scholarly journals Three dimensional compressed sensing for wireless networks-based multiple node localization in multi-floor buildings

2015 ◽  
Vol 16 (13) ◽  
pp. 1837-1850 ◽  
Author(s):  
Mohamed Amine Abid ◽  
Soumaya Cherkaoui
Keyword(s):  
Wireless Networks ◽  
Compressed Sensing ◽  
Three Dimensional ◽  
Node Localization ◽  
Multiple Node

scholarly journals Neighbor discovery for wireless networks via compressed sensing

2013 ◽  
Vol 70 (7-8) ◽  
pp. 457-471 ◽  
Author(s):  
Lei Zhang ◽  
Jun Luo ◽  
Dongning Guo
Keyword(s):  
Wireless Networks ◽  
Compressed Sensing ◽  
Neighbor Discovery

Intelligent Three-dimensional Node Localization Algorithm Using Dynamic Path Planning

2021 ◽  
Vol 14 ◽  
Author(s):  
Songhao Jia ◽  
Cai Yang ◽  
Xing Chen ◽  
Yan Liu ◽  
Fangfang Li
Keyword(s):  
Path Planning ◽  
Dynamic Stiffness ◽  
Three Dimensional ◽  
Localization Algorithm ◽  
Node Localization ◽  
Positioning Accuracy ◽  
Dynamic Path Planning ◽  
Anchor Nodes ◽  
Simulation Results ◽  
Dynamic Path

Background: In the applications of wireless sensor network technology, three-dimensional node location technology is crucial. The process of node localization has some disadvantages, such as the uneven distribution of anchor nodes and the high cost of the network. Therefore, the mobile anchor nodes are introduced to effectively solve accurate positioning. Objective: Considering the estimated distance error, the received signal strength indication technology is used to optimize the measurement of the distance. At the same time, dynamic stiffness planning is introduced to increase virtual anchor nodes. Moreover, the bird swarm algorithm is also used to solve the optimal location problem of nodes. Method: Firstly, the dynamic path is introduced to increase the number of virtual anchor nodes. At the same time, the improved RSSI distance measurement technology is introduced to the node localization. Then, an intelligent three-dimensional node localization algorithm based on dynamic path planning is proposed. Finally, the proposed algorithm is compared with similar algorithms through simulation experiments. Results: Simulation results show that the node coordinates obtained by the proposed algorithm are more accurate, and the node positioning accuracy is improved. The execution time and network coverage of the algorithm are better than similar algorithms. Conclusion: The proposed algorithm significantly improves the accuracy of node positioning. However, the traffic of the algorithm is increased. A little increase in traffic in exchange for positioning accuracy is worthy of recognition. The simulation results show that the proposed algorithm is robust and can be implemented and promoted in the future.

Super Resolution Optic Three-dimensional Imaging Based on Compressed Sensing

2015 ◽  
Vol 44 (3) ◽  
pp. 328001
Author(s):  
王锋 WANG Feng ◽  
罗建军 LUO Jian-jun ◽  
唐兴佳 TANG Xing-jia ◽  
李立波 LI Li-bo ◽  
胡炳樑 HU Bin-liang
Keyword(s):  
Compressed Sensing ◽  
Three Dimensional ◽  
Super Resolution ◽  
Three Dimensional Imaging

scholarly journals 3D Dixon water-fat LGE imaging with image navigator and compressed sensing in cardiac MRI

2020 ◽  
Author(s):  
Martin Georg Zeilinger ◽  
Marco Wiesmüller ◽  
Christoph Forman ◽  
Michaela Schmidt ◽  
Camila Munoz ◽  
...  
Keyword(s):  
High Resolution ◽  
Image Quality ◽  
Compressed Sensing ◽  
Cardiac Mri ◽  
Three Dimensional ◽  
Fat Suppression ◽  
Diagnostic Confidence ◽  
Pericardial Disease ◽  
Scan Time ◽  
Wilcoxon Rank Sum Test

Abstract Objectives To evaluate an image-navigated isotropic high-resolution 3D late gadolinium enhancement (LGE) prototype sequence with compressed sensing and Dixon water-fat separation in a clinical routine setting. Material and methods Forty consecutive patients scheduled for cardiac MRI were enrolled prospectively and examined with 1.5 T MRI. Overall subjective image quality, LGE pattern and extent, diagnostic confidence for detection of LGE, and scan time were evaluated and compared to standard 2D LGE imaging. Robustness of Dixon fat suppression was evaluated for 3D Dixon LGE imaging. For statistical analysis, the non-parametric Wilcoxon rank sum test was performed. Results LGE was rated as ischemic in 9 patients and non-ischemic in 11 patients while it was absent in 20 patients. Image quality and diagnostic confidence were comparable between both techniques (p = 0.67 and p = 0.66, respectively). LGE extent with respect to segmental or transmural myocardial enhancement was identical between 2D and 3D (water-only and in-phase). LGE size was comparable (3D 8.4 ± 7.2 g, 2D 8.7 ± 7.3 g, p = 0.19). Good or excellent fat suppression was achieved in 93% of the 3D LGE datasets. In 6 patients with pericarditis, the 3D sequence with Dixon fat suppression allowed for a better detection of pericardial LGE. Scan duration was significantly longer for 3D imaging (2D median 9:32 min vs. 3D median 10:46 min, p = 0.001). Conclusion The 3D LGE sequence provides comparable LGE detection compared to 2D imaging and seems to be superior in evaluating the extent of pericardial involvement in patients suspected with pericarditis due to the robust Dixon fat suppression. Key Points • Three-dimensional LGE imaging provides high-resolution detection of myocardial scarring. • Robust Dixon water-fat separation aids in the assessment of pericardial disease. • The 2D image navigator technique enables 100% respiratory scan efficacy and permits predictable scan times.

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