Grain size analysis of sediment core GeoB1510-2

Detailed information about the sediment properties and microstructure can be provided through the analysis of digital ultrasonic P wave seismograms recorded automatically during full waveform core logging. The physical parameter which predominantly affects the elastic wave propagation in water-saturated sediments is the P wave attenuation coefficient. The related sedimentological parameter is the grain size distribution. A set of high-resolution ultrasonic transmission seismograms (-50-500 kHz), which indicate downcore variations in the grain size by their signal shape and frequency content, are presented. Layers of coarse-grained foraminiferal ooze can be identified by highly attenuated P waves, whereas almost unattenuated waves are recorded in fine-grained areas of nannofossil ooze. Color -encoded pixel graphics of the seismograms and instantaneous frequencies present full waveform images of the lithology and attenuation. A modified spectral difference method is introduced to determine the attenuation coefficient and its power law a = kF. Applied to synthetic seismograms derived using a "constant Q" model, even low attenuation coefficients can be quantified. A downcore analysis gives an attenuation log which ranges from -700 dB/m at 400 kHz and a power of n=1-2 in coarse-grained sands to few decibels per meter and n :s; 0.5 in fine-grained clays. A least squares fit of a second degree polynomial describes the mutual relationship between the mean grain size and the attenuation coefficient. When it is used to predict the mean grain size, an almost perfect coincidence with the values derived from sedimentological measurements is achieved.

Supply chain collaboration and responsiveness : a comparison between Thai automotive and electronics industries

This paper examines factors that promote firms to develop supply chain collaborations (SCC) with their partners and relationships between SCC and supply chain operational performances (SCOP), using a questionnaire survey on Thai automotive and electronics industries in 2012. This paper also carries out a comparative study on these questions between the electronics and automotive industries. Two-stage least squares (2SLS) regressions verifY that supplier evaluation and audit is a foundation for firms to share information and synchronize decision makings with their partners, and that such SCC are significantly related to SCOP indictors such as on-time delivery, fast procurement, and flexibility to customer need irrespective of industry type. On the other hand, competitive pressure motivates only electronics firms to develop sec in order to be more innovative.

A set of canonical problems in sloshing. Part 0: Experimental setup and data processing

In a series of attempts to research and document relevant sloshing type phenomena, a series of experiments have been conducted. The aim of this paper is to describe the setup and data processing of such experiments. A sloshing tank is subjected to angular motion. As a result pressure registers are obtained at several locations, together with the motion data, torque and a collection of image and video information. The experimental rig and the data acquisition systems are described. Useful information for experimental sloshing research practitioners is provided. This information is related to the liquids used in the experiments, the dying techniques, tank building processes, synchronization of acquisition systems, etc. A new procedure for reconstructing experimental data, that takes into account experimental uncertainties, is presented. This procedure is based on a least squares spline approximation of the data. Based on a deterministic approach to the first sloshing wave impact event in a sloshing experiment, an uncertainty analysis procedure of the associated first pressure peak value is described.

Performance of artificial neural networks and genetical evolved artificial neural networks unfolding techniques

With the Bonner spheres spectrometer neutron spectrum is obtained through an unfolding procedure. Monte Carlo methods, Regularization, Parametrization, Least-squares, and Maximum Entropy are some of the techniques utilized for unfolding. In the last decade methods based on Artificial Intelligence Technology have been used. Approaches based on Genetic Algorithms and Artificial Neural Networks have been developed in order to overcome the drawbacks of previous techniques. Nevertheless the advantages of Artificial Neural Networks still it has some drawbacks mainly in the design process of the network, vg the optimum selection of the architectural and learning ANN parameters. In recent years the use of hybrid technologies, combining Artificial Neural Networks and Genetic Algorithms, has been utilized to. In this work, several ANN topologies were trained and tested using Artificial Neural Networks and Genetically Evolved Artificial Neural Networks in the aim to unfold neutron spectra using the count rates of a Bonner sphere spectrometer. Here, a comparative study of both procedures has been carried out.

Markov blanket-based approach for learning multi-dimensional Bayesian network classifiers: An application to predict the European Quality of Life-5 Dimensions (EQ-5D) from the 39-item Parkinson's Disease Questionnaire (PDQ-39)

Multi-dimensional Bayesian network classifiers (MBCs) are probabilistic graphical models recently proposed to deal with multi-dimensional classification problems, where each instance in the data set has to be assigned to more than one class variable. In this paper, we propose a Markov blanket-based approach for learning MBCs from data. Basically, it consists of determining the Markov blanket around each class variable using the HITON algorithm, then specifying the directionality over the MBC subgraphs. Our approach is applied to the prediction problem of the European Quality of Life-5 Dimensions (EQ-5D) from the 39-item Parkinson’s Disease Questionnaire (PDQ-39) in order to estimate the health-related quality of life of Parkinson’s patients. Fivefold cross-validation experiments were carried out on randomly generated synthetic data sets, Yeast data set, as well as on a real-world Parkinson’s disease data set containing 488 patients. The experimental study, including comparison with additional Bayesian network-based approaches, back propagation for multi-label learning, multi-label k-nearest neighbor, multinomial logistic regression, ordinary least squares, and censored least absolute deviations, shows encouraging results in terms of predictive accuracy as well as the identification of dependence relationships among class and feature variables.

Bernstein polynomials in element-free Galerkin method

In the recent decades, meshless methods (MMs), like the element-free Galerkin method (EFGM), have been widely studied and interesting results have been reached when solving partial differential equations. However, such solutions show a problem around boundary conditions, where the accuracy is not adequately achieved. This is caused by the use of moving least squares or residual kernel particle method methods to obtain the shape functions needed in MM, since such methods are good enough in the inner of the integration domains, but not so accurate in boundaries. This way, Bernstein curves, which are a partition of unity themselves,can solve this problem with the same accuracy in the inner area of the domain and at their boundaries.

Prediction of near field overpressure from quarry blasting

This paper investigates the propagation of airblast or pressure waves in air produced by bench blasting (i.e. detonation of the explosive in a row of blastholes, breaking the burden of rock towards the free vertical face of the block). Peak overpressure is calculated as a function of blasting parameters (explosive mass per delay and velocity at which the detonation sequence proceeds along the bench) and the polar coordinates of the position of interest (distance to the source and azimuth with respect to the free face). The model has been fitted to empirical data using linear least squares. The data set is composed of 122 airblast records monitored at distances less than 400 m in 41 production blasts carried out in two quarries. The model is statistically significant and has a determination coefficient of 0.87. The formula is validated from 12 airblast measurements gathered in five additional blasts.

Examination of the quality of spinach leaves using hyperspectral imaging

The present research is focused on the application of hyperspectral images for the supervision of quality deterioration in ready to use leafy spinach during storage (Spinacia oleracea). Two sets of samples of packed leafy spinach were considered: (a) a first set of samples was stored at 20 °C (E-20) in order to accelerate the degradation process, and these samples were measured the day of reception in the laboratory and after 2 days of storage; (b) a second set of samples was kept at 10 °C (E-10), and the measurements were taken throughout storage, beginning the day of reception and repeating the acquisition of Images 3, 6 and 9 days later. Twenty leaves per test were analyzed. Hyperspectral images were acquired with a push-broom CCD camera equipped with a spectrograph VNIR (400–1000 nm). Calibration set of spectra was extracted from E-20 samples, containing three classes of degradation: class A (optimal quality), class B and class C (maximum deterioration). Reference average spectra were defined for each class. Three models, computed on the calibration set, with a decreasing degree of complexity were compared, according to their ability for segregating leaves at different quality stages (fresh, with incipient and non-visible symptoms of degradation, and degraded): spectral angle mapper distance (SAM), partial least squares discriminant analysis models (PLS-DA), and a non linear index (Leafy Vegetable Evolution, LEVE) combining five wavelengths were included among the previously selected by CovSel procedure. In sets E-10 and E-20, artificial images of the membership degree according to the distance of each pixel to the reference classes, were computed assigning each pixel to the closest reference class. The three methods were able to show the degradation of the leaves with storage time.

Robust regression applied to fractal/multifractal analysis.

Fractal and multifractal are concepts that have grown increasingly popular in recent years in the soil analysis, along with the development of fractal models. One of the common steps is to calculate the slope of a linear fit commonly using least squares method. This shouldn?t be a special problem, however, in many situations using experimental data the researcher has to select the range of scales at which is going to work neglecting the rest of points to achieve the best linearity that in this type of analysis is necessary. Robust regression is a form of regression analysis designed to circumvent some limitations of traditional parametric and non-parametric methods. In this method we don?t have to assume that the outlier point is simply an extreme observation drawn from the tail of a normal distribution not compromising the validity of the regression results. In this work we have evaluated the capacity of robust regression to select the points in the experimental data used trying to avoid subjective choices. Based on this analysis we have developed a new work methodology that implies two basic steps: ? Evaluation of the improvement of linear fitting when consecutive points are eliminated based on R pvalue. In this way we consider the implications of reducing the number of points. ? Evaluation of the significance of slope difference between fitting with the two extremes points and fitted with the available points. We compare the results applying this methodology and the common used least squares one. The data selected for these comparisons are coming from experimental soil roughness transect and simulated based on middle point displacement method adding tendencies and noise. The results are discussed indicating the advantages and disadvantages of each methodology.

Automatic detection of crop rows in maize fields with high weeds pressure

This paper proposes a new method, oriented to crop row detection in images from maize fields with high weed pressure. The vision system is designed to be installed onboard a mobile agricultural vehicle, i.e. submitted to gyros, vibrations and undesired movements. The images are captured under image perspective, being affected by the above undesired effects. The image processing consists of three main processes: image segmentation, double thresholding, based on the Otsu’s method, and crop row detection. Image segmentation is based on the application of a vegetation index, the double thresholding achieves the separation between weeds and crops and the crop row detection applies least squares linear regression for line adjustment. Crop and weed separation becomes effective and the crop row detection can be favorably compared against the classical approach based on the Hough transform. Both gain effectiveness and accuracy thanks to the double thresholding that makes the main finding of the paper.

Ab initio calculations of Ca III Stark broadening parameters,transition probabilities and radiative lifetimes

We have determined matrix elements for all experimental configurations of Ca III, including the 3s3p63d configuration. These values have been obtained using intermediate coupling (IC). For these IC calculations, we have used the standard method of least-squares fitting from the experimental energy levels, using the computer code developed by Robert Cowan. In this paper, using these matrix elements, we report the calculated values of the Ca III Stark widths and shifts for 148 spectral lines, of 56 Ca III spectral line transition probabilities and of eight radiative lifetimes of Ca III levels. The Stark widths and shifts, calculated using the Griem semi-empirical approach, correspond to the spectral lines of Ca III and are presented for an electron density of 1017 cm?3 and temperatures T = 1.0?10.0 (×104 K). The theoretical trends of the Stark broadening parameter versus the temperature are presented for transitions that are of astrophysical interest. There is good agreement between our calculations, for transition probabilities and radiative lifetimes, and the experimental values presented in the literature. We have not been able to find any values for the Stark parameters in the references.

Theoretical Stark broadening parameters for spectral lines arising from the 2p5ns, 2p5np and 2p5nd electronic configurations of MgIII

In the present work we report theoretical Stark widths and shifts calculated using the Griem semi-empirical approach, corresponding to 237 spectral lines of MgIII. Data are presented for an electron density of 1017 cm?3 and temperatures T = 0.5?10.0 (104 K). The matrix elements used in these calculations have been determined from 23 configurations of MgIII: 2s22p6, 2s22p53p, 2s22p54p, 2s22p54f and 2s22p55f for even parity and 2s22p5ns (n = 3?6), 2s22p5nd (n = 3?9), 2s22p55g and 2s2p6np (n = 3?8) for odd parity. For the intermediate coupling (IC) calculations, we use the standard method of least-squares fitting from experimental energy levels by means of the Cowan computer code. Also, in order to test the matrix elements used in our calculations, we present calculated values of 70 transition probabilities of MgIII spectral lines and 14 calculated values of radiative lifetimes of MgIII levels. There is good agreement between our calculations and experimental radiative lifetimes. Spectral lines of MgIII are relevant in astrophysics and also play an important role in the spectral analysis of laboratory plasma. Theoretical trends of the Stark broadening parameter versus the temperature for relevant lines are presented. No values of Stark parameters can be found in the bibliography.

On-line measurement of soil properties without direct spectral response in near infrared spectral range

So far, the majority of reports on on-line measurement considered soil properties with direct spectral responses in near infrared spectroscopy (NIRS). This work reports on the results of on-line measurement of soil properties with indirect spectral responses, e.g. pH, cation exchange capacity (CEC), exchangeable calcium (Caex) and exchangeable magnesium (Mgex) in one field in Bedfordshire in the UK. The on-line sensor consisted of a subsoiler coupled with an AgroSpec mobile, fibre type, visible and near infrared (vis–NIR) spectrophotometer (tec5 Technology for Spectroscopy, Germany), with a measurement range 305–2200 nm to acquire soil spectra in diffuse reflectance mode. General calibration models for the studied soil properties were developed with a partial least squares regression (PLSR) with one-leave-out cross validation, using spectra measured under non-mobile laboratory conditions of 160 soil samples collected from different fields in four farms in Europe, namely, Czech Republic, Denmark, Netherland and UK. A group of 25 samples independent from the calibration set was used as independent validation set. Higher accuracy was obtained for laboratory scanning as compared to on-line scanning of the 25 independent samples. The prediction accuracy for the laboratory and on-line measurements was classified as excellent/very good for pH (RPD = 2.69 and 2.14 and r2 = 0.86 and 0.78, respectively), and moderately good for CEC (RPD = 1.77 and 1.61 and r2 = 0.68 and 0.62, respectively) and Mgex (RPD = 1.72 and 1.49 and r2 = 0.66 and 0.67, respectively). For Caex, very good accuracy was calculated for laboratory method (RPD = 2.19 and r2 = 0.86), as compared to the poor accuracy reported for the on-line method (RPD = 1.30 and r2 = 0.61). The ability of collecting large number of data points per field area (about 12,800 point per 21 ha) and the simultaneous analysis of several soil properties without direct spectral response in the NIR range at relatively high operational speed and appreciable accuracy, encourage the recommendation of the on-line measurement system for site specific fertilisation.

Predicción de la ley de atenuación, frecuencia dominante y espectro de respuesta en vibraciones producidas por voladuras a cielo abierto

El presente proyecto de fin de carrera describe y analiza el estudio integral del efecto de las vibraciones producidas por voladuras superficiales realizadas en el proyecto del “Tercer Juego de Esclusas” ejecutado para la Expansión del Canal de Panamá. Se recopilan un total de 53 registros, data generada por el monitoreo de 7 sismógrafos en 10 voladuras de producción realizadas en el año 2010. El fenómeno vibratorio tiene dos parámetros fundamentales, la velocidad pico-partícula (PPV) y la frecuencia dominante, los cuales caracterizan cuan dañino puede ser éste frente a su influencia sobre las estructuras civiles; por ello, se pretende caracterizarlas y fundamentalmente predecirlas, lo que permitirá su debido control. En función a lo expuesto, el estudio realizado consta de dos partes, la primera describe el comportamiento del terreno mediante la estimación de la ley de atenuación de la velocidad pico-partícula a través del uso de la regresión lineal por mínimos cuadrados; la segunda detalla un procedimiento validable para la predicción de la frecuencia dominante y del pseudo-espectro de respuesta de velocidad (PVRS) basada en la teoría de Newmark & Hall. Se ha obtenido: (i) la ley de atenuación del terreno para distintos grados de fiabilidad, (ii) herramientas de diseño de voladuras basadas en la relación de carga – distancia, (iii) la demostración que los valores de PPV se ajustan a una distribución log-normal, (iv) el mapa de isolíneas de PPV para el área de estudio, (v) una técnica detallada y válida para la predicción de la frecuencia dominante y del espectro de respuesta, (vi) formulaciones matemáticas de los factores de amplificación para el desplazamiento, velocidad y aceleración, (vii) mapa de isolíneas de amplificación para el área de estudio. A partir de los resultados obtenidos se proporciona información útil para su uso en el diseño y control de las voladuras posteriores del proyecto. ABSTRACT This project work describes and analyzes the comprehensive study of the effect of the vibrations produced by surface blasting carried out in the "Third Set of Locks" project executed for the expansion of the Panama Canal. A total of 53 records were collected, with the data generated by the monitoring of 7 seismographs in 10 production blasts carried out in 2010. The vibratory phenomenon has two fundamental parameters, the peak-particle velocity (PPV) and the dominant frequency, which characterize how damaging this can be compared to their influence on structures, which is why this is intended to characterize and predict fundamentally, that which allows proper control. Based on the above, the study consists of two parts; the first describes the behavior of the terrain by estimating the attenuation law for peak-particle velocity by using the ordinary least squares regression analysis, the second details a validable procedure for the prediction of the dominant frequency and pseudo-velocity response spectrum (PVRS) based on the theory of Newmark & Hall. The following have been obtained: (i) the attenuation law of the terrain for different degrees of reliability, (ii) blast design tools based on charge-distance ratio, (iii) the demonstration that the values of PPV conform to a log-normal distribution, (iv) the map of isolines of PPV for the area of study (v) detailed and valid technique for predicting the dominant frequency response spectrum, (vi) mathematical formulations of the amplification factors for displacement, velocity and acceleration, (vii) amplification of isolines map for the study area. From the results obtained, the study provides useful information for use in the design and control of blasting for subsequent projects.