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.

Robust extended Kalman filter based technique for location management in PCS networks

Provisioning of real-time multimedia sessions over wireless cellular network poses unique challenges due to frequent handoff and rerouting of a connection. For this reason, the wireless networks with cellular architecture require efficient user mobility estimation and prediction. This paper proposes using Robust Extended Kalman Filter as a location heading altitude estimator of mobile user for next cell prediction in order to improve the connection reliability and bandwidth efficiency of the underlying system. Through analysis we demonstrate that our algorithm reduces the system complexity (compared to existing approach using pattern matching and Kalman filter) as it requires only two base station measurements or only the measurement from the closest base station. Further, the technique is robust against system uncertainties due to inherent deterministic nature in the mobility model. Through simulation, we show the accuracy and simplicity in implementation of our prediction algorithm.

Robust extended kalman filter applied to location tracking and trajectory prediction for PCS networks

Provisioning of real-time multimedia sessions over wireless cellular network poses unique challenges due to frequent handoff and rerouting of a connection. For this reason, the wireless networks with cellular architecture require efficient user mobility estimation and prediction. This paper proposes using robust extended Kalman filter (REKF) as a location heading altitude estimator of mobile user for next cell prediction in order to improve the connection reliability and bandwidth efficiency of the underlying system. Through analysis we demonstrate that our algorithm reduces the system complexity (compared to existing approach using pattern matching and Kalman filter) as it requires only two base station measurements or only the measurement from the closest base station. Further, the technique is robust against system uncertainties due to inherent deterministic nature in the mobility model and more effective in comparison with the standard Kalman filter.

Decision analysis of statistically detecting distributed denial-of-service flooding attacks

There are two statistical decision making questions regarding statistically detecting sings of denial-of-service flooding attacks. One is how to represent the distributions of detection probability, false alarm probability and miss probability. The other is how to quantitatively express a decision region within which one may make a decision that has high detection probability, low false alarm probability and low miss probability. This paper gives the answers to the above questions. In addition, a case study is demonstrated.

Study protocol for the translating research in elder care (TREC): Building context through case studies in long-term care project (project two)

Background: The organizational context in which healthcare is delivered is thought to play an important role in mediating the use of knowledge in practice. Additionally, a number of potentially modifiable contextual factors have been shown to make an organizational context more amenable to change. However, understanding of how these factors operate to influence organizational context and knowledge use remains limited. In particular, research to understand knowledge translation in the long-term care setting is scarce. Further research is therefore required to provide robust explanations of the characteristics of organizational context in relation to knowledge use.
Aim: To develop a robust explanation of the way organizational context mediates the use of knowledge in practice in long-term care facilities.
Design: This is longitudinal, in-depth qualitative case study research using exploratory and interpretive methods to explore the role of organizational context in influencing knowledge translation. The study will be conducted in two phases. In phase one, comprehensive case studies will be conducted in three facilities. Following data analysis and proposition development, phase two will continue with focused case studies to elaborate emerging themes and theory. Study sites will be purposively selected. In both phases, data will be collected using a variety of approaches, including non-participant observation, key informant interviews, family perspectives, focus groups, and documentary evidence (including, but not limited to, policies, notices, and photographs of physical resources). Data analysis will comprise an iterative process of identifying convergent evidence within each case study and then examining and comparing the evidence across multiple case studies to draw conclusions from the study as a whole. Additionally, findings that emerge through this project will be compared and considered alongside those that are emerging from project one. In this way, pattern matching based on explanation building will be used to frame the analysis and develop an explanation of organizational context and knowledge use over time. An improved understanding of the contextual factors that mediate knowledge use will inform future development and testing of interventions to enhance knowledge use, with the ultimate aim of improving the outcomes for residents in long-term care settings.

Hierarchical rule generalisation for speaker identification in fiction books

This paper presents a hierarchical pattern matching and generalisation technique which is applied to the problem of locating the correct speaker of quoted speech found in fiction books. Patterns from a training set are generalised to create a small number of rules, which can be used to identify items of interest within the text. The pattern matching technique is applied to finding the Speech-Verb, Actor and Speaker of quotes found in ction books. The technique performs well over the training data, resulting in rule-sets many times smaller than the training set, but providing very high accuracy. While the rule-set generalised from one book is less effective when applied to different books than an approach based on hand coded heuristics, performance is comparable when testing on data closely related to the training set.

Object oriented regular expressions

Regular expressions are used to parse textual data to match patterns and extract variables. They have been implemented in a vast number of programming languages with a significant quantity of research devoted to improving their operational efficiency. However, regular expressions are limited to finding linear matches. Little research has been done in the field of object-oriented results which would allow textual or binary data to be converted to multi-layered objects. This is significantly relevant as many of todaypsilas data formats are object-based. This paper extends our previous work by detailing an algorithmic approach to perform object-oriented parsing, and provides an initial study of benchmarks of the algorithms of our contribution

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.