Computer techniques towards the automatic characterization of graphite particles in metallographic images of industrial materials

The automatic characterization of particles in metallographic images has been paramount, mainly because of the importance of quantifying such microstructures in order to assess the mechanical properties of materials common used in industry. This automated characterization may avoid problems related with fatigue and possible measurement errors. In this paper, computer techniques are used and assessed towards the accomplishment of this crucial industrial goal in an efficient and robust manner. Hence, the use of the most actively pursued machine learning classification techniques. In particularity, Support Vector Machine, Bayesian and Optimum-Path Forest based classifiers, and also the Otsu's method, which is commonly used in computer imaging to binarize automatically simply images and used here to demonstrated the need for more complex methods, are evaluated in the characterization of graphite particles in metallographic images. The statistical based analysis performed confirmed that these computer techniques are efficient solutions to accomplish the aimed characterization. Additionally, the Optimum-Path Forest based classifier demonstrated an overall superior performance, both in terms of accuracy and speed. © 2012 Elsevier Ltd. All rights reserved.

Evaluation via multivariate techniques of scale factor variability in the rietveld method applied to quantitative phase analysis with X ray powder diffraction

ABSTRACT: The present work uses multivariate statistical analysis as a form of establishing the main sources of error in the Quantitative Phase Analysis (QPA) using the Rietveld method. The quantitative determination of crystalline phases using x ray powder diffraction is a complex measurement process whose results are influenced by several factors. Ternary mixtures of Al2O3, MgO and NiO were prepared under controlled conditions and the diffractions were obtained using the Bragg-Brentano geometric arrangement. It was possible to establish four sources of critical variations: the experimental absorption and the scale factor of NiO, which is the phase with the greatest linear absorption coefficient of the ternary mixture; the instrumental characteristics represented by mechanical errors of the goniometer and sample displacement; the other two phases (Al2O3 and MgO); and the temperature and relative humidity of the air in the laboratory. The error sources excessively impair the QPA with the Rietveld method. Therefore it becomes necessary to control them during the measurement procedure.

Effect of Sodium Ascorbate on Dentin Bonding After Two Bleaching Techniques

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Evaluation of bond strength and thickness of adhesive layer according to the techniques of applying adhesives in composite resin restorations

Adhesive restorations have increasingly been used in dentistry, and the adhesive system application technique may determine the success of the restorative procedure. The aim of this study was to evaluate the influence of the application technique of two adhesive systems (Clearfil SE Bond and Adper Scotchbond MultiPurpose) on the bond strength and adhesive layer of composite resin restorations. Eight human third molars were selected and prepared with Class I occlusal cavities. The teeth were restored with composite using various application techniques for both adhesives, according to the following groups (n = 10): group 1 (control), systems were applied and adhesive was immediately light activated for 20 seconds without removing excesses; group 2, excess adhesive was removed with a gentle jet of air for 5 seconds; group 3, excess was removed with a dry microbrush-type device; and group 4, a gentle jet of air was applied after the microbrush and then light activation was performed. After this, the teeth were submitted to microtensile testing. For the two systems tested, no statistical differences were observed between groups 1 and 2. Groups 3 and 4 presented higher bond strength values compared with the other studied groups, allowing the conclusion that excess adhesive removal with a dry micro-brush could improve bond strength in composite restorations. Predominance of adhesive fracture and thicker adhesive layer were observed via scanning electron microscopy (SEM) in groups 1 and 2. For groups 3 and 4, a mixed failure pattern and thinner adhesive layer were verified. Clinicians should be aware that excess adhesive may negatively affect bond strength, whereas a thin, uniform adhesive layer appears to be favorable. (Quintessence Int 2013;44:9-15)

Methodological Difficulties of Conducting Agroecological Studies from a Statistical Perspective

Statistical methods for analyzing agroecological data might not be able to help agroecologists to solve all of the current problems concerning crop and animal husbandry, but such methods could well help them assess, tackle, and resolve several agroecological issues in a more reliable and accurate manner. Therefore, our goal in this article is to discuss the importance of statistical tools for alternative agronomic approaches, because alternative approaches, such as organic farming, should not only be promoted by encouraging farmers to deploy agroecological techniques, but also by providing agroecologists with robust analyses based on rigorous statistical procedures.

Biomechanical Study in Polyurethane Mandibles of Different Metal Plates and Internal Fixation Techniques, Employed in Mandibular Angle Fractures

The aim of this study was to perform a physicochemical and morphological characterization and compare the mechanical behavior of an experimental Ti-Mo alloy to the analogous metallic Ti-based fixation system, for mandibular angle fractures. Twenty-eight polyurethane mandibles were uniformly sectioned on the left angle. These were divided into 4 groups: group Eng 1P, one 2.0-mm plate and 4 screws 6 mm long; group Eng 2P, two 2.0-mm plates, the first fixed with 4 screws 6 mm long and the second with 4 screws 12 mm long. The same groups were created for the Ti-15Mo alloy. Each group was subjected to linear vertical loading at the first molar on the plated side in a mechanical testing unit. Means and standard deviations were compared with respect to statistical significance using ANOVA. The chemical composition of the Ti-15Mo alloy was close to the nominal value. The mapping of Mo and Ti showed a homogeneous distribution. SEM of the screw revealed machining debris. For the plates, only the cpTi plate undergoes a surface treatment. The metallographic analysis reveals granular microstructure, from the thermomechanical trials. A statistically significant difference was found (P < 0.05) when the comparison between both internal fixation techniques was performed. The 2P technique showed better mechanical behavior than 1P.

Comparative study on direct and indirect bracket bonding techniques regarding time length and bracket detachment

OBJECTIVE: The aim of this study was to assess the time spent for direct (DBB - direct bracket bonding) and indirect (IBB - indirect bracket bonding) bracket bonding techniques. The time length of laboratorial (IBB) and clinical steps (DBB and IBB) as well as the prevalence of loose bracket after a 24-week follow-up were evaluated. METHODS: Seventeen patients (7 men and 10 women) with a mean age of 21 years, requiring orthodontic treatment were selected for this study. A total of 304 brackets were used (151 DBB and 153 IBB). The same bracket type and bonding material were used in both groups. Data were submitted to statistical analysis by Wilcoxon non-parametric test at 5% level of significance. RESULTS: Considering the total time length, the IBB technique was more time-consuming than the DBB (p < 0.001). However, considering only the clinical phase, the IBB took less time than the DBB (p < 0.001). There was no significant difference (p = 0.910) for the time spent during laboratorial positioning of the brackets and clinical session for IBB in comparison to the clinical procedure for DBB. Additionally, no difference was found as for the prevalence of loose bracket between both groups. CONCLUSION: the IBB can be suggested as a valid clinical procedure since the clinical session was faster and the total time spent for laboratorial positioning of the brackets and clinical procedure was similar to that of DBB. In addition, both approaches resulted in similar frequency of loose bracket.

Response of human pulps to different in-office bleaching techniques: preliminary findings

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

The effect of power-ultrasound on the pretreatment of acidified aqueous solutions of banana flower-stalk: Structural, chemical and statistical analysis

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Statistical analysis of texture in trunk images for biometric identification of tree species

The identification of tree species is a key step for sustainable management plans of forest resources, as well as for several other applications that are based on such surveys. However, the present available techniques are dependent on the presence of tree structures, such as flowers, fruits, and leaves, limiting the identification process to certain periods of the year Therefore, this article introduces a study on the application of statistical parameters for texture classification of tree trunk images. For that, 540 samples from five Brazilian native deciduous species were acquired and measures of entropy, uniformity, smoothness, asymmetry (third moment), mean, and standard deviation were obtained from the presented textures. Using a decision tree, a biometric species identification system was constructed and resulted to a 0.84 average precision rate for species classification with 0.83accuracy and 0.79 agreement. Thus, it can be considered that the use of texture presented in trunk images can represent an important advance in tree identification, since the limitations of the current techniques can be overcome.

The fitness of copings constructed over UCLA abutments and the implant, constructed by different techniques: casting and casting with laser welding

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

From "wet biology" to statistical analysis of structural features with bioinformatics tools

Many new Escherichia coli outer membrane proteins have recently been identified by proteomics techniques. However, poorly expressed proteins and proteins expressed only under certain conditions may escape detection when wild-type cells are grown under standard conditions. Here, we have taken a complementary approach where candidate outer membrane proteins have been identified by bioinformatics prediction, cloned and overexpressed, and finally localized by cell fractionation experiments. Out of eight predicted outer membrane proteins, we have confirmed the outer membrane localization for five—YftM, YaiO, YfaZ, CsgF, and YliI—and also provide preliminary data indicating that a sixth—YfaL—may be an outer membrane autotransporter.

Statistical methods for biomedical signal analysis and processing

Statistical modelling and statistical learning theory are two powerful analytical frameworks for analyzing signals and developing efficient processing and classification algorithms. In this thesis, these frameworks are applied for modelling and processing biomedical signals in two different contexts: ultrasound medical imaging systems and primate neural activity analysis and modelling. In the context of ultrasound medical imaging, two main applications are explored: deconvolution of signals measured from a ultrasonic transducer and automatic image segmentation and classification of prostate ultrasound scans. In the former application a stochastic model of the radio frequency signal measured from a ultrasonic transducer is derived. This model is then employed for developing in a statistical framework a regularized deconvolution procedure, for enhancing signal resolution. In the latter application, different statistical models are used to characterize images of prostate tissues, extracting different features. These features are then uses to segment the images in region of interests by means of an automatic procedure based on a statistical model of the extracted features. Finally, machine learning techniques are used for automatic classification of the different region of interests. In the context of neural activity signals, an example of bio-inspired dynamical network was developed to help in studies of motor-related processes in the brain of primate monkeys. The presented model aims to mimic the abstract functionality of a cell population in 7a parietal region of primate monkeys, during the execution of learned behavioural tasks.

Spatial and temporal characterisation of ground deformation recorded by geodetic techniques

A critical point in the analysis of ground displacements time series is the development of data driven methods that allow the different sources that generate the observed displacements to be discerned and characterised. A widely used multivariate statistical technique is the Principal Component Analysis (PCA), which allows reducing the dimensionality of the data space maintaining most of the variance of the dataset explained. Anyway, PCA does not perform well in finding the solution to the so-called Blind Source Separation (BSS) problem, i.e. in recovering and separating the original sources that generated the observed data. This is mainly due to the assumptions on which PCA relies: it looks for a new Euclidean space where the projected data are uncorrelated. The Independent Component Analysis (ICA) is a popular technique adopted to approach this problem. However, the independence condition is not easy to impose, and it is often necessary to introduce some approximations. To work around this problem, I use a variational bayesian ICA (vbICA) method, which models the probability density function (pdf) of each source signal using a mix of Gaussian distributions. This technique allows for more flexibility in the description of the pdf of the sources, giving a more reliable estimate of them. Here I present the application of the vbICA technique to GPS position time series. First, I use vbICA on synthetic data that simulate a seismic cycle (interseismic + coseismic + postseismic + seasonal + noise) and a volcanic source, and I study the ability of the algorithm to recover the original (known) sources of deformation. Secondly, I apply vbICA to different tectonically active scenarios, such as the 2009 L'Aquila (central Italy) earthquake, the 2012 Emilia (northern Italy) seismic sequence, and the 2006 Guerrero (Mexico) Slow Slip Event (SSE).

On the accuracy of Software-based Energy Estimation Techniques

This paper examines the accuracy of software-based on-line energy estimation techniques. It evaluates today’s most widespread energy estimation model in order to investigate whether the current methodology of pure software-based energy estimation running on a sensor node itself can indeed reliably and accurately determine its energy consumption - independent of the particular node instance, the traffic load the node is exposed to, or the MAC protocol the node is running. The paper enhances today’s widely used energy estimation model by integrating radio transceiver switches into the model, and proposes a methodology to find the optimal estimation model parameters. It proves by statistical validation with experimental data that the proposed model enhancement and parameter calibration methodology significantly increases the estimation accuracy.