Search results for "NEURAL NETWORK"
showing 10 items of 1385 documents
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.
Type-2 Fuzzy Control of a Bioreactor
2009
Abstract—In this paper the control of a bioprocess using an adaptive type-2 fuzzy logic controller is proposed. The process is concerned with the aerobic alcoholic fermentation for the growth of Saccharomyces Cerevisiae a n d i s characterized by nonlinearity and parameter uncertainty. Three type-2 fuzzy controllers heve been developed and tested by simulation: a simple type-2 fuzzy logic controller with 49 rules; a type-2 fuzzyneuro- predictive controller (T2FNPC); a t y p e -2 selftuning fuzzy controller ( T2STFC). The T2FNPC combines the capability of the type-2 fuzzy logic to handle uncertainties, with the ability of predictive control to predict future plant performance making use of a…
Dosage individualization of erythropoietin using a profile-dependent support vector regression
2003
The external administration of recombinant human erythropoietin is the chosen treatment for those patients with secondary anemia due to chronic renal failure in periodic hemodialysis. The objective of this paper is to carry out an individualized prediction of the EPO dosage to be administered to those patients. The high cost of this medication, its side-effects and the phenomenon of potential resistance which some individuals suffer all justify the need for a model which is capable of optimizing dosage individualization. A group of 110 patients and several patient factors were used to develop the models. The support vector regressor (SVR) is benchmarked with the classical multilayer percept…
Criss‐crossing autism spectrum disorder and adult neurogenesis
2021
Autism spectrum disorder (ASD) comprises a group of multifactorial neurodevelopmental disorders primarily characterized by deficits in social interaction and repetitive behavior. Although the onset is typically in early childhood, ASD poses a lifelong challenge for both patients and caretakers. Adult neurogenesis (AN) is the process by which new functional neurons are created from neural stem cells existing in the post-natal brain. The entire event is based on a sequence of cellular processes, such as proliferation, specification of cell fate, maturation, and ultimately, synaptic integration into the existing neural circuits. Hence, AN is implicated in structural and functional brain plasti…
Spatiotemporal Neurodynamics Underlying Internally and Externally Driven Temporal Prediction: A High Spatial Resolution ERP Study
2015
Abstract Temporal prediction (TP) is a flexible and dynamic cognitive ability. Depending on the internal or external nature of information exploited to generate TP, distinct cognitive and brain mechanisms are engaged with the same final goal of reducing uncertainty about the future. In this study, we investigated the specific brain mechanisms involved in internally and externally driven TP. To this end, we employed an experimental paradigm purposely designed to elicit and compare externally and internally driven TP and a combined approach based on the application of a distributed source reconstruction modeling on a high spatial resolution electrophysiological data array. Specific spatiotemp…