Using multiple abstraction levels to speedup an MPSoC virtual platform simulator

Virtual platforms are of paramount importance for design space exploration and their usage in early software development and verification is crucial. In particular, enabling accurate and fast simulation is specially useful, but such features are usually conflicting and tradeoffs have to be made. In this paper we describe how we integrated TLM communication mechanisms into a state-of-the-art, cycle-accurate, MPSoC simulation platform. More specifically, we show how we adapted ArchC fast functional instruction set simulators to the MPARM platform in order to achieve both fast simulation speed and accuracy. Our implementation led to a much faster hybrid platform, reaching speedups of up to 2.9 and 2.1x on average with negligible impact on power estimation accuracy (average 3.26% and 2.25% of standard deviation). © 2011 IEEE.

Evaluation of MPPT techniques for photovoltaic applications

This paper presents a careful evaluation among the most usual MPPT (Maximum Power Point Tracking) techniques, doing meaningful comparisons with respect to the amount of energy extracted from the photovoltaic (PV) panel, PV voltage ripple, dynamic response and use of sensors. Firstly, the MPPT and boost converter models were implemented via MatLab/Simulink®, and after a DC to DC boost converter, digitally controlled, was implemented and connected to an Agilent Solar Array simulator, in order to validate the simulation results. The algorithms are digitally developed and the main experimental results are also presented from the implemented prototype. Furthermore, the experimental dynamic results and the computed tracking factors are presented. © 2011 IEEE.

Comparative analysis of MPPT techniques for PV applications

This paper presents a careful evaluation among the most usual MPPT techniques, doing meaningful comparisons with respect to the amount of energy extracted from the photovoltaic (PV) panel, PV voltage ripple, dynamic response and use of sensors, considering that the models are first implemented via MatLab/Simulink®, and after a digitally controlled boost DC-DC converter was implemented and connected to an Agilent Solar Array simulator in order to verify the simulation results. The prototype was built, the algorithms are digitally developed and the main experimental results are also presented, including dynamic responses and the experimental tracking factor (TF) for the analyzed MPPT techniques. © 2011 IEEE.

Spatial clustering applied to health area

The significant volume of work accidents in the cities causes an expressive loss to society. The development of Spatial Data Mining technologies presents a new perspective for the extraction of knowledge from the correlation between conventional and spatial attributes. One of the most important techniques of the Spatial Data Mining is the Spatial Clustering, which clusters similar spatial objects to find a distribution of patterns, taking into account the geographical position of the objects. Applying this technique to the health area, will provide information that can contribute towards the planning of more adequate strategies for the prevention of work accidents. The original contribution of this work is to present an application of tools developed for Spatial Clustering which supply a set of graphic resources that have helped to discover knowledge and support for management in the work accidents area. © 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.

A visual tool for building synchronous generator capability curves

Synchronous generators are essential components of electric power systems. They are present both in hydro and thermal power plants, performing the function of converting mechanical into electrical energy. This paper presents a visual approach to manipulate parameters that affect operation limits of synchronous generators, using a specifically designed software. The operating characteristics of synchronous generators, for all possible modes of operation, are revised in order to link the concepts to the graphic objects. The approach matches the distance learning tool requirements and also enriches the learning process by developing student trust and understanding of the concepts involved in building synchronous machine capability curves. © 2012 IEEE.

Scheduler simulation using iSPD, an iconic-based computer grid simulator

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.

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.

iSPD: An iconic-based modeling simulator for distributed grids

Simulation of large and complex systems, such as computing grids, is a difficult task. Current simulators, despite providing accurate results, are significantly hard to use. They usually demand a strong knowledge of programming, what is not a standard pattern in today's users of grids and high performance computing. The need for computer expertise prevents these users from simulating how the environment will respond to their applications, what may imply in large loss of efficiency, wasting precious computational resources. In this paper we introduce iSPD, iconic Simulator of Parallel and Distributed Systems, which is a simulator where grid models are produced through an iconic interface. We describe the simulator and its intermediate model languages. Results presented here provide an insight in its easy-of-use and accuracy.

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.

BBA: A binary bat algorithm for feature selection

Feature selection aims to find the most important information from a given set of features. As this task can be seen as an optimization problem, the combinatorial growth of the possible solutions may be in-viable for a exhaustive search. In this paper we propose a new nature-inspired feature selection technique based on the bats behaviour, which has never been applied to this context so far. The wrapper approach combines the power of exploration of the bats together with the speed of the Optimum-Path Forest classifier to find the set of features that maximizes the accuracy in a validating set. Experiments conducted in five public datasets have demonstrated that the proposed approach can outperform some well-known swarm-based techniques. © 2012 IEEE.

Improving image classification through descriptor combination

The efficiency in image classification tasks can be improved using combined information provided by several sources, such as shape, color, and texture visual properties. Although many works proposed to combine different feature vectors, we model the descriptor combination as an optimization problem to be addressed by evolutionary-based techniques, which compute distances between samples that maximize their separability in the feature space. The robustness of the proposed technique is assessed by the Optimum-Path Forest classifier. Experiments showed that the proposed methodology can outperform individual information provided by single descriptors in well-known public datasets. © 2012 IEEE.

Suíte plutônica Alumiador, grupo Amonguijá, maciço rio apa - MS

The Rio Apa Massif corresponds the southern portion of the Amazon Craton and is located in the southwest of Mato Grosso do Sul State. It consists on Paleoproterozoic rocks of Rio Apa Complex, Alto Tererê Group and Amonguijá Group, is subdivided into Alumiador Plutonic Suite and Serra da Bocaina Volcanic Suite. The volcanic suite is comprises sub volcanic, volcanic and varied volcanoclastics rocks with composition ranging from alkali-rhyolitic to rhyolite types. The plutonic suite corresponds to an N-S elongated batholith and is characterized by four main segments delimited by NW-SE faults. The southern and central main segments, discussed in this paper, are characterized by the following petrographic facies: medium to fine grained hornblende-biotite monzogranites, coarse grained biotite monzogranites, graphic biotite sienogranites and muscovite sienogranites and the northern segment is contemporaneous and is composed of two different sequences of rocks, one acid and another of basic to ultrabasic composition. The southern and central segment consists of to chemically compatible rocks with the types I and A Granites. These are calc-alkaline rocks of high potassium to the shoshonitic and subalkaline. Constitute sin-collisional granites of metaluminous the peraluminous characters of the Amonguijá Magmatic Arc, but they exhibit late litotypes with chemical characteristics of post tectonic granites from intraplate environment.

Determination of disease biomarkers in Eucalyptus by comprehensive two-dimensional gas chromatography and multivariate data analysis

In this paper is reported the use of the chromatographic profiles of volatiles to determine disease markers in plants - in this case, leaves of Eucalyptus globulus contaminated by the necrotroph fungus Teratosphaeria nubilosa. The volatile fraction was isolated by headspace solid phase microextraction (HS-SPME) and analyzed by comprehensive two-dimensional gas chromatography-fast quadrupole mass spectrometry (GC. ×. GC-qMS). For the correlation between the metabolic profile described by the chromatograms and the presence of the infection, unfolded-partial least squares discriminant analysis (U-PLS-DA) with orthogonal signal correction (OSC) were employed. The proposed method was checked to be independent of factors such as the age of the harvested plants. The manipulation of the mathematical model obtained also resulted in graphic representations similar to real chromatograms, which allowed the tentative identification of more than 40 compounds potentially useful as disease biomarkers for this plant/pathogen pair. The proposed methodology can be considered as highly reliable, since the diagnosis is based on the whole chromatographic profile rather than in the detection of a single analyte. © 2013 Elsevier B.V..

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.