110 resultados para Protocolos transaccionais multi-Agente


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Endophyte-assisted phytoremediation has recently been suggested as a successful approach for ecological restoration of metal contaminated soils, however little information is available on the influence of endophytic bacteria on the phytoextraction capacity of metal hyperaccumulating plants in multi-metal polluted soils. The aims of our study were to isolate and characterize metal-resistant and 1-aminocyclopropane-1-carboxylate (ACC) utilizing endophytic bacteria from tissues of the newly discovered Zn/Cd hyperaccumulator Sedum plumbizincicola and to examine if these endophytic bacterial strains could improve the efficiency of phytoextraction of multi-metal contaminated soils. Among a collection of 42 metal resistant bacterial strains isolated from the tissues of S. plumbizincicola grown on Pb/Zn mine tailings, five plant growth promoting endophytic bacterial strains (PGPE) were selected due to their ability to promote plant growth and to utilize ACC as the sole nitrogen source. The five isolates were identified as Bacillus pumilus E2S2, Bacillus sp. E1S2, Bacillus sp. E4S1, Achromobacter sp. E4L5 and Stenotrophomonas sp. E1L and subsequent testing revealed that they all exhibited traits associated with plant growth promotion, such as production of indole-3-acetic acid and siderophores and solubilization of phosphorus. These five strains showed high resistance to heavy metals (Cd, Zn and Pb) and various antibiotics. Further, inoculation of these ACC utilizing strains significantly increased the concentrations of water extractable Cd and Zn in soil. Moreover, a pot experiment was conducted to elucidate the effects of inoculating metal-resistant ACC utilizing strains on the growth of S. plumbizincicola and its uptake of Cd, Zn and Pb in multi-metal contaminated soils. Out of the five strains, B. pumilus E2S2 significantly increased root (146%) and shoot (17%) length, fresh (37%) and dry biomass (32%) of S. plumbizincicola as well as plant Cd uptake (43%), whereas Bacillus sp. E1S2 significantly enhanced the accumulation of Zn (18%) in plants compared with non-inoculated controls. The inoculated strains also showed high levels of colonization in rhizosphere and plant tissues. Results demonstrate the potential to improve phytoextraction of soils contaminated with multiple heavy metals by inoculating metal hyperaccumulating plants with their own selected functional endophytic bacterial strains.

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5th International Conference on Climbing and Walking Robots and the Support Technologies for Mobile Machines

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4th International Conference on Climbing and Walking Robots - From Biology to Industrial Applications

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Target tracking with bearing-only sensors is a challenging problem when the target moves dynamically in complex scenarios. Besides the partial observability of such sensors, they have limited field of views, occlusions can occur, etc. In those cases, cooperative approaches with multiple tracking robots are interesting, but the different sources of uncertain information need to be considered appropriately in order to achieve better estimates. Even though there exist probabilistic filters that can estimate the position of a target dealing with incertainties, bearing-only measurements bring usually additional problems with initialization and data association. In this paper, we propose a multi-robot triangulation method with a dynamic baseline that can triangulate bearing-only measurements in a probabilistic manner to produce 3D observations. This method is combined with a decentralized stochastic filter and used to tackle those initialization and data association issues. The approach is validated with simulations and field experiments where a team of aerial and ground robots with cameras track a dynamic target.

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13th International Conference on Autonomous Robot Systems (Robotica), 2013

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4th International Conference, SIMPAR 2014, Bergamo, Italy, October 20-23, 2014

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The paper presents a multi-robot cooperative framework to estimate the 3D position of dynamic targets, based on bearing-only vision measurements. The uncertainty of the observation provided by each robot equipped with a bearing-only vision system is effectively addressed for cooperative triangulation purposes by weighing the contribution of each monocular bearing ray in a probabilistic manner. The envisioned framework is evaluated in an outdoor scenario with a team of heterogeneous robots composed of an Unmanned Ground and Aerial Vehicle.

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Os sistemas de perceção visual são das principais fontes de informação sensorial utilizadas pelos robôs autónomos, para localização e navegação em diferentes meios de operação. O objetivo passa por obter uma grande quantidade de informação sobre o ambiente que a câmara está a visualizar, processar e extrair informação que permita realizar as tarefas de uma forma e ciente. Uma informação em particular que os sistemas de visão podem fornecer, e a informação tridimensional acerca do meio envolvente. Esta informação pode ser adquirida recorrendo a sistemas de visão monoculares ou com múltiplas câmaras. Nestes sistemas a informação tridimensional pode ser obtida recorrendo a técnica de triangulação, tirando partido do conhecimento da posição relativa entre as câmaras. No entanto, para calcular as coordenadas de um ponto tridimensional no referencial da câmara e necessário existir correspondência entre pontos comuns às imagens adquiridas pelo sistema. No caso de más correspondências a informação 3D e obtida de forma incorreta. O problema associado à correspondência de pontos pode ser agravado no caso das câmaras do sistema terem características intrínsecas diferentes nomeadamente: resolução, abertura da lente, distorção. Outros fatores como as orientações e posições das câmaras também podem condicionar a correspondência de pontos. Este trabalho incide sobre problemática de correspondência de pontos existente no processo de cálculo da informação tridimensional. A presente dissertação visa o desenvolvimento de uma abordagem de correspondência de pontos para sistemas de visão no qual é conhecida a posição relativa entre câmaras.

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Smart Cities are designed to be living systems and turn urban dwellers life more comfortable and interactive by keeping them aware of what surrounds them, while leaving a greener footprint. The Future Cities Project [1] aims to create infrastructures for research in smart cities including a vehicular network, the BusNet, and an environmental sensor platform, the Urban Sense. Vehicles within the BusNet are equipped with On Board Units (OBUs) that offer free Wi-Fi to passengers and devices near the street. The Urban Sense platform is composed by a set of Data Collection Units (DCUs) that include a set of sensors measuring environmental parameters such as air pollution, meteorology and noise. The Urban Sense platform is expanding and receptive to add new sensors to the platform. The parnership with companies like TNL were made and the need to monitor garbage street containers emerged as air pollution prevention. If refuse collection companies know prior to the refuse collection which route is the best to collect the maximum amount of garbage with the shortest path, they can reduce costs and pollution levels are lower, leaving behind a greener footprint. This dissertation work arises in the need to monitor the garbage street containers and integrate these sensors into an Urban Sense DCU. Due to the remote locations of the garbage street containers, a network extension to the vehicular network had to be created. This dissertation work also focus on the Multi-hop network designed to extend the vehicular network coverage area to the remote garbage street containers. In locations where garbage street containers have access to the vehicular network, Roadside Units (RSUs) or Access Points (APs), the Multi-hop network serves has a redundant path to send the data collected from DCUs to the Urban Sense cloud database. To plan this highly dynamic network, the Wi-Fi Planner Tool was developed. This tool allowed taking measurements on the field that led to an optimized location of the Multi-hop network nodes with the use of radio propagation models. This tool also allowed rendering a temperature-map style overlay for Google Earth [2] application. For the DCU for garbage street containers the parner company provided the access to a HUB (device that communicates with the sensor inside the garbage containers). The Future Cities use the Raspberry pi as a platform for the DCUs. To collect the data from the HUB a RS485 to RS232 converter was used at the physical level and the Modbus protocol at the application level. To determine the location and status of the vehicles whinin the vehicular network a TCP Server was developed. This application was developed for the OBUs providing the vehicle Global Positioning System (GPS) location as well as information of when the vehicle is stopped, moving, on idle or even its slope. To implement the Multi-hop network on the field some scripts were developed such as pingLED and “shark”. These scripts helped upon node deployment on the field as well as to perform all the tests on the network. Two setups were implemented on the field, an urban setup was implemented for a Multi-hop network coverage survey and a sub-urban setup was implemented to test the Multi-hop network routing protocols, Optimized Link State Routing Protocol (OLSR) and Babel.

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EMC2 finds solutions for dynamic adaptability in open systems. It provides handling of mixed criticality multicore applications in r eal-time conditions, withscalability and utmost flexibility, full-scale deployment and management of integrated tool chains, through the entire lifecycle.

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In the traditional paradigm, the large power plants supply the reactive power required at a transmission level and the capacitors and transformer tap changer were also used at a distribution level. However, in a near future will be necessary to schedule both active and reactive power at a distribution level, due to the high number of resources connected in distribution levels. This paper proposes a new multi-objective methodology to deal with the optimal resource scheduling considering the distributed generation, electric vehicles and capacitor banks for the joint active and reactive power scheduling. The proposed methodology considers the minimization of the cost (economic perspective) of all distributed resources, and the minimization of the voltage magnitude difference (technical perspective) in all buses. The Pareto front is determined and a fuzzy-based mechanism is applied to present the best compromise solution. The proposed methodology has been tested in the 33-bus distribution network. The case study shows the results of three different scenarios for the economic, technical, and multi-objective perspectives, and the results demonstrated the importance of incorporating the reactive scheduling in the distribution network using the multi-objective perspective to obtain the best compromise solution for the economic and technical perspectives.

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The electricity market restructuring, and its worldwide evolution into regional and even continental scales, along with the increasing necessity for an adequate integration of renewable energy sources, is resulting in a rising complexity in power systems operation. Several power system simulators have been developed in recent years with the purpose of helping operators, regulators, and involved players to understand and deal with this complex and constantly changing environment. The main contribution of this paper is given by the integration of several electricity market and power system models, respecting to the reality of different countries. This integration is done through the development of an upper ontology which integrates the essential concepts necessary to interpret all the available information. The continuous development of Multi-Agent System for Competitive Electricity Markets platform provides the means for the exemplification of the usefulness of this ontology. A case study using the proposed multi-agent platform is presented, considering a scenario based on real data that simulates the European Electricity Market environment, and comparing its performance using different market mechanisms. The main goal is to demonstrate the advantages that the integration of various market models and simulation platforms have for the study of the electricity markets’ evolution.

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In this paper, we formulate the electricity retailers’ short-term decision-making problem in a liberalized retail market as a multi-objective optimization model. Retailers with light physical assets, such as generation and storage units in the distribution network, are considered. Following advances in smart grid technologies, electricity retailers are becoming able to employ incentive-based demand response (DR) programs in addition to their physical assets to effectively manage the risks of market price and load variations. In this model, the DR scheduling is performed simultaneously with the dispatch of generation and storage units. The ultimate goal is to find the optimal values of the hourly financial incentives offered to the end-users. The proposed model considers the capacity obligations imposed on retailers by the grid operator. The profit seeking retailer also has the objective to minimize the peak demand to avoid the high capacity charges in form of grid tariffs or penalties. The non-dominated sorting genetic algorithm II (NSGA-II) is used to solve the multi-objective problem. It is a fast and elitist multi-objective evolutionary algorithm. A case study is solved to illustrate the efficient performance of the proposed methodology. Simulation results show the effectiveness of the model for designing the incentive-based DR programs and indicate the efficiency of NSGA-II in solving the retailers’ multi-objective problem.

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This study proposes a new methodology to increase the power delivered to any load point in a radial distribution network, through the identification of new investments in order to improve the repair time. This research work is innovative and consists in proposing a full optimisation model based on mixed-integer non-linear programming considering the Pareto front technique. The goal is to achieve a reduction in repair times of the distribution networks components, while minimising the costs of that reduction as well as non-supplied energy costs. The optimisation model considers the distribution network technical constraints, the substation transformer taps, and it is able to choose the capacitor banks size. A case study based on a 33-bus distribution network is presented in order to illustrate in detail the application of the proposed methodology.

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Metal contamination of the environment is frequently associated to the presence of two or more metals. This work aimed to study the impact of a mixture of metals (Cd, Pb and Zn) on the physiology of the non-conventional yeast Pichia kudriavzevii. The incubation of yeast cells with 5 mg/l Cd, 10 mg/l Pb and 5 mg/l Zn, for 6 h, induced a loss of metabolic activity (assessed by FUN-1 staining) and proliferation capacity (evaluated by a clonogenic assay), with a small loss of membrane integrity (measured by trypan blue exclusion assay). The staining of yeast cells with calcofluor white revealed that no modification of chitin deposition pattern occurred during the exposure to metal mixture. Extending for 24 h, the exposure of yeast cells to metal mixture provoked a loss of membrane integrity, which was accompanied by the leakage of intracellular components. A marked loss of the metabolic activity and the loss of proliferation capacity were also observed. The analysis of the impact of a single metal has shown that, under the conditions studied, Pb was the metal responsible for the toxic effect observed in the metal mixture. Intracellular accumulation of Pb seems to be correlated with the metals' toxic effects observed.