874 resultados para herbaceous agent


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In this article, the problem of two Unmanned Aerial Vehicles (UAVs) cooperatively searching an unknown region is addressed. The search region is discretized into hexagonal cells and each cell is assumed to possess an uncertainty value. The UAVs have to cooperatively search these cells taking limited endurance, sensor and communication range constraints into account. Due to limited endurance, the UAVs need to return to the base station for refuelling and also need to select a base station when multiple base stations are present. This article proposes a route planning algorithm that takes endurance time constraints into account and uses game theoretical strategies to reduce the uncertainty. The route planning algorithm selects only those cells that ensure the agent will return to any one of the available bases. A set of paths are formed using these cells which the game theoretical strategies use to select a path that yields maximum uncertainty reduction. We explore non-cooperative Nash, cooperative and security strategies from game theory to enhance the search effectiveness. Monte-Carlo simulations are carried out which show the superiority of the game theoretical strategies over greedy strategy for different look ahead step length paths. Within the game theoretical strategies, non-cooperative Nash and cooperative strategy perform similarly in an ideal case, but Nash strategy performs better than the cooperative strategy when the perceived information is different. We also propose a heuristic based on partitioning of the search space into sectors to reduce computational overhead without performance degradation.

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In this paper, we present self assessment schemes (SAS) for multiple agents performing a search mission on an unknown terrain. The agents are subjected to limited communication and sensor ranges. The agents communicate and coordinate with their neighbours to arrive at route decisions. The self assessment schemes proposed here have very low communication and computational overhead. The SAS also has attractive features like scalability to large number of agents and fast decision-making capability. SAS can be used with partial or complete information sharing schemes during the search mission. We validate the performance of SAS using simulation on a large search space consisting of 100 agents with different information structures and self assessment schemes. We also compare the results obtained using SAS with that of a previously proposed negotiation scheme. The simulation results show that the SAS is scalable to large number of agents and can perform as good as the negotiation schemes with reduced communication requirement (almost 20% of that required for negotiation).

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Bonding between ammonium perchlorate (AP) and hydroxy-terminated polybutadiene (HTPB), constituting a nonreinforcing filler system, has been studied in the presence of a unique bonding agent (BA)–a switter ion molecule, 2,4-dinitrophenylhydrazone derivative of 1,1′-bisacetylferrocene (DNPHD AF). Extensive conjugation and a permanent ionic character makes the DNPHD AF to bond strongly with the ionic oxidizer AP. Through its terminal OH group, HTPH bonds with the NO2 groups of DNPHD AF. Bonding sites in the molecules have been located from IR studies and from the first-order rate constant measurements of the bonding of DNPHD AF and other model BAs with HTPB and AP. The bonding ability of DNPHD AF is further evidenced from SEM micrographs.

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Phlebiopsis gigantea has been for a long time known as a strong competitor against Heterobasidion annosum and intensively applied as a biological control agent on stump surfaces of Picea abies in Fennoscandia. However, the mechanism underlying its antagonistic activity is still unknown. A primary concern is the possible impact of P. gigantea treatment on resident non-target microbial biota of conifer stumps. Additional risk factor is the potential of P. gigantea to acquire a necrotrophic habit through adaptation to living wood tissues. This study focused on the differential screening of several P. gigantea isolates from diverse geographical sources as well as the use of breeding approach to enhance the biocontrol efficacy against H. annosum infection. The results showed a significant positive correlation between growth rate in wood and high biocontrol efficacy. Furthermore, with aid of breeding approach, several progeny strains were obtained that had better growth rate and control efficacy than parental isolates. To address the issue of the potential of P. gigantea to acquire necrotrophic capability, a combination of histochemical, molecular and transcript profiling (454 sequencing) were used to investigate the interactions between these two fungi and ten year old P. sylvestris seedlings. The results revealed that both P. gigantea and H. annosum provoked strong necrotic lesions, but after prolonged incubation, P. gigantea lesions shrank and ceased to expand further. Tree seedlings pre-treated with P. gigantea further restricted H. annosum-induced necrosis and had elevated transcript levels of genes important for lignification, cell death regulation and jasmonic acid signalling. These suggest that induced localized resistance is a contributory factor for the biocontrol efficacy of P.gigantea, and it has a comparatively limited necrotrophic capability than H. annosum. Finally, to investigate the potential impact of P. gigantea on the stump bacterial biota, 16S rDNA isolated from tissue samples from stumps of P. abies after 1-, 6- and 13-year post treatment was sequenced using bar-coded 454 Titanium pyrosequencing. Proteobacteria were found to be the most abundant at the initial stages of stump decay but were selectively replaced by Acidobacteria at advanced stages of the decay. Moreover, P. gigantea treatment significantly decreased the bacterial richness at initial decay stage in the stumps. Over time, the bacterial community in the stumps gradually recovered and the negative effects of P. gigantea was attenuated.

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One of the major tasks in swarm intelligence is to design decentralized but homogenoeus strategies to enable controlling the behaviour of swarms of agents. It has been shown in the literature that the point of convergence and motion of a swarm of autonomous mobile agents can be controlled by using cyclic pursuit laws. In cyclic pursuit, there exists a predefined cyclic connection between agents and each agent pursues the next agent in the cycle. In this paper we generalize this idea to a case where an agent pursues a point which is the weighted average of the positions of the remaining agents. This point correspond to a particular pursuit sequence. Using this concept of centroidal cyclic pursuit, the behavior of the agents is analyzed such that, by suitably selecting the agents' gain, the rendezvous point of the agents can be controlled, directed linear motion of the agents can be achieved, and the trajectories of the agents can be changed by switching between the pursuit sequences keeping some of the behaviors of the agents invariant. Simulation experiments are given to support the analytical proofs.

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The aim of this paper is to develop a computationally efficient decentralized rendezvous algorithm for a group of autonomous agents. The algorithm generalizes the notion of sensor domain and decision domain of agents to enable implementation of simple computational algorithms. Specifically, the algorithm proposed in this paper uses a rectilinear decision domain (RDD) as against the circular decision domain assumed in earlier work. Because of this, the computational complexity of the algorithm reduces considerably and, when compared to the standard Ando's algorithm available in the literature, the RDD algorithm shows very significant improvement in convergence time performance. Analytical results to prove convergence and supporting simulation results are presented in the paper.

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In this paper we develop a Linear Programming (LP) based decentralized algorithm for a group of multiple autonomous agents to achieve positional consensus. Each agent is capable of exchanging information about its position and orientation with other agents within their sensing region. The method is computationally feasible and easy to implement. Analytical results are presented. The effectiveness of the approach is illustrated with simulation results.

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The present investigation explores the adaptability of a microwave assisted route to obtain silver nanoparticles by the reduction of AgNO3 with vanillin, an environmentally benign material. Anionic surfactants such as AOT and SDS were used separately for encapsulating AgNPs and their role was compared. The UV-Visible absorption spectra present a broad SPR band consisting of two peaks suggesting the formation of silver nanoparticle with bimodal size distribution. The TEM image shows particles with spherical and hexagonal morphologies which confirms the results of UV-Vis studies. The anisotropy in the particle morphology can be attributed to the surface oxidation which in turn produces Ag@Ag2O core-shell nanostructures. Thus an intriguing feature of this system is that the obtained colloid is a mixture of AgNPs with and without Ag2O layers. Studies on the influence of pH on the stability of the synthesized nanoparticles revealed that the presence of excess Ag2O layers has a profound influence on it. Ag2O layers can be removed from AgNPs' surface by changing the solution pH to the acidic regime. The present study attests the enhanced ability of AOT in stabilizing the AgNPs in aqueous media. (C) 2011 Elsevier B.V. All rights reserved.

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This paper addresses the problem of automated multiagent search in an unknown environment. Autonomous agents equipped with sensors carry out a search operation in a search space, where the uncertainty, or lack of information about the environment, is known a priori as an uncertainty density distribution function. The agents are deployed in the search space to maximize single step search effectiveness. The centroidal Voronoi configuration, which achieves a locally optimal deployment, forms the basis for the proposed sequential deploy and search strategy. It is shown that with the proposed control law the agent trajectories converge in a globally asymptotic manner to the centroidal Voronoi configuration. Simulation experiments are provided to validate the strategy. Note to Practitioners-In this paper, searching an unknown region to gather information about it is modeled as a problem of using search as a means of reducing information uncertainty about the region. Moreover, multiple automated searchers or agents are used to carry out this operation optimally. This problem has many applications in search and surveillance operations using several autonomous UAVs or mobile robots. The concept of agents converging to the centroid of their Voronoi cells, weighted with the uncertainty density, is used to design a search strategy named as sequential deploy and search. Finally, the performance of the strategy is validated using simulations.

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Epoxy-terminated polystyrene has been synthesized by radical polymerization using alpha-(t-butylperoxymethyl) styrene (TPMS) as the chain transfer agent. The chain transfer constants were found to be 0.66 and 0.80 at 60 and 70 degrees C, respectively. The presence of epoxy end groups was confirmed by functional group modification of epoxide to aldehyde by treatment with BF3.Et(2)O. Thermal stability of TPMS was followed by differential scanning calorimetry and iodimetry. Thermal decomposition of TPMS in toluene follows first order kinetics with an activation energy of 23 kcal/mol. (C) 1996 John Wiley & Sons, Inc.

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Synthesis of short peptides using propargyloxycarbonyl amino acid chlorides as effective coupling reagents and polymer supported tetrathiomolybdate as an efficient deblocking agent are reported.

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In this thesis we address the problem of multi-agent search. We formulate two deploy and search strategies based on optimal deployment of agents in search space so as to maximize the search effectiveness in a single step. We show that a variation of centroidal Voronoi configuration is the optimal deployment. When the agents have sensors with different capabilities, the problem will be heterogeneous in nature. We introduce a new concept namely, generalized Voronoi partition in order to formulate and solve the heterogeneous multi-agent search problem. We address a few theoretical issues such as optimality of deployment, convergence and spatial distributedness of the control law and the search strategies. Simulation experiments are carried out to compare performances of the proposed strategies with a few simple search strategies.

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This paper addresses the problem of multiagent search in an unknown environment. The agents are autonomous in nature and are equipped with necessary sensors to carry out the search operation. The uncertainty, or lack of information about the search area is known a priori as a probability density function. The agents are deployed in an optimal way so as to maximize the one step uncertainty reduction. The agents continue to deploy themselves and reduce uncertainty till the uncertainty density is reduced over the search space below a minimum acceptable level. It has been shown, using LaSalle’s invariance principle, that a distributed control law which moves each of the agents towards the centroid of its Voronoi partition, modified by the sensor range leads to single step optimal deployment. This principle is now used to devise search trajectories for the agents. The simulations were carried out in 2D space with saturation on speeds of the agents. The results show that the control strategy per step indeed moves the agents to the respective centroid and the algorithm reduces the uncertainty distribution to the required level within a few steps.

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Presented is a thermodynamic feasibility analysis of extracting base metal chlorides fiom low-grade,multimetallic oxide ores using CaClz as a chlorinating agent in the presence of SOz undoz. The oxides react to form corresponding chlorides, while CaClz is converted to CaS04. The Ellingham diagram is usedfor comparing the standard Gibbs' fiee energy chanlpef or the su(fation-chlorinationr eaction of a large number of oxides. Except for alumina, silica and chromia, most of the other metal oxides will be converted to their respective chlorides. The volatile chlorides can be condensed, and the chlorides present in the condensed state can be leached. A process is proposed that uses a nontoxic chlorinating agent and gives an eficient sepurutiort cftlte metallic vuluesfr.om the garlgue.

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The nanochemistry of calcium remains unexplored, which is largely due to the inaccessibility of calcium nanoparticles in an easy to handle form by conventional methods of synthesis as well as its highly reactive and pyrophoric nature. The synthesis of colloidal Ca nanoparticles by the solvated metal atom dispersion (SMAD) method is described. The as-prepared Ca-THF nanoparticles, which are polydisperse, undergo digestive ripening in the presence of a capping agent, hexadecyl amine (HDA) to afford highly monodisperse colloids consisting of 2-3 nm sized Ca-HDA nanoparticles. These are quite stable towards precipitation for long periods of time, thereby providing access to the study of the nanochemistry of Ca. Particles synthesized in this manner were characterized by UV-visible spectroscopy, high resolution electron microscopy, and powder X-ray diffraction methods. Under an electron beam, two adjacent Ca nanoparticles undergo coalescence to form a larger particle.