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23,166 results on '"Moorthy A"'

155. Enterprise Risk Management Maturity: A Clinical Study of a U.S. Multinational Nonprofit Firm.

Author

Jalilvand, Abolhassan and Moorthy, Sidharth

Subjects
RISK management in business, NONPROFIT organizations, COVID-19 pandemic, BOARDS of directors, HAZARD mitigation, ACTUARIAL risk
Abstract

This study, which is based on actual events, presents a dynamic analysis of the development, implementation, and post-implementation review of establishing an enterprise risk management (ERM) system for a U.S. multinational nonprofit firm over a 5-year period, 2015–2020. Using the Risk and Insurance Management Society Risk Maturity Model (RIMS RMM), questionnaire-based risk data and multi-dimensional risk mapping indices are used to identify and prioritize the firm's key strategic risks leading to the development of mitigation strategies whose performance are reviewed post ERM implementation, including during the 2020 Coronavirus pandemic. The results reveal that the firm's risk management system has been ad hoc and uncoordinated. Post-implementation review of the ERM program shows improvements in financial and operating positions resulting from risk diversification, enhanced profitability, exploitation of natural hedges, and improved board governance. The results further show that the recommended mitigation strategies have been effective in managing the adverse impact of the pandemic. Overall, the evidence offered in this study provides further support on the valuation benefits of ERM maturity within a real-world environment. [ABSTRACT FROM AUTHOR]

Published
2024
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156. Local-dimension-invariant Calderbank-Shor-Steane Codes with an Improved Distance Promise

Author

Moorthy, Arun J. and Gunderman, Lane G.

Subjects
Quantum Physics
Abstract

Quantum computers will need effective error-correcting codes. Current quantum processors require precise control of each particle, so having fewer particles to control might be beneficial. Although traditionally quantum computers are considered as using qubits (2-level systems), qudits (systems with more than 2-levels) are appealing since they can have an equivalent computational space using fewer particles, meaning fewer particles need to be controlled. In this work we prove how to construct codes with parameters $[[2^N,2^N-1-2N,\geq 3]]_q$ for any choice of prime $q$ and natural number $N$. This is accomplished using the technique of local-dimension-invariant (LDI) codes. Generally LDI codes have the drawback of needing large local-dimensions to ensure the distance is at least preserved, and so this work also reduces this requirement by utilizing the structure of CSS codes, allowing for the aforementioned code family to be imported for any local-dimension choice., Comment: 7 pages, 1 figure

Published
2021

157. Gaia May Detect Hundreds of Well-characterised Stellar Black Holes

Author

Chawla, Chirag, Chatterjee, Sourav, Breivik, Katelyn, Moorthy, Chaithanya Krishna, Andrews, Jeff J., and Sanderson, Robyn E.

Subjects
Astrophysics - Astrophysics of Galaxies, Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Solar and Stellar Astrophysics
Abstract

Detection of black holes (BHs) with detached luminous companions (LCs) can be instrumental in connecting the BH properties with their progenitors' since the latter can be inferred from the observable properties of the LC. Past studies showed the promise of Gaia astrometry in detecting BH-LC binaries. We build upon these studies by: 1) initialising the zero-age binary properties based on realistic, metallicity-dependent star-formation history in the Milky Way (MW), 2) evolving these binaries to current epoch to generate realistic MW populations of BH-LC binaries, 3) distributing these binaries in the MW preserving the complex age-metallicity-Galactic position correlations, 4) accounting for extinction and reddening using three-dimensional dust maps, 5) examining the extended Gaia mission's ability to resolve BH-LC binaries. We restrict ourselves to detached BH-LC binaries with orbital period <10 yr such that Gaia can observe at least one full orbit. We find: 1) the extended Gaia mission can astrometrically resolve 30-300 detached BH-LC binaries depending on our assumptions of supernova physics and astrometric detection threshold; 2) Gaia's astrometry alone can indicate BH candidates for 10-100 BH-LC binaries by constraining the dark primary mass >3 Msun; 3) distributions of observables including orbital periods, eccentricities, and component masses are sensitive to the adopted binary evolution model, hence can directly inform binary evolution models. Finally, we comment on the potential to further characterise these BH binaries through radial velocity measurements and observation of X-ray counterparts., Comment: 26 pages, 18 figures, and 1 table; accepted for publication in The Astrophysical Journal

Published
2021
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183. Self-training with Few-shot Rationalization: Teacher Explanations Aid Student in Few-shot NLU

Author

Bhat, Meghana Moorthy, Sordoni, Alessandro, and Mukherjee, Subhabrata

Subjects
Computer Science - Computation and Language
Abstract

While pre-trained language models have obtained state-of-the-art performance for several natural language understanding tasks, they are quite opaque in terms of their decision-making process. While some recent works focus on rationalizing neural predictions by highlighting salient concepts in the text as justifications or rationales, they rely on thousands of labeled training examples for both task labels as well as an-notated rationales for every instance. Such extensive large-scale annotations are infeasible to obtain for many tasks. To this end, we develop a multi-task teacher-student framework based on self-training language models with limited task-specific labels and rationales, and judicious sample selection to learn from informative pseudo-labeled examples1. We study several characteristics of what constitutes a good rationale and demonstrate that the neural model performance can be significantly improved by making it aware of its rationalized predictions, particularly in low-resource settings. Extensive experiments in several bench-mark datasets demonstrate the effectiveness of our approach., Comment: To Appear in EMNLP 2021

Published
2021

184. Building Resilient Information Systems for Child Nutrition in Post-conflict Sri Lanka during COVID-19 Pandemic

Author

Amarakoon, Pamod, Braa, Jørn, Sahay, Sundeep, Magodarathna, Lakmini, and Moorthy, Rajeev

Subjects
Computer Science - Computers and Society
Abstract

Post-conflict, low-resource settings are menaced with challenges related to low-resources, economic and social instability. The objective of the study is to understand the socio-technical determinants of resilience of resilience of routine information systems a backdrop of an implementation of a mobile-based nutrition information system in a post-conflict district in Sri Lanka. The longitudinal events in the study spans across several years into the period of COVID-19 pandemic and tries to understand the process of developing resilience of in a vulnerable district. The qualitative study deploys interviews, observations and document analysis for collection of empirical data. The case study reveals the long-standing capacity building, leadership and local governance, multisector collaboration, platform resilience and empowering of field health staff contribute in building resilience in everyday context. The empirical insights include the mechanisms in building resilience in routine system in low resource settings while promoting data quality and data use at field level., Comment: In proceedings of the 1st Virtual Conference on Implications of Information and Digital Technologies for Development, 2021

Published
2021

185. First-Generation Inference Accelerator Deployment at Facebook

Author

Anderson, Michael, Chen, Benny, Chen, Stephen, Deng, Summer, Fix, Jordan, Gschwind, Michael, Kalaiah, Aravind, Kim, Changkyu, Lee, Jaewon, Liang, Jason, Liu, Haixin, Lu, Yinghai, Montgomery, Jack, Moorthy, Arun, Nadathur, Satish, Naghshineh, Sam, Nayak, Avinash, Park, Jongsoo, Petersen, Chris, Schatz, Martin, Sundaram, Narayanan, Tang, Bangsheng, Tang, Peter, Yang, Amy, Yu, Jiecao, Yuen, Hector, Zhang, Ying, Anbudurai, Aravind, Balan, Vandana, Bojja, Harsha, Boyd, Joe, Breitbach, Matthew, Caldato, Claudio, Calvo, Anna, Catron, Garret, Chandwani, Sneh, Christeas, Panos, Cottel, Brad, Coutinho, Brian, Dalli, Arun, Dhanotia, Abhishek, Duncan, Oniel, Dzhabarov, Roman, Elmir, Simon, Fu, Chunli, Fu, Wenyin, Fulthorp, Michael, Gangidi, Adi, Gibson, Nick, Gordon, Sean, Hernandez, Beatriz Padilla, Ho, Daniel, Huang, Yu-Cheng, Johansson, Olof, Juluri, Shishir, Kanaujia, Shobhit, Kesarkar, Manali, Killinger, Jonathan, Kim, Ben, Kulkarni, Rohan, Lele, Meghan, Li, Huayu, Li, Huamin, Li, Yueming, Liu, Cynthia, Liu, Jerry, Maher, Bert, Mallipedi, Chandra, Mangla, Seema, Matam, Kiran Kumar, Mehta, Jubin, Mehta, Shobhit, Mitchell, Christopher, Muthiah, Bharath, Nagarkatte, Nitin, Narasimha, Ashwin, Nguyen, Bernard, Ortiz, Thiara, Padmanabha, Soumya, Pan, Deng, Poojary, Ashwin, Ye, Qi, Raginel, Olivier, Rajagopal, Dwarak, Rice, Tristan, Ross, Craig, Rotem, Nadav, Russ, Scott, Shah, Kushal, Shan, Baohua, Shen, Hao, Shetty, Pavan, Skandakumaran, Krish, Srinivasan, Kutta, Sumbaly, Roshan, Tauberg, Michael, Tzur, Mor, Verma, Sidharth, Wang, Hao, Wang, Man, Wei, Ben, Xia, Alex, Xu, Chenyu, Yang, Martin, Zhang, Kai, Zhang, Ruoxi, Zhao, Ming, Zhao, Whitney, Zhu, Rui, Mathews, Ajit, Qiao, Lin, Smelyanskiy, Misha, Jia, Bill, and Rao, Vijay

Subjects
Computer Science - Hardware Architecture
Abstract

In this paper, we provide a deep dive into the deployment of inference accelerators at Facebook. Many of our ML workloads have unique characteristics, such as sparse memory accesses, large model sizes, as well as high compute, memory and network bandwidth requirements. We co-designed a high-performance, energy-efficient inference accelerator platform based on these requirements. We describe the inference accelerator platform ecosystem we developed and deployed at Facebook: both hardware, through Open Compute Platform (OCP), and software framework and tooling, through Pytorch/Caffe2/Glow. A characteristic of this ecosystem from the start is its openness to enable a variety of AI accelerators from different vendors. This platform, with six low-power accelerator cards alongside a single-socket host CPU, allows us to serve models of high complexity that cannot be easily or efficiently run on CPUs. We describe various performance optimizations, at both platform and accelerator level, which enables this platform to serve production traffic at Facebook. We also share deployment challenges, lessons learned during performance optimization, as well as provide guidance for future inference hardware co-design.

Published
2021

186. Africa-specific human genetic variation near CHD1L associates with HIV-1 load

Author

McLaren, Paul J., Porreca, Immacolata, Iaconis, Gennaro, Mok, Hoi Ping, Mukhopadhyay, Subhankar, Karakoc, Emre, Cristinelli, Sara, Pomilla, Cristina, Bartha, István, Thorball, Christian W., Tough, Riley H., Angelino, Paolo, Kiar, Cher S., Carstensen, Tommy, Fatumo, Segun, Porter, Tarryn, Jarvis, Isobel, Skarnes, William C., Bassett, Andrew, DeGorter, Marianne K., Sathya Moorthy, Mohana Prasad, Tuff, Jeffrey F., Kim, Eun-Young, Walter, Miriam, Simons, Lacy M., Bashirova, Arman, Buchbinder, Susan, Carrington, Mary, Cossarizza, Andrea, De Luca, Andrea, Goedert, James J., Goldstein, David B., Haas, David W., Herbeck, Joshua T., Johnson, Eric O., Kaleebu, Pontiano, Kilembe, William, Kirk, Gregory D., Kootstra, Neeltje A., Kral, Alex H., Lambotte, Olivier, Luo, Ma, Mallal, Simon, Martinez-Picado, Javier, Meyer, Laurence, Miro, José M., Moodley, Pravi, Motala, Ayesha A., Mullins, James I., Nam, Kireem, Obel, Niels, Pirie, Fraser, Plummer, Francis A., Poli, Guido, Price, Matthew A., Rauch, Andri, Theodorou, Ioannis, Trkola, Alexandra, Walker, Bruce D., Winkler, Cheryl A., Zagury, Jean-François, Montgomery, Stephen B., Ciuffi, Angela, Hultquist, Judd F., Wolinsky, Steven M., Dougan, Gordon, Lever, Andrew M. L., Gurdasani, Deepti, Groom, Harriet, Sandhu, Manjinder S., and Fellay, Jacques

Published
2023
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188. Federated benchmarking of medical artificial intelligence with MedPerf

Author

Karargyris, Alexandros, Umeton, Renato, Sheller, Micah J., Aristizabal, Alejandro, George, Johnu, Wuest, Anna, Pati, Sarthak, Kassem, Hasan, Zenk, Maximilian, Baid, Ujjwal, Narayana Moorthy, Prakash, Chowdhury, Alexander, Guo, Junyi, Nalawade, Sahil, Rosenthal, Jacob, Kanter, David, Xenochristou, Maria, Beutel, Daniel J., Chung, Verena, Bergquist, Timothy, Eddy, James, Abid, Abubakar, Tunstall, Lewis, Sanseviero, Omar, Dimitriadis, Dimitrios, Qian, Yiming, Xu, Xinxing, Liu, Yong, Goh, Rick Siow Mong, Bala, Srini, Bittorf, Victor, Puchala, Sreekar Reddy, Ricciuti, Biagio, Samineni, Soujanya, Sengupta, Eshna, Chaudhari, Akshay, Coleman, Cody, Desinghu, Bala, Diamos, Gregory, Dutta, Debo, Feddema, Diane, Fursin, Grigori, Huang, Xinyuan, Kashyap, Satyananda, Lane, Nicholas, Mallick, Indranil, Mascagni, Pietro, Mehta, Virendra, Moraes, Cassiano Ferro, Natarajan, Vivek, Nikolov, Nikola, Padoy, Nicolas, Pekhimenko, Gennady, Reddi, Vijay Janapa, Reina, G. Anthony, Ribalta, Pablo, Singh, Abhishek, Thiagarajan, Jayaraman J., Albrecht, Jacob, Wolf, Thomas, Miller, Geralyn, Fu, Huazhu, Shah, Prashant, Xu, Daguang, Yadav, Poonam, Talby, David, Awad, Mark M., Howard, Jeremy P., Rosenthal, Michael, Marchionni, Luigi, Loda, Massimo, Johnson, Jason M., Bakas, Spyridon, and Mattson, Peter

Published
2023
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196. Multi-Omic Analysis of Esophageal Adenocarcinoma Uncovers Candidate Therapeutic Targets and Cancer-Selective Posttranscriptional Regulation

Author

Fitzgerald, Rebecca C., Edwards, Paul A.W., Grehan, Nicola, Nutzinger, Barbara, Loreno, Christine, Redmond, Aisling M., Abbas, Sujath, Freeman, Adam, Smyth, Elizabeth C., O'Donovan, Maria, Miremadi, Ahmad, Malhotra, Shalini, Tripathi, Monika, Cheah, Calvin, Coles, Hannah, Millington, Curtis, Devonshire, Ginny, Eldridge, Matthew, Secrier, Maria, Jammula, Sriganesh, Davies, Jim, Crichton, Charles, Carroll, Nick, Hardwick, Richard H., Safranek, Peter, Hindmarsh, Andrew, Sujendran, Vijayendran, Hayes, Stephen J., Ang, Yeng, Sharrocks, Andrew, Preston, Shaun R., Bagwan, Izhar, Save, Vicki, Skipworth, Richard J.E., Hupp, Ted R., O'Neill, J Robert, Tucker, Olga, Beggs, Andrew, Taniere, Philippe, Puig, Sonia, Contino, Gianmarco, Underwood, Timothy J., Walker, Robert C., Grace, Ben L., Lagergren, Jesper, Gossage, James, Davies, Andrew, Chang, Fuju, Mahadeva, Ula, Goh, Vicky, Ciccarelli, Francesca D., Sanders, Grant, Berrisford, Richard, Chan, David, Cheong, Ed, Kumar, Bhaskar, Sreedharan, L., Parsons, Simon L., Soomro, Irshad, Kaye, Philip, Saunders, John, Lovat, Laurence, Haidry, Rehan, Scott, Michael, Sothi, Sharmila, Lishman, Suzy, Hanna, George B., Peters, Christopher J., Moorthy, Krishna, Grabowska, Anna, Turkington, Richard, McManus, Damian, Coleman, Helen, Petty, Russell D., Bartlet, Freddie, O'Neill, J. Robert, Yébenes Mayordomo, Marcos, Mitulović, Goran, Al Shboul, Sofian, Bedran, Georges, Faktor, Jakub, Hernychova, Lenka, Uhrik, Lukas, Gómez-Herranz, Maria, Kocikowski, Mikołaj, Vojtěšek, Bořivoj, Arends, Mark J., Hupp, Ted, and Alfaro, Javier Antonio

Published
2024
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199. Multi-tissue profiling of oxylipins reveal a conserved up-regulation of epoxide:diol ratio that associates with white adipose tissue inflammation and liver steatosis in obesity

Author

Hateley, Charlotte, Olona, Antoni, Halliday, Laura, Edin, Matthew L., Ko, Jeong-Hun, Forlano, Roberta, Terra, Ximena, Lih, Fred B., Beltrán-Debón, Raúl, Manousou, Penelopi, Purkayastha, Sanjay, Moorthy, Krishna, Thursz, Mark R., Zhang, Guodong, Goldin, Robert D., Zeldin, Darryl C., Petretto, Enrico, and Behmoaras, Jacques

Published
2024
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