Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Daniel Merl"'
Publikováno v:
Journal of Statistical Software, Vol 36, Iss 06 (2010)
The amei package for R is a tool that provides a flexible statistical framework for generating optimal epidemiological interventions that are designed to minimize the total expected cost of an emerging epidemic. Uncertainty regarding the underlying d
Externí odkaz:
https://doaj.org/article/18191133a8424c4ba94c54d9976b0a48
Autor:
Julia Ling-Yu Chen, Daniel Merl, Christopher W Peterson, Jianli Wu, Patrick Yantyng Liu, Hanwei Yin, Deborah M Muoio, Don E Ayer, Mike West, Jen-Tsan Chi
Publikováno v:
PLoS Genetics, Vol 6, Iss 9, p e1001093 (2010)
Although lactic acidosis is a prominent feature of solid tumors, we still have limited understanding of the mechanisms by which lactic acidosis influences metabolic phenotypes of cancer cells. We compared global transcriptional responses of breast ca
Externí odkaz:
https://doaj.org/article/63b1b63381834dcca4325d2a5db10c33
Publikováno v:
PLoS ONE, Vol 4, Iss 6, p e5807 (2009)
BACKGROUND: Epidemiological interventions aim to control the spread of infectious disease through various mechanisms, each carrying a different associated cost. METHODOLOGY: We describe a flexible statistical framework for generating optimal epidemio
Externí odkaz:
https://doaj.org/article/4934ac7ba932415aa8bd320e79ee92ad
Autor:
Tomas Kalincik, Jeannette Lechner-Scott, Helmut Butzkueven, Trevor Kilpatrick, Robert Hyde, David Darby, Michael Barnett, Anneke Van Der Walt, Yi Chao Foong, Bruce Taylor, Katherine Buzzard, Daniel Merlo, Melissa Gresle, Chao Zhu, Johan van Beek, Pamela Dobay
Publikováno v:
BMJ Neurology Open, Vol 6, Iss Suppl 1 (2024)
Externí odkaz:
https://doaj.org/article/fae49c68eed7436fbf0dd03889f36cba
Autor:
Tomas Kalincik, Jeannette Lechner-Scott, Helmut Butzkueven, Trevor Kilpatrick, Robert Hyde, David Darby, Michael Barnett, Anneke Van Der Walt, Yi Chao Foong, Bruce Taylor, Katherine Buzzard, Daniel Merlo, Melissa Gresle, Chao Zhu, Johan van Beek, Pamela Dobay
Publikováno v:
BMJ Neurology Open, Vol 6, Iss Suppl 1 (2024)
Externí odkaz:
https://doaj.org/article/72c65b45075f4589bfe9a03854f97c88
Autor:
Zachary R. Atkins, Christopher J. Vogl, Achintya Madduri, Nan Duan, Agnieszka K. Miedlar, Daniel Merl
As photovoltaic (PV) penetration continues to rise and smart inverter functionality continues to expand, smart inverters and other distributed energy resources (DERs) will play increasingly important roles in distribution system power management and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8043d8feae5a8a4794ae48afdf223ab0
http://arxiv.org/abs/2101.04816
http://arxiv.org/abs/2101.04816
Publikováno v:
2018 IEEE 9th International Symposium on Sensorless Control for Electrical Drives (SLED).
Sensorless position estimation algorithms for electromagnetic actuators are becoming increasingly significant in the field of control and condition monitoring since they allow the estimation of the actuator position without any mechanical sensor. Suc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a0487dc1cd61188248da5caa36cf8b35
https://doi.org/10.1109/sled.2018.8485843
https://doi.org/10.1109/sled.2018.8485843
Autor:
Bhuwan Chopra, Vinayak Borkar, Daniel Merl, Oleksandr Barykin, Janet L. Wiener, Subbu N. Subramanian, David Scott Reiss, Lior Abraham, Josh Metzler, John R. Allen, Okay Zed, Ciprian Gerea
Publikováno v:
Proceedings of the VLDB Endowment. 6:1057-1067
Facebook takes performance monitoring seriously. Performance issues can impact over one billion users so we track thousands of servers, hundreds of PB of daily network traffic, hundreds of daily code changes, and many other metrics. We require latenc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::84ad9b8a8aeff9a69117979699198aed
https://doi.org/10.14778/2536222.2536231
https://doi.org/10.14778/2536222.2536231
Publikováno v:
Computational Statistics & Data Analysis. 56:3809-3820
A primary challenge in unsupervised clustering using mixture models is the selection of a family of basis distributions flexible enough to succinctly represent the distributions of the target subpopulations. In this paper we introduce a new family of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c3e53697998d3ec1b899b308addd6f58
https://doi.org/10.1016/j.csda.2012.03.027
https://doi.org/10.1016/j.csda.2012.03.027