Zobrazeno 1 - 10
of 2 297
pro vyhledávání: '"Jagadeeswaran P"'
Monte Carlo and Quasi-Monte Carlo methods present a convenient approach for approximating the expected value of a random variable. Algorithms exist to adaptively sample the random variable until a user defined absolute error tolerance is satisfied wi
Externí odkaz:
http://arxiv.org/abs/2311.07555
Autor:
Choi, Sou-Cheng T., Ding, Yuhan, Hickernell, Fred J., Rathinavel, Jagadeeswaran, Sorokin, Aleksei G.
Quasi-Monte Carlo (QMC) methods have developed over several decades. With the explosion in computational science, there is a need for great software that implements QMC algorithms. We summarize the QMC software that has been developed to date, propos
Externí odkaz:
http://arxiv.org/abs/2311.06162
Autor:
Rathinavel, Jagadeeswaran
Automatic cubatures approximate integrals to user-specified error tolerances. For high dimensional problems, it is difficult to adaptively change the sampling pattern to focus on peaks because peaks can hide more easily in high dimensional space. But
Externí odkaz:
http://arxiv.org/abs/2210.03253
Autor:
Meena Arumugam Gopalakrishnan, Gopalakrishnan Chellappan, Kamalakannan Ayyanar, Jagadeeswaran Ramasamy, Patil Santhosh Ganapati, Sathyamoorthy Nagaranai Karuppasamy
Publikováno v:
Frontiers in Microbiology, Vol 15 (2024)
Rice (Oryza sativa L.) is a vital crop feeding more than half of the world’s population, with production occurring predominantly in Asian countries. However, rice cultivation faces challenges from various fronts, including biotic stresses intensifi
Externí odkaz:
https://doaj.org/article/aacc49fdffdb41139f7910fd7aac0063
Autor:
Warren Burggren, Regina Abramova, Naim M. Bautista, Regina Fritsche Danielson, Ben Dubansky, Avi Gupta, Kenny Hansson, Neha Iyer, Pudur Jagadeeswaran, Karin Jennbacken, Katarina Rydén-Markinhutha, Vishal Patel, Revathi Raman, Hersh Trivedi, Karem Vazquez Roman, Steven Williams, Qing-Dong Wang
Publikováno v:
Biology Open, Vol 13, Iss 9 (2024)
Externí odkaz:
https://doaj.org/article/5f605a67762b4e0881bfb294c2fafedc
Publikováno v:
Egyptian Journal of Biological Pest Control, Vol 34, Iss 1, Pp 1-10 (2024)
Abstract Background Pasteuria penetrans is a mycelial, endospore forming, obligate, bacterial parasite that has shown enormous potential for biological control of root-knot nematode, Meloidogyne spp. In the present study, the effort has been made to
Externí odkaz:
https://doaj.org/article/e7e4197ceb214b409a07eb01d247e32c
Publikováno v:
Egyptian Journal of Biological Pest Control, Vol 34, Iss 1, Pp 1-17 (2024)
Abstract Background Nematode egg parasitic fungus, Purpureocillium lilacinum is the most effective biocontrol agent and has been widely used commercially in many countries for the management of root-knot nematode, Meloidogyne incognita. Availability
Externí odkaz:
https://doaj.org/article/cf3fa2aebbce444f93240f3298b35b49
Autor:
Thamizh Vendan Tarun Kshatriya, Ramalingam Kumaraperumal, Sellaperumal Pazhanivelan, Nivas Raj Moorthi, Dhanaraju Muthumanickam, Kaliaperumal Ragunath, Jagadeeswaran Ramasamy
Publikováno v:
Agronomy, Vol 14, Iss 11, p 2707 (2024)
Large-scale mapping of soil resources can be crucial and indispensable for several of the managerial applications and policy implications. With machine learning models being the most utilized modeling technique for digital soil mapping (DSM), the imp
Externí odkaz:
https://doaj.org/article/55f54f0584bc4a96874d952051fada1f
Autor:
Dhinoja S; Department of Biological Sciences, University of North Texas, Denton, Texas, USA., Mary J, Qaryoute AA, De Maria A, Jagadeeswaran P
Publikováno v:
Blood coagulation & fibrinolysis : an international journal in haemostasis and thrombosis [Blood Coagul Fibrinolysis] 2024 Dec 02. Date of Electronic Publication: 2024 Dec 02.
Autor:
Choi, Sou-Cheng T., Hickernell, Fred J., Jagadeeswaran, R., McCourt, Michael J., Sorokin, Aleksei G.
Practitioners wishing to experience the efficiency gains from using low discrepancy sequences need correct, robust, well-written software. This article, based on our MCQMC 2020 tutorial, describes some of the better quasi-Monte Carlo (QMC) software a
Externí odkaz:
http://arxiv.org/abs/2102.07833