Zobrazeno 1 - 10
of 117
pro vyhledávání: '"Sivaramakrishnan Lakshmivarahan"'
Publikováno v:
Atmosphere, Vol 13, Iss 10, p 1647 (2022)
Data assimilation in chaotic regimes is challenging, and among the challenging aspects is placement of observations to induce convexity of the cost function in the space of control. This problem is examined by using Saltzman’s spectral model of con
Externí odkaz:
https://doaj.org/article/edeb0e5eea0b4266bee3d3d59e207167
Publikováno v:
Journal of Marine Science and Engineering, Vol 4, Iss 4, p 73 (2016)
The Forward Sensitivity Method (FSM) is applied to a GWCE-based shallow water model to analyze the sensitivity to the numerical parameter, G, that determines the balance between the wave and primitive forms of the continuity equation. Results show th
Externí odkaz:
https://doaj.org/article/7cddd7c04b114dae9e06224eb18a82fd
Autor:
Matthew J. Pranter, Kurt J. Marfurt, Thang Ha, Sivaramakrishnan Lakshmivarahan, David Lubo-Robles
Publikováno v:
Interpretation. 9:T421-T441
Machine learning (ML) algorithms, such as principal component analysis, independent component analysis, self-organizing maps, and artificial neural networks, have been used by geoscientists to not only accelerate the interpretation of their data, but
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c209b6153a3fe09bc8ebd3385f38d459
https://doi.org/10.1190/int-2020-0102.1
https://doi.org/10.1190/int-2020-0102.1
Publikováno v:
Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. IV) ISBN: 9783030777210
A method of data assimilation that is complementary to traditional 4D-Var (4D-Var) has been developed. 4D-Var has appealed to scientists because of the efficiency with which it determines the cost function gradient with respect to control and availab
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7d402d2505be2b88f01a0ba821773aed
https://doi.org/10.1007/978-3-030-77722-7_9
https://doi.org/10.1007/978-3-030-77722-7_9
Publikováno v:
NODYCON Conference Proceedings Series ISBN: 9783030811693
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b21b7b5a79abe0b7af35e8f97663b834
https://doi.org/10.1007/978-3-030-81170-9_9
https://doi.org/10.1007/978-3-030-81170-9_9
Publikováno v:
Journal of the Atmospheric Sciences. 76:1587-1608
In Saltzman’s seminal paper from 1962, the author developed a framework based on the spectral method for the analysis of the solution to the classical Rayleigh–Bénard convection problem using low-order models (LOMs), LOM (n) with n ≤ 52. By wa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9d2e7b251d1efa19cedc0fbddfb9eb7c
https://doi.org/10.1175/jas-d-17-0344.1
https://doi.org/10.1175/jas-d-17-0344.1
Autor:
Sivaramakrishnan Lakshmivarahan, Seyedehnafiseh Mirniaharikandehei, Gopichandh Danala, Bin Zheng, Morteza Heidari
Publikováno v:
Medical Imaging 2021: Computer-Aided Diagnosis.
Developing radiomic based machine learning models has drawn considerable attention in recent years. However, identifying a small and optimal feature vector to build a robust machine learning models has always been a controversial issue. In this study
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::57f6194df44bcc1056621c553572601d
https://doi.org/10.1117/12.2580732
https://doi.org/10.1117/12.2580732
Autor:
Hung N. Pham, Morteza Heidari, Sivaramakrishnan Lakshmivarahan, Seyedehnafiseh Mirniaharikandehei, Abolfazl Zargari Khuzani, Gopichandh Danala, Bin Zheng
Publikováno v:
Medical Imaging 2021: Imaging Informatics for Healthcare, Research, and Applications.
The purpose of this study is to develop a machine learning model with the optimal features computed from mammograms to classify suspicious regions as benign and malignant. To this aim, we investigate the benefits of implementing a machine learning ap
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::528f1df383de652212c0424e8e49c21c
https://doi.org/10.1117/12.2580944
https://doi.org/10.1117/12.2580944
Autor:
Sivaramakrishnan Lakshmivarahan, Gopichandh Danala, Seyedehnafiseh Mirniaharikandehei, Morteza Heidari, Bin Zheng
Publikováno v:
Comput Methods Programs Biomed
Background and Objective: Non-invasively predicting the risk of cancer metastasis before surgery plays an essential role in determining optimal treatment methods for cancer patients (including who can benefit from neoadjuvant chemotherapy). Although
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1dadf8966940be86396b284b3444ca3c
https://europepmc.org/articles/PMC7920928/
https://europepmc.org/articles/PMC7920928/
Autor:
Sivaramakrishnan Lakshmivarahan, Seyedehnafiseh Mirniaharikandehei, Hong Liu, Sai Kiran Reddy Maryada, Morteza Heidari, Gopichandh Danala, Bin Zheng
Publikováno v:
IEEE Trans Biomed Eng
Machine learning is widely used in developing computer-aided diagnosis (CAD) schemes of medical images. However, CAD usually computes large number of image features from the targeted regions, which creates a challenge of how to identify a small and o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1e8ad65c42e2081a84685f88b2126abf
http://arxiv.org/abs/2009.09937
http://arxiv.org/abs/2009.09937