Context-sensitive analysis of x86 obfuscated executables

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Semi-supervised learning with concept drift using particle dynamics applied to network intrusion detection data

Concept drift, which refers to non stationary learning problems over time, has increasing importance in machine learning and data mining. Many concept drift applications require fast response, which means an algorithm must always be (re)trained with the latest available data. But the process of data labeling is usually expensive and/or time consuming when compared to acquisition of unlabeled data, thus usually only a small fraction of the incoming data may be effectively labeled. Semi-supervised learning methods may help in this scenario, as they use both labeled and unlabeled data in the training process. However, most of them are based on assumptions that the data is static. Therefore, semi-supervised learning with concept drifts is still an open challenging task in machine learning. Recently, a particle competition and cooperation approach has been developed to realize graph-based semi-supervised learning from static data. We have extend that approach to handle data streams and concept drift. The result is a passive algorithm which uses a single classifier approach, naturally adapted to concept changes without any explicit drift detection mechanism. It has built-in mechanisms that provide a natural way of learning from new data, gradually "forgetting" older knowledge as older data items are no longer useful for the classification of newer data items. The proposed algorithm is applied to the KDD Cup 1999 Data of network intrusion, showing its effectiveness.

Particle competition and cooperation for semi-supervised learning with label noise

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

Doxycycline hyclate: a review of properties, applications and analytical methods

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

A Graph Model for DynamicWaveband Switching in WDM Mesh Networks

We investigate the problem of waveband switching (WBS) in a wavelength-division multiplexing (WDM) mesh network with dynamic traffic requests. To solve the WBS problem in a homogeneous dynamic WBS network, where every node is a multi-granular optical cross-connect (MG-OXC), we construct an auxiliary graph. Based on the auxiliary graph, we develop two heuristic on-line WBS algorithms with different grouping policies, namely the wavelength-first WBS algorithm based on the auxiliary graph (WFAUG) and the waveband-first WBS algorithm based on the auxiliary graph (BFAUG). Our results show that the WFAUG algorithm outperforms the BFAUG algorithm.

Particle Competition and Cooperation in Networks for Semi-Supervised Learning

Semi-supervised learning is one of the important topics in machine learning, concerning with pattern classification where only a small subset of data is labeled. In this paper, a new network-based (or graph-based) semi-supervised classification model is proposed. It employs a combined random-greedy walk of particles, with competition and cooperation mechanisms, to propagate class labels to the whole network. Due to the competition mechanism, the proposed model has a local label spreading fashion, i.e., each particle only visits a portion of nodes potentially belonging to it, while it is not allowed to visit those nodes definitely occupied by particles of other classes. In this way, a "divide-and-conquer" effect is naturally embedded in the model. As a result, the proposed model can achieve a good classification rate while exhibiting low computational complexity order in comparison to other network-based semi-supervised algorithms. Computer simulations carried out for synthetic and real-world data sets provide a numeric quantification of the performance of the method.

A MODIS-Based Energy Balance to Estimate Evapotranspiration for Clear-Sky Days in Brazilian Tropical Savannas

Evapotranspiration (ET) plays an important role in global climate dynamics and in primary production of terrestrial ecosystems; it represents the mass and energy transfer from the land to atmosphere. Limitations to measuring ET at large scales using ground-based methods have motivated the development of satellite remote sensing techniques. The purpose of this work is to evaluate the accuracy of the SEBAL algorithm for estimating surface turbulent heat fluxes at regional scale, using 28 images from MODIS. SEBAL estimates are compared with eddy-covariance (EC) measurements and results from the hydrological model MGB-IPH. SEBAL instantaneous estimates of latent heat flux (LE) yielded r(2) = 0.64 and r(2) = 0.62 over sugarcane croplands and savannas when compared against in situ EC estimates. At the same sites, daily aggregated estimates of LE were r(2) = 0.76 and r(2) = 0.66, respectively. Energy balance closure showed that turbulent fluxes over sugarcane croplands were underestimated by 7% and 9% over savannas. Average daily ET from SEBAL is in close agreement with estimates from the hydrological model for an overlay of 38,100 km(2) (r(2) = 0.88). Inputs to which the algorithm is most sensitive are vegetation index (NDVI), gradient of temperature (dT) to compute sensible heat flux (H) and net radiation (Re). It was verified that SEBAL has a tendency to overestimate results both at local and regional scales probably because of low sensitivity to soil moisture and water stress. Nevertheless the results confirm the potential of the SEBAL algorithm, when used with MODIS images for estimating instantaneous LE and daily ET from large areas.

Genetic diversity of Leishmania amazonensis strains isolated in northeastern Brazil as revealed by DNA sequencing, PCR-based analyses and molecular karyotyping

Abstract Background Leishmania (Leishmania) amazonensis infection in man results in a clinical spectrum of disease manifestations ranging from cutaneous to mucosal or visceral involvement. In the present study, we have investigated the genetic variability of 18 L. amazonensis strains isolated in northeastern Brazil from patients with different clinical manifestations of leishmaniasis. Parasite DNA was analyzed by sequencing of the ITS flanking the 5.8 S subunit of the ribosomal RNA genes, by RAPD and SSR-PCR and by PFGE followed by hybridization with gene-specific probes. Results ITS sequencing and PCR-based methods revealed genetic heterogeneity among the L. amazonensis isolates examined and molecular karyotyping also showed variation in the chromosome size of different isolates. Unrooted genetic trees separated strains into different groups. Conclusion These results indicate that L. amazonensis strains isolated from leishmaniasis patients from northeastern Brazil are genetically diverse, however, no correlation between genetic polymorphism and phenotype were found.

The performance of four molecular methods for the laboratory diagnosis of congenital toxoplasmosis in amniotic fluid samples

Introduction Toxoplasmosis may be life-threatening in fetuses and in immune-deficient patients. Conventional laboratory diagnosis of toxoplasmosis is based on the presence of IgM and IgG anti-Toxoplasma gondii antibodies; however, molecular techniques have emerged as alternative tools due to their increased sensitivity. The aim of this study was to compare the performance of 4 PCR-based methods for the laboratory diagnosis of toxoplasmosis. One hundred pregnant women who seroconverted during pregnancy were included in the study. The definition of cases was based on a 12-month follow-up of the infants. Methods Amniotic fluid samples were submitted to DNA extraction and amplification by the following 4 Toxoplasma techniques performed with parasite B1 gene primers: conventional PCR, nested-PCR, multiplex-nested-PCR, and real-time PCR. Seven parameters were analyzed, sensitivity (Se), specificity (Sp), positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (PLR), negative likelihood ratio (NLR) and efficiency (Ef). Results Fifty-nine of the 100 infants had toxoplasmosis; 42 (71.2%) had IgM antibodies at birth but were asymptomatic, and the remaining 17 cases had non-detectable IgM antibodies but high IgG antibody titers that were associated with retinochoroiditis in 8 (13.5%) cases, abnormal cranial ultrasound in 5 (8.5%) cases, and signs/symptoms suggestive of infection in 4 (6.8%) cases. The conventional PCR assay detected 50 cases (9 false-negatives), nested-PCR detected 58 cases (1 false-negative and 4 false-positives), multiplex-nested-PCR detected 57 cases (2 false-negatives), and real-time-PCR detected 58 cases (1 false-negative). Conclusions The real-time PCR assay was the best-performing technique based on the parameters of Se (98.3%), Sp (100%), PPV (100%), NPV (97.6%), PLR (â^ž), NLR (0.017), and Ef (99%).

Coarse-graining methods and polymer dynamics

This thesis studies molecular dynamics simulations on two levels of resolution: the detailed level of atomistic simulations, where the motion of explicit atoms in a many-particle system is considered, and the coarse-grained level, where the motion of superatoms composed of up to 10 atoms is modeled. While atomistic models are capable of describing material specific effects on small scales, the time and length scales they can cover are limited due to their computational costs. Polymer systems are typically characterized by effects on a broad range of length and time scales. Therefore it is often impossible to atomistically simulate processes, which determine macroscopic properties in polymer systems. Coarse-grained (CG) simulations extend the range of accessible time and length scales by three to four orders of magnitude. However, no standardized coarse-graining procedure has been established yet. Following the ideas of structure-based coarse-graining, a coarse-grained model for polystyrene is presented. Structure-based methods parameterize CG models to reproduce static properties of atomistic melts such as radial distribution functions between superatoms or other probability distributions for coarse-grained degrees of freedom. Two enhancements of the coarse-graining methodology are suggested. Correlations between local degrees of freedom are implicitly taken into account by additional potentials acting between neighboring superatoms in the polymer chain. This improves the reproduction of local chain conformations and allows the study of different tacticities of polystyrene. It also gives better control of the chain stiffness, which agrees perfectly with the atomistic model, and leads to a reproduction of experimental results for overall chain dimensions, such as the characteristic ratio, for all different tacticities. The second new aspect is the computationally cheap development of nonbonded CG potentials based on the sampling of pairs of oligomers in vacuum. Static properties of polymer melts are obtained as predictions of the CG model in contrast to other structure-based CG models, which are iteratively refined to reproduce reference melt structures. The dynamics of simulations at the two levels of resolution are compared. The time scales of dynamical processes in atomistic and coarse-grained simulations can be connected by a time scaling factor, which depends on several specific system properties as molecular weight, density, temperature, and other components in mixtures. In this thesis the influence of molecular weight in systems of oligomers and the situation in two-component mixtures is studied. For a system of small additives in a melt of long polymer chains the temperature dependence of the additive diffusion is predicted and compared to experiments.

Permutation-based stochastic ordering using pairwise comparisons

The topic of this work concerns nonparametric permutation-based methods aiming to find a ranking (stochastic ordering) of a given set of groups (populations), gathering together information from multiple variables under more than one experimental designs. The problem of ranking populations arises in several fields of science from the need of comparing G>2 given groups or treatments when the main goal is to find an order while taking into account several aspects. As it can be imagined, this problem is not only of theoretical interest but it also has a recognised relevance in several fields, such as industrial experiments or behavioural sciences, and this is reflected by the vast literature on the topic, although sometimes the problem is associated with different keywords such as: "stochastic ordering", "ranking", "construction of composite indices" etc., or even "ranking probabilities" outside of the strictly-speaking statistical literature. The properties of the proposed method are empirically evaluated by means of an extensive simulation study, where several aspects of interest are let to vary within a reasonable practical range. These aspects comprise: sample size, number of variables, number of groups, and distribution of noise/error. The flexibility of the approach lies mainly in the several available choices for the test-statistic and in the different types of experimental design that can be analysed. This render the method able to be tailored to the specific problem and the to nature of the data at hand. To perform the analyses an R package called SOUP (Stochastic Ordering Using Permutations) has been written and it is available on CRAN.

Proteomic analysis of ocular surface components by use of HPLC based mass spectrometric strategies

In der vorliegenden Arbeit wurde eine Top Down (TD) und zwei Bottom Up (BU) MALDI/ESI Massenspektrometrie/HPLC-Methoden entwickelt mit dem Ziel Augenoberfächenkomponenten, d.h. Tränenfilm und Konjunktivalzellen zu analysieren. Dabei wurde ein detaillierter Einblick in die Entwicklungsschritte gegeben und die Ansätze auf Eignung und methodische Grenzen untersucht. Während der TD Ansatz vorwiegend Eignung zur Analyse von rohen, weitgehend unbearbeiteten Zellproben fand, konnten mittels des BU Ansatzes bearbeitete konjunktivale Zellen, aber auch Tränenfilm mit hoher Sensitivität und Genauigkeit proteomisch analysiert werden. Dabei konnten mittels LC MALDI BU-Methode mehr als 200 Tränenproteine und mittels der LC ESI Methode mehr als 1000 Tränen- sowie konjunktivale Zellproteine gelistet werden. Dabei unterschieden sich ESI- and MALDI- Methoden deutlich bezüglich der Quantität und Qualität der Ergebnisse, weshalb differente proteomische Anwendungsgebiete der beiden Methoden vorgeschlagen wurden. Weiterhin konnten mittels der entwickelten LC MALDI/ESI BU Plattform, basierend auf den Vorteilen gegenüber dem TD Ansatz, therapeutische Einflüsse auf die Augenoberfläche mit Fokus auf die topische Anwendung von Taurin sowie Taflotan® sine, untersucht werden. Für Taurin konnten entzündungshemmende Effekte, belegt durch dynamische Veränderungen des Tränenfilms, dokumentiert werden. Außerdem konnten vorteilhafte, konzentrationsabhängige Wirkweisen auch in Studien an konjunktival Zellen gezeigt werden. Für die Anwendung von konservierungsmittelfreien Taflotan® sine, konnte mittels LC ESI BU Analyse eine Regenerierung der Augenoberfläche in Patienten mit Primärem Offenwinkel Glaukom (POWG), welche unter einem “Trockenem Auge“ litten nach einem therapeutischen Wechsel von Xalatan® basierend auf dynamischen Tränenproteomveränderungen gezeigt werden. Die Ergebnisse konnten mittels Microarray (MA) Analysen bestätigt werden. Sowohl in den Taurin Studien, als auch in der Taflotan® sine Studie, konnten charakteristische Proteine der Augenoberfläche dokumentiert werden, welche eine objektive Bewertung des Gesundheitszustandes der Augenoberfläche ermöglichen. Eine Kombination von Taflotan® sine und Taurin wurde als mögliche Strategie zur Therapie des Trockenen Auges bei POWG Patienten vorgeschlagen und diskutiert.

Novel materials for direct X-ray detectors based on semiconducting organic polymers

Conventional inorganic materials for x-ray radiation sensors suffer from several drawbacks, including their inability to cover large curved areas, me- chanical sti ffness, lack of tissue-equivalence and toxicity. Semiconducting organic polymers represent an alternative and have been employed as di- rect photoconversion material in organic diodes. In contrast to inorganic detector materials, polymers allow low-cost and large area fabrication by sol- vent based methods. In addition their processing is compliant with fexible low-temperature substrates. Flexible and large-area detectors are needed for dosimetry in medical radiotherapy and security applications. The objective of my thesis is to achieve optimized organic polymer diodes for fexible, di- rect x-ray detectors. To this end polymer diodes based on two different semi- conducting polymers, polyvinylcarbazole (PVK) and poly(9,9-dioctyluorene) (PFO) have been fabricated. The diodes show state-of-the-art rectifying be- haviour and hole transport mobilities comparable to reference materials. In order to improve the X-ray stopping power, high-Z nanoparticle Bi2O3 or WO3 where added to realize a polymer-nanoparticle composite with opti- mized properities. X-ray detector characterization resulted in sensitivties of up to 14 uC/Gy/cm2 for PVK when diodes were operated in reverse. Addition of nanoparticles could further improve the performance and a maximum sensitivy of 19 uC/Gy/cm2 was obtained for the PFO diodes. Compared to the pure PFO diode this corresponds to a five-fold increase and thus highlights the potentiality of nanoparticles for polymer detector design. In- terestingly the pure polymer diodes showed an order of magnitude increase in sensitivity when operated in forward regime. The increase was attributed to a different detection mechanism based on the modulation of the diodes conductivity.

A Hybrid Multimodal Non-Rigid Registration of MR Images Based on Diffeomorphic Demons

n this paper we present a novel hybrid approach for multimodal medical image registration based on diffeomorphic demons. Diffeomorphic demons have proven to be a robust and efficient way for intensity-based image registration. A very recent extension even allows to use mutual information (MI) as a similarity measure to registration multimodal images. However, due to the intensity correspondence uncertainty existing in some anatomical parts, it is difficult for a purely intensity-based algorithm to solve the registration problem. Therefore, we propose to combine the resulting transformations from both intensity-based and landmark-based methods for multimodal non-rigid registration based on diffeomorphic demons. Several experiments on different types of MR images were conducted, for which we show that a better anatomical correspondence between the images can be obtained using the hybrid approach than using either intensity information or landmarks alone.

Influence of different professional prophylactic methods on fluorescence measurements for detection of occlusal caries

This study aimed to evaluate the influence of professional prophylactic methods on the DIAGNOdent 2095, DIAGNOdent 2190 and VistaProof performance in detecting occlusal caries. Assessments were performed in 110 permanent teeth at baseline and after bicarbonate jet or prophylactic paste and rinsing. Performance in terms of sensitivity improved after rinsing of the occlusal surfaces when the prophylactic paste was used. However, the sodium bicarbonate jet did not significantly influence the performance of the fluorescence-based methods. It can be concluded that different professional prophylactic methods can significantly influence the performance of fluorescence-based methods for occlusal caries detection.