956 resultados para second pre-image attack
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To meet the increasing demands of the complex inter-organizational processes and the demand for continuous innovation and internationalization, it is evident that new forms of organisation are being adopted, fostering more intensive collaboration processes and sharing of resources, in what can be called collaborative networks (Camarinha-Matos, 2006:03). Information and knowledge are crucial resources in collaborative networks, being their management fundamental processes to optimize. Knowledge organisation and collaboration systems are thus important instruments for the success of collaborative networks of organisations having been researched in the last decade in the areas of computer science, information science, management sciences, terminology and linguistics. Nevertheless, research in this area didn’t give much attention to multilingual contexts of collaboration, which pose specific and challenging problems. It is then clear that access to and representation of knowledge will happen more and more on a multilingual setting which implies the overcoming of difficulties inherent to the presence of multiple languages, through the use of processes like localization of ontologies. Although localization, like other processes that involve multilingualism, is a rather well-developed practice and its methodologies and tools fruitfully employed by the language industry in the development and adaptation of multilingual content, it has not yet been sufficiently explored as an element of support to the development of knowledge representations - in particular ontologies - expressed in more than one language. Multilingual knowledge representation is then an open research area calling for cross-contributions from knowledge engineering, terminology, ontology engineering, cognitive sciences, computational linguistics, natural language processing, and management sciences. This workshop joined researchers interested in multilingual knowledge representation, in a multidisciplinary environment to debate the possibilities of cross-fertilization between knowledge engineering, terminology, ontology engineering, cognitive sciences, computational linguistics, natural language processing, and management sciences applied to contexts where multilingualism continuously creates new and demanding challenges to current knowledge representation methods and techniques. In this workshop six papers dealing with different approaches to multilingual knowledge representation are presented, most of them describing tools, approaches and results obtained in the development of ongoing projects. In the first case, Andrés Domínguez Burgos, Koen Kerremansa and Rita Temmerman present a software module that is part of a workbench for terminological and ontological mining, Termontospider, a wiki crawler that aims at optimally traverse Wikipedia in search of domainspecific texts for extracting terminological and ontological information. The crawler is part of a tool suite for automatically developing multilingual termontological databases, i.e. ontologicallyunderpinned multilingual terminological databases. In this paper the authors describe the basic principles behind the crawler and summarized the research setting in which the tool is currently tested. In the second paper, Fumiko Kano presents a work comparing four feature-based similarity measures derived from cognitive sciences. The purpose of the comparative analysis presented by the author is to verify the potentially most effective model that can be applied for mapping independent ontologies in a culturally influenced domain. For that, datasets based on standardized pre-defined feature dimensions and values, which are obtainable from the UNESCO Institute for Statistics (UIS) have been used for the comparative analysis of the similarity measures. The purpose of the comparison is to verify the similarity measures based on the objectively developed datasets. According to the author the results demonstrate that the Bayesian Model of Generalization provides for the most effective cognitive model for identifying the most similar corresponding concepts existing for a targeted socio-cultural community. In another presentation, Thierry Declerck, Hans-Ulrich Krieger and Dagmar Gromann present an ongoing work and propose an approach to automatic extraction of information from multilingual financial Web resources, to provide candidate terms for building ontology elements or instances of ontology concepts. The authors present a complementary approach to the direct localization/translation of ontology labels, by acquiring terminologies through the access and harvesting of multilingual Web presences of structured information providers in the field of finance, leading to both the detection of candidate terms in various multilingual sources in the financial domain that can be used not only as labels of ontology classes and properties but also for the possible generation of (multilingual) domain ontologies themselves. In the next paper, Manuel Silva, António Lucas Soares and Rute Costa claim that despite the availability of tools, resources and techniques aimed at the construction of ontological artifacts, developing a shared conceptualization of a given reality still raises questions about the principles and methods that support the initial phases of conceptualization. These questions become, according to the authors, more complex when the conceptualization occurs in a multilingual setting. To tackle these issues the authors present a collaborative platform – conceptME - where terminological and knowledge representation processes support domain experts throughout a conceptualization framework, allowing the inclusion of multilingual data as a way to promote knowledge sharing and enhance conceptualization and support a multilingual ontology specification. In another presentation Frieda Steurs and Hendrik J. Kockaert present us TermWise, a large project dealing with legal terminology and phraseology for the Belgian public services, i.e. the translation office of the ministry of justice, a project which aims at developing an advanced tool including expert knowledge in the algorithms that extract specialized language from textual data (legal documents) and whose outcome is a knowledge database including Dutch/French equivalents for legal concepts, enriched with the phraseology related to the terms under discussion. Finally, Deborah Grbac, Luca Losito, Andrea Sada and Paolo Sirito report on the preliminary results of a pilot project currently ongoing at UCSC Central Library, where they propose to adapt to subject librarians, employed in large and multilingual Academic Institutions, the model used by translators working within European Union Institutions. The authors are using User Experience (UX) Analysis in order to provide subject librarians with a visual support, by means of “ontology tables” depicting conceptual linking and connections of words with concepts presented according to their semantic and linguistic meaning. The organizers hope that the selection of papers presented here will be of interest to a broad audience, and will be a starting point for further discussion and cooperation.
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The effect of pre-meal tomato intake in the anthropometric indices and blood levels of triglycerides, cholesterol, glucose, and uric acid of a young women population (n=35, 19.6 ± 1.3 years) was evaluated. During 4 weeks, daily, participants ingested a raw ripe tomato (~90 g) before lunch. Their anthropometric and biochemical parameters were measured repeatedly during the follow-up time. At the end of the 4 weeks, significant reductions were observed on body weight (-1.09 ± 0.12 kg on average), % fat (-1.54 ± 0.52%), fasting blood glucose (-5.29 ± 0.80 mg/dl), triglycerides (-8.31 ± 1.34 mg/dl), cholesterol (-10.17 ± 1.21 mg/ dl), and uric acid (-0.16 ± 0.04 mg/dl) of the participants. The tomato pre-meal ingestion seemed to interfere positively in body weight, fat percentage, and blood levels of glucose, triglycerides, cholesterol, and uric acid of the young adult women that participated in this study.
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Trabalho de projeto apresentado à Escola Superior de Comunicação Social como parte dos requisitos para obtenção de grau de mestre em Publicidade e Marketing.
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Trabalho de Projeto apresentado ao Instituto de Contabilidade e Administração do Porto para a obtenção do grau de Mestre em Marketing Digital, sob orientação de Doutor Freitas Santos
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We introduce a simple model for a biaxial nematic liquid crystal. This consists of hard spheroids that can switch shape between prolate (rodlike) and oblate (platelike) subject to an energy penalty Δε. The spheroids are approximated as hard Gaussian overlap particles and are treated at the level of Onsager's second-virial description. We use both bifurcation analysis and a numerical minimization of the free energy to show that, for additive particle shapes, (i) there is no stable biaxial phase even for Δε=0 (although there is a metastable biaxial phase in the same density range as the stable uniaxial phase) and (ii) the isotropic-to-nematic transition is into either one of two degenerate uniaxial phases, rod rich or plate rich. We confirm that even a small amount of shape nonadditivity may stabilize the biaxial nematic phase.
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Partial dynamic reconfiguration of FPGAs can be used to implement complex applications using the concept of virtual hardware. In this work we have used partial dynamic reconfiguration to implement a JPEG decoder with reduced area. The image decoding process was adapted to be implemented on the FPGA fabric using this technique. The architecture was tested in a low cost ZYNQ-7020 FPGA that supports dynamic reconfiguration. The results show that the proposed solution needs only 40% of the resources utilized by a static implementation. The performance of the dynamic solution is about 9X slower than the static solution by trading-off internal resources of the FPGA. A throughput of 7 images per second is achievable with the proposed partial dynamic reconfiguration solution.
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This paper proposes an FPGA-based architecture for onboard hyperspectral unmixing. This method based on the Vertex Component Analysis (VCA) has several advantages, namely it is unsupervised, fully automatic, and it works without dimensionality reduction (DR) pre-processing step. The architecture has been designed for a low cost Xilinx Zynq board with a Zynq-7020 SoC FPGA based on the Artix-7 FPGA programmable logic and tested using real hyperspectral datasets. Experimental results indicate that the proposed implementation can achieve real-time processing, while maintaining the methods accuracy, which indicate the potential of the proposed platform to implement high-performance, low cost embedded systems.
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Mestrado em Engenharia Electrotécnica e de Computadores - Ramo de Sistemas Autónomos
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This paper introduces a new toolbox for hyperspectral imagery, developed under the MATLAB environment. This toolbox provides easy access to different supervised and unsupervised classification methods. This new application is also versatile and fully dynamic since the user can embody their own methods, that can be reused and shared. This toolbox, while extends the potentiality of MATLAB environment, it also provides a user-friendly platform to assess the results of different methodologies. In this paper it is also presented, under the new application, a study of several different supervised and unsupervised classification methods on real hyperspectral data.
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Hyperspectral remote sensing exploits the electromagnetic scattering patterns of the different materials at specific wavelengths [2, 3]. Hyperspectral sensors have been developed to sample the scattered portion of the electromagnetic spectrum extending from the visible region through the near-infrared and mid-infrared, in hundreds of narrow contiguous bands [4, 5]. The number and variety of potential civilian and military applications of hyperspectral remote sensing is enormous [6, 7]. Very often, the resolution cell corresponding to a single pixel in an image contains several substances (endmembers) [4]. In this situation, the scattered energy is a mixing of the endmember spectra. A challenging task underlying many hyperspectral imagery applications is then decomposing a mixed pixel into a collection of reflectance spectra, called endmember signatures, and the corresponding abundance fractions [8–10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. Linear mixing model holds approximately when the mixing scale is macroscopic [13] and there is negligible interaction among distinct endmembers [3, 14]. If, however, the mixing scale is microscopic (or intimate mixtures) [15, 16] and the incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [17], the linear model is no longer accurate. Linear spectral unmixing has been intensively researched in the last years [9, 10, 12, 18–21]. It considers that a mixed pixel is a linear combination of endmember signatures weighted by the correspondent abundance fractions. Under this model, and assuming that the number of substances and their reflectance spectra are known, hyperspectral unmixing is a linear problem for which many solutions have been proposed (e.g., maximum likelihood estimation [8], spectral signature matching [22], spectral angle mapper [23], subspace projection methods [24,25], and constrained least squares [26]). In most cases, the number of substances and their reflectances are not known and, then, hyperspectral unmixing falls into the class of blind source separation problems [27]. Independent component analysis (ICA) has recently been proposed as a tool to blindly unmix hyperspectral data [28–31]. ICA is based on the assumption of mutually independent sources (abundance fractions), which is not the case of hyperspectral data, since the sum of abundance fractions is constant, implying statistical dependence among them. This dependence compromises ICA applicability to hyperspectral images as shown in Refs. [21, 32]. In fact, ICA finds the endmember signatures by multiplying the spectral vectors with an unmixing matrix, which minimizes the mutual information among sources. If sources are independent, ICA provides the correct unmixing, since the minimum of the mutual information is obtained only when sources are independent. This is no longer true for dependent abundance fractions. Nevertheless, some endmembers may be approximately unmixed. These aspects are addressed in Ref. [33]. Under the linear mixing model, the observations from a scene are in a simplex whose vertices correspond to the endmembers. Several approaches [34–36] have exploited this geometric feature of hyperspectral mixtures [35]. Minimum volume transform (MVT) algorithm [36] determines the simplex of minimum volume containing the data. The method presented in Ref. [37] is also of MVT type but, by introducing the notion of bundles, it takes into account the endmember variability usually present in hyperspectral mixtures. The MVT type approaches are complex from the computational point of view. Usually, these algorithms find in the first place the convex hull defined by the observed data and then fit a minimum volume simplex to it. For example, the gift wrapping algorithm [38] computes the convex hull of n data points in a d-dimensional space with a computational complexity of O(nbd=2cþ1), where bxc is the highest integer lower or equal than x and n is the number of samples. The complexity of the method presented in Ref. [37] is even higher, since the temperature of the simulated annealing algorithm used shall follow a log( ) law [39] to assure convergence (in probability) to the desired solution. Aiming at a lower computational complexity, some algorithms such as the pixel purity index (PPI) [35] and the N-FINDR [40] still find the minimum volume simplex containing the data cloud, but they assume the presence of at least one pure pixel of each endmember in the data. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. PPI algorithm uses the minimum noise fraction (MNF) [41] as a preprocessing step to reduce dimensionality and to improve the signal-to-noise ratio (SNR). The algorithm then projects every spectral vector onto skewers (large number of random vectors) [35, 42,43]. The points corresponding to extremes, for each skewer direction, are stored. A cumulative account records the number of times each pixel (i.e., a given spectral vector) is found to be an extreme. The pixels with the highest scores are the purest ones. N-FINDR algorithm [40] is based on the fact that in p spectral dimensions, the p-volume defined by a simplex formed by the purest pixels is larger than any other volume defined by any other combination of pixels. This algorithm finds the set of pixels defining the largest volume by inflating a simplex inside the data. ORA SIS [44, 45] is a hyperspectral framework developed by the U.S. Naval Research Laboratory consisting of several algorithms organized in six modules: exemplar selector, adaptative learner, demixer, knowledge base or spectral library, and spatial postrocessor. The first step consists in flat-fielding the spectra. Next, the exemplar selection module is used to select spectral vectors that best represent the smaller convex cone containing the data. The other pixels are rejected when the spectral angle distance (SAD) is less than a given thresh old. The procedure finds the basis for a subspace of a lower dimension using a modified Gram–Schmidt orthogonalizati on. The selected vectors are then projected onto this subspace and a simplex is found by an MV T pro cess. ORA SIS is oriented to real-time target detection from uncrewed air vehicles using hyperspectral data [46]. In this chapter we develop a new algorithm to unmix linear mixtures of endmember spectra. First, the algorithm determines the number of endmembers and the signal subspace using a newly developed concept [47, 48]. Second, the algorithm extracts the most pure pixels present in the data. Unlike other methods, this algorithm is completely automatic and unsupervised. To estimate the number of endmembers and the signal subspace in hyperspectral linear mixtures, the proposed scheme begins by estimating sign al and noise correlation matrices. The latter is based on multiple regression theory. The signal subspace is then identified by selectin g the set of signal eigenvalue s that best represents the data, in the least-square sense [48,49 ], we note, however, that VCA works with projected and with unprojected data. The extraction of the end members exploits two facts: (1) the endmembers are the vertices of a simplex and (2) the affine transformation of a simplex is also a simplex. As PPI and N-FIND R algorithms, VCA also assumes the presence of pure pixels in the data. The algorithm iteratively projects data on to a direction orthogonal to the subspace spanned by the endmembers already determined. The new end member signature corresponds to the extreme of the projection. The algorithm iterates until all end members are exhausted. VCA performs much better than PPI and better than or comparable to N-FI NDR; yet it has a computational complexity between on e and two orders of magnitude lower than N-FINDR. The chapter is structure d as follows. Section 19.2 describes the fundamentals of the proposed method. Section 19.3 and Section 19.4 evaluate the proposed algorithm using simulated and real data, respectively. Section 19.5 presents some concluding remarks.
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The currently used pre-exposure anti-rabies immunization schedule in Brazil is the one called 3+1, employing suckling mouse brain vaccine (3 doses on alternate days and the last one on day 30). Although satisfactory results were obtained in well controlled experimental groups using this immunization schedule, in our routine practice, VNA levels lower than 0.5 IU/ml are frequently found. We studied the pre-exposure 3+1 schedule under field conditions in different cities on the State of São Paulo, Brazil, under variable and sometimes adverse circumstances, such as the use of different batches of vaccine with different titers, delivered, stored and administered under local conditions. Fifty out of 256 serum samples (19.5%) showed VNA titers lower than 0.5 IU/ml, but they were not distributed homogeneously among the localities studied. While in some cities the results were completely satisfactory, in others almost 40% did not attain the minimum VNA titer required. The results presented here, considered separately, question our currently used procedures for human pre-exposure anti-rabies immunization. The reasons determining this situation are discussed.
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This study reports preliminary results of virus neutralizing antibody (VNA) titers obtained on different days in the course of human anti-rabies immunization with the 2-1-1 schedule (one dose is given in the right arm and one dose in the left arm at day 0, and one dose is apllied on days 7 and 21), recommended by WHO for post-exposure treatment with cell culture vaccines. A variant schedule (double dose on day zero and another on day 14) was also tested, both employing suckling mouse brain vaccine. A complete seroconversion rate was obtained after only 3 vaccine doses, and almost all patients (11 of 12) presented titers higher than 1.0 IU/ml. Both neutralizing response and seroconversion rates were lower in the group receiving only 3 doses, regardless of the sample collecting day. Although our results are lower than those found with cell culture vaccines, the geometry mean of VNA is fully satisfactory, overcoming the lower limit recommended by WHO of 0.5 IU/ml. The 2-1-1 schedule could be an alternative one for pre exposure immunization, shorter than the classical 3+1 regimen (one dose on days 0, 2, 4 and 30) with only three visits to the doctor, instead of four.
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Lunacloud is a cloud service provider with offices in Portugal, Spain, France and UK that focus on delivering reliable, elastic and low cost cloud Infrastructure as a Service (IaaS) solutions. The company currently relies on a proprietary IaaS platform - the Parallels Automation for Cloud Infrastructure (PACI) - and wishes to expand and integrate other IaaS solutions seamlessly, namely open source solutions. This is the challenge addressed in this thesis. This proposal, which was fostered by Eurocloud Portugal Association, contributes to the promotion of interoperability and standardisation in Cloud Computing. The goal is to investigate, propose and develop an interoperable open source solution with standard interfaces for the integrated management of IaaS Cloud Computing resources based on new as well as existing abstraction libraries or frameworks. The solution should provide bothWeb and application programming interfaces. The research conducted consisted of two surveys covering existing open source IaaS platforms and PACI (features and API) and open source IaaS abstraction solutions. The first study was focussed on the characteristics of most popular open source IaaS platforms, namely OpenNebula, OpenStack, CloudStack and Eucalyptus, as well as PACI and included a thorough inventory of the provided Application Programming Interfaces (API), i.e., offered operations, followed by a comparison of these platforms in order to establish their similarities and dissimilarities. The second study on existing open source interoperability solutions included the analysis of existing abstraction libraries and frameworks and their comparison. The approach proposed and adopted, which was supported on the conclusions of the carried surveys, reuses an existing open source abstraction solution – the Apache Deltacloud framework. Deltacloud relies on the development of software driver modules to interface with different IaaS platforms, officially provides and supports drivers to sixteen IaaS platform, including OpenNebula and OpenStack, and allows the development of new provider drivers. The latter functionality was used to develop a new Deltacloud driver for PACI. Furthermore, Deltacloud provides a Web dashboard and REpresentational State Transfer (REST) API interfaces. To evaluate the adopted solution, a test bed integrating OpenNebula, Open- Stack and PACI nodes was assembled and deployed. The tests conducted involved time elapsed and data payload measurements via the Deltacloud framework as well as via the pre-existing IaaS platform API. The Deltacloud framework behaved as expected, i.e., introduced additional delays, but no substantial overheads. Both the Web and the REST interfaces were tested and showed identical measurements. The developed interoperable solution for the seamless integration and provision of IaaS resources from PACI, OpenNebula and OpenStack IaaS platforms fulfils the specified requirements, i.e., provides Lunacloud with the ability to expand the range of adopted IaaS platforms and offers a Web dashboard and REST API for the integrated management. The contributions of this work include the surveys and comparisons made, the selection of the abstraction framework and, last, but not the least, the PACI driver developed.
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This chapter examines the cross-cultural influence of training on the adjustment of international assignees. We focus on the pre-departure training (PDT) before an international assignment. It is an important topic because in the globalized world of today more and more expatriations are needed. The absence of PDT may generate the failure of the expatriation experience. Companies may neglect PDT due to cost reduction practices and ignorance of the need for it. Data were collected through semi-structured interviews to 42 Portuguese international assignees and 18 organizational representatives from nine Portuguese companies. The results suggest that companies should develop PDT programs, particularly when the cultural distance to the host country is bigger and when there is no previous experience of expatriation to that country in the company. The study is original because it details in depth the methods of PDT, its problems, and consequences. Some limitations linked to the research design and detailed in the conclusion should be overcome in future studies.
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Considering that the number of day-care centers for pre-school-age children has expanded rapidly in developing countries, and that these institutions presenting conditions that facilitate the transmission of many enteric agents, a parasitological survey was carried out in three municipal day-cares from Botucatu: two in the urban area (one in downtown area and the other one in the city periphery area) and the third in the rural area. Three separate stool specimens were collected from 147 children ranging from 0 to 72 months old and 20 staff members. Each stool specimen was processed by Lutz and zinc sulfate flotation methods. The frequency of giardiasis observed among children of downtown, periphery and rural day-cares was 69.6%, 52.7% and 69.6%, respectively. Only one employee was positive for G. lamblia. The examination of three stool specimens increased the positivity for G. lamblia: from the ninety three final positive examinations, 24 (25.5%) and 8 (8.5%) were positives only after examination of the second and third samples, respectively. Others intestinal organisms like Ascaris lumbricoides (20.4%), Trichuris trichiura (19.0%). Hymenolepis nana (8.8%), Entamoeba coli (22.4%) and Blastocystis hominis (32.0%) were frequently found in the children. There was no significant association among localization of the day-cares, sex of the children and the levels of G. lamblia infection. According to the age, G. lamblia was found mainly in children between 12 to 47 months old.