Search results for "Neural"

Signal Spectrum-Based Machine Learning Approach for Fault Prediction and Maintenance of Electrical Machines

2022

Industrial revolution 4.0 has enabled the advent of new technological advancements, including the introduction of information technology with physical devices. The implementation of information technology in industrial applications has helped streamline industrial processes and make them more cost-efficient. This combination of information technology and physical devices gave birth to smart devices, which opened up a new research area known as the Internet of Things (IoT). This has enabled researchers to help reduce downtime and maintenance costs by applying condition monitoring on electrical machines utilizing machine learning algorithms. Although the industry is trying to move from schedu…

Anomaly Detection in Traffic Surveillance Videos Using Deep Learning

2022

In the recent past, a huge number of cameras have been placed in a variety of public and private areas for the purposes of surveillance, the monitoring of abnormal human actions, and traffic surveillance. The detection and recognition of abnormal activity in a real-world environment is a big challenge, as there can be many types of alarming and abnormal activities, such as theft, violence, and accidents. This research deals with accidents in traffic videos. In the modern world, video traffic surveillance cameras (VTSS) are used for traffic surveillance and monitoring. As the population is increasing drastically, the likelihood of accidents is also increasing. The VTSS is used to detect abno…

Validation procedures in radiological diagnostic models. Neural network and logistic regression

1999

The objective of this paper is to compare the performance of two predictive radiological models, logistic regression (LR) and neural network (NN), with five different resampling methods. One hundred and sixty-seven patients with proven calvarial lesions as the only known disease were enrolled. Clinical and CT data were used for LR and NN models. Both models were developed with cross validation, leave-one-out and three different bootstrap algorithms. The final results of each model were compared with error rate and the area under receiver operating characteristic curves (Az). The neural network obtained statistically higher Az than LR with cross validation. The remaining resampling validatio…

Infants and Children Making Sense of Scents

2017

This chapter summarizes research on the development of human olfactory skills to rely on different cues conveyed by odorants, such as odor quality, intensity, position in space, novelty/familiarity, and hedonic value. The sensory, neural, and psychological dimensions at the root of these early aptitudes remain poorly explored in humans, but one can safely affirm that any weak odor to which the infant has previously been nonadversely exposed will have a higher reinforcing value than any novel odor. Developmental differences in odor discrimination and appreciation are certainly causally multiple and may depend on general or olfaction-specific cognitive factors which can be traced back to pren…

High levels of HIF-2α highlight an immature neural crest-like neuroblastoma cell cohort located in a perivascular niche

2007

High HIF-2alpha protein levels in the sympathetic nervous system-derived childhood tumour neuroblastoma as well as immature phenotype correlate to unfavourable outcome. Here we show that a small subset of perivascularly located, strongly HIF-2alpha-positive tumour cells (MYCN amplified) lacks expression of differentiation markers, but expresses neural crest and early sympathetic progenitor marker genes such as Notch-1, HES-1, c-Kit, dHAND, and vimentin. HIF-2alpha- and CD68-positive tumour-associated macrophages were frequently found close to the immature and HIF-2alpha-positive neuroblastoma cells and as VEGF levels are high in the perivascular niche, we hypothesize that neuroblastoma neur…

Reproduction of kinematics of cars involved in crash events using nonlinear autoregressive models

2012

Vehicle crashworthiness can be assessed by the variety of methods - the most common and direct one is a vehicle crash test. Visual inspection and obtained measurements, such as car acceleration, are used to examine impact severity of an occupant and overall car safety. However, those experiments are complex, time-consuming, and expensive. We propose a method to reproduce car kinematics during a collision using a feedforward neural network to estimate the system by use of nonlinear autoregressive (NAR) models. Specifically, feasibility of applying neural networks with an NAR model to the analysis of experimental data is explored by application to measurements of a vehicle crash test. This mo…

2021

Abstract Reliable patient-specific ventricular repolarization times (RTs) can identify regions of functional block or afterdepolarizations, indicating arrhythmogenic cardiac tissue and the risk of sudden cardiac death. Unipolar electrograms (UEs) record electric potentials, and the Wyatt method has been shown to be accurate for estimating RT from a UE. High-pass filtering is an important step in processing UEs, however, it is known to distort the T-wave phase of the UE, which may compromise the accuracy of the Wyatt method. The aim of this study was to examine the effects of high-pass filtering, and improve RT estimates derived from filtered UEs. We first generated a comprehensive set of UE…

QSPR with descriptors based on averages of vertex invariants. An artificial neural network study

2014

New type of indices, the mean molecular connectivity indices (MMCI), based on nine different concepts of mean are proposed to model, together with molecular connectivity indices (MCI), experimental parameters and random variables, eleven properties of organic solvents. Two model methodologies are used to test the different descriptors: the multilinear least-squares (MLS) methodology and the Artificial Neural Network (ANN) methodology. The top three quantitative structure–property relationships (QSPR) for each property are chosen with the MLS method. The indices of these three QSPRs were used to train the ANNs that selected the best training sets of indices to estimate the evaluation sets of…

Visual spike-based convolution processing with a Cellular Automata architecture

2010

this paper presents a first approach for implementations which fuse the Address-Event-Representation (AER) processing with the Cellular Automata using FPGA and AER-tools. This new strategy applies spike-based convolution filters inspired by Cellular Automata for AER vision processing. Spike-based systems are neuro-inspired circuits implementations traditionally used for sensory systems or sensor signal processing. AER is a neuromorphic communication protocol for transferring asynchronous events between VLSI spike-based chips. These neuro-inspired implementations allow developing complex, multilayer, multichip neuromorphic systems and have been used to design sensor chips, such as retinas an…

Intralabyrinthine neurinoma: Management, exeresis and auditory restoration with cochlear implant

2021

Abstract Background and objective Vestibular schwannoma is a benign tumour that originates in the eighth cranial nerve. It is termed intralabyrinthine schwannoma (ILS) when it develops in the inner ear, this being a rare origin. We present our experience in the management of three patients with ILS. Materials and methods The results of tumour excision and cochlear implantation were evaluated in three patients with ILS: two intracochlear schwannomas (ICS) and one intravestibular schwannoma (IVS). Results Prior to surgery, all patients presented progressive sensorineural hearing loss and tinnitus. Complete tumour resection and cochlear implantation was possible in all patients, with favourabl…