High-order spectra-based deconvolution of ultrasonic NDT signals for defect identification

In ultrasonic nondestructive testing (NDT) of materials, pulse-echo measurements are masked by the characteristics of the measuring instruments, the propagation paths taken by the ultrasonic pulses, and noise. This measured pulse-echo signal is modeled by the convolution of the defect impulse response and the measurement system response, added to noise. The deconvolution operation, therefore, seeks to undo the effect of the convolution and extract the defect impulse response which is essential for defect identification. In this contribution, we show that the defect ultrasonic model can be formulated in the higher order-spectra (HOS) domain in which the processing is more suitable to unravel the effect of the measurement system and the additive Gaussian noise. In addition, a new technique is developed to faithfully recover the impulse response signal from its HOS. Synthesized ultrasonic signals as well as real signals obtained from artificial defects are used to show that the proposed technique is superior to conventional second-order statistics-based deconvolution techniques commonly used in NDT

The Agile UX Development Lifecycle: Combining Formative Usability and Agile Methods

This paper contributes a method variation that helps cross-functional teams combine both formative usability and agile methods to develop interactive systems. Both methods are iterative, continuous and focus on delivering value to users, which makes their combination possible. The “agile UX development lifecycle” supports and facilitates the synchronization of the steps involved in both formative usability and agile sprints in an operable manner and is intended for design and development settings. We present a case study that illustrates the extent to which this tool meets the needs of real-world cross-functional teams, describing the gains in efficiency it can provide but also guidelines for increasing the benefits gained from this combination in design and development settings

Arabic Handwriting Synthesis

Training and testing data for optical character recognition are cumbersome to obtain. If large amounts of data can be produced from small amounts, much time and effort can be saved. This paper presents an approach to synthesize Arabic handwriting. We segment word images into labeled characters and then use these in synthesizing arbitrary words. The synthesized text should look natural; hence, we define some criteria to decide on what is acceptable as natural-looking. The text that is synthesized by using the natural-looking constrain is compared to text that is synthesized without using the natural-looking constrain for evaluation

ThinResNet: A New Baseline for Structured Convolutional Networks Pruning

Pruning is a compression method which aims to improve the efficiency of neural networks by reducing their number of parameters while maintaining a good performance, thus enhancing the performance-to-cost ratio in nontrivial ways. Of particular interest are structured pruning techniques, in which whole portions of parameters are removed altogether, resulting in easier to leverage shrunk architectures. Since its growth in popularity in the recent years, pruning gave birth to countless papers and contributions, resulting first in critical inconsistencies in the way results are compared, and then to a collective effort to establish standardized benchmarks. However, said benchmarks are based on training practices that date from several years ago and do not align with current practices. In this work, we verify how results in the recent literature of pruning hold up against networks that underwent both state-of-the-art training methods and trivial model scaling. We find that the latter clearly and utterly outperform all the literature we compared to, proving that updating standard pruning benchmarks and re-evaluating classical methods in their light is an absolute necessity. We thus introduce a new challenging baseline to compare structured pruning to: ThinResNet.Comment: 11 pages, 2 figures, 3 table

Determination of the total acid number (TAN) of used mineral oils in aviation engines by FTIR using regression models

[EN] Total acid number (TAN) has been considered an important indicator of the oil quality of used oils. TAN is determined by potentiometric titration, which is time-consuming and requires solvent. A more convenient approach to determine TAN is based on infrared (IR) spectral data and multivariate regression models. Predictive models for the determination of TAN using the IR data measured from ashless dispersant oils developed for aviation piston engines (SAE 50) have been developed. Different techniques, including Projection Pursuit Regression (PPR), Partial Least Square, Support Vector Machines, Linear Models and Random Forest (RF), have been used. The used methodology involved a five folder cross validation to derive the best model. Then a full error measure over the whole dataset was taken. A backward variable selection was used and 25 highly relevant variables were extracted. RF provided an acceptable modelling technology with grouped dataset predictions that allowed transformations to be performed that fitted the measured values. A hybrid method considering group of bands as features was used for modelling. An innovative mechanism for wider features selection based on genetic algorithm has been implemented. This method showed better performance than the results obtained using the other methodologies. RMSE and MAE values obtained in the validation were 0.759 and 0.359 for PPR model respectively.The authors would like to thank Roland Tones of the Universidad Metropolitana for his collaboration in oil sample processing. BLDR acknowledges financial support from the Venoco Company. The authors also thank the Universidad Politecnica de Madrid for granting access to the CESVIMA (http://www.cesvima.upm.es/) HPC infrastructure. We would also like to thank the author Beatriz Leal de Rivas (in memoriam), for her efforts to conform this team of researchers from different areas of expertise, and we want to dedicate this work to her loving memory.Leal De-Rivas, BC.; Vivancos, J.; Ordieres Meré, J.; Capuz-Rizo, SF. (2017). Determination of the total acid number (TAN) of used mineral oils in aviation engines by FTIR using regression models. Chemometrics and Intelligent Laboratory Systems. 160:32-39. doi:10.1016/j.chemolab.2016.10.015S323916

An Efficient Iris Segmentation Technique based on a Multiscale Approach

The use of biometric signatures, instead of tokens such as identification cards or computer passwords, continues to gain increasing attention as an efficient means of identification and verification of individuals for controlling access to secured areas, materials, or systems and a wide variety of biometrics has been considered over the years in support of these challenges. Iris recognition is especially attractive due to the stability of the iris texture patterns with age and health conditions. Iris image segmentation and localisation is a key step in iris recognition and plays an essential role the accuracy of matching. In this paper, we propose a new iris segmentation technique using a multiscale approach for edge detection, which is a fundamental issue in image analysis. Due to the presence of speckles, which can be modelled as a a strong multiplicative noise, edge detection for iris segmentation is very important and methods developed so far are generally applied in one single scale. In our proposed method, we introduce the concept of multiscale edge detection to improve iris segmentation. The technique is effecient for edge detetcion, greatly reduces the search space for the Hough transform and at the same time is robust to noise thus improving the overall performance. Linear Hough transform has been used for eyelids isolation, and an adaptive thresholding has been used for isolating eyelashes. Once the iris is segmented, a normalization step has been carried out by converting an iris image from cartesien into polar coordinates which are more suitable to deal with rotation and translation problems. Extensive experiments have been carried out and results obtained have shown an effectiveness of the proposed method which provides a high segmentation success of 99.6%

ON THE INVESTIGATION OF VIBRATION SIGNALS USING JOINT TIME FREQUENCY ANALYSIS

This paper addresses the problem of coupled blade bending and shaft torsional vibration signals using the Joint Time Frequency Analysis (JTFA). Simulation results for the blade bending and shaft torsional vibration are studied using the Fast Fourier Transform (FFT) and the JTFA. The FFT spectra showed little information on the nonlinear dynamic interaction between the blade bending and the shaft torsional vibration; and thus cannot be used as a tool for monitoring the blade vibration by looking into the shaft torsional vibration signal. In contrast, the JTFA in the form of Wigner Ville Distribution (WVD) has given more useful information and reflected the dynamic interaction between different vibration modes on one side and between the blade vibration and the shaft torsional vibration on the other side. The obtained WVD representations of the shaft torsional vibration showed frequency layers that represent blade vibration activity

SHAFT LATERAL AND TORSIONAL VIBRATION RESPONSES TO BLADE(S) RANDOM VIBRATION EXCITATION

In this study, an experimental set-up for blades-shaft vibration monitoring under blade(s) random vibration excitation is used. The set-up natural frequencies and mode shapes are found using the ANSYS finite element package. The blades and shaft lateral and torsional vibration are monitored using blades strain-gages, bearing accelerometers and shaft torsional strain-gages stations. The results showed that the shaft torsional vibration measurement represents the blade(s) vibration more closely than the bearing accelerometers. In particular, the blades vibration at low frequencies corresponding to the blades bending and shaft torsional coupled modes is closely represented by the shaft torsional vibration signals. The results of this study increased the confidence in using the torsional vibration measurement for blades vibration identification and shed more light on the nature of coupling between the blade bending and shaft torsional vibration that occur at low frequencies