239,324 research outputs found
The accuracy of volume flow measurements derived from pulsed wave Doppler: a study in the complex setting of forearm vascular access for hemodialysis
Purpose: Maturation of an arterio-venous fistula (AVF) frequently fails, with low postoperative fistula flow as a prognostic marker for this event. As pulsed wave Doppler (PWD) is commonly used to assess volume flow, we studied the accuracy of this measurement in the setting of a radio-cephalic AVF. Methods: As in-vivo validation of fistula flow measurements is cumbersome, we performed simulations, integrating computational fluid dynamics with an ultrasound (US) simulator. Flow in the arm was calculated, based on a patient-specific model of the arm vasculature pre and post AVF creation. Next, raw ultrasound signals were simulated, from which the Doppler spectra were calculated in both a proximal (brachial) and a distal (radial) location. Results: The velocity component in the direction of the US beam, in a centred, small, sample volume, can be captured accurately using PWD spectrum mean-tracking. However, deriving flow rate from these measurements is prone to errors: (i) the angle-correction which is influenced by the radial velocity components in the complex flow field; (ii) the largest error is introduced due to a lack of knowledge on the spatial flow profile
SAFETY PATROL: MECHANISMS FOR IMPROVING EMERGENCY RESPONSE TIMES
To equip first responders with critical, time-sensitive information and accelerate emergency services response times, various solutions are provided herein through several techniques. Under a first technique, after an emergency event such as a gunshot is either automatically detected by a camera or manually initiated by a user, or when a dangerous object such as a gun is detected by a camera, a network may react by associating the source of the dangerous event or object with a person based on proximity data; identifying the physical characteristics of the person (such as height, hair color, clothing, visible tattoos, etc.); attaching such characteristics as textual metadata; and then transmitting that metadata to first responders. A second technique automatically develops a radio frequency (RF) signature profile of a person of interest (from RF signals emitted by devices carried by the person), associates that profile to the person, and leverages that profile to track the person as they move throughout a building or campus, allowing a user to look back in time (to, for example, identify where a person came from and how they entered a building) by tracking the RF profile over time. The above-described data is extremely important during any ongoing emergency and equips first responders with critical information which only a network can provide
Full waveform inversion with extrapolated low frequency data
The availability of low frequency data is an important factor in the success
of full waveform inversion (FWI) in the acoustic regime. The low frequencies
help determine the kinematically relevant, low-wavenumber components of the
velocity model, which are in turn needed to avoid convergence of FWI to
spurious local minima. However, acquiring data below 2 or 3 Hz from the field
is a challenging and expensive task. In this paper we explore the possibility
of synthesizing the low frequencies computationally from high-frequency data,
and use the resulting prediction of the missing data to seed the frequency
sweep of FWI. As a signal processing problem, bandwidth extension is a very
nonlinear and delicate operation. It requires a high-level interpretation of
bandlimited seismic records into individual events, each of which is
extrapolable to a lower (or higher) frequency band from the non-dispersive
nature of the wave propagation model. We propose to use the phase tracking
method for the event separation task. The fidelity of the resulting
extrapolation method is typically higher in phase than in amplitude. To
demonstrate the reliability of bandwidth extension in the context of FWI, we
first use the low frequencies in the extrapolated band as data substitute, in
order to create the low-wavenumber background velocity model, and then switch
to recorded data in the available band for the rest of the iterations. The
resulting method, EFWI for short, demonstrates surprising robustness to the
inaccuracies in the extrapolated low frequency data. With two synthetic
examples calibrated so that regular FWI needs to be initialized at 1 Hz to
avoid local minima, we demonstrate that FWI based on an extrapolated [1, 5] Hz
band, itself generated from data available in the [5, 15] Hz band, can produce
reasonable estimations of the low wavenumber velocity models
Adaptive intermittent control: A computational model explaining motor intermittency observed in human behavior
It is a fundamental question how our brain performs a given motor task in a real-time fashion with the slow sensorimotor system. Computational theory proposed an influential idea of feed-forward control, but it has mainly treated the case that the movement is ballistic (such as reaching) because the motor commands should be calculated in advance of movement execution. As a possible mechanism for operating feed-forward control in continuous motor tasks (such as target tracking), we propose a control model called "adaptive intermittent control" or "segmented control," that brain adaptively divides the continuous time axis into discrete segments and executes feed-forward control in each segment. The idea of intermittent control has been proposed in the fields of control theory, biological modeling and nonlinear dynamical system. Compared with these previous models, the key of the proposed model is that the system speculatively determines the segmentation based on the future prediction and its uncertainty. The result of computer simulation showed that the proposed model realized faithful visuo-manual tracking with realistic sensorimotor delays and with less computational costs (i.e., with fewer number of segments). Furthermore, it replicated "motor intermittency", that is, intermittent discontinuities commonly observed in human movement trajectories. We discuss that the temporally segmented control is an inevitable strategy for brain which has to achieve a given task with small computational (or cognitive) cost, using a slow control system in an uncertain variable environment, and the motor intermittency is the side-effect of this strategy
On web user tracking of browsing patterns for personalised advertising
This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Parallel, Emergent and Distributed Systems on 19/02/2017, available online: http://www.tandfonline.com/doi/abs/10.1080/17445760.2017.1282480On today’s Web, users trade access to their private data for content and services. App and service providers want to know everything they can about their users, in order to improve their product experience. Also, advertising sustains the business model of many websites and applications. Efficient and successful advertising relies on predicting users’ actions and tastes to suggest a range of products to buy. Both service providers and advertisers try to track users’ behaviour across their product network. For application providers this means tracking users’ actions within their platform. For third-party services following users, means being able to track them across different websites and applications. It is well known how, while surfing the Web, users leave traces regarding their identity in the form of activity patterns and unstructured data. These data constitute what is called the user’s online footprint. We analyse how advertising networks build and collect users footprints and how the suggested advertising reacts to changes in the user behaviour.Peer ReviewedPostprint (author's final draft
On Web User Tracking: How Third-Party Http Requests Track Users' Browsing Patterns for Personalised Advertising
On today's Web, users trade access to their private data for content and
services. Advertising sustains the business model of many websites and
applications. Efficient and successful advertising relies on predicting users'
actions and tastes to suggest a range of products to buy. It follows that,
while surfing the Web users leave traces regarding their identity in the form
of activity patterns and unstructured data. We analyse how advertising networks
build user footprints and how the suggested advertising reacts to changes in
the user behaviour.Comment: arXiv admin note: substantial text overlap with arXiv:1605.0653
You never surf alone. Ubiquitous tracking of users' browsing habits
In the early age of the internet users enjoyed a large level of anonymity. At
the time web pages were just hypertext documents; almost no personalisation of
the user experience was o ered. The Web today has evolved as a world wide
distributed system following specific architectural paradigms. On the web now,
an enormous quantity of user generated data is shared and consumed by a network
of applications and services, reasoning upon users expressed preferences and
their social and physical connections. Advertising networks follow users'
browsing habits while they surf the web, continuously collecting their traces
and surfing patterns. We analyse how users tracking happens on the web by
measuring their online footprint and estimating how quickly advertising
networks are able to pro le users by their browsing habits
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