Sartis Stay Slim System
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Once in place, both healthcare workers and management benefit from the radiation insight gained. Moreover, focus is returned to treating patients, versus worrying about unnecessary radiation exposure. Data is transferred wirelessly to the i2 real-time display. It is maintenance-free, easy to wear and can be personalized with different colors and names. For especially dose-sensitive patients, it is possible to generate a special low-dose acquisition protocol. Footswitch-on time: footswitch-on time controls how long the beam is on the body and thus how long the body is irradiated; less time means less radiation.
High frame rates are used to visualize fast motion without stroboscopic effects. However, the higher the frame rate, the more radiation. Therefore it is best to keep the frame rate as low as possible. SID: according to the quadratic law and a constant requested dose at the detector, a greater distance between the source and the imager increases the patient entrance dose.
The grid factor i. This rule of thumb is based on the assumption that tissue absorbs radiation in a similar manner as water and that a certain quality of beam is applied. For every 3 cm patient thickness, entrance dose is doubled for const. A similar effect occurs when the direction of projection is changed to an oblique position. Troty is bringing electric scooter-sharing in free-float.
You can now trace, book and ride an electric scooter, keyless. The firm sees its fleet as offering a simple solution to congestion in the capital and aims to help fill the niche between journeys which are too long to make on foot but too short to go by car. A specially created application helps users to find the nearest available scooter.
The e-scooter startup Flash renamed as Circ , which was founded by Lukasz Gadowski, is now called Circ. Recently, the company clocked up 1 million rides in just 4. Circ, therefore, reflects how our vehicles circumnavigate each city as they are. These days, travellers use digital tools to book tickets, accommodation, etc. Entrepreneurs are focusing on sectors such as consumer tourism, hotel management, online booking, price comparison and more to help their users plan and book the whole trip without much….
The world of taxis witnessed a blow due to cab-hailing services such as Uber that changed the situation drastically using the dependence on smartphones. As this made up for the shortage of affordable services, it became an instant hit across the world. Now, the mobility industry is witnessing a…. Just like any other industry, the automotive field is undergoing a massive transformation, thanks to technology and global warming.
In favour of environmental sustainability and cost-effective options, a lot of them are inclined towards shared mobility options. Our results also show that the elevation of the propagation directions may be quantized coarsely without audible impairment.
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However, measuring such HRTFs requires special and expensive equipment, which may be unavailable for most users. Recently, the spherical-harmonics SH representation has been suggested for performing spatial interpolation. However, the fact that HRTFs are naturally of high spatial order leads to truncation and aliasing errors in the SH representation. Thus, pre-processing of HRTFs with the aim of reducing their effective SH order is a potential solution of great interest.
A recent study compared between several pre-processing methods, and concluded that time-alignment leads to the lowest SH order. However, time-alignment of an HRTF requires an accurate estimation of its time delay, which is not always available, especially for contralateral directions. In this paper, a pre-processing method based on ear alignment is presented.
This method is performed parametrically, which makes it more robust to measurement noise. Evaluation of the method is performed numerically, showing significant reduction in the effective SH order and in the interpolation error. In this work, we explore the potential for morphological weighting of different regions of the pinna outer ear to improve the prediction of acoustic directivity patterns associated with head-related transfer functions.
Using a large deformation diffeomorphic metric mapping framework, we apply kernel principal component analysis to model the pinna morphology.
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Different regions of the pinna can be weighted differently prior to the kernel principal component analysis. By varying the weights applied to the various regions of the pinna, we begin to learn the relative importance of the various regions to the acoustic directivity of the ear as a function of frequency. The pinna is divided into nine parts comprising the helix, scaphoid fossa, triangular fossa, concha rim, cymba concha, cavum concha, conchal ridge, ear lobe, and back of the ear. Results indicate that weighting the conchal region concha rim, cavum and cymba concha improves the predicted acoustic directivity for frequency bands centered around 3 kHz, 7 kHz, 10 kHz and 13 kHz.
Similarly, weighting the triangular and scaphoid fossa improves the prediction of acoustic directivity in frequency bands centered around 7 kHz, 13 kHz and In this work, we address the problem of EEG-based decoding of auditory attention to a target instrument in realistic polyphonic music. To this end, we exploit the so-called multivariate temporal response function, which was proven to decode successfully the attention to speech in multi-speaker environments.
To our knowledge, this model was never applied to musical stimuli for decoding attention.
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The task we consider here is quite complex as the stimuli used are polyphonic, including duets and trios, and are reproduced using loudspeakers instead of headphones. Speech quality, as perceived by humans, is an important performance metric for telephony and voice services. It is typically measured through subjective listening tests, which can be tedious and expensive. Here we propose using a convolutional neural network to predict the perceived quality of speech with noise, reverberation, and distortions, both intrusively and non-intrusively, i.
The network model is trained and evaluated on a corpus of about ten thousand utterances labeled by human listeners to derive a Mean Opinion Score MOS for each utterance. The proposed method reduces the root mean squared error from 0.
Audio processing methods operating on a time-frequency representation of the signal can introduce unpleasant sounding artifacts known as musical noise. These artifacts are observed in the context of audio coding, speech enhancement, and source separation. The change in kurtosis of the power spectrum introduced during the processing was shown to correlate with the human perception of musical noise in the context of speech enhancement, leading to the proposal of measures based on it.
These baseline measures are here shown to correlate with human perception only in a limited manner. As ground truth for the human perception, the results from two listening tests are considered: one involving audio coding and one involving source separation. Simple but effective perceptually motivated improvements are proposed and the resulting new measure is shown to clearly outperform the baselines in terms of correlation with the results of both listening tests.
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Moreover, with respect to the listening test on musical noise in audio coding, the exhibited correlation is nearly as good as the one exhibited by the Artifact-related Perceptual Score APS , which was found to be the best objective measure for this task. The APS is however computationally very expensive. The proposed measure is easily computed, requiring only a fraction of the computational cost of the APS. Audio source separation, i.
https://quispygisco.tk Applications emerge which allow users to manipulate a given music recording to create a personal mix of a music recording or to adapt the audio level of the sports commentator and the atmosphere in sports broadcast to their own preference or hearing abilities. The perceived quality of the produced audio signals is an important key factor to rate these separation systems. In order to optimize them, an efficient, perceptually based measurement scheme to predict the perceived audio quality would be highly beneficial.
In this paper a model for prediction of the perceived audio quality of separated audio source signals is presented, solely based on two timbre features, demanding less computational effort than current perceptual measurement schemes for audio source separation. High correlation of the model output with perceived quality is demonstrated. Objective metrics, such as the perceptual evaluation of speech quality PESQ have become standard measures for evaluating speech.
These metrics enable efficient and costless evaluations, where ratings are often computed by comparing a degraded speech signal to its underlying clean reference signal.
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Reference-based metrics, however, cannot be used to evaluate real-world signals that have inaccessible references. This project develops a nonintrusive framework for evaluating the perceptual quality of noisy and enhanced speech. We propose an utterance-level classification-aided nonintrusive UCAN assessment approach that combines the task of quality score classification with the regression task of quality score estimation. Our approach uses a categorical quality ranking as an auxiliary constraint to assist with quality score estimation, where we jointly train a multi-layered convolutional neural network in a multi-task manner.
This approach is evaluated using the TIMIT speech corpus and several noises under a wide range of signal-to-noise ratios. The results show that the proposed system significantly improves quality score estimation as compared to several state-of-the-art approaches. Voice disorders affect a large portion of the population, in particular impacting heavy voice users such as teachers or call-center workers. Voice therapy—the recommended behavioral treatment for a variety of voice disorders—requires regular voice technique practice under the guidance of a voice therapist.
Patients commonly have difficulty reproducing this technique without clinician feedback once they get home. Therefore, we developed a system for use in voice therapy to provide feedback to the patient about the quality of their voice practice. Six adults were recorded producing 5 different voice quality modes: normal, breathy, fry, twang and hyponasal. An i-vector-based algorithm was trained on 6 participants to classify these vocal modes with The system can be used to detect different voice quality modes in unscripted, connected speech, which has potential to automate analysis of home practice in voice therapy and to serve as a feedback tool to extend therapist judgment beyond the clinic walls.
This paper provides a 3D localized sound zone generation method using a planar omni-directional loudspeaker array.