Search results for "test"
showing 10 items of 19001 documents
Broker and Federation Based Cloud Networking Architecture for IaaS and NaaS QoS Guarantee
2016
International audience; Today, the Cloud networking aspect is a critical factor for adopting the Cloud computing approach. The main drawback of Cloud networking consists in the lack of Quality of Service (QoS) guarantee and management in conformance with a corresponding Service Level Agreement (SLA). This paper presents a framework for resource allocation according to an end-to-end SLA established between a Cloud Service User (CSU) and several Cloud Service Providers (CSPs) in a Cloud networking environment. We focus on QoS parameters for Network as a Service (NaaS) and Infrastructure as a Service (IaaS) services. In addition, we propose algorithms for the best CSPs selection to allocate Vi…
A validity and reliability study of Conditional Entropy Measures of Pulse Rate Variability
2019
In this work, we present the feasibility to use a simpler methodological approach for the assessment of the short-term complexity of Heart Rate Variability (HRV). Specifically, we propose to exploit Pulse Rate Variability (PRV) recorded through photoplethysmography in place of HRV measured from the ECG, and to compute complexity via a linear Gaussian approximation in place of the standard model-free methods (e.g., nearest neighbor entropy estimates) usually applied to HRV. Linear PRV-based and model-free HRV-based complexity measures were compared via statistical tests, correlation analysis and Bland-Altman plots, demonstrating an overall good agreement. These results support the applicabil…
Selecting students for medical school: What predicts success during basic science studies? A cognitive approach
1996
This study focuses on differences between multiple-choice science tests and a learning-from-text (LFT) test, and how these tests predict success in basic medical studies. The subjects (N = 503) were applicants to the Helsinki University Medical Faculty. All of them had to take an entrance examination in order to be considered for admission to a 6-year study programme combining medical school and graduate studies. The entrance examination consisted of three traditional multiple-choice science tests and one LFT test, the latter designed to measure deep-level processing of text. A follow-up study was conducted in order to see how the different tasks were related to the grades and pace of study…
Hybrid Deep Shallow Network for Assessment of Depression Using Electroencephalogram Signals
2020
Depression is a mental health disorder characterised by persistently depressed mood or loss of interest in activities resulting impairment in daily life significantly. Electroencephalography (EEG) can assist with the accurate diagnosis of depression. In this paper, we present two different hybrid deep learning models for classification and assessment of patient suffering with depression. We have combined convolutional neural network with Gated recurrent units (RGUs), thus the proposed network is shallow and much smaller in size in comparison to its counter LSTM network. In addition to this, proposed approach is less sensitive to parameter settings. Extensive experiments on EEG dataset shows…
Effect of high hydrostatic pressure on extraction of B-phycoerythrin from Porphyridium cruentum: Use of confocal microscopy and image processing
2019
International audience; The aim of the study was to extract B-phycoerythrin from Porphyridium cruentum while preserving its structure. The high hydrostatic pressure treatments were chosen as extraction technology. Different methods have been used to observe the effects of the treatment: spectrophotometry and confocal laser scanning microscopy followed by image processing analysis. Image processing led to the generation of masks used for the identification of three clusters: intra, extra and intercellular. All methods showed that high hydrostatic pressure treatments between 50 and 500 MPa failed to extract B-phycoerythrin from Porphyridium cruentum cells. The fluorescence emission was negati…
Optimality Conditions for Non-Qualified Parabolic Control Problems
1994
We consider parabolic state constrained optimal control problems where the usual Slater condition is not necessarily satisfied. Instead, a weaker interiority property is assumed. Optimality conditions with a Lagrange multiplier are given. As an application we present an augmented Lagrangian algorithm. Numerical test results are included.
A Mathematical Model for Vehicle-Occupant Frontal Crash Using Genetic Algorithm
2016
In this paper, a mathematical model for vehicle-occupant frontal crash is developed. The developed model is represented as a double-spring-mass-damper system, whereby the front mass and the rear mass represent the vehicle chassis and the occupant, respectively. The springs and dampers in the model are nonlinear piecewise functions of displacements and velocities respectively. More specifically, a genetic algorithm (GA) approach is proposed for estimating the parameters of vehicle front structure and restraint system. Finally, it is shown that the obtained model can accurately reproduce the real crash test data taken from the National Highway Traffic Safety Administration (NHTSA). The maximu…
Scalable implementation of measuring distances in a Riemannian manifold based on the Fisher Information metric
2019
This paper focuses on the scalability of the Fisher Information manifold by applying techniques of distributed computing. The main objective is to investigate methodologies to improve two bottlenecks associated with the measurement of distances in a Riemannian manifold formed by the Fisher Information metric. The first bottleneck is the quadratic increase in the number of pairwise distances. The second is the computation of global distances, approximated through a fully connected network of the observed pairwise distances, where the challenge is the computation of the all sources shortest path (ASSP). The scalable implementation for the pairwise distances is performed in Spark. The scalable…
Prediction of Vehicle Crashworthiness Parameters Using Piecewise Lumped Parameters and Finite Element Models
2018
Estimating the vehicle crashworthiness parameters experimentally is expensive and time consuming. For these reasons different modelling approaches are utilized to predict the vehicle behaviour and reduce the need for full-scale crash testing. The earlier numerical methods used for vehicle crashworthiness analysis were based on the use of lumped parameters models (LPM), a combination of masses and nonlinear springs interconnected in various configurations. Nowadays, the explicit nonlinear finite element analysis (FEA) is probably the most widely recognized modelling technique. Although informative, finite element models (FEM) of vehicle crash are expensive both in terms of man-hours put into…
Accelerated bearing life-Time test rig development for low speed data acquisition
2017
Condition monitoring plays an important role in rotating machinery to ensure reliability of the equipment, and to detect fault conditions at an early stage. Although health monitoring methodologies have been thoroughly developed for rotating machinery, low-speed conditions often pose a challenge due to the low signal-to-noise ratio. To this aim, sophisticated algorithms that reduce noise and highlight the bearing faults are necessary to accurately diagnose machines undergoing this condition. In the development phase, sensor data from a healthy and damaged bearing rotating at low-speed is required to verify the performance of such algorithms. A test rig for performing accelerated life-time t…