Search results for "Neural"
showing 10 items of 2783 documents
Revista electrónica de investigación y evaluación educativa
2018
Prevenir la deserción escolar requiere de un trabajo interprofesional que aborde de manera coordinada los múltiples factores individuales, escolares y estructurales que llevan a un joven a dejar la escolarización formal. Este estudio examina la configuración del trabajo interprofesional que se diseña e implementa en dos Departamentos Municipales de Educación en Chile para abordar la inasistencia y deserción de estudiantes en la educación secundaria creciendo en situación de vulnerabilidad social. Los datos fueron producidos a través de entrevistas en profundidad con la participación de 63 personas, incluyendo a profesionales, apoderados y estudiantes. El modelo del primer caso está orienta…
Machine Learning to Predict In-Hospital Mortality in COVID-19 Patients Using Computed Tomography-Derived Pulmonary and Vascular Features
2021
Pulmonary parenchymal and vascular damage are frequently reported in COVID-19 patients and can be assessed with unenhanced chest computed tomography (CT), widely used as a triaging exam. Integrating clinical data, chest CT features, and CT-derived vascular metrics, we aimed to build a predictive model of in-hospital mortality using univariate analysis (Mann–Whitney U test) and machine learning models (support vectors machines (SVM) and multilayer perceptrons (MLP)). Patients with RT-PCR-confirmed SARS-CoV-2 infection and unenhanced chest CT performed on emergency department admission were included after retrieving their outcome (discharge or death), with an 85/15% training/test dataset spli…
Glial expression of Swiss cheese (SWS), the Drosophila orthologue of neuropathy target esterase (NTE), is required for neuronal ensheathment and func…
2016
ABSTRACT Mutations in Drosophila Swiss cheese (SWS) or its vertebrate orthologue neuropathy target esterase (NTE), respectively, cause progressive neuronal degeneration in Drosophila and mice and a complex syndrome in humans that includes mental retardation, spastic paraplegia and blindness. SWS and NTE are widely expressed in neurons but can also be found in glia; however, their function in glia has, until now, remained unknown. We have used a knockdown approach to specifically address SWS function in glia and to probe for resulting neuronal dysfunctions. This revealed that loss of SWS in pseudocartridge glia causes the formation of multi-layered glial whorls in the lamina cortex, the firs…
Seasonal patterns of biodiversity in Mediterranean coastal lagoons
2019
Aim: Understanding and quantifying the seasonal patterns in biodiversity of phyto- benthos, macro-zoobenthos and fishes in Mediterranean coastal lagoons, and the species dependence upon environmental factors. Location: The study was carried out in the “Stagnone di Marsala e Saline di Trapani e Paceco,” the largest coastal lagoon system in the central Mediterranean Sea (Sicily, Italy), a Special Protection Area located along one of the central ecological corridors joining Africa and Europe. Methods: The coastal lagoon system was selected as a model ecosystem to investi- gate the seasonal variations in biodiversity indices and dominance–diversity relation- ships in phytobenthos, macro-zoobent…
Modeling the Target-Note Technique of Bebop-Style Jazz Improvisation: An Artificial Neural Network Approach
1995
In cognitive science and research on artificial intelligence, there are two central paradigms: symbolic and analogical. Within the analogical paradigm, artificial neural networks (ANNs) have recently been successfully used to model and simulate cognitive phenomena. One of the most prominent features of ANNs is their ability to learn by example and, to a certain extent, generalize what they have learned. Improvisation, the art of spontaneously creating music while playing or singing, fundamentally has an imitative nature. Regardless of how much one studies and analyzes, the art of improvisation is learned mostly by example. Instead of memorizing explicit rules, the student mimics the playing…
Simulating music with associative self-organizing maps
2018
Abstract We present an architecture able to recognise pitches and to internally simulate likely continuations of partially heard melodies. Our architecture consists of a novel version of the Associative Self-Organizing Map (A-SOM) with generalized ancillary connections. We tested the performance of our architecture with melodies from a publicly available database containing 370 Bach chorale melodies. The results showed that the architecture could learn to represent and perfectly simulate the remaining 20% of three different interrupted melodies when using a context length of 8 centres of activity in the A-SOM. These promising and encouraging results show that our architecture offers somethi…
Bacterial Cytolysin Perturbs Round Window Membrane Permeability Barrier In Vivo: Possible Cause of Sensorineural Hearing Loss in Acute Otitis Media
1998
ABSTRACT The passage of radioiodinated streptolysin-O (SLO) and albumin through the round window membrane (RWM) was studied in vivo. When applied to the middle ear, SLO became quantitatively entrapped in this compartment and no passage to the cochlea occurred. However, flux of radioiodinated albumin through the toxin-damaged RWM was observed. We propose that the passage of noxious macromolecules, such as proteases, from a purulent middle-ear effusion may be facilitated by pore-forming toxins, resulting in cochlear damage and sensorineural hearing loss.
The Dreaming Variational Autoencoder for Reinforcement Learning Environments
2018
Reinforcement learning has shown great potential in generalizing over raw sensory data using only a single neural network for value optimization. There are several challenges in the current state-of-the-art reinforcement learning algorithms that prevent them from converging towards the global optima. It is likely that the solution to these problems lies in short- and long-term planning, exploration and memory management for reinforcement learning algorithms. Games are often used to benchmark reinforcement learning algorithms as they provide a flexible, reproducible, and easy to control environment. Regardless, few games feature a state-space where results in exploration, memory, and plannin…
Neural Networks and Metabolic Networks: Fault Tolerance and Robustness Features
2009
The main objective of this work is the comparison between metabolic networks and neural networks (ANNs) in terms of their robustness and fault tolerance capabilities. In the context of metabolic networks errors are random removal of network nodes, while attacks are failures in the network caused intentionally. In the contest of neural networks errors are usually defined configurations of input submitted to the network that are affected by noise, while the failures are defined as the removal of some network neurons. This study have proven that ANNs are very robust networks, with respect to the presence of noise in the inputs, and the partial removal of some nodes, until it reached a critical…
Neural Network Techniques for Metal Forming Design
1993
Neural networks are computing structures able to predict the behaviour of a system on the basis of the knowledge of facts; main characteristic of a network is the capability to find a rule in a very complex environment. In the paper a neural network, based on the results of FEM simulations, is utilized to predict the occurrence of defects in a forward extrusion metal forming process. In particular a three layers neural network, relating the operative parameters with the failure or the success of the working process, has been used and the back-propagation algorithm has been employed to train the network. Few experimental data were enough to train the neural network allowing to achieve better…