values.

Published
2023

12. Structural and Electrical Characterization of Gadolinium and Sodium Co-Doped Barium Strontium Titanate

Author

Sahil, Kumar, Sahil, Gaur, Anshu, Ahamad Mohiddon, Md., Preeti, 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, Khan, Zishan Husain, editor, Jackson, Mark, editor, and Salah, Numan A., editor

Published
2024
Full Text
View/download PDF

14. Leptogenesis and Neutrinoless Double Beta Decay in the Scotogenic Hybrid Textures of Neutrino Mass Matrix

Author

Ankush, Verma, Rishu, Kumar, Sahil, and Chauhan, B. C.

Subjects
High Energy Physics - Phenomenology
Abstract

In our recent work we identify the hybrid textures of neutrino mass matrix which simultaneously account for dark matter (DM) and neutrinoless double beta decay ($0\nu\beta\beta$). We also obtained the bounds on dark matter mass and effective Majorana mass $|M_{ee}|$. In this work we look for those hybrid textures which altogether accounts for DM, $0\nu\beta\beta$ and leptogenesis. We have found correlation of baryon asymmetry of universe $Y$ with dark matter mass $M_1$ and effective Majorana mass $|M_{ee}|$. We use experimental bounds on relic density of dark matter ($\Omega h^2$) and baryon asymmetry of universe to identify the hybrid textures. We found that out of five hybrid textures which simultaneously satisfies the physics observations of the DM and $0\nu\beta\beta$ only three hybrid textures altogether satisfy the DM, $0\nu\beta\beta$ and leptogenesis. It is interesting to note that these three hybrid textures gives lower bound to the effective Majorana mass $|M_{ee}|$ which can be probed in current and future experiments like SuperNEMO, KamLAND-Zen, NEXT, and nEXO (5 year) have sensitivity reaches of 0.05 eV, 0.045 eV, 0.03 eV, and 0.015 eV, respectively., Comment: 19 pages, 6 figures, 4 tables, section 2, 3 and 5 restructured

Published
2023

20. Mammalian cell expressed recombinant trimeric spike protein is a potent vaccine antigen and confers near-complete protection against SARS-CoV-2 infection in Hamster

Author

Jitender, Vikram Kumar, B., Singh, Sneha, Verma, Geetika, Kumar, Reetesh, Mishra, Pranaya M., Kumar, Sahil, Nagaraj, Santhosh K., Nag, Joydeep, Joy, Christy M., Nikam, Bhushan, Singh, Dharmendra, Pooja, Kalidas, Nidhi, Singh, Shubham, Mumtaz, Bhardwaj, Ashwani K., Mankotia, Dhananjay S., Ringe, Rajesh P., Gupta, Nimesh, Tripathi, Shashank, and Mishra, Ravi P.N.

Published
2024
Full Text
View/download PDF

25. Very high particulate pollution over northwest India captured by a high-density in situ sensor network

Author

Singh, Tanbir, Matsumi, Yutaka, Nakayama, Tomoki, Hayashida, Sachiko, Patra, Prabir K., Yasutomi, Natsuko, Kajino, Mizuo, Yamaji, Kazuyo, Khatri, Pradeep, Takigawa, Masayuki, Araki, Hikaru, Kurogi, Yuki, Kuji, Makoto, Muramatsu, Kanako, Imasu, Ryoichi, Ananda, Anamika, Arbain, Ardhi A., Ravindra, Khaiwal, Bhardwaj, Sanjeev, Kumar, Sahil, Mor, Sahil, Dhaka, Surendra K., Dimri, A. P., Sharma, Aka, Singh, Narendra, Bhatti, Manpreet S., Yadav, Rekha, Vatta, Kamal, and Mor, Suman

Published
2023
Full Text
View/download PDF

26. Prediction of Heart Disease with Machine Learning Methods: Comparison and Analysis

Author

Singh, Bharat, Nandan, Savita, Kumar, Sahil, Kushwaha, Nidhi, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Tuba, Milan, editor, Akashe, Shyam, editor, and Joshi, Amit, editor

Published
2023
Full Text
View/download PDF

30. An androgen receptor switch underlies lineage infidelity in treatment-resistant prostate cancer

Author

Davies, Alastair, Nouruzi, Shaghayegh, Ganguli, Dwaipayan, Namekawa, Takeshi, Thaper, Daksh, Linder, Simon, Karaoğlanoğlu, Fatih, Omur, Meltem E, Kim, Soojin, Kobelev, Maxim, Kumar, Sahil, Sivak, Olena, Bostock, Chiara, Bishop, Jennifer, Hoogstraat, Marlous, Talal, Amina, Stelloo, Suzan, van der Poel, Henk, Bergman, Andries M, Ahmed, Musaddeque, Fazli, Ladan, Huang, Haojie, Tilley, Wayne, Goodrich, David, Feng, Felix Y, Gleave, Martin, He, Housheng Hansen, Hach, Faraz, Zwart, Wilbert, Beltran, Himisha, Selth, Luke, and Zoubeidi, Amina

Subjects
Prostate Cancer, Genetics, Cancer, Stem Cell Research, Urologic Diseases, Aetiology, 1.1 Normal biological development and functioning, Underpinning research, 2.1 Biological and endogenous factors, Cell Line, Tumor, Enhancer of Zeste Homolog 2 Protein, Gene Expression Regulation, Neoplastic, Gene Regulatory Networks, Humans, Male, Prostatic Neoplasms, Receptors, Androgen, Signal Transduction, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

Cancers adapt to increasingly potent targeted therapies by reprogramming their phenotype. Here we investigated such a phenomenon in prostate cancer, in which tumours can escape epithelial lineage confinement and transition to a high-plasticity state as an adaptive response to potent androgen receptor (AR) antagonism. We found that AR activity can be maintained as tumours adopt alternative lineage identities, with changes in chromatin architecture guiding AR transcriptional rerouting. The epigenetic regulator enhancer of zeste homologue 2 (EZH2) co-occupies the reprogrammed AR cistrome to transcriptionally modulate stem cell and neuronal gene networks-granting privileges associated with both fates. This function of EZH2 was associated with T350 phosphorylation and establishment of a non-canonical polycomb subcomplex. Our study provides mechanistic insights into the plasticity of the lineage-infidelity state governed by AR reprogramming that enabled us to redirect cell fate by modulating EZH2 and AR, highlighting the clinical potential of reversing resistance phenotypes.

Published
2021

37. Trop2 is a driver of metastatic prostate cancer with neuroendocrine phenotype via PARP1

Author

Hsu, En-Chi, Rice, Meghan A, Bermudez, Abel, Marques, Fernando Jose Garcia, Aslan, Merve, Liu, Shiqin, Ghoochani, Ali, Zhang, Chiyuan Amy, Chen, Yun-Sheng, Zlitni, Aimen, Kumar, Sahil, Nolley, Rosalie, Habte, Frezghi, Shen, Michelle, Koul, Kashyap, Peehl, Donna M, Zoubeidi, Amina, Gambhir, Sanjiv S, Kunder, Christian A, Pitteri, Sharon J, Brooks, James D, and Stoyanova, Tanya

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Oncology and Carcinogenesis, Urologic Diseases, Aging, Prostate Cancer, Cancer, Development of treatments and therapeutic interventions, 5.1 Pharmaceuticals, Animals, Antigens, Neoplasm, Apoptosis, Biomarkers, Tumor, Bone Neoplasms, Carcinoma, Neuroendocrine, Cell Adhesion Molecules, Cell Movement, Cell Proliferation, Follow-Up Studies, Gene Expression Regulation, Neoplastic, Humans, Male, Mice, Mice, Inbred NOD, Mice, SCID, Neoplasm Invasiveness, Phenotype, Poly (ADP-Ribose) Polymerase-1, Poly(ADP-ribose) Polymerase Inhibitors, Prognosis, Prostatic Neoplasms, Castration-Resistant, Survival Rate, Tumor Cells, Cultured, Xenograft Model Antitumor Assays, prostate, cancer, NEPC, Trop2
Abstract

Resistance to androgen deprivation therapy, or castration-resistant prostate cancer (CRPC), is often accompanied by metastasis and is currently the ultimate cause of prostate cancer-associated deaths in men. Recently, secondary hormonal therapies have led to an increase of neuroendocrine prostate cancer (NEPC), a highly aggressive variant of CRPC. Here, we identify that high levels of cell surface receptor Trop2 are predictive of recurrence of localized prostate cancer. Moreover, Trop2 is significantly elevated in CRPC and NEPC, drives prostate cancer growth, and induces neuroendocrine phenotype. Overexpression of Trop2 induces tumor growth and metastasis while loss of Trop2 suppresses these abilities in vivo. Trop2-driven NEPC displays a significant up-regulation of PARP1, and PARP inhibitors significantly delay tumor growth and metastatic colonization and reverse neuroendocrine features in Trop2-driven NEPC. Our findings establish Trop2 as a driver and therapeutic target for metastatic prostate cancer with neuroendocrine phenotype and suggest that high Trop2 levels could identify cancers that are sensitive to Trop2-targeting therapies and PARP1 inhibition.

Published
2020

38. Localized Hop-Count Based Routing (LHR) Protocol for Underwater Acoustic Sensor Networks

Author

Kumar, Sahil, Chandavarkar, B. R., Nazareth, Pradeep, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Panda, Sanjaya Kumar, editor, Rout, Rashmi Ranjan, editor, Sadam, Ravi Chandra, editor, Rayanoothala, Bala Venkata Subramaanyam, editor, Li, Kuan-Ching, editor, and Buyya, Rajkumar, editor

Published
2022
Full Text
View/download PDF

49. Prioritization of Wheel Materials Using MCDM Techniques (TOPSIS) for Automobile Wheels

Author

Bhatia, Aditya, Kumar, Sahil, Bhatt, Sarthak, Dadge, Mukesh Shamrao, Shuaib, Mohd, Cavas-Martínez, Francisco, Series Editor, Chaari, Fakher, Series Editor, Gherardini, Francesco, Series Editor, Haddar, Mohamed, Series Editor, Ivanov, Vitalii, Series Editor, Kwon, Young W., Series Editor, Trojanowska, Justyna, Series Editor, Kumar, Anil, editor, Pal, Amit, editor, Kachhwaha, Surendra Singh, editor, and Jain, Prashant Kumar, editor

Published
2021
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results