Proposing a hybrid-intelligent framework to secure e-government web applications

One of the essential needs to implement a successful e-Government web application is security. Web application firewalls (WAF) are the most important tool to secure web applications against the increasing number of web application attacks nowadays. WAFs work in different modes depending on the web traffic filtering approach used, such as positive security mode, negative security mode, session-based mode, or mixed modes. The proposed WAF, which is called (HiWAF), is a web application firewall that works in three modes: positive, negative and session based security modes. The new approach that distinguishes this WAF among other WAFs is that it utilizes the concepts of Artificial Intelligence (AI) instead of regular expressions or other traditional pattern matching techniques as its filtering engine. Both artificial neural networks and fuzzy logic concepts will be used to implement a hybrid intelligent web application firewall that works in three security modes.

Small-world effects in lattice stochastic diffusion search

Stochastic Diffusion Search is an efficient probabilistic bestfit search technique, capable of transformation invariant pattern matching. Although inherently parallel in operation it is difficult to implement efficiently in hardware as it requires full inter-agent connectivity. This paper describes a lattice implementation, which, while qualitatively retaining the properties of the original algorithm, restricts connectivity, enabling simpler implementation on parallel hardware. Diffusion times are examined for different network topologies, ranging from ordered lattices, over small-world networks to random graphs.

The impact of uncertainty in satellite data on the assessment of flood inundation models

The performance of flood inundation models is often assessed using satellite observed data; however these data have inherent uncertainty. In this study we assess the impact of this uncertainty when calibrating a flood inundation model (LISFLOOD-FP) for a flood event in December 2006 on the River Dee, North Wales, UK. The flood extent is delineated from an ERS-2 SAR image of the event using an active contour model (snake), and water levels at the flood margin calculated through intersection of the shoreline vector with LiDAR topographic data. Gauged water levels are used to create a reference water surface slope for comparison with the satellite-derived water levels. Residuals between the satellite observed data points and those from the reference line are spatially clustered into groups of similar values. We show that model calibration achieved using pattern matching of observed and predicted flood extent is negatively influenced by this spatial dependency in the data. By contrast, model calibration using water elevations produces realistic calibrated optimum friction parameters even when spatial dependency is present. To test the impact of removing spatial dependency a new method of evaluating flood inundation model performance is developed by using multiple random subsamples of the water surface elevation data points. By testing for spatial dependency using Moran’s I, multiple subsamples of water elevations that have no significant spatial dependency are selected. The model is then calibrated against these data and the results averaged. This gives a near identical result to calibration using spatially dependent data, but has the advantage of being a statistically robust assessment of model performance in which we can have more confidence. Moreover, by using the variations found in the subsamples of the observed data it is possible to assess the effects of observational uncertainty on the assessment of flooding risk.

The use of land-sea warming contrast under climate change to improve impact metrics

A favoured method of assimilating information from state-of-the-art climate models into integrated assessment models of climate impacts is to use the transient climate response (TCR) of the climate models as an input, sometimes accompanied by a pattern matching approach to provide spatial information. More recent approaches to the problem use TCR with another independent piece of climate model output: the land-sea surface warming ratio (φ). In this paper we show why the use of φ in addition to TCR has such utility. Multiple linear regressions of surface temperature change onto TCR and φ in 22 climate models from the CMIP3 multi-model database show that the inclusion of φ explains a much greater fraction of the inter-model variance than using TCR alone. The improvement is particularly pronounced in North America and Eurasia in the boreal summer season, and in the Amazon all year round. The use of φ as the second metric is beneficial for three reasons: firstly it is uncorrelated with TCR in state-of-the-art climate models and can therefore be considered as an independent metric; secondly, because of its projected time-invariance, the magnitude of φ is better constrained than TCR in the immediate future; thirdly, the use of two variables is much simpler than approaches such as pattern scaling from climate models. Finally we show how using the latest estimates of φ from climate models with a mean value of 1.6—as opposed to previously reported values of 1.4—can significantly increase the mean time-integrated discounted damage projections in a state-of-the-art integrated assessment model by about 15 %. When compared to damages calculated without the inclusion of the land-sea warming ratio, this figure rises to 65 %, equivalent to almost 200 trillion dollars over 200 years.

Wavelet-based dynamic time warping

Dynamic Time Warping (DTW), a pattern matching technique traditionally used for restricted vocabulary speech recognition, is based on a temporal alignment of the input signal with the template models. The principal drawback of DTW is its high computational cost as the lengths of the signals increase. This paper shows extended results over our previously published conference paper, which introduces an optimized version of the DTW I hat is based on the Discrete Wavelet Transform (DWT). (C) 2008 Elsevier B.V. All rights reserved.

Real-Time Recognition System for Traffic Signs

The aim of this thesis project is to develop the Traffic Sign Recognition algorithm for real time. Inreal time environment, vehicles move at high speed on roads. For the vehicle intelligent system itbecomes essential to detect, process and recognize the traffic sign which is coming in front ofvehicle with high relative velocity, at the right time, so that the driver would be able to pro-actsimultaneously on instructions given in the Traffic Sign. The system assists drivers about trafficsigns they did not recognize before passing them. With the Traffic Sign Recognition system, thevehicle becomes aware of the traffic environment and reacts according to the situation.The objective of the project is to develop a system which can recognize the traffic signs in real time.The three target parameters are the system’s response time in real-time video streaming, the trafficsign recognition speed in still images and the recognition accuracy. The system consists of threeprocesses; the traffic sign detection, the traffic sign recognition and the traffic sign tracking. Thedetection process uses physical properties of traffic signs based on a priori knowledge to detect roadsigns. It generates the road sign image as the input to the recognition process. The recognitionprocess is implemented using the Pattern Matching algorithm. The system was first tested onstationary images where it showed on average 97% accuracy with the average processing time of0.15 seconds for traffic sign recognition. This procedure was then applied to the real time videostreaming. Finally the tracking of traffic signs was developed using Blob tracking which showed theaverage recognition accuracy to 95% in real time and improved the system’s average response timeto 0.04 seconds. This project has been implemented in C-language using the Open Computer VisionLibrary.

Negociações de ganhos mútuos: um estudo de caso na empresa pública delta

A negociação é a ferramenta mais eficiente de conseguir algo que se deseja, ela ocorre quando existem conflitos e alternativas a serem selecionadas que podem envolver toda a empresa. As diversas alternativas apresentam interesses comuns e conflitantes, expressando a complexidade das relações. Com a crescente demanda por agilidade na resposta aos novos perfis de procura, as organizações precisam ser mais versáteis nos processos e mais rápidas para reagir às mudanças do mercado, e as Negociações de Ganhos Mútuos (NGM) são uma forma atual de condução de criação de valor. Esta dissertação tem como objetivo propor a utilização das ferramentas da teoria de NGM como instrumento apoiador aos gestores de compras públicas adquirentes de produtos e serviços de TI a atingir os resultados esperados. Para isso, foi realizada uma pesquisa de natureza descritiva-exploratória por meio de abordagem qualitativa. Para atingir este objetivo, foram feitos estudos teóricos das temáticas: Flexibilidade Organizacional, Gestão de Compras Públicas, Sistemas de Informação, Alinhamento Estratégico e Teoria da Negociação, de forma a se obter um melhor entendimento da pesquisa. Foi elaborado um questionário não estruturado, sendo este o instrumento de pesquisa que foi utilizado neste estudo. Aplicado o questionário diretamente aos participantes, obteve-se uma participação de 10 respondentes, sendo todos participantes dos processos licitatórios na empresa pública Delta. Uma vez efetuada a coleta de dados, foram analisadas as respostas utilizando uma modalidade da técnica de análise de conteúdo, chamada pattern-matching, com o propósito de comparar os resultados com o referencial teórico utilizado no estudo. Como resultado do estudo, identificou-se a utilização da abordagem distributiva nos processos licitatórios.

Arquiteturas eficientes para sensoriamento espectral e classificação automática de modulações usando características cicloestacionárias

The increasing demand for high performance wireless communication systems has shown the inefficiency of the current model of fixed allocation of the radio spectrum. In this context, cognitive radio appears as a more efficient alternative, by providing opportunistic spectrum access, with the maximum bandwidth possible. To ensure these requirements, it is necessary that the transmitter identify opportunities for transmission and the receiver recognizes the parameters defined for the communication signal. The techniques that use cyclostationary analysis can be applied to problems in either spectrum sensing and modulation classification, even in low signal-to-noise ratio (SNR) environments. However, despite the robustness, one of the main disadvantages of cyclostationarity is the high computational cost for calculating its functions. This work proposes efficient architectures for obtaining cyclostationary features to be employed in either spectrum sensing and automatic modulation classification (AMC). In the context of spectrum sensing, a parallelized algorithm for extracting cyclostationary features of communication signals is presented. The performance of this features extractor parallelization is evaluated by speedup and parallel eficiency metrics. The architecture for spectrum sensing is analyzed for several configuration of false alarm probability, SNR levels and observation time for BPSK and QPSK modulations. In the context of AMC, the reduced alpha-profile is proposed as as a cyclostationary signature calculated for a reduced cyclic frequencies set. This signature is validated by a modulation classification architecture based on pattern matching. The architecture for AMC is investigated for correct classification rates of AM, BPSK, QPSK, MSK and FSK modulations, considering several scenarios of observation length and SNR levels. The numerical results of performance obtained in this work show the eficiency of the proposed architectures

Developing a research agenda for promoting physical activity in Brazil through environmental and policy change

Objective. To identify the highest priorities for research on environmental and policy changes for promoting physical activity (PA) in Brazil; to uncover any gaps between researchers' and practitioners' priorities; and to consider which tools, methods, collaborative strategies, and actions could be useful to moving a research agenda forward.Methods. This was a mixed-methods study (qualitative and quantitative) conducted by Project GUIA (Guide for Useful Interventions for Activity in Brazil and Latin America) in February 2010-January 2011. A total of 240 individuals in the PA field (186 practitioners and 54 researchers) were asked to generate research ideas; 82 participants provided 266 original statements from which 52 topics emerged. Participants rated topics by "importance" and "feasibility;" a separate convenience sample of 21 individuals categorized them. Cluster analysis and multidimensional scaling were used to create concept maps and pattern matches.Results. Five distinct clusters emerged from the concept mapping, of which " effectiveness and innovation in PA interventions" was rated most important by both practitioners and researchers. Pattern matching showed a divergence between the groups, especially regarding feasibility, where there was no consensus.Conclusions. The study results provided the basis for a research agenda to advance the understanding of environmental and policy influences on PA promotion in Brazil and Latin America. These results should stimulate future research and, ultimately, contribute to the evidence-base of successful PA strategies in Latin America.

Identification of Drosophila heart-specific Cis-Regulatory Modules under Hox control

Cardiac morphogenesis is a complex process governed by evolutionarily conserved transcription factors and signaling molecules. The Drosophila cardiac tube is linear, made of 52 pairs of cardiomyocytes (CMs), which express specific transcription factor genes that have human homologues implicated in Congenital Heart Diseases (CHDs) (NKX2-5, GATA4 and TBX5). The Drosophila cardiac tube is linear and composed of a rostral portion named aorta and a caudal one called heart, distinguished by morphological and functional differences controlled by Hox genes, key regulators of axial patterning. Overexpression and inactivation of the Hox gene abdominal-A (abd-A), which is expressed exclusively in the heart, revealed that abd-A controls heart identity. The aim of our work is to isolate the heart-specific cisregulatory sequences of abd-A direct target genes, the realizator genes granting heart identity. In each segment of the heart, four pairs of cardiomyocytes (CMs) express tinman (tin), homologous to NKX2-5, and acquire strong contractile and automatic rhythmic activities. By tyramide amplified FISH, we found that seven genes, encoding ion channels, pumps or transporters, are specifically expressed in the Tin-CMs of the heart. We initially used online available tools to identify their heart-specific cisregutatory modules by looking for Conserved Non-coding Sequences containing clusters of binding sites for various cardiac transcription factors, including Hox proteins. Based on these data we generated several reporter gene constructs and transgenic embryos, but none of them showed reporter gene expression in the heart. In order to identify additional abd-A target genes, we performed microarray experiments comparing the transcriptomes of aorta versus heart and identified 144 genes overexpressed in the heart. In order to find the heart-specific cis-regulatory regions of these target genes we developed a new bioinformatic approach where prediction is based on pattern matching and ordered statistics. We first retrieved Conserved Noncoding Sequences from the alignment between the D.melanogaster and D.pseudobscura genomes. We scored for combinations of conserved occurrences of ABD-A, ABD-B, TIN, PNR, dMEF2, MADS box, T-box and E-box sites and we ranked these results based on two independent strategies. On one hand we ranked the putative cis-regulatory sequences according to best scored ABD-A biding sites, on the other hand we scored according to conservation of binding sites. We integrated and ranked again the two lists obtained independently to produce a final rank. We generated nGFP reporter construct flies for in vivo validation. We identified three 1kblong heart-specific enhancers. By in vivo and in vitro experiments we are determining whether they are direct abd-A targets, demonstrating the role of a Hox gene in the realization of heart identity. The identified abd-A direct target genes may be targets also of the NKX2-5, GATA4 and/or TBX5 homologues tin, pannier and Doc genes, respectively. The identification of sequences coregulated by a Hox protein and the homologues of transcription factors causing CHDs, will provide a mean to test whether these factors function as Hox cofactors granting cardiac specificity to Hox proteins, increasing our knowledge on the molecular mechanisms underlying CHDs. Finally, it may be investigated whether these Hox targets are involved in CHDs.

Methodologies for visual correspondence

Visual correspondence is a key computer vision task that aims at identifying projections of the same 3D point into images taken either from different viewpoints or at different time instances. This task has been the subject of intense research activities in the last years in scenarios such as object recognition, motion detection, stereo vision, pattern matching, image registration. The approaches proposed in literature typically aim at improving the state of the art by increasing the reliability, the accuracy or the computational efficiency of visual correspondence algorithms. The research work carried out during the Ph.D. course and presented in this dissertation deals with three specific visual correspondence problems: fast pattern matching, stereo correspondence and robust image matching. The dissertation presents original contributions to the theory of visual correspondence, as well as applications dealing with 3D reconstruction and multi-view video surveillance.