Gráficos de probabilidade normal para avaliação de mecanismos de distribuição de sementes em semeadoras

Currently great emphasis is given for seed metering that assist rigorous demands in relation to longitudinal distribution of seeds, as well as to the index of fails in spacing laws, breaks and double seeds. The evaluation of these variable demands much time and work of attainment of data and processing. The objective of this work went propose to use of graphs of normal probability, facilitating the treatment of the data and decreasing the time of processing. The evaluation methodology consists in the counting of broken seeds, fail spacing and double seeds through the measure of the spacing among seeds, preliminary experiments through combinations of treatments had been carried through whose factors of variation were the level of the reservoir of seeds, the leveling of the seed metering, the speed of displacement and dosage of seeds. The evaluation was carried through in two parts, first through preliminary experiments for elaboration of the graphs of normal probability and later in experiments with bigger sampling for evaluation of the influence of the factors most important. It was done the evaluation of seed metering of rotating internal ring, and the amount of necessary data for the evaluation was very decreased through of the graphs of normal probability that facilitated to prioritize only the significant factors. The dosage of seeds was factor that more important because factor (D) have greater significance.

Alimentação de peixes: proposta para análise de itens registrados em conteúdos gástricos

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

X̄ charts with variable sample size

The usual practice in using a control chart to monitor a process is to take samples of size n from the process every h hours. This article considers the properties of the X̄ chart when the size of each sample depends on what is observed in the preceding sample. The idea is that the sample should be large if the sample point of the preceding sample is close to but not actually outside the control limits and small if the sample point is close to the target. The properties of the variable sample size (VSS) X̄ chart are obtained using Markov chains. The VSS X̄ chart is substantially quicker than the traditional X̄ chart in detecting moderate shifts in the process.

Automatic segmentation of digital images applied in cardiac medical images

The digital image processing has been applied in several areas, especially where it is necessary use tools for feature extraction and to get patterns of the studied images. In an initial stage, the segmentation is used to separate the image in parts that represents a interest object, that may be used in a specific study. There are several methods that intends to perform such task, but is difficult to find a method that can easily adapt to different type of images, that often are very complex or specific. To resolve this problem, this project aims to presents a adaptable segmentation method, that can be applied to different type of images, providing an better segmentation. The proposed method is based in a model of automatic multilevel thresholding and considers techniques of group histogram quantization, analysis of the histogram slope percentage and calculation of maximum entropy to define the threshold. The technique was applied to segment the cell core and potential rejection of tissue in myocardial images of biopsies from cardiac transplant. The results are significant in comparison with those provided by one of the best known segmentation methods available in the literature. © 2010 IEEE.

Semiautomatic dental recognition using a graph-based segmentation algorithm and teeth shapes features

Dental recognition is very important for forensic human identification, mainly regarding the mass disasters, which have frequently happened due to tsunamis, airplanes crashes, etc. Algorithms for automatic, precise, and robust teeth segmentation from radiograph images are crucial for dental recognition. In this work we propose the use of a graph-based algorithm to extract the teeth contours from panoramic dental radiographs that are used as dental features. In order to assess our proposal, we have carried out experiments using a database of 1126 tooth images, obtained from 40 panoramic dental radiograph images from 20 individuals. The results of the graph-based algorithm was qualitatively assessed by a human expert who reported excellent scores. For dental recognition we propose the use of the teeth shapes as biometric features, by the means of BAS (Bean Angle Statistics) and Shape Context descriptors. The BAS descriptors showed, on the same database, a better performance (EER 14%) than the Shape Context (EER 20%). © 2012 IEEE.

Particle competition and cooperation to prevent error propagation from mislabeled data in semi-supervised learning

Semi-supervised learning is applied to classification problems where only a small portion of the data items is labeled. In these cases, the reliability of the labels is a crucial factor, because mislabeled items may propagate wrong labels to a large portion or even the entire data set. This paper aims to address this problem by presenting a graph-based (network-based) semi-supervised learning method, specifically designed to handle data sets with mislabeled samples. The method uses teams of walking particles, with competitive and cooperative behavior, for label propagation in the network constructed from the input data set. The proposed model is nature-inspired and it incorporates some features to make it robust to a considerable amount of mislabeled data items. Computer simulations show the performance of the method in the presence of different percentage of mislabeled data, in networks of different sizes and average node degree. Importantly, these simulations reveals the existence of the critical points of the mislabeled subset size, below which the network is free of wrong label contamination, but above which the mislabeled samples start to propagate their labels to the rest of the network. Moreover, numerical comparisons have been made among the proposed method and other representative graph-based semi-supervised learning methods using both artificial and real-world data sets. Interestingly, the proposed method has increasing better performance than the others as the percentage of mislabeled samples is getting larger. © 2012 IEEE.

Fuzzy community structure detection by particle competition and cooperation

Identification and classification of overlapping nodes in networks are important topics in data mining. In this paper, a network-based (graph-based) semi-supervised learning method is proposed. It is based on competition and cooperation among walking particles in a network to uncover overlapping nodes by generating continuous-valued outputs (soft labels), corresponding to the levels of membership from the nodes to each of the communities. Moreover, the proposed method can be applied to detect overlapping data items in a data set of general form, such as a vector-based data set, once it is transformed to a network. Usually, label propagation involves risks of error amplification. In order to avoid this problem, the proposed method offers a mechanism to identify outliers among the labeled data items, and consequently prevents error propagation from such outliers. Computer simulations carried out for synthetic and real-world data sets provide a numeric quantification of the performance of the method. © 2012 Springer-Verlag.

The use of elevation map histograms for topographic heterogeneity analysis

Surface defects are extremely important in mechanical characterization of several different materials. Therefore, the analysis of surface finishing is essential for a further simulation of surface mechanical properties in a customized project in materials science and technology. One of the methods commonly employed for such purpose is the statistical mapping of different sample surface regions using the depth from focus technique. The analysis is usually performed directly from the elevation maps which are obtained from the digital image processing. In this paper, the possibility of quantifying the surface heterogeneity of Silicon Carbide porous ceramics by elevation map histograms is presented. The advantage of this technique is that it allows the qualitative or quantitative verification of all surface image fields that cannot be done by using the Surface Plot plugin of image J™ platform commonly used in digital image processing. © 2012 Springer Science+Business Media, LLC.

Técnicas de obtenção da posição de relação central em pacientes edêntulos

Edentulism causes loss of horizontal intermaxillary relationship, which is defined by the condyle position in the joint cavities, called centric relation. The correct record of centric relation in edentulous pacients has a strong influence on the treatment final result and is considered one of the most difficult clinical steps to achieve success. The aim of this study was to describe the main centric relation recording methods for edentulous patients reported in the literature. The study described physiological methods such as swallowing and pull tongue back, manipulative and graphic methods. It is concluded that the combination of different methods facilitates the correct centric relation record. Dentists must have a good knowledge of those techniques to perform this procedure satisfactorily.

Influence of Different Base Thicknesses on Maxillary Complete Denture Processing: Linear and Angular Graphic Analysis on the Movement of Artificial Teeth

Objective: The purpose of this study was to compare the dental movement that occurs during the processing of maxillary complete dentures with 3 different base thicknesses, using 2 investment methods, and microwave polymerization.Methods: A sample of 42 denture models was randomly divided into 6 groups (n = 7), with base thicknesses of 1.25, 2.50, and 3.75 mm and gypsum or silicone flask investment. Points were demarcated on the distal surface of the second molars and on the back of the gypsum cast at the alveolar ridge level to allow linear and angular measurement using AutoCAD software. The data were subjected to analysis of variance with double factor, Tukey test and Fisher (post hoc).Results: Angular analysis of the varying methods and their interactions generated a statistical difference (P = 0.023) when the magnitudes of molar inclination were compared. Tooth movement was greater for thin-based prostheses, 1.25 mm (-0.234), versus thick 3.75 mm (0.2395), with antagonistic behavior. Prosthesis investment with silicone (0.053) showed greater vertical change compared with the gypsum investment (0.032). There was a difference between the point of analysis, demonstrating that the changes were not symmetric.Conclusions: All groups evaluated showed change in the position of artificial teeth after processing. The complete denture with a thin base (1.25 mm) and silicone investment showed the worst results, whereas intermediate thickness (2.50 mm) was demonstrated to be ideal for the denture base.

The infuence of production systems in postponement make-to-stock compagny in the graphic industry

The supply chain management, postponement and demand management operations are of strategic importance to the economic success of organizations because they directly influence the production process. The aim of this paper is to analyze the influence of the postponement in an enterprise production system with make-to-stock and with seasonal demand. The research method used was a case study, the instruments of data collection were semi-structured interviews, document analysis and site visits. The research is based on the following issues: Demand Management which can be understood as a practice that allows you to manage and coordinate the supply chain in reverse, in which consumers trigger actions for the delivery of products. The Supply Chain Management is able to allow the addition of value, exceeding the expectations of consumers, developing a relationship with suppliers and customer's win-win. The Postponement strategy must fit the characteristics of markets that require variety of customized products and services, lower cost and higher quality, aiming to support decision making. The production system make-to-stock shows enough interest to organizations that are operating in markets with high demand variability. © 2011 IEEE.

Doppler ultrasonography principles and methods of evaluation of the reproductive tract in mares

Background: Doppler ultrasonography is a non-invasive real time pulse-wave technique recently used for the transrectal study of the reproductive system hemodynamics in large animals. This technic is based in the Doppler Effect Principle that proposes the change in frequency of a wave for an observer (red blood cells) moving relative to the source of the respective wave (ultrasonic transducer). This method had showed to be effective and useful for the evaluation of the in vivo equine reproductive tract increasing the diagnostic, monitoring, and predictive capabilities of theriogenology in mares. However, an accurate and truthful ultrasonic exam requires the previous knowledge of the Doppler ultrasonography principles. Review: In recent years, the capabilities of ultrasound flow imaging have increased enormously. The current Doppler ultrasound machines offer three methods of evaluation that may be used simultaneously (triplex mode). In B-mode ultrasound, a linear array of transducers simultaneously scans a plane through the tissue that can be viewed as a two-dimensional gray-scale image on screen. This mode is primarily used to identify anatomically a structure for its posterior evaluation using colored ultrasound modes (Color or Spectral modes). Colored ultrasound images of flow, whether Color or Spectral modes, are essentially obtained from measurements of moving red cells. In Color mode, velocity information is presented as a color coded overlay on top of a B-mode image, while Pulsed Wave Doppler provides a measure of the changing velocity throughout the cardiac cycle and the distribution of velocities in the sample volume represented by a spectral graphic. Color images conception varies according to the Doppler Frequency that is the difference between the frequency of received echoes by moving blood red cells and wave frequency transmitted by the transducer. To produce an adequate spectral graphic it is important determine the position and size of the simple gate. Furthermore, blood flow velocity measurement is influence by the intersection angle between ultrasonic pulses and the direction of moving blood-red cells (Doppler angle). Objectively colored ultrasound exam may be done on large arteries of the reproductive tract, as uterine and ovary arteries, or directly on the target tissue (follicle, for example). Mesovarium and mesometrium attachment arteries also can be used for spectral evaluation of the equine reproductive system. Subjectively analysis of the ovarian and uterine vascular perfusion must be done directly on the corpus luteum, follicular wall and uterus (endometrium and myometrium associated), respectively. Power-flow imaging has greater sensitivity to weak blood flow and independent of the Doppler angle, improving the evaluation of vessels with small diameters and slow blood flow. Conclusion: Doppler ultrasonography principles, methods of evaluation and reproductive system anatomy have been described. This knowledge is essential for the competent equipment acquisition and precise collection and analysis of colored ultrasound images. Otherwise, the reporting of inconsistent and not reproducible findings may result in the discredit of Doppler technology ahead of the scientific veterinary community.