scholarly journals Semi-device-independent certification of multiple unsharpness parameters through sequential measurements

2021 ◽  
Vol 104 (6) ◽  
Author(s):  
Sumit Mukherjee ◽  
A. K. Pan
Keyword(s):  
Sequential Measurements

scholarly journals Sequential measurements of conjugate observables

2011 ◽  
Vol 44 (28) ◽  
pp. 285304 ◽  
Author(s):  
Claudio Carmeli ◽  
Teiko Heinosaari ◽  
Alessandro Toigo
Keyword(s):  
Sequential Measurements

Sequential measurements of the tibial plateau angle in large-breed, growing dogs

2004 ◽  
Vol 65 (4) ◽  
pp. 513-518 ◽  
Author(s):  
Jacob W. Odders ◽  
Carl R. Jessen ◽  
Alan J. Lipowitz
Keyword(s):  
Tibial Plateau ◽  
Sequential Measurements

scholarly journals Sequential decoding of a general classical-quantum channel

2013 ◽  
Vol 469 (2157) ◽  
pp. 20130259 ◽  
Author(s):  
Mark M. Wilde
Keyword(s):  
Quantum Measurement ◽  
Failure Probability ◽  
High Probability ◽  
Polar Codes ◽  
Sequential Decoding ◽  
Single Instance ◽  
Small Failure Probability ◽  
Classical Quantum ◽  
Union Bound ◽  
Sequential Measurements

Because a quantum measurement generally disturbs the state of a quantum system, one might think that it should not be possible for a sender and receiver to communicate reliably when the receiver performs a large number of sequential measurements to determine the message of the sender. We show here that this intuition is not true, by demonstrating that a sequential decoding strategy works well even in the most general ‘one-shot’ regime, where we are given a single instance of a channel and wish to determine the maximal number of bits that can be communicated up to a small failure probability. This result follows by generalizing a non-commutative union bound to apply for a sequence of general measurements. We also demonstrate two ways in which a receiver can recover a state close to the original state after it has been decoded by a sequence of measurements that each succeed with high probability. The second of these methods will be useful in realizing an efficient decoder for fully quantum polar codes, should a method ever be found to realize an efficient decoder for classical-quantum polar codes.

Dynamic Mode Decomposition and Its Variants

2021 ◽  
Vol 54 (1) ◽  
Author(s):  
Peter J. Schmid
Keyword(s):  
Dynamic Mode Decomposition ◽  
Annual Review ◽  
Dynamic Mode ◽  
Publication Date ◽  
Fluid Systems ◽  
Mode Decomposition ◽  
Dimensionality Reduction Technique ◽  
Essential Components ◽  
Complex Fluid ◽  
Sequential Measurements

Dynamic mode decomposition (DMD) is a factorization and dimensionality reduction technique for data sequences. In its most common form, it processes high-dimensional sequential measurements, extracts coherent structures, isolates dynamic behavior, and reduces complex evolution processes to their dominant features and essential components. The decomposition is intimately related to Koopman analysis and, since its introduction, has spawned various extensions, generalizations, and improvements. It has been applied to numerical and experimental data sequences taken from simple to complex fluid systems and has also had an impact beyond fluid dynamics in, for example, video surveillance, epidemiology, neurobiology, and financial engineering. This review focuses on the practical aspects of DMD and its variants, as well as on its usage and characteristics as a quantitative tool for the analysis of complex fluid processes. Expected final online publication date for the Annual Review of Fluid Mechanics, Volume 54 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

scholarly journals A nonlinear updating algorithm captures suboptimal inference in the presence of signal-dependent noise

2018 ◽  
Author(s):  
Seth W. Egger ◽  
Mehrdad Jazayeri
Keyword(s):  
Probability Distributions ◽  
Nonlinear Function ◽  
Alternative View ◽  
Time Interval ◽  
Prior Beliefs ◽  
Optimal Behavior ◽  
Multiple Measurements ◽  
The Brain ◽  
Full Probability ◽  
Sequential Measurements

AbstractBayesian models of behavior have advanced the idea that humans combine prior beliefs and sensory observations to minimize uncertainty. How the brain implements Bayes-optimal inference, however, remains poorly understood. Simple behavioral tasks suggest that the brain can flexibly represent and manipulate probability distributions. An alternative view is that brain relies on simple algorithms that can implement Bayes-optimal behavior only when the computational demands are low. To distinguish between these alternatives, we devised a task in which Bayes-optimal performance could not be matched by simple algorithms. We asked subjects to estimate and reproduce a time interval by combining prior information with one or two sequential measurements. In the domain of time, measurement noise increases with duration. This property makes the integration of multiple measurements beyond the reach of simple algorithms. We found that subjects were able to update their estimates using the second measurement but their performance was suboptimal, suggesting that they were unable to update full probability distributions. Instead, subjects’ behavior was consistent with an algorithm that predicts upcoming sensory signals, and applies a nonlinear function to errors in prediction to update estimates. These results indicate that inference strategies humans deploy may deviate from Bayes-optimal integration when the computational demands are high.

scholarly journals Incremental 3D Cuboid Modeling with Drift Compensation

Sensors ◽  
2019 ◽  
Vol 19 (1) ◽  
pp. 178 ◽  
Author(s):  
Masashi Mishima ◽  
Hideaki Uchiyama ◽  
Diego Thomas ◽  
Rin-ichiro Taniguchi ◽  
Rafael Roberto ◽  
...  
Keyword(s):  
Augmented Reality ◽  
Point Cloud ◽  
Detection Method ◽  
False Detection ◽  
Cluttered Environments ◽  
Plane Map ◽  
Localization And Mapping ◽  
Cad Models ◽  
Drift Compensation ◽  
Sequential Measurements

This paper presents a framework of incremental 3D cuboid modeling by using the mapping results of an RGB-D camera based simultaneous localization and mapping (SLAM) system. This framework is useful in accurately creating cuboid CAD models from a point cloud in an online manner. While performing the RGB-D SLAM, planes are incrementally reconstructed from a point cloud in each frame to create a plane map. Then, cuboids are detected in the plane map by analyzing the positional relationships between the planes, such as orthogonality, convexity, and proximity. Finally, the position, pose, and size of a cuboid are determined by computing the intersection of three perpendicular planes. To suppress the false detection of the cuboids, the cuboid shapes are incrementally updated with sequential measurements to check the uncertainty of the cuboids. In addition, the drift error of the SLAM is compensated by the registration of the cuboids. As an application of our framework, an augmented reality-based interactive cuboid modeling system was developed. In the evaluation at cluttered environments, the precision and recall of the cuboid detection were investigated, compared with a batch-based cuboid detection method, so that the advantages of our proposed method were clarified.

scholarly journals Tidal airway closure in asthma and COPD

2016 ◽  
Vol 83 (1-2) ◽  
Author(s):  
Claudio Tantucci ◽  
Laura Pini
Keyword(s):  
Stress And Strain ◽  
Small Airways ◽  
Airway Closure ◽  
Functional Tests ◽  
Tidal Breathing ◽  
Copd Patients ◽  
Ventilation Heterogeneity ◽  
Residual Capacity ◽  
Dangerous Condition ◽  
Sequential Measurements

<span style="font-family: 'Times','serif'; font-size: 12pt; mso-ansi-language: EN-US; mso-fareast-font-family: Times; mso-bidi-font-family: 'Times New Roman'; mso-fareast-language: IT; mso-bidi-language: AR-SA;" lang="EN-US">Functional closure of small airways can occur during tidal breathing above functional residual capacity (FRC) both in asthma and COPD patients, especially during exacerbations. Such event has several noxious consequences on gas exchange, airway hyperresponsiveness and mechanical stress and strain within lung tissue and airway wall, mostly due to increase in ventilation heterogeneity. The availability of simple functional tests based on sequential measurements of lung volumes (i.e.: FRC), by plethysmography and dilutional techniques may reveal and monitor easily tidal airway closure that can be and should be treated with the aim of abolishing or at least reducing this dangerous condition.</span>

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