Fast petroleum well drilling monitoring through optimum-path forest

Automatic inspection of petroleum well drilling has became paramount in the last years, mainly because of the crucial importance of saving time and operations during the drilling process in order to avoid some problems, such as the collapse of the well borehole walls. In this paper, we extended another work by proposing a fast petroleum well drilling monitoring through a modified version of the Optimum-Path Forest classifier. Given that the cutting's volume at the vibrating shale shaker can provide several information about drilling, we used computer vision techniques to extract texture informations from cutting images acquired by a digital camera. A collection of supervised classifiers were applied in order to allow comparisons about their accuracy and effciency. We used the Optimum-Path Forest (OPF), EOPF (Efficient OPF), Artificial Neural Network using Multilayer Perceptrons (ANN-MLP) Support Vector Machines (SVM), and a Bayesian Classifier (BC) to assess the robustness of our proposed schema for petroleum well drilling monitoring through cutting image analysis.

Smear layer removal for collagen fiber exposure after citric acid conditionings

Aim: The aim of the present study was to compare the removal of the smear layer and exposure of collagen fibers of the root surface following the application of five citric acid solution concentrations. Methods and Materials: Two hundred seventy (270) samples were equally divided into six groups (n=45) for treatment with saline solution (control) and five different concentrations of citric acid (0.5, 1, 2, 15, and 25 percent). Three acid application methods were used (passive, brushing, and burnishing) as well as three application periods (1, 2, and 3 minutes). A previously trained, calibrated (kappa score = 0.93), and blind examiner subsequently scored scanning electron micrographs (SEMs) of the samples. Statistical analyses were performed by using Kruskal-Wallis and Dunn's post-hoc tests. Results: According to the results obtained and within the limitations of the methodology used, the citric acid applications were more effective than the control treatment of applying saline solution (p<0.05). However, no statistically significant differences were observed among the three application methods and three application periods. Descriptive analyses showed that best results for exposure of collagen fibers were obtained with the application of citric acid at 25 percent by brushing for 1 or 3 minutes. Conclusions: The best results for exposure of collagen fibers in this study were obtained with application of citric acid at 25 percent by brushing for 1 or 3 minutes, even though there were no statistically significant differences among the groups. Clinical Significance: The best results for exposure of collagen fibers on root surfaces noted in this study were obtained with application of citric acid at 25 percent by brushing for 1 or 3 minutes. © 2010 Seer Publishing LLC.

Precipitates segmentation from scanning electron microscope images through machine learning techniques

The presence of precipitates in metallic materials affects its durability, resistance and mechanical properties. Hence, its automatic identification by image processing and machine learning techniques may lead to reliable and efficient assessments on the materials. In this paper, we introduce four widely used supervised pattern recognition techniques to accomplish metallic precipitates segmentation in scanning electron microscope images from dissimilar welding on a Hastelloy C-276 alloy: Support Vector Machines, Optimum-Path Forest, Self Organizing Maps and a Bayesian classifier. Experimental results demonstrated that all classifiers achieved similar recognition rates with good results validated by an expert in metallographic image analysis. © 2011 Springer-Verlag Berlin Heidelberg.

Effect of maintenance therapy with or without the use of chlorhexidine in teeth restored with composite resin in patients with diabetes mellitus

The objective of this study was to evaluate the effects of maintenance therapy with or without the use of 0.12% chlorhexidine in the periodontal tissues of patients with diabetes mellitus who had carious lesions restored with composed resin. Twenty patients were selected, all of whom had diabetes mellitus in addition to carious cervical lesions in previously treated teeth. After 90 days, improvement in plaque and gingival indices and probing depth were noticed among patients in the group that received 0.12% chlorhexidine.

Morphological alterations on human radicular dentin after exposure to different fruit juice drinks

Purpose: This in vitro study aimed to evaluate the effect of different fruit juice drinks available in the Brazilian market on smear layer removal and dentinal tubules opening, as well as to verify the effect of toothbrushing subsequently to the juices exposure. Methods: Dentin specimens were prepared and randomly distributed into the control group (distilled water) and twelve types of fruit juice drinks (cashew, orange, mandarin, apple, passion fruit, guava, strawberry, grape, mango, pear, peach, pineapple). The following treatments were applied: immersion or immersion + brushing. After preparation for SEM, photomicrographs were assessed using an index of smear layer removal. Results: No significant differences regarding smear layer removal and dentinal tubules exposure could be observed between the groups after both treatments (Kruskal-Wallis, post-hoc paired comparisons, P>0.05). The control solution and the fruit juice drinks were not able to remove smear layer and to open dentinal tubules. Significant difference between the applied treatments was detected only for the mango juice group (Mann-Whitney, P<0.05). Conclusion: Under the experimental conditions, the different fruit juice drinks did not promote significant alterations on human radicular dentin morphology regardless of the subsequent application of brushing procedures. Copyright: © 2011 Zandim et al.

Image categorization through optimum path forest and visual words

Different from the first attempts to solve the image categorization problem (often based on global features), recently, several researchers have been tackling this research branch through a new vantage point - using features around locally invariant interest points and visual dictionaries. Although several advances have been done in the visual dictionaries literature in the past few years, a problem we still need to cope with is calculation of the number of representative words in the dictionary. Therefore, in this paper we introduce a new solution for automatically finding the number of visual words in an N-Way image categorization problem by means of supervised pattern classification based on optimum-path forest. © 2011 IEEE.

Optimum-Path Forest pruning parameter estimation through Harmony Search

Pattern recognition in large amount of data has been paramount in the last decade, since that is not straightforward to design interactive and real time classification systems. Very recently, the Optimum-Path Forest classifier was proposed to overcome such limitations, together with its training set pruning algorithm, which requires a parameter that has been empirically set up to date. In this paper, we propose a Harmony Search-based algorithm that can find near optimal values for that. The experimental results have showed that our algorithm is able to find proper values for the OPF pruning algorithm parameter. © 2011 IEEE.

Análise temporal do uso do solo e comparação entre os índices de vegetação ndvi e savi no município de Santa Cruz do Rio Pardo - SP usando imagens landsat-5

This work aims to analyze the land use evolution in the city of Santa Cruz do Rio Pardo - SP through supervised classification of Landsat-5 TM satellite images according to the maximum likelihood (Maxlike), as well as verifying the mapping accuracy through Kappa index, comparing NDVI and SAVI vegetation indexes in different adjustment factors for the canopy substrate and determining the vegetal coverage percentage in all methods used on 2007, May 26 th; 2009, January 7 th and 2009, April 29 th. The Maxlike classification showed several spatial changes in land use over the study period. The most appropriated vegetation indexes were NDVI and SAVI - 0,25 factor, which showed similar values of vegetal coverage percentage, but discrepant from the inferred value for Maxlike classification.

Automatic classification of fish germ cells through optimum-path forest

The spermatogenesis is crucial to the species reproduction, and its monitoring may shed light over some important information of such process. Thus, the germ cells quantification can provide useful tools to improve the reproduction cycle. In this paper, we present the first work that address this problem in fishes with machine learning techniques. We show here how to obtain high recognition accuracies in order to identify fish germ cells with several state-of-the-art supervised pattern recognition techniques. © 2011 IEEE.

Influence of acid-etching and ceramic primers on the repair of a glass ceramic

The objective of this study was to evaluate the influence of different primers on the microtensile bond strength (μT BS) between a feldspathic ceramic and two composites. Forty blocks (6.0 × 6.0 × 5.0 mm 3) were prepared from Vita Mark II . After polishing, they were randomly divided into 10 groups according to the surface treatment: Group 1, hydrofluoric acid 10% (HF) + silane; Group 2, CoJet + silane; Group 3, HF + Metal/Zirconia Primer; Group 4, HF + Clearfil Primer; Group 5, HF + Alloy Primer; Group 6, HF + V-Primer; Group 7, Metal/Zirconia Primer; Group 8, Clearfil Primer; Group 9, Alloy Primer; Group 10, V-Primer. After each surface treatment, an adhesive was applied and one of two composite resins was incrementally built up. The sticks obtained from each block (bonded area: 1.0 mm2 ± 0.2 mm) were stored in distilled water at 37°C for 30 days and submitted to thermocycling (7,000 cycles; 5°C/55°C ± 1°C). The μT BS test was carried out using a universal testing machine (1.0 mm/min). Data were analyzed using ANOVA and a Tukey test (α = 0.05). The surface treatments significantly affected the results (P < 0.05); no difference was observed between the composites (P > 0.05). The bond strength means (MPa) were as follows: Group 1a = 29.6; Group 1b = 33.7; Group 2a = 28.9; Group 2b = 27.1; Group 3a = 13.8; Group 3b = 14.9; Group 4a = 18.6; Group 4b = 19.4; Group 5a = 15.3; Group 5b = 16.5; Group 6a = 11; Group 6b = 18; Groups 7a to 10b = 0. While the use of primers alone was not sufficient for adequate bond strengths to feldspathic ceramic, HF etching followed by any silane delivered higher bond strength.