scholarly journals Adaptable Two-Dimension Sliding Windows on NVIDIA GPUs with Runtime Compilation

2011 ◽  
Author(s):  
Nicholas Moore ◽  
Miriam Leeser ◽  
Laurie Smith King
Keyword(s):  
Sliding Windows ◽  
Two Dimension

Spectroholoellipsometer with Light Scattering and Reflecting From the Optically Uniaxial Two-Dimension Crystal

2013 ◽  
Vol 2 (4) ◽  
pp. 95-107
Author(s):  
M. Ali ◽  
◽  
A. P. Kiryanov ◽  
V. I. Kovalev ◽  
V. I. Pustovoit ◽  
...  
Keyword(s):  
Light Scattering ◽  
Two Dimension

Anomaly Detection via Mining Numerical Workflow Relations from Logs

2020 ◽  
Author(s):  
Bo Zhang ◽  
Hongyu Zhang ◽  
Pablo Moscato
Keyword(s):  
Distributed Systems ◽  
Anomaly Detection ◽  
Text Messages ◽  
Distributed File System ◽  
Log Data ◽  
Sliding Windows ◽  
Novel Approach ◽  
Hadoop Distributed File System ◽  
Blue Gene ◽  
Online Anomaly Detection

<div>Complex software intensive systems, especially distributed systems, generate logs for troubleshooting. The logs are text messages recording system events, which can help engineers determine the system's runtime status. This paper proposes a novel approach named ADR (stands for Anomaly Detection by workflow Relations) that employs matrix nullspace to mine numerical relations from log data. The mined relations can be used for both offline and online anomaly detection and facilitate fault diagnosis. We have evaluated ADR on log data collected from two distributed systems, HDFS (Hadoop Distributed File System) and BGL (IBM Blue Gene/L supercomputers system). ADR successfully mined 87 and 669 numerical relations from the logs and used them to detect anomalies with high precision and recall. For online anomaly detection, ADR employs PSO (Particle Swarm Optimization) to find the optimal sliding windows' size and achieves fast anomaly detection.</div><div>The experimental results confirm that ADR is effective for both offline and online anomaly detection. </div>

Theory and application of two-dimension viscous hydraulic design of the ultra-low specific-speed centrifugal pump

2019 ◽  
Vol 234 (1) ◽  
pp. 58-71 ◽  
Author(s):  
Cong Wang ◽  
Yongxue Zhang ◽  
Hucan Hou ◽  
Zhiyi Yuan
Keyword(s):  
Boundary Layer ◽  
Centrifugal Pump ◽  
Diagnostic Model ◽  
Two Dimension ◽  
Cavitation Performance ◽  
Hydraulic Design ◽  
Displacement Thickness ◽  
Low Specific Speed ◽  
Specific Speed ◽  
Low Efficiency

Low efficiency and bad cavitation performance restrict the development of the ultra-low specific-speed centrifugal pump (ULSSCP). In this research, combined turbulent boundary layer theory with two-dimension design and two-dimension viscous hydraulic design method has been proposed to redesign a ULSSCP. Through the solution of the displacement thickness in the boundary layer, a less curved blade profile with a larger outlet angle was obtained. Then the hydraulic and cavitation performance of the reference pump and the designed pump were numerically studied. The comparison of performance of the reference pump calculated by the numerical and experimental results revealed a better agreement. Research shows that the average hydraulic efficiency and head of the designed pump improve by 2.9% and 3.3%, respectively. Besides, the designed pump has a better cavitation performance. Finally, through the internal flow analysis with entropy production diagnostic model, a 24.8% drop in head loss occurred in the designed pump.

A new visual/inertial integrated navigation algorithm based on sliding-window factor graph optimisation

2020 ◽  
pp. 1-17
Author(s):  
Haiying Liu ◽  
Jingqi Wang ◽  
Jianxin Feng ◽  
Xinyao Wang
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Prior Information ◽  
Sliding Window ◽  
Factor Graph ◽  
Navigation Systems ◽  
Integrated Navigation ◽  
Sliding Windows ◽  
Navigation Algorithm ◽  
Almost All

Abstract Visual–Inertial Navigation Systems (VINS) plays an important role in many navigation applications. In order to improve the performance of VINS, a new visual/inertial integrated navigation method, named Sliding-Window Factor Graph optimised algorithm with Dynamic prior information (DSWFG), is proposed. To bound computational complexity, the algorithm limits the scale of data operations through sliding windows, and constructs the states to be optimised in the window with factor graph; at the same time, the prior information for sliding windows is set dynamically to maintain interframe constraints and ensure the accuracy of the state estimation after optimisation. First, the dynamic model of vehicle and the observation equation of VINS are introduced. Next, as a contrast, an Invariant Extended Kalman Filter (InEKF) is constructed. Then, the DSWFG algorithm is described in detail. Finally, based on the test data, the comparison experiments of Extended Kalman Filter (EKF), InEKF and DSWFG algorithms in different motion scenes are presented. The results show that the new method can achieve superior accuracy and stability in almost all motion scenes.

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