Experimental analysis for aerodynamic drag of the electric locomotives

The purpose of this paper is to make a comparative analysis on the influence of the aerodynamic drag, in case of the electric rail vehicles for a series of situations encountered in exploitation. The article presents experimental results obtained following a geometric modelling at scale 1: 12, on a modular model for the electric locomotives LE 060EA 5100kW and LE-MA 060 TransMontana 6000kW. Tests were made at INCAS (National Institute for Aerospace Research “ElieCarafoli”) in the subsonic wind tunnel

Computational Techniques in Multispectral Image Processing : Application to the Syriac Galen Palimpsest

Multispectral and hyperspectral image analysis has experienced much development in the last decade. The application of these methods to palimpsests has produced significant results, enabling researchers to recover texts that would be otherwise lost under the visible overtext, by improving the contrast between the undertext and the overtext. In this paper we explore an extended number of multispectral and hyperspectral image analysis methods, consisting of supervised and unsupervised dimensionality reduction techniques, on a part of the Syriac Galen Palimpsest dataset (www.digitalgalen.net). Of this extended set of methods, eight methods gave good results: three were supervised methods Generalized Discriminant Analysis (GDA), Linear Discriminant Analysis (LDA), and Neighborhood Component Analysis (NCA); and the other five methods were unsupervised methods (but still used in a supervised way) Gaussian Process Latent Variable Model (GPLVM), Isomap, Landmark Isomap, Principal Component Analysis (PCA), and Probabilistic Principal Component Analysis (PPCA). The relative success of these methods was determined visually, using color pictures, on the basis of whether the undertext was distinguishable from the overtext, resulting in the following ranking of the methods: LDA, NCA, GDA, Isomap, Landmark Isomap, PPCA, PCA, and GPLVM. These results were compared with those obtained using the Canonical Variates Analysis (CVA) method on the same dataset, which showed remarkably accuracy (LDA is a particular case of CVA where the objects are classified to two classes).Comment: 29 February - 2 March 2016, Second International Conference on Natural Sciences and Technology in Manuscript Analysis, Centre for the study of Manuscript Cultures, Hamburg, German

Impact of demand side response on a commercial retail refrigeration system

The UK National Grid has placed increased emphasis on the development of Demand Side Response (DSR) tariff mechanisms to manage load at peak times. Refrigeration systems, along with HVAC, are estimated to consume 14% of the UK’s electricity and could have a significant role for DSR application. However, characterized by relatively low individual electrical loads and massive asset numbers, multiple low power refrigerators need aggregation for inclusion in these tariffs. In this paper, the impact of the Demand Side Response (DSR) control mechanisms on food retailing refrigeration systems is investigated. The experiments are conducted in a test-rig built to resemble a typical small supermarket store. The paper demonstrates how the temperature and pressure profiles of the system, the active power and the drawn current of the compressors are affected following a rapid shut down and subsequent return to normal operation as a response to a DSR event. Moreover, risks and challenges associated with primary and secondary Firm Frequency Response (FFR) mechanisms, where the load is rapidly shed at high speed in response to changes in grid frequency, is considered. For instance, measurements are included that show a significant increase in peak inrush currents of approx. 30% when the system returns to normal operation at the end of a DSR event. Consideration of how high inrush currents after a DSR event can produce voltage fluctuations of the supply and we assess risks to the local power supply system

Continuing research on the Syriac Galen Palimpsest:Collaborative Implementation within the Framework of Two European Projects

International audienc

High-performance and distributed computing in a probabilistic finite element comparison study of the human lower leg model with total knee replacement

Reliability theory is used to assess the sensitivity of a passive flexion and active flexion of the human lower leg Finite Element (FE) models with Total Knee Replacement (TKR) to the variability in the input parameters of the respective FE models. The sensitivity of the active flexion simulating the stair ascent of the human lower leg FE model with TKR was presented before in [1,2] whereas now in this paper a comparison is made with the passive flexion of the human lower leg FE model with TKR. First, with the Monte Carlo Simulation Technique (MCST), a number of randomly generated input data of the FE model(s) are obtained based on the normal standard deviations of the respective input parameters. Then a series of FE simulations are done and the output kinematics and peak contact pressures are obtained for the respective FE models (passive flexion and/or active flexion models). Seven output performance measures are reported for the passive flexion model and one more parameter was reported for the active flexion FE model (patello-femoral peak contact pressure) in [1]. A sensitivity study will be implemented based on the Response Surface Method (RSM) to identify the key parameters that influence the kinematics and peak contact pressures of the passive flexion FE model. Another two MCST and RSM-based probabilistic FE analyses will be performed based on a reduced list of 19 key input parameters. In total 4 probabilistic FE analyses will be performed: 2 probabilistic FE analyses (MCST and RSM) based on an extended set of 78 input variables and another 2 probabilistic FE analyses (MCST and RSM) based on a reduced set of 19 input variables. Due to the likely computation cost in order to make hundreds of FE simulations with MCST, a High-Performance and Distributed Computing (HPDC) system will be used for the passive flexion FE model the same as it was used for the active flexion FE model in [1].</p

Revealing the Palimpsest

An article published in the New York Times on June 1, 2015, described the discovery of a Syriac manuscript that contained the oldest known translation of Galen's On the Mixtures and Powers of Simple Drugs. The text of this manuscript was erased in the eleventh century. Scientists and scholars from around the world are working to recover it. This symposium featured the manuscript itself and presentations by imaging specialists, Syriac scholars, and historians of medicine working to reveal the secrets of this challenging manuscript. Session 4 - Part

Complex Deep Learning Models for Denoising of Human Heart ECG signals

Effective and powerful methods for denoising real electrocardiogram (ECG) signals are important for wearable sensors and devices. Deep Learning (DL) models have been used extensively in image processing and other domains with great success but only very recently have been used in processing ECG signals. This paper presents several DL models namely Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM), Restricted Boltzmann Machine (RBM) together with the more conventional filtering methods (low pass filtering, high pass filtering, Notch filtering) and the standard wavelet-based technique for denoising EEG signals. These methods are trained, tested and evaluated on different synthetic and real ECG datasets taken from the MIT PhysioNet database and for different simulation conditions (i.e. various lengths of the ECG signals, single or multiple records). The results show the CNN model is a performant model that can be used for off-line denoising ECG applications where it is satisfactory to train on a clean part of an ECG signal from an ECG record, and then to test on the same ECG signal, which would have some high level of noise added to it. However, for real-time applications or near-real time applications, this task becomes more cumbersome, as the clean part of an ECG signal is very probable to be very limited in size. Therefore the solution put forth in this work is to train a CNN model on 1 second ECG noisy artificial multiple heartbeat data (i.e. ECG at effort), which was generated in a first instance based on few sequences of real signal heartbeat ECG data (i.e. ECG at rest). Afterwards it would be possible to use the trained CNN model in real life situations to denoise the ECG signal.Comment: 51 pages, 23 figure

Modelling and Simulation of Water Networks based on Least Square Loop Flows State Estimator

<p>Modelling and Simulation of Water Networks based on Least Square Loop Flows State Estimator</p> <p>This Matlab software implements the Least Squares state estimator described in the below papers and which state estimator is based on the loop corrective flows and the variation of nodal demands as independent variables.</p> <ol> <li> <p>Corneliu T.C. Arsene, "Uncertainty Quantification of Water Distribution System Measurement Data based on a Least Squares Loop Flows State Estimator", arXiv:1701.03147, https://arxiv.org/abs/1701.03147, 2017.</p> </li> <li> <p>Corneliu T.C. Arsene, Bogdan Gabrys, “Mixed simulation-state estimation in water distribution systems based on a least squares loop flows state estimator”, Applied Mathematical Modelling, DOI 10.1016/ j.apm.2013.06.012 , 2014.</p> </li> <li> <p>Corneliu T. C. Arsene, Bogdan Gabrys, David Al-Dabass: Decision support system for water distribution systems based on neural networks and graphs theory for leakage detection. Expert Syst. Appl. 39(18): 13214-13224, 2012.</p> </li> <li> <p>Arsene, C.T.C., Bargiela, A., and Al-Dabass, D. “Modelling and Simulation of Network Systems based on Loop Flows Algorithms”, Int. J. of Simulation: Systems,Science & Technology Vol.5, No. 1 & 2, pp61-72, June 2004.</p> </li> <li> <p>Arsene, C.T.C., & Bargiela, A., “Decision support for forecasting and fault diagnosis in water distribution systems – robust loop flows state estimation technique”, In Water Software Systems: theory and applications, Research Studies Press Ltd., UK, Vol. 1, pp. 133-145, 2001.</p> </li> <li> <p>Arsene, C.T.C., Bargiela, A., Al-Dabass, D., “Simulation of Network Systems based on Loop Flows Algorithms”, In the proceedings of the 7th Simulation Society Conference - UKSim 2004, Oxford, U.K., 2004, ISBN 1-84233-099-3, UKSIM-2004.</p> </li> </ol> <p>Please acknowledge the PhD project financed by the Nottingham Trent University of United Kingdom and Mr Corneliu Arsene if you are going to use this software anywhere in your work. This is in addition to the license for this software which is in a different file.</p> <p>It is provided here with no warranty. Direct all questions and requests to [email protected]. Technical details (not to be confused by the name of the files):</p