911 resultados para Traffic Pattern Analysis


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Texture is one of the most important visual attributes for image analysis. It has been widely used in image analysis and pattern recognition. A partially self-avoiding deterministic walk has recently been proposed as an approach for texture analysis with promising results. This approach uses walkers (called tourists) to exploit the gray scale image contexts in several levels. Here, we present an approach to generate graphs out of the trajectories produced by the tourist walks. The generated graphs embody important characteristics related to tourist transitivity in the image. Computed from these graphs, the statistical position (degree mean) and dispersion (entropy of two vertices with the same degree) measures are used as texture descriptors. A comparison with traditional texture analysis methods is performed to illustrate the high performance of this novel approach. (C) 2011 Elsevier Ltd. All rights reserved.

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This paper introduces a novel methodology to shape boundary characterization, where a shape is modeled into a small-world complex network. It uses degree and joint degree measurements in a dynamic evolution network to compose a set of shape descriptors. The proposed shape characterization method has all efficient power of shape characterization, it is robust, noise tolerant, scale invariant and rotation invariant. A leaf plant classification experiment is presented on three image databases in order to evaluate the method and compare it with other descriptors in the literature (Fourier descriptors, Curvature, Zernike moments and multiscale fractal dimension). (C) 2008 Elsevier Ltd. All rights reserved.

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Complex networks exist in many areas of science such as biology, neuroscience, engineering, and sociology. The growing development of this area has led to the introduction of several topological and dynamical measurements, which describe and quantify the structure of networks. Such characterization is essential not only for the modeling of real systems but also for the study of dynamic processes that may take place in them. However, it is not easy to use several measurements for the analysis of complex networks, due to the correlation between them and the difficulty of their visualization. To overcome these limitations, we propose an effective and comprehensive approach for the analysis of complex networks, which allows the visualization of several measurements in a few projections that contain the largest data variance and the classification of networks into three levels of detail, vertices, communities, and the global topology. We also demonstrate the efficiency and the universality of the proposed methods in a series of real-world networks in the three levels.

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This work presents a novel approach in order to increase the recognition power of Multiscale Fractal Dimension (MFD) techniques, when applied to image classification. The proposal uses Functional Data Analysis (FDA) with the aim of enhancing the MFD technique precision achieving a more representative descriptors vector, capable of recognizing and characterizing more precisely objects in an image. FDA is applied to signatures extracted by using the Bouligand-Minkowsky MFD technique in the generation of a descriptors vector from them. For the evaluation of the obtained improvement, an experiment using two datasets of objects was carried out. A dataset was used of characters shapes (26 characters of the Latin alphabet) carrying different levels of controlled noise and a dataset of fish images contours. A comparison with the use of the well-known methods of Fourier and wavelets descriptors was performed with the aim of verifying the performance of FDA method. The descriptor vectors were submitted to Linear Discriminant Analysis (LDA) classification method and we compared the correctness rate in the classification process among the descriptors methods. The results demonstrate that FDA overcomes the literature methods (Fourier and wavelets) in the processing of information extracted from the MFD signature. In this way, the proposed method can be considered as an interesting choice for pattern recognition and image classification using fractal analysis.

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Recently, the deterministic tourist walk has emerged as a novel approach for texture analysis. This method employs a traveler visiting image pixels using a deterministic walk rule. Resulting trajectories provide clues about pixel interaction in the image that can be used for image classification and identification tasks. This paper proposes a new walk rule for the tourist which is based on contrast direction of a neighborhood. The yielded results using this approach are comparable with those from traditional texture analysis methods in the classification of a set of Brodatz textures and their rotated versions, thus confirming the potential of the method as a feasible texture analysis methodology. (C) 2010 Elsevier B.V. All rights reserved.

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Burst firing is ubiquitous in nervous systems and has been intensively studied in central pattern generators (CPGs). Previous works have described subtle intraburst spike patterns (IBSPs) that, despite being traditionally neglected for their lack of relation to CPG motor function, were shown to be cell-type specific and sensitive to CPG connectivity. Here we address this matter by investigating how a bursting motor neuron expresses information about other neurons in the network. We performed experiments on the crustacean stomatogastric pyloric CPG, both in control conditions and interacting in real-time with computer model neurons. The sensitivity of postsynaptic to presynaptic IBSPs was inferred by computing their average mutual information along each neuron burst. We found that details of input patterns are nonlinearly and inhomogeneously coded through a single synapse into the fine IBSPs structure of the postsynaptic neuron following burst. In this way, motor neurons are able to use different time scales to convey two types of information simultaneously: muscle contraction (related to bursting rhythm) and the behavior of other CPG neurons (at a much shorter timescale by using IBSPs as information carriers). Moreover, the analysis revealed that the coding mechanism described takes part in a previously unsuspected information pathway from a CPG motor neuron to a nerve that projects to sensory brain areas, thus providing evidence of the general physiological role of information coding through IBSPs in the regulation of neuronal firing patterns in remote circuits by the CNS.

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Royal palm tree peroxidase (RPTP) is a very stable enzyme in regards to acidity, temperature, H(2)O(2), and organic solvents. Thus, RPTP is a promising candidate for developing H(2)O(2)-sensitive biosensors for diverse applications in industry and analytical chemistry. RPTP belongs to the family of class III secretory plant peroxidases, which include horseradish peroxidase isozyme C, soybean and peanut peroxidases. Here we report the X-ray structure of native RPTP isolated from royal palm tree (Roystonea regia) refined to a resolution of 1.85 angstrom. RPTP has the same overall folding pattern of the plant peroxidase superfamily, and it contains one heme group and two calcium-binding sites in similar locations. The three-dimensional structure of RPTP was solved for a hydroperoxide complex state, and it revealed a bound 2-(N-morpholino) ethanesulfonic acid molecule (MES) positioned at a putative substrate-binding secondary site. Nine N-glycosylation sites are clearly defined in the RPTP electron-density maps, revealing for the first time conformations of the glycan chains of this highly glycosylated enzyme. Furthermore, statistical coupling analysis (SCA) of the plant peroxidase superfamily was performed. This sequence-based method identified a set of evolutionarily conserved sites that mapped to regions surrounding the heme prosthetic group. The SCA matrix also predicted a set of energetically coupled residues that are involved in the maintenance of the structural folding of plant peroxidases. The combination of crystallographic data and SCA analysis provides information about the key structural elements that could contribute to explaining the unique stability of RPTP. (C) 2009 Elsevier Inc. All rights reserved.

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The Neoproterozoic (Ediacaran) Itapucumi Group in northern Paraguay is composed of carbonate and siliciclastic rocks, including ooid grainstones, marls, shales and sandstones, containing Cloudina fossils in the eastern region. It is almost undeformed over the Rio Apa Cratonic Block but shows a strong deformational pattern at its western edge. A detailed structural analysis of the Itapucumi Group was conducted in the Vallemi Mine, along with a regional survey in other outcrops downstream in the Paraguay River and in the San Alfredo, Cerro Paiva and Sargent Jose E. Lopez regions. In the main Vallemi quarry, the structural style is characterized by an axial-plane slaty cleavage in open to isoclinal folds, sometimes overturned, associated with N-S trending thrust faults and shear zones of E-vergence and with a low-grade chlorite zone metamorphism. The structural data presented here are compatible with the hypothesis of a newly recognized mobile belt on the western side of the Rio Apa Cratonic Block, with opposite vergence to that of the Paraguay Mobile Belt in Brazil. Both belts are related to the Late Brasiliano/Pan-African tectonic cycle with a Lower Cambrian deformation and metamorphism age. The deformation could be due to the late collision of the Amazonian Craton with the remainder of Western Gondwana or to the western active plate boundary related to the Pampean Belt. The structural and lithologic differences between the western Itapucumi Group in the Vallemi and Paraguay River region and the eastern region, near San Alfredo and Cerro Paiva, suggest that this group could be divided into two lithostratigraphic units, but more stratigraphic and geochronological analyses are required to confirm this possibility. (C) 2010 Elsevier Ltd. All rights reserved.

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Statement of the problem: The performance of self-etch systems on enamel is controversial and seems to be dependent on the application technique and the enamel preparation. Purpose of the Study: To examine the effects of conditioning time and enamel surface preparation on bond strength and etching pattern of adhesive systems to enamel. Materials and Methods: Ninety-six teeth were divided into 16 conditions (N = 6) in function of enamel preparation and conditioning time for bond strength test. The adhesive systems OptiBond FL (Kerr, Orange, CA, USA), OptiBond SOLO Plus (Kerr), Clearfil SE Bond (Kuraray, Osaka, Japan), and Adper Prompt L-Pop (3M ESPE, St. Paul, MN, USA) were applied on unground or ground enamel following the manufacturers` directions or doubling the conditioning time. Cylinders of Filtek Flow (0.5-mm height) were applied to each bonded enamel surface using a Tygon tube (0.7 mm in diameter; Saint-Gobain Corp., Aurora, OH, USA). After storage (24 h/37 degrees C), the specimens were subjected to shear force (0.5 mm/min). The data were treated by a three-way analysis of variance and Tukey`s test (alpha = 0.05). The failure modes of the debonded interfaces and the etching pattern of adhesives were observed using scanning electron microscopy. Results: Only the main factor ""adhesive"" was statistically significant (p < 0.001). The lowest bond strength value was observed for OptiBond FL. The most defined etching pattern was observed for 35% phosphoric acid and for Adper Prompt L-Pop. Mixed failures were observed for all adhesives, but OptiBond FL showed cohesive failures in resin predominantly. Conclusions: The increase in the conditioning time as well as the enamel pretreatment did not provide an increase in the resin-enamel bond strength values for the studied adhesives. CLINICAL SIGNIFICANCE The surface enamel preparation and the conditioning time do not affect the performance of self-etch systems to enamel. (J Esthet Restor Dent 20:322-336, 2008)

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Blastocladiella emersonii is an aquatic fungus of the Chytridiomycete class. During germination, the zoospore, a motile nongrowing cell, goes through a cascade of morphological changes that culminates with its differentiation into the germling cell, capable of coenocytic vegetative growth. Transcriptome analyses of B. emersonii cells were carried out during germination induced under various environmental conditions. Microarray data analyzing 3,563 distinct B. emersonii genes revealed that 26% of them are differentially expressed during germination in nutrient medium at at least one of the time points investigated. Over 500 genes are upregulated during the time course of germination under those conditions, most being related to cell growth, including genes involved in protein biosynthesis, DNA transcription, energetic metabolism, carbohydrate and oligopeptide transport, and cell cycle control. On the other hand, several transcripts stored in the zoospores are downregulated during germination in nutrient medium, such as genes involved in signal transduction, amino acid transport, and chromosome organization. In addition, germination induced in the presence of nutrients was compared with that triggered either by adenine or potassium ions in inorganic salt solution. Several genes involved in cell growth, induced during germination in nutrient medium, do not show increased expression when B. emersonii zoospores germinate in inorganic solution, suggesting that nutrients exert a positive effect on gene transcription. The transcriptome data also revealed that most genes involved in cell signaling show the same expression pattern irrespective of the initial germination stimulus.

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An analytical procedure for the separation and quantification of ethyl acetate, ethyl butyrate, ethyl hexanoate, ethyl lactate, ethyl octanoate, ethyl nonanoate, ethyl decanoate, isoamyl octanoate, and ethyl laurate in cachaca, rum, and whisky by direct injection gas chromatography-mass spectrometry was developed. The analytical method is simple, selective, and appropriated for the determination of esters in distilled spirits. The limit of detection ranged from 29 (ethyl hexanoate) to 530 (ethyl acetate) mu g L-1, whereas the standard deviation for repeatability was between 0.774% (ethyl hexanoate) and 5.05% (isoamyl octanoate). Relative standard deviation values for accuracy vary from 90.3 to 98.5% for ethyl butyrate and ethyl acetate, respectively. Ethyl acetate was shown to be the major ester in cachaca (median content of 22.6 mg 100 mL(-1) anhydrous alcohol), followed by ethyl lactate (median content of 8.32 mg 100 mL(-1) anhydrous alcohol). Cachaca produced in copper and hybrid alembic present a higher content of ethyl acetate and ethyl lactate than those produced in a stainless-steel column, whereas cachaca produced by distillation in a stainless-steel column present a higher content of ethyl octanoate, ethyl decanoate, and ethyl laurate. As expected, ethyl acetate is the major ester in whiskey and rum, followed by ethyl lactate for samples of rum. Nevertheless, whiskey samples exhibit ethyl lactate at contents lower or at the same order of magnitude of the fatty esters.

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Intelligent Transportation System (ITS) is a system that builds a safe, effective and integrated transportation environment based on advanced technologies. Road signs detection and recognition is an important part of ITS, which offer ways to collect the real time traffic data for processing at a central facility.This project is to implement a road sign recognition model based on AI and image analysis technologies, which applies a machine learning method, Support Vector Machines, to recognize road signs. We focus on recognizing seven categories of road sign shapes and five categories of speed limit signs. Two kinds of features, binary image and Zernike moments, are used for representing the data to the SVM for training and test. We compared and analyzed the performances of SVM recognition model using different features and different kernels. Moreover, the performances using different recognition models, SVM and Fuzzy ARTMAP, are observed.

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The purpose of this study was to investigate pupils’ knowledge about science and what role science center is playing as a medium of communication to increase knowledge among students. This study also tried to find out pupils’ interaction: how they use science center as a source of scientific information, what they learn from their visit to a science center, their pattern of communication with it. This project also measured attraction, holding and learning power of exhibits of the science center at Dalarna University in Borlänge and learning power of planetarium program and slide show of Stella Nova Planetarium at Dalarna University.The subjects of this study consisted of students of class seven and eight and teachers of an urban school in Borlänge, Sweden. To find out students’ learning in a science center a pre and post visit test were conducted through questionnaires. Interview method by questionnaires was also used to explore pupils’ interaction with science center.The results of this study show that students learn by their visit to a science center but learning was not statistically significant (0.05).Girls learnt better than boys. School classes that have better pre-knowledge about science before a visit to a science center learnt worse than other classes having less pre-knowledge. Girls and boys interact with a science center in different ways. Science center is playing important role as a science communicator.

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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.

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Internet protocol TV (IPTV) is predicted to be the key technology winner in the future. Efforts to accelerate the deployment of IPTV centralized model which is combined of VHO, encoders, controller, access network and Home network. Regardless of whether the network is delivering live TV, VOD, or Time-shift TV, all content and network traffic resulting from subscriber requests must traverse the entire network from the super-headend all the way to each subscriber's Set-Top Box (STB).IPTV services require very stringent QoS guarantees When IPTV traffic shares the network resources with other traffic like data and voice, how to ensure their QoS and efficiently utilize the network resources is a key and challenging issue. For QoS measured in the network-centric terms of delay jitter, packet losses and bounds on delay. The main focus of this thesis is on the optimized bandwidth allocation and smooth datatransmission. The proposed traffic model for smooth delivering video service IPTV network with its QoS performance evaluation. According to Maglaris et al [5] First, analyze the coding bit rate of a single video source. Various statistical quantities are derived from bit rate data collected with a conditional replenishment inter frame coding scheme. Two correlated Markov process models (one in discrete time and one incontinuous time) are shown to fit the experimental data and are used to model the input rates of several independent sources into a statistical multiplexer. Preventive control mechanism which is to be include CAC, traffic policing used for traffic control.QoS has been evaluated of common bandwidth scheduler( FIFO) by use fluid models with Markovian queuing method and analysis the result by using simulator andanalytically, Which is measured the performance of the packet loss, overflow and mean waiting time among the network users.