57 resultados para Computer terminals
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The knowledge of cell-cycle control has shown that the capacity of malignant growth is acquired by the stepwise accumulation of defects in specific genes regulating cell growth. Histologic diagnosis might be improved by a quantitative evaluation of more specific diagnosis biomarkers, which could help to precisely identify pre-malignant and malignant oral lesions. The aim of the present study is to evaluate whether computer-based quantitative assessment of p53, PCNA and Ki-67 immunohistochemical expression, could be used clinically to foresee the risk of oral malignant transformation. This retrospective study was carried out in ninety-five oral biopsies, 27 were classified as fibrous inflammatory hyperplasia, 40 as leukoplakia and 28 as oral squamous cell carcinoma. Sixteen out of the 40 leukoplakia were diagnosed as non-dysplastic leukoplakia, the other 24 being dysplastic leukoplakia, of which 50.0% were classified as moderate to severe dysplasia. Comparison of the four groups of oral tissues showed significant rises in p53 and Ki-67 positivity index, which increased steadily in the order benign, pre-malignant, and malignant. In contrast, it was not possible to relate higher PCNA levels with pre-malignant and malignant oral lesions. We therefore conclude that PCNA immunohistochemistry expression is probably an inappropriate marker to identify oral carcinogenesis, whereas joint quantitative evaluation of p53 and Ki-67, appears to be useful as a tumor marker, providing a pre-diagnostic estimate of the potential for cell-cycle deregulation of the oral proliferate status.
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The suprachiasmatic nucleus, an essential diencephalic component of the circadian timing system, plays a role in the generation and modulation of behavioral and neuroendocrine rhythms in mammals. Its cytoarchitecture, neurochemical and hodological characteristics have been investigated in various mammalian species, particularly in rodents. In most species, two subdivisions, based on these aspects and considered to reflect functional specialization within the nucleus, can be recognized. Many studies reveal a typical dense innervation by serotonergic fibers in this nucleus, mainly in the ventromedial area, overlapping the retinal afferents. However, a different pattern occurs in certain animals, which lead us to investigate the distribution of serotonergic afferents in the suprachiasmatic nucleus of the Capuchin monkey, Cebus apella, compared to the marmoset, Callithrix jacchus, and two Rattus norvegicus lines (Long Evans and Wistar), and to reported findings for other mammalian species. Our morphometric data show the volume and length of the suprachiasmatic nucleus along the rostrocaudal axis to be greatest in C. apella > C. jacchus > Long Evans ≥ Wistar rats, in agreement with their body sizes. In C. apella, however, the serotonergic terminals occupy only some 10% of the nucleus' area, less than the 25% seen in the marmoset and rats. The distribution of the serotonergic fibers in C. apella does not follow the characteristic ventral organization pattern seen in the rodents. These findings raise questions concerning the intrinsic organization of the nucleus, as well as regarding the functional relationship between serotonergic input and retinal afferents in this diurnal species. © 2007 Elsevier B.V. All rights reserved.
Resumo:
In order to simplify computer management, several system administrators are adopting advanced techniques to manage software configuration of enterprise computer networks, but the tight coupling between hardware and software makes every PC an individual managed entity, lowering the scalability and increasing the costs to manage hundreds or thousands of PCs. Virtualization is an established technology, however its use is been more focused on server consolidation and virtual desktop infrastructure, not for managing distributed computers over a network. This paper discusses the feasibility of the Distributed Virtual Machine Environment, a new approach for enterprise computer management that combines virtualization and distributed system architecture as the basis of the management architecture. © 2008 IEEE.
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This project aims to apply image processing techniques in computer vision featuring an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. To carry through this task, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for pattern recognition. Therefore, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave platforms, along with the application of customized Back-propagation algorithm and statistical methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of patterns in which reasonably accurate results were obtained.
ANN statistical image recognition method for computer vision in agricultural mobile robot navigation
Resumo:
The main application area in this project, is to deploy image processing and segmentation techniques in computer vision through an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. Thereby, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for image recognition. Hence, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave computational platforms, along with the application of customized Back-propagation Multilayer Perceptron (MLP) algorithm and statistical methods as structured heuristics methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of segmented images in which reasonably accurate results were obtained. © 2010 IEEE.
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This paper presents an approach for probabilistic analysis of unbalanced three-phase weakly meshed distribution systems considering uncertainty in load demand. In order to achieve high computational efficiency this approach uses both an efficient method for probabilistic analysis and a radial power flow. The probabilistic approach used is the well-known Two-Point Estimate Method. Meanwhile, the compensation-based radial power flow is used in order to extract benefits from the topological characteristics of the distribution systems. The generation model proposed allows modeling either PQ or PV bus on the connection point between the network and the distributed generator. In addition allows control of the generator operating conditions, such as the field current and the power delivery at terminals. Results on test with IEEE 37 bus system is given to illustrate the operation and effectiveness of the proposed approach. A Monte Carlo Simulations method is used to validate the results. © 2011 IEEE.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The term human factor is used by professionals of various fields meant for understanding the behavior of human beings at work. The human being, while developing a cooperative activity with a computer system, is subject to cause an undesirable situation in his/her task. This paper starts from the principle that human errors may be considered as a cause or factor contributing to a series of accidents and incidents in many diversified fields in which human beings interact with automated systems. We propose a simulator of performance in error with potentiality to assist the Human Computer Interaction (HCI) project manager in the construction of the critical systems. © 2011 Springer-Verlag.
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This paper presents novel simulation tools to assist the lecturers about learning processes on renewable energy sources, considering photovoltaic (PV) systems. The PV behavior, functionality and its interaction with power electronic converters are investigated in the simulation tools. The main PV output characteristics, I (current) versus V (voltage) and P (power) versus V (voltage), were implemented in the tools, in order to aid the users for the design steps. In order to verify the effectiveness of the developed tools the simulation results were compared with Matlab. Finally, a prototype was implemented with the purpose to compare the experimental results with the results from the proposed tools, validating its operational feasibility. © 2011 IEEE.
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Increased accessibility to high-performance computing resources has created a demand for user support through performance evaluation tools like the iSPD (iconic Simulator for Parallel and Distributed systems), a simulator based on iconic modelling for distributed environments such as computer grids. It was developed to make it easier for general users to create their grid models, including allocation and scheduling algorithms. This paper describes how schedulers are managed by iSPD and how users can easily adopt the scheduling policy that improves the system being simulated. A thorough description of iSPD is given, detailing its scheduler manager. Some comparisons between iSPD and Simgrid simulations, including runs of the simulated environment in a real cluster, are also presented. © 2012 IEEE.
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In this paper we propose a nature-inspired approach that can boost the Optimum-Path Forest (OPF) clustering algorithm by optimizing its parameters in a discrete lattice. The experiments in two public datasets have shown that the proposed algorithm can achieve similar parameters' values compared to the exhaustive search. Although, the proposed technique is faster than the traditional one, being interesting for intrusion detection in large scale traffic networks. © 2012 IEEE.
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Nowadays, organizations face the problem of keeping their information protected, available and trustworthy. In this context, machine learning techniques have also been extensively applied to this task. Since manual labeling is very expensive, several works attempt to handle intrusion detection with traditional clustering algorithms. In this paper, we introduce a new pattern recognition technique called Optimum-Path Forest (OPF) clustering to this task. Experiments on three public datasets have showed that OPF classifier may be a suitable tool to detect intrusions on computer networks, since it outperformed some state-of-the-art unsupervised techniques. © 2012 IEEE.
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The objective of this paper is to show a methodology to estimate transmission line parameters. The method is applied in a single-phase transmission line using the method of least squares. In this method the longitudinal and transversal parameters of the line are obtained as a function of a set of measurements of currents and voltages (as well as their derivatives with respect to time) at the terminals of the line during the occurrence of a short-circuit phase-ground near the load. The method is based on the assumption that a transmission line can be represented by a single circuit π. The results show that the precision of the method depends on the length of the line, where it has a better performance for short lines and medium length. © 2012 IEEE.
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Understanding the biological activity profile of the snake venom components is fundamental for improving the treatment of snakebite envenomings and may also contribute for the development of new potential therapeutic agents. In this work, we tested the effects of BthTX-I, a Lys49 PLA2 homologue from the Bothrops jararacussu snake venom. While this toxin induces conspicuous myonecrosis by a catalytically independent mechanism, a series of in vitro studies support the hypothesis that BthTX-I might also exert a neuromuscular blocking activity due to its ability to alter the integrity of muscle cell membranes. To gain insight into the mechanisms of this inhibitory neuromuscular effect, for the first time, the influence of BthTX-I on nerve-evoked ACh release was directly quantified by radiochemical and real-time video-microscopy methods. Our results show that the neuromuscular blockade produced by in vitro exposure to BthTX-I (1 μM) results from the summation of both pre- and postsynaptic effects. Modifications affecting the presynaptic apparatus were revealed by the significant reduction of nerve-evoked [3H]-ACh release; real-time measurements of transmitter exocytosis using the FM4-64 fluorescent dye fully supported radiochemical data. The postsynaptic effect of BthTX-I was characterized by typical histological alterations in the architecture of skeletal muscle fibers, increase in the outflow of the intracellular lactate dehydrogenase enzyme and progressive depolarization of the muscle resting membrane potential. In conclusion, these findings suggest that the neuromuscular blockade produced by BthTX-I results from transient depolarization of skeletal muscle fibers, consequent to its general membrane-destabilizing effect, and subsequent decrease of evoked ACh release from motor nerve terminals. © 2012 Elsevier Ltd.
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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.