902 resultados para Person detection and tracking
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We designed FISH-probes for two distinct microsporidian clades and demonstrated their application in detecting respectively Nosema/Vairimorpha and Dictyoceola species. We applied them to study the vertical transmission of two microsporidia infecting the amphipod Gammarus duebeni
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Safety is an element of extreme priority in mining operations, currently many traditional mining countries are investing in the implementation of wireless sensors capable of detecting risk factors; through early warning signs to prevent accidents and significant economic losses. The objective of this research is to contribute to the implementation of sensors for continuous monitoring inside underground mines providing technical parameters for the design of sensor networks applied in underground coal mines. The application of sensors capable of measuring in real time variables of interest, promises to be of great impact on safety for mining industry. The relationship between the geological conditions and mining method design, establish how to implement a system of continuous monitoring. In this paper, the main causes of accidents for underground coal mines are established based on existing worldwide reports. Variables (temperature, gas, structural faults, fires) that can be related to the most frequent causes of disaster and its relevant measuring range are then presented, also the advantages, management and mining operations are discussed, including the analyzed of applying these systems in terms of Benefit, Opportunity, Cost and Risk. The publication focuses on coal mining, based on the proportion of these events a year worldwide, where a significant number of workers are seriously injured or killed. Finally, a dynamic assessment of safety at underground mines it is proposed, this approach offers a contribution to design personalized monitoring networks, the experience developed in coal mines provides a tool that facilitates the application development of technology within underground coal mines.
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For Northern Hemisphere extra-tropical cyclone activity, the dependency of a potential anthropogenic climate change signal on the identification method applied is analysed. This study investigates the impact of the used algorithm on the changing signal, not the robustness of the climate change signal itself. Using one single transient AOGCM simulation as standard input for eleven state-of-the-art identification methods, the patterns of model simulated present day climatologies are found to be close to those computed from re-analysis, independent of the method applied. Although differences in the total number of cyclones identified exist, the climate change signals (IPCC SRES A1B) in the model run considered are largely similar between methods for all cyclones. Taking into account all tracks, decreasing numbers are found in the Mediterranean, the Arctic in the Barents and Greenland Seas, the mid-latitude Pacific and North America. Changing patterns are even more similar, if only the most severe systems are considered: the methods reveal a coherent statistically significant increase in frequency over the eastern North Atlantic and North Pacific. We found that the differences between the methods considered are largely due to the different role of weaker systems in the specific methods.
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BACKGROUND Methyl benzimidazole carbamate (MBC) fungicides are used to control the oilseed rape pathogen Pyrenopeziza brassicae. Resistance to MBCs has been reported in P. brassicae, but the molecular mechanism(s) associated with reductions in sensitivity have not been verified in this species. Elucidation of the genetic changes responsible for resistance, hypothesised to be target-site mutations in β-tubulin, will enable resistance diagnostics and thereby inform resistance management strategies. RESULTS P. brassicae isolates were classified as sensitive, moderately resistant or resistant to MBCs. Crossing P. brassicae isolates of different MBC sensitivities indicated that resistance was conferred by a single gene. The MBC-target encoding gene β-tubulin was cloned and sequenced. Reduced MBC sensitivity of field isolates correlated with β-tubulin amino acid substitutions L240F and E198A. The highest level of MBC resistance was measured for isolates carrying E198A. Negative cross-resistance between MBCs and the fungicides diethofencarb and zoxamide was only measured in E198A isolates. PCR-RFLP was used to screen isolates for the presence of L240F and E198A. The substitutions E198G and F200Y were also detected in DNA samples from P. brassicae populations after cloning and sequencing of PCR products. The frequencies of L240F and E198A in different P. brassicae populations were quantified by pyrosequencing. There were no differences in the frequencies of these alleles between P. brassicae populations sampled from different locations or after fungicide treatment regimes. CONCLUSIONS The molecular mechanisms affecting sensitivity to MBCs in P. brassicae have been identified. Pyrosequencing assays are a powerful tool for quantifying fungicide-resistant alleles in pathogen populations.
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A method of automatically identifying and tracking polar-cap plasma patches, utilising data inversion and feature-tracking methods, is presented. A well-established and widely used 4-D ionospheric imaging algorithm, the Multi-Instrument Data Assimilation System (MIDAS), inverts slant total electron content (TEC) data from ground-based Global Navigation Satellite System (GNSS) receivers to produce images of the free electron distribution in the polar-cap ionosphere. These are integrated to form vertical TEC maps. A flexible feature-tracking algorithm, TRACK, previously used extensively in meteorological storm-tracking studies is used to identify and track maxima in the resulting 2-D data fields. Various criteria are used to discriminate between genuine patches and "false-positive" maxima such as the continuously moving day-side maximum, which results from the Earth's rotation rather than plasma motion. Results for a 12-month period at solar minimum, when extensive validation data are available, are presented. The method identifies 71 separate structures consistent with patch motion during this time. The limitations of solar minimum and the consequent small number of patches make climatological inferences difficult, but the feasibility of the method for patches larger than approximately 500 km in scale is demonstrated and a larger study incorporating other parts of the solar cycle is warranted. Possible further optimisation of discrimination criteria, particularly regarding the definition of a patch in terms of its plasma concentration enhancement over the surrounding background, may improve results.
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Twitter has become a dependable microblogging tool for real time information dissemination and newsworthy events broadcast. Its users sometimes break news on the network faster than traditional newsagents due to their presence at ongoing real life events at most times. Different topic detection methods are currently used to match Twitter posts to real life news of mainstream media. In this paper, we analyse tweets relating to the English FA Cup finals 2012 by applying our novel method named TRCM to extract association rules present in hash tag keywords of tweets in different time-slots. Our system identify evolving hash tag keywords with strong association rules in each time-slot. We then map the identified hash tag keywords to event highlights of the game as reported in the ground truth of the main stream media. The performance effectiveness measure of our experiments show that our method perform well as a Topic Detection and Tracking approach.
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This paper presents the two datasets (ARENA and P5) and the challenge that form a part of the PETS 2015 workshop. The datasets consist of scenarios recorded by us- ing multiple visual and thermal sensors. The scenarios in ARENA dataset involve different staged activities around a parked vehicle in a parking lot in UK and those in P5 dataset involve different staged activities around the perimeter of a nuclear power plant in Sweden. The scenarios of each dataset are grouped into ‘Normal’, ‘Warning’ and ‘Alarm’ categories. The Challenge specifically includes tasks that account for different steps in a video understanding system: Low-Level Video Analysis (object detection and tracking), Mid-Level Video Analysis (‘atomic’ event detection) and High-Level Video Analysis (‘complex’ event detection). The evaluation methodology used for the Challenge includes well-established measures.
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This paper describes the dataset and vision challenges that form part of the PETS 2014 workshop. The datasets are multisensor sequences containing different activities around a parked vehicle in a parking lot. The dataset scenarios were filmed from multiple cameras mounted on the vehicle itself and involve multiple actors. In PETS2014 workshop, 22 acted scenarios are provided of abnormal behaviour around the parked vehicle. The aim in PETS 2014 is to provide a standard benchmark that indicates how detection, tracking, abnormality and behaviour analysis systems perform against a common database. The dataset specifically addresses several vision challenges corresponding to different steps in a video understanding system: Low-Level Video Analysis (object detection and tracking), Mid-Level Video Analysis (‘simple’ event detection: the behaviour recognition of a single actor) and High-Level Video Analysis (‘complex’ event detection: the behaviour and interaction recognition of several actors).
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Future extreme-scale high-performance computing systems will be required to work under frequent component failures. The MPI Forum's User Level Failure Mitigation proposal has introduced an operation, MPI_Comm_shrink, to synchronize the alive processes on the list of failed processes, so that applications can continue to execute even in the presence of failures by adopting algorithm-based fault tolerance techniques. This MPI_Comm_shrink operation requires a fault tolerant failure detection and consensus algorithm. This paper presents and compares two novel failure detection and consensus algorithms. The proposed algorithms are based on Gossip protocols and are inherently fault-tolerant and scalable. The proposed algorithms were implemented and tested using the Extreme-scale Simulator. The results show that in both algorithms the number of Gossip cycles to achieve global consensus scales logarithmically with system size. The second algorithm also shows better scalability in terms of memory and network bandwidth usage and a perfect synchronization in achieving global consensus.
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Internal gravity waves are generated as adjustment radiation whenever a sudden change in forcing causes the atmosphere to depart from its large-scale balanced state. Such a forcing anomaly occurs during a solar eclipse, when the Moon’s shadow cools part of the Earth’s surface. The resulting atmospheric gravity waves are associated with pressure and temperature perturbations, which in principle are detectable both at the surface and aloft. In this study, surface pressure and temperature data from two UK sites at Reading and Lerwick are analysed for eclipse-driven gravity-wave perturbations during the 20 March 2015 solar eclipse over north-west Europe. Radiosonde wind data from the same two sites are also analysed using a moving parcel analysis method, to determine the periodicities of the waves aloft. On this occasion, the perturbations both at the surface and aloft are found not to be confidently attributable to eclipse-driven gravity waves. We conclude that the complex synoptic weather conditions over the UK at the time of this particular eclipse helped to mask any eclipse-driven gravity waves.
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Understanding how human influence on climate is affecting precipitation around the world is immensely important for defining mitigation policies, and for adaptation planning. Yet despite increasing evidence for the influence of climate change on global patterns of precipitation, and expectations that significant changes in regional precipitation should have already occurred as a result of human influence on climate, compelling evidence of anthropogenic fingerprints on regional precipitation is obscured by observational and modelling uncertainties and is likely to remain so using current methods for years to come. This is in spite of substantial ongoing improvements in models, new reanalyses and a satellite record that spans over thirty years. If we are to quantify how human-induced climate change is affecting the regional water cycle, we need to consider novel ways of identifying the effects of natural and anthropogenic influences on precipitation that take full advantage of our physical expectations.
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The DNA Checkerboard method enables the simultaneous identification of distinct microorganisms in a large number of samples and employs up to 45 whole genomic DNA probes to gram-negative and gram-positive bacterial species present in subgingival biofilms. Collectively, they account for 55%-60% of the bacteria in subgingival biofilms. In this study, we present the DNA Checkerboard hybridization as an alternative method for the detection and quantitation of Candida species in oral cavities. Our results reveal that DNA Checkerboard is sensitive enough and constitutes a powerful and appropriate method for detecting and quantifying Candida species found in the oral cavity.
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Aeromonads are inhabitants of aquatic ecosystems and are described as being involved in intestinal disturbances and other infections. A total of 200 drinking water samples from domestic and public reservoirs and drinking fountains located in Sao Paulo (Brazil), were analyzed for the presence of Aeromonas. Samples were concentrated by membrane filtration and enriched in APW. ADA medium was used for Aeromonas isolation and colonies were confirmed by biochemical characterization. Strains isolated were tested for hemolysin and toxin production. Aeromonas was detected in 12 samples (6.0%). Aeromonas strains (96) were isolated and identified as: A. caviae (41.7%), A. hydrophila (15.7%), A. allosacharophila (10.4%), A. schubertii (1.0%) and Aeromonas spp. (31.2%). The results revealed that 70% of A. caviare, 66.7% of A. hydrophila, 80% of A. allosacharophila and 46.6% of Aeromonas spp. were hemolytic. The assay for checking production of toxins showed that 17.5% of A. caviae, 73.3% of A. hydrophila, 60% of A. allosacharophila, 100% of A. schubertii, and 33.3% of Aeromonas spp. were able to produce toxins. The results demonstrated the pathogenic potential of Aeromonas, indicating that the presence of this emerging pathogen in water systems is a public health concern.
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GPR (Ground Penetrating Radar) results are shown for perpendicular broadside and parallel broadside antenna orientations. Performance in detection and localization of concrete tubes and steel tanks is compared as a function of acquisition configuration. The comparison is done using 100 MHz and 200 MHz center frequency antennas. All tubes and tanks are buried at the geophysical test site of IAG/USP in Sao Paulo city, Brazil. The results show that the long steel pipe with a 38-mm diameter was well detected with the perpendicular broadside configuration. The concrete tubes were better detected with the parallel broadside configuration, clearly showing hyperbolic diffraction events from all targets up to 2-m depth. Steel tanks were detected with the two configurations. However, the parallel broadside configuration was generated to a much lesser extent an apparent hyperbolic reflection corresponding to constructive interference of diffraction hyperbolas of adjacent targets placed at the same depth. Vertical concrete tubes and steel tanks were better contained with parallel broadside antennas, where the apexes of the diffraction hyperbolas better corresponded to the horizontal location of the buried target disposition. The two configurations provide details about buried targets emphasizing how GPR multi-component configurations have the potential to improve the subsurface image quality as well as to discriminate different buried targets. It is judged that they hold some applicability in geotechnical and geoscientific studies. (C) 2009 Elsevier B.V. All rights reserved.