Search results for "EURA"
showing 10 items of 3336 documents
Comparing identification of vocal imitations and computational sketches of everyday sounds
2016
International audience; Sounds are notably difficult to describe. It is thus not surprising that human speakers often use many imitative vocalizations to communicate about sounds. In practice,vocal imitations of non-speech everyday sounds (e.g. the sound of a car passing by) arevery effective: listeners identify sounds better with vocal imitations than with verbal descriptions, despite the fact that vocal imitations are often inaccurate, constrained by the human vocal apparatus. The present study investigated the semantic representations evoked by vocal imitations by experimentally quantifying how well listeners could match sounds to category labels. Itcompared two different types of sounds…
Mini-COVIDNet: Efficient Lightweight Deep Neural Network for Ultrasound Based Point-of-Care Detection of COVID-19
2021
Lung ultrasound (US) imaging has the potential to be an effective point-of-care test for detection of COVID-19, due to its ease of operation with minimal personal protection equipment along with easy disinfection. The current state-of-the-art deep learning models for detection of COVID-19 are heavy models that may not be easy to deploy in commonly utilized mobile platforms in point-of-care testing. In this work, we develop a lightweight mobile friendly efficient deep learning model for detection of COVID-19 using lung US images. Three different classes including COVID-19, pneumonia, and healthy were included in this task. The developed network, named as Mini-COVIDNet, was bench-marked with …
Glycoprotein and ganglioside changes in human trophoblasts after exposure to pulsed doppler ultrasound
1995
Changes in glycoprotein and ganglioside composition in human trophoblasts (eighth week of gestation) after in vitro exposure to pulsed Doppler ultrasound (pulse duration 1.22 microseconds; repetition frequency 11.1 kHz; center frequency 4 MHz; ISPPA = 175.5 W/cm2; ISPTA = 0.59 W/cm2) were investigated. Evacuated trophoblasts were divided in two halves and insonated for 10 min on top of a 6-cm layer of 5% gelatin in 50-mL tubes (Falcon) at 37 degrees C. One half of each trophoblast was sham insonated and served as an internal control. After insonation trophoblasts were maintained at 37 degrees C for 24 h. Glycoproteins were detected using alpha-D-mannose specific lectins from Galanthus nival…
An ASSOM neural network to represent actions performed by an autonomous agent
1997
An ASSOM neural network to describe the action performed by an autonomous reactive agent is proposed. The neural network receives in input the sequences of data acquired by the agent internal sensors and it classifies them by generating the corresponding symbolic assertions. Experimental results performed on a RWI B12 autonomous robot are reported.
Dropping out of school as a meaningful action for adolescents with social, emotional and behavioural difficulties
2013
This study examines and discusses dropping out of school related to adolescents with social, emotional and behavioural difficulties (SEBD). It is based on in-depth interviews of 10 adolescents between the ages of 16 and 20, three girls and two boys with internalised problems, and two girls and three boys with extroverted behavioural problems. Given this group of students' challenges at school, the aim of this paper is to explore the narratives of this adolescent group as they relate to the significance they attach to their dropout behaviour. An additional objective is to draw attention to what these findings are likely to mean for implementing preventive practices in school. Results show th…
Rapid developmental switch in the mechanisms driving early cortical columnar networks
2006
The immature cerebral cortex self-organizes into local neuronal clusters long before it is activated by patterned sensory inputs. In the cortical anlage of newborn mammals, neurons coassemble through electrical or chemical synapses either spontaneously or by activation of transmitter-gated receptors. The neuronal network and the cellular mechanisms underlying this cortical self-organization process during early development are not completely understood. Here we show in an intact in vitro preparation of the immature mouse cerebral cortex that neurons are functionally coupled in local clusters by means of propagating network oscillations in the beta frequency range. In the newborn mouse, this…
A New Adaptive Neural Harmonic Compensator for Inverter Fed Distributed Generation
2004
This paper deals with the command of inverters in DG (distributed generation) systems by use of linear neural networks in such a way that, with a slight upgrade of their control software, they can be used also to compensate for the harmonic distortion in the node where they are connected (local compensation), that is in the in the point of common coupling (PCC). To this purpose a neural estimator based on linear neurons (ADALINEs) has been developed which is able to act as a selective noise cancellers for each harmonic of the node voltage. The use of linear neurons permits the drawbacks of classical neural networks to be overcome and moreover the neural estimator is easy to implement, thus …
Is the nonREM–REM sleep cycle reset by forced awakenings from REM sleep?
2002
In selective REM sleep deprivation (SRSD), the occurrence of stage REM is repeatedly interrupted by short awakenings. Typically, the interventions aggregate in clusters resembling the REM episodes in undisturbed sleep. This salient phenomenon can easily be explained if the nonREM–REM sleep process is continued during the periods of forced wakefulness. However, earlier studies have alternatively suggested that awakenings from sleep might rather discontinue and reset the ultradian process. Theoretically, the two explanations predict a different distribution of REM episode duration. We evaluated 117 SRSD treatment nights recorded from 14 depressive inpatients receiving low dosages of Trimipram…
Combining Benford's Law and machine learning to detect money laundering. An actual Spanish court case.
2017
Abstract Objectives This paper is based on the analysis of the database of operations from a macro-case on money laundering orchestrated between a core company and a group of its suppliers, 26 of which had already been identified by the police as fraudulent companies. In the face of a well-founded suspicion that more companies have perpetrated criminal acts and in order to make better use of what are very limited police resources, we aim to construct a tool to detect money laundering criminals. Methods We combine Benford’s Law and machine learning algorithms (logistic regression, decision trees, neural networks, and random forests) to find patterns of money laundering criminals in the conte…
Using adaptive fuzzy-neural control to minimize response time in cluster-based web systems
2005
We have developed content-aware request distribution algorithm called FARD which is a client-and-server-aware, dynamic and adaptive distribution policy in cluster-based Web systems. It assigns each incoming request to the server with the least expected response time. To estimate the expected response times it uses the fuzzy estimation mechanism. The system is adaptive as it uses a neural network learning ability for its adaptation. Simulations based on traces from the 1998 World Cup show that when we consider the response time, FARD can be more effective than the state-of-the-art content-aware policy LARD.