968 resultados para Multi-robot cooperation
Resumo:
A total of 63 isolates of Pasteurella multocida from Australian poultry, all associated with fowl cholera outbreaks, and three international reference strains, representing the three subspecies within P. multocida were used to develop a multi-locus sequence typing scheme. Primers were designed for conserved regions of seven house-keeping enzymes - adk, est, gdh, mdh, pgi, pmi and zwf - and internal fragments of 570-784 bp were sequenced for all isolates and strains. The number of alleles at the different loci ranged from 11 to 20 and a total of 29 allelic profiles or sequence types were recognised amongst the 66 strains. There was a strong concordance between the MLST data and the existing multi-locus enzyme electrophoresis and ribotyping data. When used to study a sub-set of isolates with a known detailed epidemiological history, the MLST data matched the results given by restriction endonuclease analysis, pulsed-field gel electrophoresis, ribotyping and REP-PCR. The MLST scheme provides a high level of resolution and is an excellent tool for studying the population structure and epidemiology of P. multocida.
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Multi-access techniques are widely used in computer networking and distributed multiprocessor systems. On-the-fly arbitration schemes permit one of the many contenders to access the medium without collisions. Serial arbitration is cost effective but is slow and hence unsuitable for high-speed multiprocessor environments supporting very high data transfer rates. A fully parallel arbitration scheme takes less time but is not practically realisable for large numbers of contenders. In this paper, a generalised parallel-serial scheme is proposed which significantly reduces the arbitration time and is practically realisable.
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We study the performance of greedy scheduling in multihop wireless networks where the objective is aggregate utility maximization. Following standard approaches, we consider the dual of the original optimization problem. Optimal scheduling requires selecting independent sets of maximum aggregate price, but this problem is known to be NP-hard. We propose and evaluate a simple greedy heuristic. We suggest how the greedy heuristic can be implemented in a distributed manner. We evaluate an analytical bound in detail, for the special case of a line graph and also provide a loose bound on the greedy heuristic for the case of an arbitrary graph.
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A pheromone-based trapping system will be developed for both A. lutescens and A. nitida to improve insecticide timing and to rationalise use.
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The results are presented of applying multi-time scale analysis using the singular perturbation technique for long time simulation of power system problems. A linear system represented in state-space form can be decoupled into slow and fast subsystems. These subsystems can be simulated with different time steps and then recombined to obtain the system response. Simulation results with a two-time scale analysis of a power system show a large saving in computational costs.
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A recent work obtained closed-form solutions to the.problem of optimally grouping a multi-item inventory into subgroups with a common order cycle per group, when the distribution by value of the inventory could be described by a Pareto function. This paper studies the sensitivity of the optimal subgroup boundaries so obtained. Closed-form expressions have been developed to find intervals for the subgroup boundaries for any given level of suboptimality. Graphs have been provided to aid the user in selecting a cost-effective level of aggregation and choosing appropriate subgroup boundaries for a whole range of inventory distributions. The results of sensitivity analyses demonstrate the availability of flexibility in the partition boundaries and the cost-effectiveness of any stock control system through three groups, and thus also provide a theoretical support to the intuitive ABC system of classifying the items.
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We present a participatory modelling framework that integrates information from interviews and discussions with farmers and consultants, with dynamic bio-economic models to answer complex questions on the allocation of limited resources at the farm business level. Interviews and discussions with farmers were used to: describe the farm business; identify relevant research questions; identify potential solutions; and discuss and learn from the whole-farm simulations. The simulations are done using a whole-farm, multi-field configuration of APSIM (APSFarm). APSFarm results were validated against farmers' experience. Once the model was accepted by the participating farmers as a fair representation of their farm business, the model was used to explore changes in the tactical or strategic management of the farm and results were then discussed to identify feasible options for improvement. Here we describe the modelling framework and present an example of the application of integrative whole farm system tools to answer relevant questions from an irrigated farm business case study near Dalby (151.27E - 27.17S), Queensland, Australia. Results indicated that even though cotton crops generates more farm income per hectare a more diversified rotation with less cotton would be relatively more profitable, with no increase in risk, as a more cotton dominated traditional rotation. Results are discussed in terms of the benefits and constraints from developing and applying more integrative approaches to represent farm businesses and their management in participatory research projects with the aim of designing more profitable and sustainable irrigated farming systems.
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Understanding the ontogenetic habitat linkages of sharks is important for conservation and managing human interactions. We used acoustic telemetry, catch data, elemental and stable isotope signatures and dietary analyses to investigate ontogenetic habitat use in south-east Queensland, Australia, by the bull shark Carcharhinus leucas, a IUCN 'near-threatened' species that is implicated in many shark attacks on humans in urban estuaries. Sequential analyses for delta(15)N and delta(13)C of vertebrae from five adult C. leucas and laser ablation inductively coupled plasma mass spectrometry (LA-ICPMS) for elemental composition from 23 C. leucas, including a pregnant female, were also used to trace ontogenetic habitat dependence. Acoustic telemetry indicated large juvenile and subadult C. leucas remained in estuarine habitats. delta(15)N values across shark vertebrae showed an ontogenetic shift in diet with total length (TL), confirmed by stomach contents. LA-ICPMS data reflected the ontogenetic movements of C. leucas from natal habitats. Differences among adults were gender related. Shifts in habitat use by subadults were correlated with a sigmoidal delta(13)C relationship with TL. C. leucas have a multipartite, stage-specific dependency in their transition between habitats along the freshwater-estuarine-marine continuum, making them particularly susceptible to the habitat alteration that is occurring globally.
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Bread undergoes several physicochemical changes during storage that results in a rapid loss of freshness. These changes depend on moisture content present in bread product. An instrument based on electrical impedance spectroscopy technique is developed to estimate moisture content of bread at different zones using designed multi-channel ring electrodes. A dedicated AT89S52 microcontroller and associated peripherals are employed for hardware. A constant current is applied across bread loaf through central pair of electrodes and developed potential across different zones of bread loaf are measured using remaining four ring electrode pairs. These measured values of voltage and current are used to measure the impedance at each zone. Electrical impedance behavior of the bread loaf at crust and crumb is investigated during storage. A linear relationship is observed between the measured impedance and moisture content present in crust and crumb of bread loaf during storage of 120 hours.
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During the last decades there has been a global shift in forest management from a focus solely on timber management to ecosystem management that endorses all aspects of forest functions: ecological, economic and social. This has resulted in a shift in paradigm from sustained yield to sustained diversity of values, goods and benefits obtained at the same time, introducing new temporal and spatial scales into forest resource management. The purpose of the present dissertation was to develop methods that would enable spatial and temporal scales to be introduced into the storage, processing, access and utilization of forest resource data. The methods developed are based on a conceptual view of a forest as a hierarchically nested collection of objects that can have a dynamically changing set of attributes. The temporal aspect of the methods consists of lifetime management for the objects and their attributes and of a temporal succession linking the objects together. Development of the forest resource data processing method concentrated on the extensibility and configurability of the data content and model calculations, allowing for a diverse set of processing operations to be executed using the same framework. The contribution of this dissertation to the utilisation of multi-scale forest resource data lies in the development of a reference data generation method to support forest inventory methods in approaching single-tree resolution.
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In this paper, we propose an extension to the I/O device architecture, as recommended in the PCI-SIG IOV specification, for virtualizing network I/O devices. The aim is to enable fine-grained controls to a virtual machine on the I/O path of a shared device. The architecture allows native access of I/O devices to virtual machines and provides device level QoS hooks for controlling VM specific device usage. For evaluating the architecture we use layered queuing network (LQN) models. We implement the architecture and evaluate it using simulation techniques, on the LQN model, to demonstrate the benefits. With the architecture, the benefit for network I/O is 60% more than what can be expected on the existing architecture. Also, the proposed architecture improves scalability in terms of the number of virtual machines intending to share the I/O device.
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The aim of this thesis is to develop a fully automatic lameness detection system that operates in a milking robot. The instrumentation, measurement software, algorithms for data analysis and a neural network model for lameness detection were developed. Automatic milking has become a common practice in dairy husbandry, and in the year 2006 about 4000 farms worldwide used over 6000 milking robots. There is a worldwide movement with the objective of fully automating every process from feeding to milking. Increase in automation is a consequence of increasing farm sizes, the demand for more efficient production and the growth of labour costs. As the level of automation increases, the time that the cattle keeper uses for monitoring animals often decreases. This has created a need for systems for automatically monitoring the health of farm animals. The popularity of milking robots also offers a new and unique possibility to monitor animals in a single confined space up to four times daily. Lameness is a crucial welfare issue in the modern dairy industry. Limb disorders cause serious welfare, health and economic problems especially in loose housing of cattle. Lameness causes losses in milk production and leads to early culling of animals. These costs could be reduced with early identification and treatment. At present, only a few methods for automatically detecting lameness have been developed, and the most common methods used for lameness detection and assessment are various visual locomotion scoring systems. The problem with locomotion scoring is that it needs experience to be conducted properly, it is labour intensive as an on-farm method and the results are subjective. A four balance system for measuring the leg load distribution of dairy cows during milking in order to detect lameness was developed and set up in the University of Helsinki Research farm Suitia. The leg weights of 73 cows were successfully recorded during almost 10,000 robotic milkings over a period of 5 months. The cows were locomotion scored weekly, and the lame cows were inspected clinically for hoof lesions. Unsuccessful measurements, caused by cows standing outside the balances, were removed from the data with a special algorithm, and the mean leg loads and the number of kicks during milking was calculated. In order to develop an expert system to automatically detect lameness cases, a model was needed. A probabilistic neural network (PNN) classifier model was chosen for the task. The data was divided in two parts and 5,074 measurements from 37 cows were used to train the model. The operation of the model was evaluated for its ability to detect lameness in the validating dataset, which had 4,868 measurements from 36 cows. The model was able to classify 96% of the measurements correctly as sound or lame cows, and 100% of the lameness cases in the validation data were identified. The number of measurements causing false alarms was 1.1%. The developed model has the potential to be used for on-farm decision support and can be used in a real-time lameness monitoring system.
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The peptide hormone ghrelin is a potent orexigen produced predominantly in the stomach. It has a number of other biological actions, including roles in appetite stimulation, energy balance, the stimulation of growth hormone release and the regulation of cell proliferation. Recently, several ghrelin gene splice variants have been described. Here, we attempted to identify conserved alternative splicing of the ghrelin gene by cross-species sequence comparisons. We identified a novel human exon 2-deleted variant and provide preliminary evidence that this splice variant and in1-ghrelin encode a C-terminally truncated form of the ghrelin peptide, termed minighrelin. These variants are expressed in humans and mice, demonstrating conservation of alternative splicing spanning 90 million years. Minighrelin appears to have similar actions to full-length ghrelin, as treatment with exogenous minighrelin peptide stimulates appetite and feeding in mice. Forced expression of the exon 2-deleted preproghrelin variant mirrors the effect of the canonical preproghrelin, stimulating cell proliferation and migration in the PC3 prostate cancer cell line. This is the first study to characterise an exon 2-deleted preproghrelin variant and to demonstrate sequence conservation of ghrelin gene-derived splice variants that encode a truncated ghrelin peptide. This adds further impetus for studies into the alternative splicing of the ghrelin gene and the function of novel ghrelin peptides in vertebrates.
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Spontaneous sequence changes and the selection of beneficial mutations are driving forces of gene diversification and key factors of evolution. In highly dynamic co-evolutionary processes such as plant-pathogen interactions, the plant's ability to rapidly adapt to newly emerging pathogens is paramount. The hexaploid wheat gene Lr34, which encodes an ATP-binding cassette (ABC) transporter, confers durable field resistance against four fungal diseases. Despite its extensive use in breeding and agriculture, no increase in virulence towards Lr34 has been described over the last century. The wheat genepool contains two predominant Lr34 alleles of which only one confers disease resistance. The two alleles, located on chromosome 7DS, differ by only two exon-polymorphisms. Putatively functional homoeologs and orthologs of Lr34 are found on the B-genome of wheat and in rice and sorghum, but not in maize, barley and Brachypodium. In this study we present a detailed haplotype analysis of homoeologous and orthologous Lr34 genes in genetically and geographically diverse selections of wheat, rice and sorghum accessions. We found that the resistant Lr34 haplotype is unique to the wheat D-genome and is not found in the B-genome of wheat or in rice and sorghum. Furthermore, we only found the susceptible Lr34 allele in a set of 252 Ae. tauschii genotypes, the progenitor of the wheat D-genome. These data provide compelling evidence that the Lr34 multi-pathogen resistance is the result of recent gene diversification occurring after the formation of hexaploid wheat about 8,000 years ago.