1000 resultados para predator recognition


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The baculovirus expression system using the Autographa californica nuclear polyhedrosis virus (AcNPV) has been extensively utilized for high-level expression of cloned foreign genes, driven by the strong viral promoters of polyhedrin (polh) and p10 encoding genes. A parallel system using Bombyx mori nuclear polyhedrosis virus (BmNPV) is much less exploited because the choice and variety of BmNPV-based transfer vectors are limited. Using a transient expression assay, we have demonstrated here that the heterologous promoters of the very late genes polh and p10 from AcNPV function as efficiently in BmN cells as the BmNPV promoters. The location of the cloned foreign gene with respect to the promoter sequences was critical for achieving the highest levels of expression, following the order +35 > +1 > -3 > -8 nucleotides (nt) with respect to the polh or p10 start codons. We have successfully generated recombinant BmNPV harboring AcNPV promoters by homeologous recombination between AcNPV-based transfer vectors and BmNPV genomic DNA. Infection of BmN cell lines with recombinant BmNPV showed a temporal expression pattern, reaching very high levels in 60-72 h post infection. The recombinant BmNPV harboring the firefly luciferase-encoding gene under the control of AcNPV polh or p10 promoters, on infection of the silkworm larvae led to the synthesis of large quantities of luciferase. Such larvae emanated significant luminiscence instantaneously on administration of the substrate luciferin resulting in 'glowing silkworms'. The virus-infected larvae continued to glow for several hours and revealed the most abundant distribution of virus in the fat bodies. In larval expression also, the highest levels were achieved when the reporter gene was located at +35 nt of the polh.

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Abstract-The success of automatic speaker recognition in laboratory environments suggests applications in forensic science for establishing the Identity of individuals on the basis of features extracted from speech. A theoretical model for such a verification scheme for continuous normaliy distributed featureIss developed. The three cases of using a) single feature, b)multipliendependent measurements of a single feature, and c)multpleindependent features are explored.The number iofndependent features needed for areliable personal identification is computed based on the theoretcal model and an expklatory study of some speech featues.

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An adaptive learning scheme, based on a fuzzy approximation to the gradient descent method for training a pattern classifier using unlabeled samples, is described. The objective function defined for the fuzzy ISODATA clustering procedure is used as the loss function for computing the gradient. Learning is based on simultaneous fuzzy decisionmaking and estimation. It uses conditional fuzzy measures on unlabeled samples. An exponential membership function is assumed for each class, and the parameters constituting these membership functions are estimated, using the gradient, in a recursive fashion. The induced possibility of occurrence of each class is useful for estimation and is computed using 1) the membership of the new sample in that class and 2) the previously computed average possibility of occurrence of the same class. An inductive entropy measure is defined in terms of induced possibility distribution to measure the extent of learning. The method is illustrated with relevant examples.

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The minimum cost classifier when general cost functionsare associated with the tasks of feature measurement and classification is formulated as a decision graph which does not reject class labels at intermediate stages. Noting its complexities, a heuristic procedure to simplify this scheme to a binary decision tree is presented. The optimizationof the binary tree in this context is carried out using ynamicprogramming. This technique is applied to the voiced-unvoiced-silence classification in speech processing.

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trychnine was coupled to fluorescein isothiocyanate to mark strychnine binding sites in spinal cord of rat. Specific binding of strychnine could be demonstrated in synaptosomal fraction. Addition of glycine to the strychninised membrane led to a decrease in fluorescence indicating same receptor loci.

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1. Mammalian predators are controlled by poison baiting in many parts of the world, often to alleviate their impacts on agriculture or the environment. Although predator control can have substantial benefits, the poisons used may also be potentially harmful to other wildlife. 2. Impacts on non-target species must be minimized, but can be difficult to predict or quantify. Species and individuals vary in their sensitivity to toxins and their propensity to consume poison baits, while populations vary in their resilience. Wildlife populations can accrue benefits from predator control, which outweigh the occasional deaths of non-target animals. We review recent advances in Australia, providing a framework for assessing non-target effects of poisoning operations and for developing techniques to minimize such effects. We also emphasize that weak or circumstantial evidence of non-target effects can be misleading. 3. Weak evidence that poison baiting presents a potential risk to non-target species comes from measuring the sensitivity of species to the toxin in the laboratory. More convincing evidence may be obtained by quantifying susceptibility in the field. This requires detailed information on the propensity of animals to locate and consume poison baits, as well as the likelihood of mortality if baits are consumed. Still stronger evidence may be obtained if predator baiting causes non-target mortality in the field (with toxin detected by post-mortem examination). Conclusive proof of a negative impact on populations of non-target species can be obtained only if any observed non-target mortality is followed by sustained reductions in population density. 4. Such proof is difficult to obtain and the possibility of a population-level impact cannot be reliably confirmed or dismissed without rigorous trials. In the absence of conclusive evidence, wildlife managers should adopt a precautionary approach which seeks to minimize potential risk to non-target individuals, while clarifying population-level effects through continued research.

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This letter presents the development of simplified algorithms based on Haar functions for signal extraction in relaying signals. These algorithms, being computationally simple, are better suited for microprocessor-based power system protection relaying. They provide accurate estimates of the signal amplitude and phase.

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An important question in the host-finding behaviour of a polyphagous insect is whether the insect recognizes a suite or template of chemicals that are common to many plants? To answer this question, headspace volatiles of a subset of commonly used host plants (pigeon pea, tobacco, cotton and bean) and nonhost plants (lantana and oleander) of Helicoverpa armigera Hübner (Lepidoptera: Noctuidae) are screened by gas chromatography (GC) linked to a mated female H. armigera electroantennograph (EAG). In the present study, pigeon pea is postulated to be a primary host plant of the insect, for comparison of the EAG responses across the test plants. EAG responses for pigeon pea volatiles are also compared between females of different physiological status (virgin and mated females) and the sexes. Eight electrophysiologically active compounds in pigeon pea headspace are identified in relatively high concentrations using GC linked to mass spectrometry (GC-MS). These comprised three green leaf volatiles [(2E)-hexenal, (3Z)-hexenylacetate and (3Z)-hexenyl-2-methylbutyrate] and five monoterpenes (α-pinene, β-myrcene, limonene, E-β-ocimene and linalool). Other tested host plants have a smaller subset of these electrophysiologically active compounds and even the nonhost plants contain some of these compounds, all at relatively lower concentrations than pigeon pea. The physiological status or sex of the moths has no effect on the responses for these identified compounds. The present study demonstrates how some host plants can be primary targets for moths that are searching for hosts whereas the other host plants are incidental or secondary targets.

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This paper describes a vision-only system for place recognition in environments that are tra- versed at different times of day, when chang- ing conditions drastically affect visual appear- ance, and at different speeds, where places aren’t visited at a consistent linear rate. The ma- jor contribution is the removal of wheel-based odometry from the previously presented algo- rithm (SMART), allowing the technique to op- erate on any camera-based device; in our case a mobile phone. While we show that the di- rect application of visual odometry to our night- time datasets does not achieve a level of perfor- mance typically needed, the VO requirements of SMART are orthogonal to typical usage: firstly only the magnitude of the velocity is required, and secondly the calculated velocity signal only needs to be repeatable in any one part of the environment over day and night cycles, but not necessarily globally consistent. Our results show that the smoothing effect of motion constraints is highly beneficial for achieving a locally consis- tent, lighting-independent velocity estimate. We also show that the advantage of our patch-based technique used previously for frame recogni- tion, surprisingly, does not transfer to VO, where SIFT demonstrates equally good performance. Nevertheless, we present the SMART system us- ing only vision, which performs sequence-base place recognition in extreme low-light condi- tions where standard 6-DOF VO fails and that improves place recognition performance over odometry-less benchmarks, approaching that of wheel odometry.

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The statistical minimum risk pattern recognition problem, when the classification costs are random variables of unknown statistics, is considered. Using medical diagnosis as a possible application, the problem of learning the optimal decision scheme is studied for a two-class twoaction case, as a first step. This reduces to the problem of learning the optimum threshold (for taking appropriate action) on the a posteriori probability of one class. A recursive procedure for updating an estimate of the threshold is proposed. The estimation procedure does not require the knowledge of actual class labels of the sample patterns in the design set. The adaptive scheme of using the present threshold estimate for taking action on the next sample is shown to converge, in probability, to the optimum. The results of a computer simulation study of three learning schemes demonstrate the theoretically predictable salient features of the adaptive scheme.

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We are addressing the problem of jointly using multiple noisy speech patterns for automatic speech recognition (ASR), given that they come from the same class. If the user utters a word K times, the ASR system should try to use the information content in all the K patterns of the word simultaneously and improve its speech recognition accuracy compared to that of the single pattern based speech recognition. T address this problem, recently we proposed a Multi Pattern Dynamic Time Warping (MPDTW) algorithm to align the K patterns by finding the least distortion path between them. A Constrained Multi Pattern Viterbi algorithm was used on this aligned path for isolated word recognition (IWR). In this paper, we explore the possibility of using only the MPDTW algorithm for IWR. We also study the properties of the MPDTW algorithm. We show that using only 2 noisy test patterns (10 percent burst noise at -5 dB SNR) reduces the noisy speech recognition error rate by 37.66 percent when compared to the single pattern recognition using the Dynamic Time Warping algorithm.

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Odour emission rates were measured for seven different anaerobic ponds treating piggery wastes at six to nine discrete locations across the surface of each pond on each sampling occasion over a thirteen month period. Significant variability in emission rates were observed for each pond. Measurement of a number of water quality variables in pond liquor samples collected at the same time and from the same locations as the odour samples indicated that the composition of the pond liquor was also variable. The results indicated that spatial variability was a real phenomenon and could have a significant impact on odour assessment practices. Considerably more odour samples would be required to characterise pond emissions than currently recommended by most practitioners, or regulatory agencies.

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Displacement of herbivorous insects by the presence of predators on whole plants has rarely been studied. By semi-continuous observations of an externally feeding insect herbivore and a predator, we show how the mere presence of the predator, Geocoris lubra Kirkaldy (Hemiptera: Geocoridae), on a plant can have a strong influence on the movement and behaviors of Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae) larvae. The presence of predators, as opposed to mortality by predators, influenced the proportion of larvae feeding, resting and implementing avoidance activities. In addition, the proportion of time individual larvae allocated to feeding, resting and dropping off plants was affected when predators were present with and without contact between the two. Predators do more than just reduce numbers of herbivores; they influence feeding, displacement and subsequently the distribution of plant damage.

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Deep convolutional network models have dominated recent work in human action recognition as well as image classification. However, these methods are often unduly influenced by the image background, learning and exploiting the presence of cues in typical computer vision datasets. For unbiased robotics applications, the degree of variation and novelty in action backgrounds is far greater than in computer vision datasets. To address this challenge, we propose an “action region proposal” method that, informed by optical flow, extracts image regions likely to contain actions for input into the network both during training and testing. In a range of experiments, we demonstrate that manually segmenting the background is not enough; but through active action region proposals during training and testing, state-of-the-art or better performance can be achieved on individual spatial and temporal video components. Finally, we show by focusing attention through action region proposals, we can further improve upon the existing state-of-the-art in spatio-temporally fused action recognition performance.

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The constitutional recognition campaign has received party-wide support and its efforts have been promoted by Prime Minister Tony Abbott as being something that would ‘complete our Constitution.’ The broader rhetoric surrounding this campaign suggests that it will result in a just, albeit delayed, recognition of indigenous peoples in the Australian legal system. However, beneath the surface of this seemingly benevolent gesture, is a reaffirmation of the colonial subordination and erasure of the several hundred original nations’ peoples and ways of being.