861 resultados para Network-based analysis


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Next-generation networks are likely to be non-uniform in all their aspects, including number of lightpaths carried per link, number of wavelengths per link, number of fibres per link, asymmetry of the links, and traffic flows. Routing and wavelength allocation models generally assume that the optical network is uniform and that the number of wavelengths per link is a constant. In practice however, some nodes and links carry heavy traffic and additional wavelengths are needed in those links. We study a wavelength-routed optical network based on the UK JANET topology where traffic demands between nodes are assumed to be non-uniform. We investigate how network capacity can be increased by locating congested links and suggesting cost-effective upgrades. Different traffic demands patterns, hop distances, number of wavelengths per link, and routing algorithms are considered. Numerical results show that a 95% increase in network capacity is possible by overlaying fibre on just 5% of existing links. We conclude that non-uniform traffic allocation can be beneficial to localize traffic in nodes and links deep in the network core and provisioning of additional resources there can efficiently and cost-effectively increase network capacity. © 2013 IEEE.

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Switched reluctance motor (SRM) drives are one competitive technology for traction motor drives. This paper proposes a novel and flexible SRM fault-tolerant topology with fault diagnosis, fault tolerance, and advanced control functions. The converter is composed of a single-phase bridge and a relay network, based on the traditional asymmetrical half-bridge driving topology. When the SRM-driving system is subjected to fault conditions including open-circuit and short-circuit faults, the proposed converter starts its fault-diagnosis procedure to locate the fault. Based on the relay network, the faulty part can be bypassed by the single-phase bridge arm, while the single-phase bridge arm and the healthy part of the converter can form a fault-tolerant topology to sustain the driving operation. A fault-tolerant control strategy is developed to decrease the influence of the fault. Furthermore, the proposed fault-tolerant strategy can be applied to three-phase 12/8 SRM and four-phase 8/6 SRM. Simulation results in MATLAB/Simulink and experiments on a three-phase 12/8 SRM and a four-phase 8/6 SRM validate the effectiveness of the proposed strategy, which may have significant economic implications in traction drive systems.

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With the advantages and popularity of Permanent Magnet (PM) motors due to their high power density, there is an increasing incentive to use them in variety of applications including electric actuation. These applications have strict noise emission standards. The generation of audible noise and associated vibration modes are characteristics of all electric motors, it is especially problematic in low speed sensorless control rotary actuation applications using high frequency voltage injection technique. This dissertation is aimed at solving the problem of optimizing the sensorless control algorithm for low noise and vibration while achieving at least 12 bit absolute accuracy for speed and position control. The low speed sensorless algorithm is simulated using an improved Phase Variable Model, developed and implemented in a hardware-in-the-loop prototyping environment. Two experimental testbeds were developed and built to test and verify the algorithm in real time.^ A neural network based modeling approach was used to predict the audible noise due to the high frequency injected carrier signal. This model was created based on noise measurements in an especially built chamber. The developed noise model is then integrated into the high frequency based sensorless control scheme so that appropriate tradeoffs and mitigation techniques can be devised. This will improve the position estimation and control performance while keeping the noise below a certain level. Genetic algorithms were used for including the noise optimization parameters into the developed control algorithm.^ A novel wavelet based filtering approach was proposed in this dissertation for the sensorless control algorithm at low speed. This novel filter was capable of extracting the position information at low values of injection voltage where conventional filters fail. This filtering approach can be used in practice to reduce the injected voltage in sensorless control algorithm resulting in significant reduction of noise and vibration.^ Online optimization of sensorless position estimation algorithm was performed to reduce vibration and to improve the position estimation performance. The results obtained are important and represent original contributions that can be helpful in choosing optimal parameters for sensorless control algorithm in many practical applications.^

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The applications of micro-end-milling operations have increased recently. A Micro-End-Milling Operation Guide and Research Tool (MOGART) package has been developed for the study and monitoring of micro-end-milling operations. It includes an analytical cutting force model, neural network based data mapping and forecasting processes, and genetic algorithms based optimization routines. MOGART uses neural networks to estimate tool machinability and forecast tool wear from the experimental cutting force data, and genetic algorithms with the analytical model to monitor tool wear, breakage, run-out, cutting conditions from the cutting force profiles. ^ The performance of MOGART has been tested on the experimental data of over 800 experimental cases and very good agreement has been observed between the theoretical and experimental results. The MOGART package has been applied to the micro-end-milling operation study of Engineering Prototype Center of Radio Technology Division of Motorola Inc. ^

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The applications of micro-end-milling operations have increased recently. A Micro-End-Milling Operation Guide and Research Tool (MOGART) package has been developed for the study and monitoring of micro-end-milling operations. It includes an analytical cutting force model, neural network based data mapping and forecasting processes, and genetic algorithms based optimization routines. MOGART uses neural networks to estimate tool machinability and forecast tool wear from the experimental cutting force data, and genetic algorithms with the analytical model to monitor tool wear, breakage, run-out, cutting conditions from the cutting force profiles. The performance of MOGART has been tested on the experimental data of over 800 experimental cases and very good agreement has been observed between the theoretical and experimental results. The MOGART package has been applied to the micro-end-milling operation study of Engineering Prototype Center of Radio Technology Division of Motorola Inc.

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Emotion-based analysis has raised a lot of interest, particularly in areas such as forensics, medicine, music, psychology, and human-machine interface. Following this trend, the use of facial analysis (either automatic or human-based) is the most common subject to be investigated once this type of data can easily be collected and is well accepted in the literature as a metric for inference of emotional states. Despite this popularity, due to several constraints found in real world scenarios (e.g. lightning, complex backgrounds, facial hair and so on), automatically obtaining affective information from face accurately is a very challenging accomplishment. This work presents a framework which aims to analyse emotional experiences through naturally generated facial expressions. Our main contribution is a new 4-dimensional model to describe emotional experiences in terms of appraisal, facial expressions, mood, and subjective experiences. In addition, we present an experiment using a new protocol proposed to obtain spontaneous emotional reactions. The results have suggested that the initial emotional state described by the participants of the experiment was different from that described after the exposure to the eliciting stimulus, thus showing that the used stimuli were capable of inducing the expected emotional states in most individuals. Moreover, our results pointed out that spontaneous facial reactions to emotions are very different from those in prototypic expressions due to the lack of expressiveness in the latter.

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Marine microorganisms adapt to their habitat by structural modification of their membrane lipids. This concept is the basis of numerous molecular proxies used for paleoenvironmental reconstruction. Archaeal tetraether lipids from ubiquitous marine planktonic archaea are particularly abundant, well preserved in the sedimentary record and utilized in several molecular proxies. We here introduce the direct, extraction-free analysis of these compounds in intact sediment core sections using laser desorption ionization (LDI) coupled to Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). LDI FTICR-MS can detect the target lipids in single sub-mm sized spots on sediment sections, equivalent to a sample mass in the nanogram range, and could thus pave the way for biomarker-based reconstruction of past environments and ecosystems at subannual to decadal resolution. We demonstrate that ratios of selected archaeal tetraethers acquired by LDI FTICR-MS are highly correlated with values obtained by conventional LC/MS protocols. The ratio of the major archaeal lipids, caldarchaeol and crenarchaeol, analyzed in a 6.2-cm intact section of Mediterranean sapropel S1 at 250-µm resolution (~4-year temporal resolution), provides an unprecedented view of the fine-scale patchiness of sedimentary biomarker distributions and the processes involved in proxy signal formation. Temporal variations of this lipid ratio indicate a strong influence of the 200-yr de Vries solar cycle on reconstructed sea surface temperatures with possible amplitudes of several degrees, and suggest signal amplification by a complex interplay of ecological and hydrological factors. Laser-based biomarker analysis of geological samples has the potential to revolutionize molecular stratigraphic studies of paleoenvironments.

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This work presents the design of a real-time system to model visual objects with the use of self-organising networks. The architecture of the system addresses multiple computer vision tasks such as image segmentation, optimal parameter estimation and object representation. We first develop a framework for building non-rigid shapes using the growth mechanism of the self-organising maps, and then we define an optimal number of nodes without overfitting or underfitting the network based on the knowledge obtained from information-theoretic considerations. We present experimental results for hands and faces, and we quantitatively evaluate the matching capabilities of the proposed method with the topographic product. The proposed method is easily extensible to 3D objects, as it offers similar features for efficient mesh reconstruction.

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Purines are nitrogen-rich compounds that are widely distributed in the marine environment and are an important component of the dissolved organic nitrogen (DON) pool. Even though purines have been shown to be degraded by bacterioplankton, the identities of marine bacteria capable of purine degradation and their underlying catabolic mechanisms are currently unknown. This study shows that Ruegeria pomeroyi, a model marine bacterium and Marine Roseobacter Clade (MRC) representative, utilizes xanthine as a source of carbon and nitrogen. The R. pomeroyi genome contains putative genes that encode xanthine dehydrogenase (XDH), which is expressed during growth with xanthine. RNAseq-based analysis of the R. pomeroyi transcriptome revealed that the transcription of an XDH-initiated catabolic pathway is up-regulated during growth with xanthine, with transcription greatest when xanthine was the only available carbon source. The RNAseq-deduced pathway indicates that glyoxylate and ammonia are the key intermediates from xanthine degradation. Utilising a laboratory model, this study has identified the potential genes and catabolic pathway active during xanthine degradation. The ability of R. pomeroyi to utilize xanthine provides novel insights into the capabilities of the MRC that may contribute to their success in marine ecosystems and the potential biogeochemical importance of the group in processing DON.

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Purines are nitrogen-rich compounds that are widely distributed in the marine environment and are an important component of the dissolved organic nitrogen (DON) pool. Even though purines have been shown to be degraded by bacterioplankton, the identities of marine bacteria capable of purine degradation and their underlying catabolic mechanisms are currently unknown. This study shows that Ruegeria pomeroyi, a model marine bacterium and Marine Roseobacter Clade (MRC) representative, utilizes xanthine as a source of carbon and nitrogen. The R. pomeroyi genome contains putative genes that encode xanthine dehydrogenase (XDH), which is expressed during growth with xanthine. RNAseq-based analysis of the R. pomeroyi transcriptome revealed that the transcription of an XDH-initiated catabolic pathway is up-regulated during growth with xanthine, with transcription greatest when xanthine was the only available carbon source. The RNAseq-deduced pathway indicates that glyoxylate and ammonia are the key intermediates from xanthine degradation. Utilising a laboratory model, this study has identified the potential genes and catabolic pathway active during xanthine degradation. The ability of R. pomeroyi to utilize xanthine provides novel insights into the capabilities of the MRC that may contribute to their success in marine ecosystems and the potential biogeochemical importance of the group in processing DON.

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The present study focuses on the frequency of phrasal verbs with the particle up in the context of crime and police investigative work. This research emerges from the need to enlarge McCarthy and O’Dell’s (2004) scope from purely criminal behavior to police investigative actions. To do so, we relied on a corpus of 504,124 running words made up of spoken dialogues extracted from the script of the American TV series Castle shown on ABC since 2009. Based on Rudzka-Ostyn’s (2003) cognitive motivations for the particle up, we have identified five different meaning extensions for our phrasal verbs. Drawing from these findings, we have designed pedagogical activities for those L2 learners that study English at the Police Academy.

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Following and contributing to the ongoing shift from more structuralist, system-oriented to more pragmatic, socio-cultural oriented anglicism research, this paper verifies to what extent the global spread of English affects naming patterns in Flanders. To this end, a diachronic database of first names is constructed, containing the top 75 most popular boy and girl names from 2005 until 2014. In a first step, the etymological background of these names is documented and the evolution in popularity of the English names in the database is tracked. Results reveal no notable surge in the preference for English names. This paper complements these database-driven results with an experimental study, aiming to show how associations through referents are in this case more telling than associations through phonological form (here based on etymology). Focusing on the socio-cultural background of first names in general and of Anglo-American pop culture in particular, the second part of the study specifically reports on results from a survey where participants are asked to name the first three celebrities that leap to mind when hearing a certain first name (e.g. Lana, triggering the response Del Rey). Very clear associations are found between certain first names and specific celebrities from Anglo-American pop culture. Linking back to marketing research and the social turn in onomastics, we will discuss how these celebrities might function as referees, and how social stereotypes surrounding these referees are metonymically attached to their first names. Similar to the country-of-origin-effect in marketing, these metonymical links could very well be the reason why parents select specific “celebrity names”. Although further attitudinal research is needed, this paper supports the importance of including socio-cultural parameters when conducting onomastic research.

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BACKGROUND: Proteins belonging to the serine protease inhibitor (serpin) superfamily play essential physiological roles in many organisms. In pathogens, serpins are thought to have evolved specifically to limit host immune responses by interfering with the host immune-stimulatory signals. Serpins are less well characterised in parasitic helminths, although some are thought to be involved in mechanisms associated with host immune modulation. In this study, we cloned and partially characterised a secretory serpin from Schistosoma japonicum termed SjB6, these findings provide the basis for possible functional roles.

METHODS: SjB6 gene was identified through database mining of our previously published microarray data, cloned and detailed sequence and structural analysis and comparative modelling carried out using various bioinformatics and proteomics tools. Gene transcriptional profiling was determined by real-time PCR and the expression of native protein determined by immunoblotting. An immunological profile of the recombinant protein produced in insect cells was determined by ELISA.

RESULTS: SjB6 contains an open reading frame of 1160 base pairs that encodes a protein of 387 amino acid residues. Detailed sequence analysis, comparative modelling and structural-based alignment revealed that SjB6 contains the essential structural motifs and consensus secondary structures typical of inhibitory serpins. The presence of an N-terminal signal sequence indicated that SjB6 is a secretory protein. Real-time data indicated that SjB6 is expressed exclusively in the intra-mammalian stage of the parasite life cycle with its highest expression levels in the egg stage (p < 0.0001). The native protein is approximately 60 kDa in size and recombinant SjB6 (rSjB6) was recognised strongly by sera from rats experimentally infected with S. japonicum.

CONCLUSIONS: The significantly high expression of SjB6 in schistosome eggs, when compared to other life cycle stages, suggests a possible association with disease pathology, while the strong reactivity of sera from experimentally infected rats against rSjB6 suggests that native SjB6 is released into host tissue and induces an immune response. This study presents a comprehensive demonstration of sequence and structural-based analysis of a secretory serpin from a trematode and suggests SjB6 may be associated with important functional roles in S. japonicum, particularly in parasite modulation of the host microenvironment.

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Serine protease inhibitors (serpin) play essential roles in many organisms. Mammalian serpins regulate the blood coagulation, fibrinolysis, inflammation and complement activation pathways. In parasitic helminths, serpins are less well characterized, but may also be involved in evasion of the host immune response. In this study, a Schistosoma japonicum serpin (SjB10), containing a 1212 bp open reading frame (ORF), was cloned, expressed and functionally characterized. Sequence analysis, comparative modelling and structural-based alignment revealed that SjB10 contains the essential structural motifs and consensus secondary structures of inhibitory serpins. Transcriptional profiling demonstrated that SjB10 is expressed in adult males, schistosomula and eggs but particularly in the cercariae, suggesting a possible role in cercarial penetration of mammalian host skin. Recombinant SjB10 (rSjB10) inhibited pancreatic elastase (PE) in a dose-dependent manner. rSjB10 was recognized strongly by experimentally infected rat sera indicating that native SjB10 is released into host tissue and induces an immune response. By immunochemistry, SjB10 localized in the S. japonicum adult foregut and extra-embryonic layer of the egg. This study provides a comprehensive demonstration of sequence and structural-based analysis of a functional S. japonicum serpin. Furthermore, our findings suggest that SjB10 may be associated with important functional roles in S. japonicum particularly in host-parasite interactions.

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Structured parallel programming, and in particular programming models using the algorithmic skeleton or parallel design pattern concepts, are increasingly considered to be the only viable means of supporting effective development of scalable and efficient parallel programs. Structured parallel programming models have been assessed in a number of works in the context of performance. In this paper we consider how the use of structured parallel programming models allows knowledge of the parallel patterns present to be harnessed to address both performance and energy consumption. We consider different features of structured parallel programming that may be leveraged to impact the performance/energy trade-off and we discuss a preliminary set of experiments validating our claims.