Tolerating correlated failures for generalized Cartesian distributions via bipartite matching

2011 ◽  
Author(s):  
Nawab Ali ◽  
Sriram Krishnamoorthy ◽  
Mahantesh Halappanavar ◽  
Jeff Daily
Keyword(s):  
Bipartite Matching ◽  
Correlated Failures

scholarly journals A Two-Stage Data Association Approach for 3D Multi-Object Tracking

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 2894
Author(s):  
Minh-Quan Dao ◽  
Vincent Frémont
Keyword(s):  
Object Detection ◽  
Object Tracking ◽  
Moving Objects ◽  
Data Association ◽  
Autonomous Driving ◽  
Tracking Accuracy ◽  
Two Stage ◽  
Bipartite Matching ◽  
3D Object ◽  
3D Object Detection

Multi-Object Tracking (MOT) is an integral part of any autonomous driving pipelines because it produces trajectories of other moving objects in the scene and predicts their future motion. Thanks to the recent advances in 3D object detection enabled by deep learning, track-by-detection has become the dominant paradigm in 3D MOT. In this paradigm, a MOT system is essentially made of an object detector and a data association algorithm which establishes track-to-detection correspondence. While 3D object detection has been actively researched, association algorithms for 3D MOT has settled at bipartite matching formulated as a Linear Assignment Problem (LAP) and solved by the Hungarian algorithm. In this paper, we adapt a two-stage data association method which was successfully applied to image-based tracking to the 3D setting, thus providing an alternative for data association for 3D MOT. Our method outperforms the baseline using one-stage bipartite matching for data association by achieving 0.587 Average Multi-Object Tracking Accuracy (AMOTA) in NuScenes validation set and 0.365 AMOTA (at level 2) in Waymo test set.

scholarly journals SURF: identifying and allocating resources during Out-of-Hospital Cardiac Arrest

2020 ◽  
Vol 20 (S11) ◽  
Author(s):  
Gaurav Rao ◽  
Salimur Choudhury ◽  
Pawan Lingras ◽  
David Savage ◽  
Vijay Mago
Keyword(s):  
Cardiac Arrest ◽  
Linear Programming ◽  
Integer Linear Programming ◽  
Processing Time ◽  
Emergency Services ◽  
Linear Programming Method ◽  
Bipartite Matching ◽  
Matching Algorithm ◽  
Hospital Cardiac Arrest ◽  
Cardiac Emergency

Abstract Background When an Out-of-Hospital Cardiac Arrest (OHCA) incident is reported to emergency services, the 911 agent dispatches Emergency Medical Services to the location and activates responder network system (RNS), if the option is available. The RNS notifies all the registered users in the vicinity of the cardiac arrest patient by sending alerts to their mobile devices, which contains the location of the emergency. The main objective of this research is to find the best match between the user who could support the OHCA patient. Methods For performing matching among the user and the AEDs, we used Bipartite Matching and Integer Linear Programming. However, these approaches take a longer processing time; therefore, a new method Preprocessed Integer Linear Programming is proposed that solves the problem faster than the other two techniques. Results The average processing time for the experimentation data was   1850 s using Bipartite matching,   32 s using the Integer Linear Programming and  2 s when using the Preprocessed Integer Linear Programming method. The proposed algorithm performs matching among users and AEDs faster than the existing matching algorithm and thus allowing it to be used in the real world. Conclusion: This research proposes an efficient algorithm that will allow matching of users with AED in real-time during cardiac emergency. Implementation of this system can help in reducing the time to resuscitate the patient.

scholarly journals A product form for the general stochastic matching model

2021 ◽  
Vol 58 (2) ◽  
pp. 449-468
Author(s):  
Pascal Moyal ◽  
Ana Bušić ◽  
Jean Mairesse
Keyword(s):  
Stationary Distribution ◽  
Product Form ◽  
Necessary Condition ◽  
Matching Model ◽  
Bipartite Matching ◽  
Compatibility Graph ◽  
Stochastic Matching ◽  
Dynamic Reversibility ◽  
Original Dynamic ◽  
Do So

AbstractWe consider a stochastic matching model with a general compatibility graph, as introduced by Mairesse and Moyal (2016). We show that the natural necessary condition of stability of the system is also sufficient for the natural ‘first-come, first-matched’ matching policy. To do so, we derive the stationary distribution under a remarkable product form, by using an original dynamic reversibility property related to that of Adan, Bušić, Mairesse, and Weiss (2018) for the bipartite matching model.

scholarly journals Benchmarking Quantum Annealing Against “Hard” Instances of the Bipartite Matching Problem

2021 ◽  
Vol 2 (2) ◽  
Author(s):  
Daniel Vert ◽  
Renaud Sirdey ◽  
Stéphane Louise
Keyword(s):  
Simulated Annealing ◽  
Polynomial Time ◽  
Optimal Solution ◽  
Quantum Computers ◽  
Quantum Annealing ◽  
Maximum Cardinality ◽  
Matching Problem ◽  
Bipartite Matching ◽  
Wave Device ◽  
D Wave

AbstractThis paper experimentally investigates the behavior of analog quantum computers as commercialized by D-Wave when confronted to instances of the maximum cardinality matching problem which is specifically designed to be hard to solve by means of simulated annealing. We benchmark a D-Wave “Washington” (2X) with 1098 operational qubits on various sizes of such instances and observe that for all but the most trivially small of these it fails to obtain an optimal solution. Thus, our results suggest that quantum annealing, at least as implemented in a D-Wave device, falls in the same pitfalls as simulated annealing and hence provides additional evidences suggesting that there exist polynomial-time problems that such a machine cannot solve efficiently to optimality. Additionally, we investigate the extent to which the qubits interconnection topologies explains these latter experimental results. In particular, we provide evidences that the sparsity of these topologies which, as such, lead to QUBO problems of artificially inflated sizes can partly explain the aforementioned disappointing observations. Therefore, this paper hints that denser interconnection topologies are necessary to unleash the potential of the quantum annealing approach.

scholarly journals Optimal Multiculture Network Design for Maximizing Resilience in the Face of Multiple Correlated Failures

2019 ◽  
Vol 9 (11) ◽  
pp. 2256
Author(s):  
Yasmany Prieto ◽  
Nicolás Boettcher ◽  
Silvia Elena Restrepo ◽  
Jorge E. Pezoa
Keyword(s):  
Network Design ◽  
Optimization Problems ◽  
Current Data ◽  
Sequential Optimization ◽  
Node Degree ◽  
Network Resilience ◽  
Correlated Failures ◽  
The Face ◽  
Network Operation ◽  
Network Topologies

Current data networks are highly homogeneous because of management, economic, and interoperability reasons. This technological homogeneity introduces shared risks, where correlated failures may entirely disrupt the network operation and impair multiple nodes. In this paper, we tackle the problem of improving the resilience of homogeneous networks, which are affected by correlated node failures, through optimal multiculture network design. Correlated failures regarded here are modeled by SRNG events. We propose three sequential optimization problems for maximizing the network resilience by selecting as different node technologies, which do not share risks, and placing such nodes in a given topology. Results show that in the 75% of real-world network topologies analyzed here, our optimal multiculture design yields networks whose probability that a pair of nodes, chosen at random, are connected is 1, i.e., its ATTR metric is 1. To do so, our method efficiently trades off the network heterogeneity, the number of nodes per technology, and their clustered location in the network. In the remaining 25% of the topologies, whose average node degree was less than 2, such probability was at least 0.7867. This means that both multiculture design and topology connectivity are necessary to achieve network resilience.

scholarly journals Instance Sequence Queries for Video Instance Segmentation with Transformers

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4507
Author(s):  
Zhujun Xu ◽  
Damien Vivet
Keyword(s):  
Data Association ◽  
Video Clip ◽  
Complex Data ◽  
Training Procedure ◽  
Post Processing ◽  
Bipartite Matching ◽  
Frame Method ◽  
Memory Constraints ◽  
Instance Segmentation

Existing methods for video instance segmentation (VIS) mostly rely on two strategies: (1) building a sophisticated post-processing to associate frame level segmentation results and (2) modeling a video clip as a 3D spatial-temporal volume with a limit of resolution and length due to memory constraints. In this work, we propose a frame-to-frame method built upon transformers. We use a set of queries, called instance sequence queries (ISQs), to drive the transformer decoder and produce results at each frame. Each query represents one instance in a video clip. By extending the bipartite matching loss to two frames, our training procedure enables the decoder to adjust the ISQs during inference. The consistency of instances is preserved by the corresponding order between query slots and network outputs. As a result, there is no need for complex data association. On TITAN Xp GPU, our method achieves a competitive 34.4% mAP at 33.5 FPS with ResNet-50 and 35.5% mAP at 26.6 FPS with ResNet-101 on the Youtube-VIS dataset.

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