62 resultados para Traffic clustering


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In this paper, we show statistical analyses of several types of traffic sources in a 3G network, namely voice, video and data sources. For each traffic source type, measurements were collected in order to, on the one hand, gain better understanding of the statistical characteristics of the sources and, on the other hand, enable forecasting traffic behaviour in the network. The latter can be used to estimate service times and quality of service parameters. The probability density function, mean, variance, mean square deviation, skewness and kurtosis of the interarrival times are estimated by Wolfram Mathematica and Crystal Ball statistical tools. Based on evaluation of packet interarrival times, we show how the gamma distribution can be used in network simulations and in evaluation of available capacity in opportunistic systems. As a result, from our analyses, shape and scale parameters of gamma distribution are generated. Data can be applied also in dynamic network configuration in order to avoid potential network congestions or overflows. Copyright © 2013 John Wiley & Sons, Ltd.

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We consider the problem of fitting a union of subspaces to a collection of data points drawn from one or more subspaces and corrupted by noise and/or gross errors. We pose this problem as a non-convex optimization problem, where the goal is to decompose the corrupted data matrix as the sum of a clean and self-expressive dictionary plus a matrix of noise and/or gross errors. By self-expressive we mean a dictionary whose atoms can be expressed as linear combinations of themselves with low-rank coefficients. In the case of noisy data, our key contribution is to show that this non-convex matrix decomposition problem can be solved in closed form from the SVD of the noisy data matrix. The solution involves a novel polynomial thresholding operator on the singular values of the data matrix, which requires minimal shrinkage. For one subspace, a particular case of our framework leads to classical PCA, which requires no shrinkage. For multiple subspaces, the low-rank coefficients obtained by our framework can be used to construct a data affinity matrix from which the clustering of the data according to the subspaces can be obtained by spectral clustering. In the case of data corrupted by gross errors, we solve the problem using an alternating minimization approach, which combines our polynomial thresholding operator with the more traditional shrinkage-thresholding operator. Experiments on motion segmentation and face clustering show that our framework performs on par with state-of-the-art techniques at a reduced computational cost.

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This article looks at the negotiations between Switzerland and Germany on air traffic regulation with the help of negotiation analysis tools. A number of factors pre-eminent in the literature on negotiation processes and outcomes are presented and critically assessed. In particular arguments of “power”, which are often insufficiently explored in analysing interstate cooperation, are brought back into the picture. The article argues that structural power best explains the negotiation results while domestic politics and information asymmetries both account for non-ratification of the treaty. Institutionalist arguments on the constraining effects of international norms and institutions as well as explanations focusing on negotiation skills are of minor importance. Moreover, the nature of the Swiss intra-governmental setting at the federal level did not encourage the Swiss negotiators to exploit all means during the different stages of the bargaining process. The article concludes by illuminating a number of policy observations in the broader context of Swiss foreign relations and indicating avenues for further research

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It is well known that sufficiently regular, one-dimensional payoff functions have an explicit static hedge by bonds, forward contracts, and options in a continuum of strikes. An easy and natural extension of the corresponding representation leads to static hedges based on the same instruments along with traffic light options, which have recently been introduced in the market. It is well known that the second strike derivative of non-discounted prices of vanilla options is related to the risk-neutral density of the underlying asset price in the corresponding absolutely continuous settings. Similar statements hold for traffic light options in sufficiently regular, bivariate settings.

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SUMMARY There is interest in the potential of companion animal surveillance to provide data to improve pet health and to provide early warning of environmental hazards to people. We implemented a companion animal surveillance system in Calgary, Alberta and the surrounding communities. Informatics technologies automatically extracted electronic medical records from participating veterinary practices and identified cases of enteric syndrome in the warehoused records. The data were analysed using time-series analyses and a retrospective space-time permutation scan statistic. We identified a seasonal pattern of reports of occurrences of enteric syndromes in companion animals and four statistically significant clusters of enteric syndrome cases. The cases within each cluster were examined and information about the animals involved (species, age, sex), their vaccination history, possible exposure or risk behaviour history, information about disease severity, and the aetiological diagnosis was collected. We then assessed whether the cases within the cluster were unusual and if they represented an animal or public health threat. There was often insufficient information recorded in the medical record to characterize the clusters by aetiology or exposures. Space-time analysis of companion animal enteric syndrome cases found evidence of clustering. Collection of more epidemiologically relevant data would enhance the utility of practice-based companion animal surveillance.

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Strengthening car drivers’ intention to prevent road-traffic noise is a first step toward noise abatement through voluntary change of behavior. We analyzed predictors of this intention based on the norm activation model (i.e., personal norm, problem awareness, awareness of consequences, social norm, and value orientations). Moreover, we studied the effects of noise exposure, noise sensitivity, and noise annoyance on problem awareness. Data came from 1,002 car drivers who participated in a two-wave longitudinal survey over 4 months. Personal norm had a large prospective effect on intention, even when the previous level of intention was controlled for, and mediated the effect of all other variables on intention. Almost 60% of variance in personal norm was explained by problem awareness, social norm, and biospheric value orientation. The effects of noise sensitivity and noise exposure on problem awareness were small and mediated by noise annoyance. We propose four communication strategies for strengthening the intention to prevent road-traffic noise in car drivers.

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Background/Study Context: Older drivers are at increased risk of becoming involved in car crashes. Contrary to well-studied illness-related factors contributing to crash risk, the non-illness-related factors that can influence safety of older drivers are underresearched. METHODS: Here, the authors review the literature on non-illness-related factors influencing driving in people over age 60. We identified six safety-relevant factors: road infrastructure, vehicle characteristics, traffic-related knowledge, accuracy of self-awareness, personality traits, and self-restricted driving. RESULTS: The literature suggests that vehicle preference, the quality of traffic-related knowledge, the location and time of traffic exposure, and personality traits should all be taken into account when assessing fitness-to-drive in older drivers. Studies indicate that self-rating of driving skills does not reliably predict fitness-to-drive. CONCLUSIONS: Most factors discussed are adaptable or accessible to training and collectively may have the potential to increase traffic safety for older drivers and other road users.

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The presented approach describes a model for a rule-based expert system calculating the temporal variability of the release of wet snow avalanches, using the assumption of avalanche triggering without the loading of new snow. The knowledge base of the model is created by using investigations on the system behaviour of wet snow avalanches in the Italian Ortles Alps, and is represented by a fuzzy logic rule-base. Input parameters of the expert system are numerical and linguistic variables, measurable meteorological and topographical factors and observable characteristics of the snow cover. Output of the inference method is the quantified release disposition for wet snow avalanches. Combining topographical parameters and the spatial interpolation of the calculated release disposition a hazard index map is dynamically generated. Furthermore, the spatial and temporal variability of damage potential on roads exposed to wet snow avalanches can be quantified, expressed by the number of persons at risk. The application of the rule base to the available data in the study area generated plausible results. The study demonstrates the potential for the application of expert systems and fuzzy logic in the field of natural hazard monitoring and risk management.

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Polydnaviruses (genera Ichnovirus and Bracovirus) have a segmented genome of circular double-stranded DNA molecules, replicate in the ovary of parasitic wasps and are essential for successful parasitism of the host. Here we show the first detailed analysis of various segments of a bracovirus, the Chelonus inanitus virus (CiV). Four segments were sequenced and two of them, CiV12 and CiV14, were found to be closely related while CiV14.5 and CiV16.8 were unrelated. CiV12, CiV14.5 and CiV16.8 are unique while CiV14 occurs also nested in another larger segment. All four segments are predicted to contain genes and predictions could be substantiated in most cases. Comparison with databases revealed no significant similarities at either the nucleotide or amino acid level. Inverted repeats with identities between 77% and 92% and lengths between 26 bp and 100 bp were found on all segments outside of predicted genes. Hybridization experiments indicate that CiV12 and CiV14 are both flanked by other virus segments, suggesting that proviral CiV segments are clustered in the genome of the wasp. The integration/excision site of CiV14 was analysed and compared to that of CiV12. On both termini of proviral CiV12 and CiV14 as well as in the excised circular molecule and the rejoined DNA a very similar repeat of 14 bp was found. A model to illustrate where the terminal repeats might recombine to yield the circular molecule is presented. Excision of CiV12 and CiV14 is restricted to the female and sets in at a very specific time-point in pupal-adult development.

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The aetiology of childhood cancers remains largely unknown. It has been hypothesized that infections may be involved and that mini-epidemics thereof could result in space-time clustering of incident cases. Most previous studies support spatio-temporal clustering for leukaemia, while results for other diagnostic groups remain mixed. Few studies have corrected for uneven regional population shifts which can lead to spurious detection of clustering. We examined whether there is space-time clustering of childhood cancers in Switzerland identifying cases diagnosed at age <16 years between 1985 and 2010 from the Swiss Childhood Cancer Registry. Knox tests were performed on geocoded residence at birth and diagnosis separately for leukaemia, acute lymphoid leukaemia (ALL), lymphomas, tumours of the central nervous system, neuroblastomas and soft tissue sarcomas. We used Baker's Max statistic to correct for multiple testing and randomly sampled time-, sex- and age-matched controls from the resident population to correct for uneven regional population shifts. We observed space-time clustering of childhood leukaemia at birth (Baker's Max p = 0.045) but not at diagnosis (p = 0.98). Clustering was strongest for a spatial lag of <1 km and a temporal lag of <2 years (Observed/expected close pairs: 124/98; p Knox test = 0.003). A similar clustering pattern was observed for ALL though overall evidence was weaker (Baker's Max p = 0.13). Little evidence of clustering was found for other diagnostic groups (p > 0.2). Our study suggests that childhood leukaemia tends to cluster in space-time due to an etiologic factor present in early life.