Search results for "NEURAL NETWORKS"
showing 10 items of 599 documents
The role of expert evaluation for microsleep detection
2015
Abstract Recently, it has been shown by overnight driving simulation studies that microsleep density is the only known sleepiness indicator which rapidly increases within a few seconds immediately before sleepiness related crashes. This indicator is based solely on EEG and EOG and subsequent adaptive pattern recognition. Accurate microsleep recognition is very important for the performance of this sleepiness indicator. The question is whether expensive evaluations of microsleep events by a) experts are necessary or b) non-experts provide sufficient evaluations. Based on 11,114 microsleep events in case a) and 12,787 in case b) recognition accuracies were investigated utilizing (i) artificia…
Nonlinear Relaxation in Population Dynamics
2001
We analyze the nonlinear relaxation of a complex ecosystem composed of many interacting species. The ecological system is described by generalized Lotka-Volterra equations with a multiplicative noise. The transient dynamics is studied in the framework of the mean field theory and with random interaction between the species. We focus on the statistical properties of the asymptotic behaviour of the time integral of the i-th population and on the distribution of the population and of the local field.
Characterization of E'delta and triplet point defects in oxygen-deficient amorphous silicon dioxide
2005
We report an experimental study by electron paramagnetic resonance (EPR) of gamma ray irradiation induced point defects in oxygen deficient amorphous SiO2 materials. We have found that three intrinsic (E'gamma, E'delta and triplet) and one extrinsic ([AlO4]0) paramagnetic centers are induced. All the paramagnetic defects but E'gamma center are found to reach a concentration limit value for doses above 10^3 kGy, suggesting a generation process from precursors. Isochronal thermal treatments of a sample irradiated at 10^3 kGy have shown that for T>500 K the concentrations of E'gamma and E'delta centers increase concomitantly to the decrease of [AlO4]0. This occurrence speaks for an hole tra…
Instrumental Odour Monitoring System Classification Performance Optimization by Analysis of Different Pattern-Recognition and Feature Extraction Tech…
2020
Instrumental odour monitoring systems (IOMS) are intelligent electronic sensing tools for which the primary application is the generation of odour metrics that are indicators of odour as perceived by human observers. The quality of the odour sensor signal, the mathematical treatment of the acquired data, and the validation of the correlation of the odour metric are key topics to control in order to ensure a robust and reliable measurement. The research presents and discusses the use of different pattern recognition and feature extraction techniques in the elaboration and effectiveness of the odour classification monitoring model (OCMM). The effect of the rise, intermediate, and peak period …
Aligned microcontact printing of biomolecules on microelectronic device surfaces
2001
Microcontact printing (/spl mu/CP) of extracellular matrix proteins is a fascinating approach to control cell positioning and outgrowth, which is essential in the development of applications ranging from cellular biosensors to tissue engineering. Microelectronic devices can be used to detect the activity from a large number of recording sites over the long term. However, signals from cells can only be recorded at small sensitive spots. Here, the authors present an innovative setup to perform aligned /spl mu/CP of extracellular matrix proteins on microelectronic devices in order to guide the growth of electrogenic cells specifically to these sensitive spots. The authors' system is based on t…
Persistence in complex systems
2022
Persistence is an important characteristic of many complex systems in nature, related to how long the system remains at a certain state before changing to a different one. The study of complex systems' persistence involves different definitions and uses different techniques, depending on whether short-term or long-term persistence is considered. In this paper we discuss the most important definitions, concepts, methods, literature and latest results on persistence in complex systems. Firstly, the most used definitions of persistence in short-term and long-term cases are presented. The most relevant methods to characterize persistence are then discussed in both cases. A complete literature r…
One Dimensional Convolutional Neural Networks for Seizure Onset Detection Using Long-term Scalp and Intracranial EEG
2021
Epileptic seizure detection using scalp electroencephalogram (sEEG) and intracranial electroencephalogram (iEEG) has attracted widespread attention in recent two decades. The accurate and rapid detection of seizures not only reflects the efficiency of the algorithm, but also greatly reduces the burden of manual detection during long-term electroencephalogram (EEG) recording. In this work, a stacked one-dimensional convolutional neural network (1D-CNN) model combined with a random selection and data augmentation (RS-DA) strategy is proposed for seizure onset detection. Firstly, we segmented the long-term EEG signals using 2-sec sliding windows. Then, the 2-sec interictal and ictal segments w…
Multilayer perceptron training with multiobjective memetic optimization
2016
Machine learning tasks usually come with several mutually conflicting objectives. One example is the simplicity of the learning device contrasted with the accuracy of its performance after learning. Another common example is the trade-off that must often be made between the rate of false positive and false negative predictions in diagnostic applications. For computer programs that learn from data, these objectives are formulated as mathematical functions, each of which describes one facet of the desired learning outcome. Even functions that intend to optimize the same facet may behave in a subtly different and mutually conflicting way, depending on the task and the dataset being examined. Mul…
Node co-activations as a means of error detection : Towards fault-tolerant neural networks
2022
Context: Machine learning has proved an efficient tool, but the systems need tools to mitigate risks during runtime. One approach is fault tolerance: detecting and handling errors before they cause harm. Objective: This paper investigates whether rare co-activations – pairs of usually segregated nodes activating together – are indicative of problems in neural networks (NN). These could be used to detect concept drift and flagging untrustworthy predictions. Method: We trained four NNs. For each, we studied how often each pair of nodes activates together. In a separate test set, we counted how many rare co-activations occurred with each input, and grouped the inputs based on whether its class…
Convolutional Neural Network Based Sleep Stage Classification with Class Imbalance
2022
Accurate sleep stage classification is vital to assess sleep quality and diagnose sleep disorders. Numerous deep learning based models have been designed for accomplishing this labor automatically. However, the class imbalance problem existing in polysomnography (PSG) datasets has been barely investigated in previous studies, which is one of the most challenging obstacles for the real-world sleep staging application. To address this issue, this paper proposes novel methods with signal-driven and image-driven ways of noise addition to balance the imbalanced relationship in the training dataset samples. We evaluate the effectiveness of the proposed methods which are integrated into a convolut…