110 research outputs found
General relativistic effects on the evolution of binary systems.
When a radio pulsar brakes down due to magnetodipole emission,its gravitational mass decreases accordingly. If the pulsar is hosted in a binary system, this mass loss will Increase the orbital period of the system. We show that this relativistic effect can be indeed observable if the neutron star is fast and magnetized enough and that, if observed, it will help to put tight constraints to the equation of state of ultradense matter. Moreover, in Low Mass X-ray Binaries that evolve towards short periods, the neutron star lights up as a radio pulsar during the "period gap". As the effect we consider contrasts the orbital period decay, the system spends a longer time in this phase. As a consequence, the neutron star can survive this phase only if it is non-supramassive, Since in such bianries similar to 0.84M(circle dot) can be accreted onto the neutron star, short period (P <= 2 h) millisecond Xray pulsars like SAX J1808.4-3658 can be formed only if either a large part of the accreting matter has been ejected from the system, or the equation of state of ultradense matter is very stiff
Hemorrhagic brain stroke detection by using microwaves: Preliminary two-dimensional reconstructions
Preliminary numerical results concerning the application of a Gauss-Newton method for diagnostic purposes of hemorrhagic brain strokes are reported. Interrogating microwaves are used in a multistatic and multiview arrangement. The reported results concern a two-dimensional model under transverse magnetic illumination conditions
Early Detection of External Neurological Symptoms through a Wearable Smart-Glasses Prototype
The Internet of Things (IoT) framework is moving the research community to provide smart systems and solutions aimed at revolutionizing medical sciences and healthcare. Given the extreme diffusion of Alzheimer’s disease (AD) and Parkinson’s disease (PD), the demand for a solution to early detect neurological symptoms of such diseases strongly arose. According to the medical literature, such early detection can be obtained through the correlation between PD and AD and some external symptoms: the Essential Tremor (ET) and the number of Eye Blinks (EBs). In this paper, which can be considered as an extended version of [1], we present a prototype of wearable smart glasses able to detect the presence of ET of the head and to count the number of EBs at the same time, in a transparent way with respect to the final user. Numerical results demonstrate the reliability of the proposed approach: the proposed algorithms are able to i) correctly recognize the ET with an overall accuracy above 97% and ii) count the number of EBs with an overall error around 9%
A Neural Clustering Algorithm for Estimating Visible Articulatory Trajectory
. The bimodal acoustic-visual nature of speech establishes sound correlations between its audio component and the corresponding articulatory information associated to the time-varying geometry of the vocal tract. In this paper we propose an estimation structure consisting of a simplified Time-Delay Neural Network (TDNN) working on 4-5 dimensional cepstrum trajectories provided by a preceding clusterization layer based on a Self Organizing Map (SOM). The use of this pre-processing layer has allowed an effective non-linear clusterization of cepstrum vectors thus simplifying of one order the complexity of the resulting system while maintaining unchanged the global estimation performances. The achieved results are shown in terms estimation precision and robustness with reference to previously published results. 1 A direct approach to articulatory estimation The objective of any direct approach to articulatory estimation is the design of a suitable mechanism for mapping a predefined acoust..
Lip Movements Synthesis Using Time Delay Neural Networks
A method exploiting the audio-visual correlation of speech in order to estimate the lip and mouth movements is presented. Its applications are in the field of aids and services for elderly people, in videotelephony, in cartoons and movie dubbing. Notice that lip movements synthesis does not imply speech recognition and that the mouth shape is not only specified by the phoneme currently uttered but it also depends on some past and future speech information. In order to take into account this temporal correlation, and considering the constraint of computational effectiveness, the Time Delay Neural Networks (TDNNs) seem to be the most appropriate analysis tool in comparison with methods like Markov Models, which are more resource consuming. 1 INTRODUCTION In a model-based videophone the encoder performs a visual analysis and transmits the extracted parameters to the receiver, which then animates a facial model. The measured visual parameters describing the shape of the person's lips are..
Cooperative Application Layer Joint Video Coding in the Internet of Remote Things
Recently the problem of interconnecting Internet of Things nodes when they are dispersed over wide geographical areas has been highlighted: This is the Internet of Remote Things (IoRT). It could be able to play a key role in disaster recovery scenarios (e.g., earthquakes, flash floods, terrorist attacks, etc.), where the presence of a communication infrastructure enabling video transmissions from the emergency areas is crucial. Local communications can be provided by incident area networks, while satellite communication systems can bridge the gap toward external networks. In this context, we propose a cooperative resource allocation mechanism, which exploits feedback from links conditions and knowledge of the adaptive coding, allowing a higher quality and more fair experience for all nodes of the IoRT transmitting videos. We implemented each element of the mentioned scenario over an emulation platform to prove the concept and show the obtained benefits
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