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pro vyhledávání: '"Chengshuo Xu"'
Autor:
Panjing Guo, Xiajing Zhang, Haoran Xu, Ruiqin Wang, Yumin Li, Chengshuo Xu, Yu Yang, Linlin Zhang, Roger Adams, Jia Han, Jie Lyu
Publikováno v:
Frontiers in Bioengineering and Biotechnology, Vol 12 (2024)
ObjectiveThis study aims to investigate the plantar biomechanics of healthy young males as they descend a single transition step from varying heights.MethodsThirty healthy young males participated the experiment using the F-scan insole plantar pressu
Externí odkaz:
https://doaj.org/article/495ea65b0e2d4312a8fb2a0fc7a81edf
Autor:
Yanfeng Huang, Wanjuan Li, Xiaojian Shi, Wenchao Wang, Chengshuo Xu, Roger David Adams, Jie Lyu, Jia Han, Yaohua He
Publikováno v:
Frontiers in Bioengineering and Biotechnology, Vol 12 (2024)
Background: Knee osteoarthritis (KOA) is a common musculoskeletal condition that affects dynamic balance control and increases the risk of falling during walking. However, the mechanisms underlying this are still unclear. Diminished ankle propriocept
Externí odkaz:
https://doaj.org/article/346f90801dce474691259d9d6d004e6f
Publikováno v:
Journal of Parallel and Distributed Computing. 164:12-27
Publikováno v:
ACM SIGOPS Operating Systems Review. 55:11-20
While much of the research on graph analytics over large power-law graphs has focused on developing algorithms for evaluating a single global graph query, in practice we may be faced with a stream of queries. We observe that, due to their global natu
Publikováno v:
EuroSys
For compute-intensive iterative queries over a streaming graph, it is critical to evaluate the queries continuously and incrementally for best efficiency. However, the existing incremental graph processing requires a priori knowledge of the query (e.
Publikováno v:
IEEE BigData
Simultaneous evaluating a batch of iterative graph queries on a distributed system enables amortization of high communication and computation costs across multiple queries. As demonstrated by our prior work on MultiLyra [BigData’19], batched graph
Publikováno v:
HiPC
Graph processing frameworks are typically designed to optimize the evaluation of a single graph query. However, in practice, we often need to respond to multiple graph queries, either from different users or from a single user performing a complex an
Publikováno v:
ASPLOS
Frequently used parallel iterative graph analytics algorithms are computationally expensive. However, researchers have observed that applications often require point-to-point versions of these analytics algorithms that are less demanding. In this pap