Dynamics of Constrained Systems Based on Mass-Orthogonal Projections

Author(s):  
M. Sofer ◽  
D. Bach ◽  
H. Brauchli
2020 ◽  
Vol 124 (5) ◽  
Author(s):  
S. C. Morampudi ◽  
A. Chandran ◽  
C. R. Laumann
Keyword(s):  

Author(s):  
Paolo Dulio ◽  
Andrea Frosini ◽  
Simone Rinaldi ◽  
Lama Tarsissi ◽  
Laurent Vuillon

AbstractA remarkable family of discrete sets which has recently attracted the attention of the discrete geometry community is the family of convex polyominoes, that are the discrete counterpart of Euclidean convex sets, and combine the constraints of convexity and connectedness. In this paper we study the problem of their reconstruction from orthogonal projections, relying on the approach defined by Barcucci et al. (Theor Comput Sci 155(2):321–347, 1996). In particular, during the reconstruction process it may be necessary to expand a convex subset of the interior part of the polyomino, say the polyomino kernel, by adding points at specific positions of its contour, without losing its convexity. To reach this goal we consider convexity in terms of certain combinatorial properties of the boundary word encoding the polyomino. So, we first show some conditions that allow us to extend the kernel maintaining the convexity. Then, we provide examples where the addition of one or two points causes a loss of convexity, which can be restored by adding other points, whose number and positions cannot be determined a priori.


2021 ◽  
Vol 51 (3) ◽  
Author(s):  
Maurice A. de Gosson

AbstractWe define and study the notion of quantum polarity, which is a kind of geometric Fourier transform between sets of positions and sets of momenta. Extending previous work of ours, we show that the orthogonal projections of the covariance ellipsoid of a quantum state on the configuration and momentum spaces form what we call a dual quantum pair. We thereafter show that quantum polarity allows solving the Pauli reconstruction problem for Gaussian wavefunctions. The notion of quantum polarity exhibits a strong interplay between the uncertainty principle and symplectic and convex geometry and our approach could therefore pave the way for a geometric and topological version of quantum indeterminacy. We relate our results to the Blaschke–Santaló inequality and to the Mahler conjecture. We also discuss the Hardy uncertainty principle and the less-known Donoho–Stark principle from the point of view of quantum polarity.


2021 ◽  
Vol 11 (13) ◽  
pp. 5908
Author(s):  
Raquel Cervigón ◽  
Brian McGinley ◽  
Darren Craven ◽  
Martin Glavin ◽  
Edward Jones

Although Atrial Fibrillation (AF) is the most frequent cause of cardioembolic stroke, the arrhythmia remains underdiagnosed, as it is often asymptomatic or intermittent. Automated detection of AF in ECG signals is important for patients with implantable cardiac devices, pacemakers or Holter systems. Such resource-constrained systems often operate by transmitting signals to a central server where diagnostic decisions are made. In this context, ECG signal compression is being increasingly investigated and employed to increase battery life, and hence the storage and transmission efficiency of these devices. At the same time, the diagnostic accuracy of AF detection must be preserved. This paper investigates the effects of ECG signal compression on an entropy-based AF detection algorithm that monitors R-R interval regularity. The compression and AF detection algorithms were applied to signals from the MIT-BIH AF database. The accuracy of AF detection on reconstructed signals is evaluated under varying degrees of compression using the state-of-the-art Set Partitioning In Hierarchical Trees (SPIHT) compression algorithm. Results demonstrate that compression ratios (CR) of up to 90 can be obtained while maintaining a detection accuracy, expressed in terms of the area under the receiver operating characteristic curve, of at least 0.9. This highlights the potential for significant energy savings on devices that transmit/store ECG signals for AF detection applications, while preserving the diagnostic integrity of the signals, and hence the detection performance.


Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3850
Author(s):  
Bastien Vincke ◽  
Sergio Rodriguez Rodriguez Florez ◽  
Pascal Aubert

Emerging technologies in the context of Autonomous Vehicles (AV) have drastically evolved the industry’s qualification requirements. AVs incorporate complex perception and control systems. Teaching the associated skills that are necessary for the analysis of such systems becomes a very difficult process and existing solutions do not facilitate learning. In this study, our efforts are devoted to proposingan open-source scale model vehicle platform that is designed for teaching the fundamental concepts of autonomous vehicles technologies that are adapted to undergraduate and technical students. The proposed platform is as realistic as possible in order to present and address all of the fundamental concepts that are associated with AV. It includes all on-board components of a stand-alone system, including low and high level functions. Such functionalities are detailed and a proof of concept prototype is presented. A set of experiments is carried out, and the results obtained using this prototype validate the usability of the model for the analysis of time- and energy-constrained systems, as well as distributed embedded perception systems.


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