Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Zhenhuan Gong"'
Autor:
Wenjing Xu, Xiong Yang, Yikang Li, Guihua Jiang, Sen Jia, Zhenhuan Gong, Yufei Mao, Shuheng Zhang, Yanqun Teng, Jiayu Zhu, Qiang He, Liwen Wan, Dong Liang, Ye Li, Zhanli Hu, Hairong Zheng, Xin Liu, Na Zhang
Publikováno v:
Frontiers in Neuroscience, Vol 16 (2022)
PurposeTo develop and evaluate an automatic segmentation method of arterial vessel walls and plaques, which is beneficial for facilitating the arterial morphological quantification in magnetic resonance vessel wall imaging (MRVWI).MethodsMRVWI images
Externí odkaz:
https://doaj.org/article/b48f845d12d94c6f961a91dc018388c4
Autor:
John Jenkins, Kanchana Padmanabhan, Scott Klasky, Isha Arkatkar, Robert Ross, Neil Shah, Zhenhuan Gong, Sriram Lakshminarasimhan, Eric R. Schendel, Nagiza F. Samatova
Publikováno v:
Data-Intensive Science
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7309569f1023826b52055ab8fb654e43
https://doi.org/10.1201/b14935-13
https://doi.org/10.1201/b14935-13
Publikováno v:
ICIA
In this paper, an one-click method for coronary artery ostia extraction from computed tomography angiography (CTA) scans is presented and a strict definition of coronary artery ostia in geometric graphics is given. Due to the presence of diverse anat
Autor:
Eric R. Schendel, John Jenkins, David A. Boyuka, Nagiza F. Samatova, Xiaocheng Zou, Norbert Podhorszki, Qing Liu, Zhenhuan Gong, Sriram Lakshminarasimhan, Scott Klasky
Publikováno v:
CCGRID
Though an abundance of novel "data transformation" technologies have been developed (such as compression, level-of-detail, layout optimization, and indexing), there remains a notable gap in the adoption of such services by scientific applications. In
Autor:
Qing Liu, Nagiza F. Samatova, Scott Klasky, Xiaocheng Zou, Norbert Podhorszki, David A. Boyuka, Zhenhuan Gong, Xiaosong Ma
Publikováno v:
CCGRID
The size and scope of cutting-edge scientific simulations are growing much faster than the I/O and storage capabilities of their run-time environments. The growing gap is exacerbated by exploratory, data-intensive analytics, such as querying simulati
Autor:
Saurabh V. Pendse, Robert Ross, John Jenkins, Qing Liu, Eric R. Schendel, Zhenhuan Gong, Scott Klasky, Nagiza F. Samatova, Sriram Lakshminarasimhan, Hemanth Kolla, Jackie Chen, David A. Boyuka
Publikováno v:
HPDC
Current peta-scale data analytics frameworks suffer from a significant performance bottleneck due to an imbalance between their enormous computational power and limited I/O bandwidth. Using data compression schemes to reduce the amount of I/O activit
Autor:
S. Ethier, Jackie Chen, Hemanth Kolla, Nagiza F. Samatova, Robert Ross, John Jenkins, Sriram Lakshminarasimhan, Zhenhuan Gong, Scott Klasky
Publikováno v:
IPDPS
The size and scope of cutting-edge scientific simulations are growing much faster than the I/O subsystems of their runtime environments, not only making I/O the primary bottleneck, but also consuming space that pushes the storage capacities of many c
Autor:
Ye Jin, Jackie Chen, Neil Shah, Hemanth Kolla, S. Ethier, Karen Schuchardt, Sriram Lakshminarasimhan, Seung-Hoe Ku, Robert Latham, Robert Ross, Nagiza F. Samatova, Scott Klasky, Choong Chang, Zhenhuan Gong
Publikováno v:
ICDM
The growing gap between the massive amounts of data generated by petascale scientific simulation codes and the capability of system hardware and software to effectively analyze this data necessitates data reduction. Yet, the increasing data complexit
Autor:
Choong-Seock Chang, Robert Ross, Isha Arkatkar, Stephane Ethier, Jackie Chen, Zhenhuan Gong, Robert Latham, John Jenkins, Sriram Lakshminarasimhan, Hemanth Kolla, Scott Klasky, Seung-Hoe Ku, Nagiza F. Samatova
Publikováno v:
SC
Efficient analytics of scientific data from extreme-scale simulations is quickly becoming a top-notch priority. The increasing simulation output data sizes demand for a paradigm shift in how analytics is conducted. In this paper, we argue that query-
Autor:
Zhenhuan Gong, Xiaohui Gu
Publikováno v:
MASCOTS
To reduce cloud system resource cost, application consolidation is a must. In this paper, we present a novel pattern driven application consolidation (PAC) system to achieve efficient resource sharing in virtualized cloud computing infrastructures. P