887 resultados para Electrical distribution systems


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The term "Brain Imaging" identi�es a set of techniques to analyze the structure and/or functional behavior of the brain in normal and/or pathological situations. These techniques are largely used in the study of brain activity. In addition to clinical usage, analysis of brain activity is gaining popularity in others recent �fields, i.e. Brain Computer Interfaces (BCI) and the study of cognitive processes. In this context, usage of classical solutions (e.g. f MRI, PET-CT) could be unfeasible, due to their low temporal resolution, high cost and limited portability. For these reasons alternative low cost techniques are object of research, typically based on simple recording hardware and on intensive data elaboration process. Typical examples are ElectroEncephaloGraphy (EEG) and Electrical Impedance Tomography (EIT), where electric potential at the patient's scalp is recorded by high impedance electrodes. In EEG potentials are directly generated from neuronal activity, while in EIT by the injection of small currents at the scalp. To retrieve meaningful insights on brain activity from measurements, EIT and EEG relies on detailed knowledge of the underlying electrical properties of the body. This is obtained from numerical models of the electric �field distribution therein. The inhomogeneous and anisotropic electric properties of human tissues make accurate modeling and simulation very challenging, leading to a tradeo�ff between physical accuracy and technical feasibility, which currently severely limits the capabilities of these techniques. Moreover elaboration of data recorded requires usage of regularization techniques computationally intensive, which influences the application with heavy temporal constraints (such as BCI). This work focuses on the parallel implementation of a work-flow for EEG and EIT data processing. The resulting software is accelerated using multi-core GPUs, in order to provide solution in reasonable times and address requirements of real-time BCI systems, without over-simplifying the complexity and accuracy of the head models.

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The continuous advancements and enhancements of wireless systems are enabling new compelling scenarios where mobile services can adapt according to the current execution context, represented by the computational resources available at the local device, current physical location, people in physical proximity, and so forth. Such services called context-aware require the timely delivery of all relevant information describing the current context, and that introduces several unsolved complexities, spanning from low-level context data transmission up to context data storage and replication into the mobile system. In addition, to ensure correct and scalable context provisioning, it is crucial to integrate and interoperate with different wireless technologies (WiFi, Bluetooth, etc.) and modes (infrastructure-based and ad-hoc), and to use decentralized solutions to store and replicate context data on mobile devices. These challenges call for novel middleware solutions, here called Context Data Distribution Infrastructures (CDDIs), capable of delivering relevant context data to mobile devices, while hiding all the issues introduced by data distribution in heterogeneous and large-scale mobile settings. This dissertation thoroughly analyzes CDDIs for mobile systems, with the main goal of achieving a holistic approach to the design of such type of middleware solutions. We discuss the main functions needed by context data distribution in large mobile systems, and we claim the precise definition and clean respect of quality-based contracts between context consumers and CDDI to reconfigure main middleware components at runtime. We present the design and the implementation of our proposals, both in simulation-based and in real-world scenarios, along with an extensive evaluation that confirms the technical soundness of proposed CDDI solutions. Finally, we consider three highly heterogeneous scenarios, namely disaster areas, smart campuses, and smart cities, to better remark the wide technical validity of our analysis and solutions under different network deployments and quality constraints.

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Starch is the main form in which plants store carbohydrates reserves, both in terms of amounts and distribution among different plant species. Carbohydrates are direct products of photosynthetic activity, and it is well know that yield efficiency and production are directly correlated to the amount of carbohydrates synthesized and how these are distributed among vegetative and reproductive organs. Nowadays, in pear trees, due to the modernization of orchards, through the introduction of new rootstocks and the development of new training systems, the understanding and the development of new approaches regarding the distribution and storage of carbohydrates, are required. The objective of this research work was to study the behavior of carbohydrate reserves, mainly starch, in different pear tree organs and tissues: i.e., fruits, leaves, woody organs, roots and flower buds, at different physiological stages during the season. Starch in fruit is accumulated at early stages, and reached a maximum concentration during the middle phase of fruit development; after that, its degradation begins with a rise in soluble carbohydrates. Moreover, relationships between fruit starch degradation and different fruit traits, soluble sugars and organic acids were established. In woody organs and roots, an interconversion between starch and soluble carbohydrates was observed during the dormancy period that confirms its main function in supporting the growth and development of new tissues during the following spring. Factors as training systems, rootstocks, types of bearing wood, and their position on the canopy, influenced the concentrations of starch and soluble carbohydrates at different sampling dates. Also, environmental conditions and cultural practices must be considered to better explain these results. Thus, a deeper understanding of the dynamics of carbohydrates reserves within the plant could provide relevant information to improve several management practices to increase crop yield efficiency.

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As continued global funding and coordination are allocated toward the improvement of access to safe sources of drinking water, alternative solutions may be necessary to expand implementation to remote communities. This report evaluates two technologies used in a small water distribution system in a mountainous region of Panama; solar powered pumping and flow-reducing discs. The two parts of the system function independently, but were both chosen for their ability to mitigate unique issues in the community. The design program NeatWork and flow-reducing discs were evaluated because they are tools taught to Peace Corps Volunteers in Panama. Even when ample water is available, mountainous terrains affect the pressure available throughout a water distribution system. Since the static head in the system only varies with the height of water in the tank, frictional losses from pipes and fittings must be exploited to balance out the inequalities caused by the uneven terrain. Reducing the maximum allowable flow to connections through the installation of flow-reducing discs can help to retain enough residual pressure in the main distribution lines to provide reliable service to all connections. NeatWork was calibrated to measured flow rates by changing the orifice coefficient (θ), resulting in a value of 0.68, which is 10-15% higher than typical values for manufactured flow-reducing discs. NeatWork was used to model various system configurations to determine if a single-sized flow-reducing disc could provide equitable flow rates throughout an entire system. There is a strong correlation between the optimum single-sized flow- reducing disc and the average elevation change throughout a water distribution system; the larger the elevation change across the system, the smaller the recommended uniform orifice size. Renewable energy can jump the infrastructure gap and provide basic services at a fraction of the cost and time required to install transmission lines. Methods for the assessment of solar powered pumping systems as a means for rural water supply are presented and assessed. It was determined that manufacturer provided product specifications can be used to appropriately design a solar pumping system, but care must be taken to ensure that sufficient water can be provided to the system despite variations in solar intensity.

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Background and aims Differences in chemical composition of root compounds and root systems among tree species may affect organic matter (OM) distribution, source and composition in forest soils. The objective of this study was to elucidate the contribution of species specific cutin and suberin biomarkers as proxies for shoot- and root-derived organic carbon (OC) to soil OM at different depths with increasing distance to the stems of four different tree species. Methods The contribution of cutin- and suberin-derived lipids to OM in a Cutanic Alisol was analyzed with increasing soil depth and distance to the stems of Fagus sylvatica L., Picea abies (L.) Karst., Quercus robur L. and Pseudotsuga menziesii (Mirb.) Franco. Cutin and suberin monomers of plants and soils were analyzed by alkaline hydrolysis and subsequent gas chromatography–mass spectrometry. Results The amount and distribution of suberin-derived lipids in soil clearly reflected the specific root system of the different tree species. The amount of cutin-derived lipids decreased strongly with soil depth, indicating that the input of leaf/needle material is restricted to the topsoil. In contrast to the suberin-derived lipids, the spatial pattern of cutin monomer contribution to soil OM did not depend on tree species. Conclusions Our results document the importance of tree species as a main factor controlling the composition and distribution of OM in forest soils. They reveal the impact of tree species on root-derived OM distribution and the necessity to distinguish among different zones when studying soil OM storage in forests.

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Statistical methods are developed which assess survival data for two attributes; (1) prolongation of life, (2) quality of life. Health state transition probabilities correspond to prolongation of life and are modeled as a discrete-time semi-Markov process. Imbedded within the sojourn time of a particular health state are the quality of life transitions. They reflect events which differentiate perceptions of pain and suffering over a fixed time period. Quality of life transition probabilities are derived from the assumptions of a simple Markov process. These probabilities depend on the health state currently occupied and the next health state to which a transition is made. Utilizing the two forms of attributes the model has the capability to estimate the distribution of expected quality adjusted life years (in addition to the distribution of expected survival times). The expected quality of life can also be estimated within the health state sojourn time making more flexible the assessment of utility preferences. The methods are demonstrated on a subset of follow-up data from the Beta Blocker Heart Attack Trial (BHAT). This model contains the structure necessary to make inferences when assessing a general survival problem with a two dimensional outcome. ^

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In recent decades, there has been an increasing interest in systems comprised of several autonomous mobile robots, and as a result, there has been a substantial amount of development in the eld of Articial Intelligence, especially in Robotics. There are several studies in the literature by some researchers from the scientic community that focus on the creation of intelligent machines and devices capable to imitate the functions and movements of living beings. Multi-Robot Systems (MRS) can often deal with tasks that are dicult, if not impossible, to be accomplished by a single robot. In the context of MRS, one of the main challenges is the need to control, coordinate and synchronize the operation of multiple robots to perform a specic task. This requires the development of new strategies and methods which allow us to obtain the desired system behavior in a formal and concise way. This PhD thesis aims to study the coordination of multi-robot systems, in particular, addresses the problem of the distribution of heterogeneous multi-tasks. The main interest in these systems is to understand how from simple rules inspired by the division of labor in social insects, a group of robots can perform tasks in an organized and coordinated way. We are mainly interested on truly distributed or decentralized solutions in which the robots themselves, autonomously and in an individual manner, select a particular task so that all tasks are optimally distributed. In general, to perform the multi-tasks distribution among a team of robots, they have to synchronize their actions and exchange information. Under this approach we can speak of multi-tasks selection instead of multi-tasks assignment, which means, that the agents or robots select the tasks instead of being assigned a task by a central controller. The key element in these algorithms is the estimation ix of the stimuli and the adaptive update of the thresholds. This means that each robot performs this estimate locally depending on the load or the number of pending tasks to be performed. In addition, it is very interesting the evaluation of the results in function in each approach, comparing the results obtained by the introducing noise in the number of pending loads, with the purpose of simulate the robot's error in estimating the real number of pending tasks. The main contribution of this thesis can be found in the approach based on self-organization and division of labor in social insects. An experimental scenario for the coordination problem among multiple robots, the robustness of the approaches and the generation of dynamic tasks have been presented and discussed. The particular issues studied are: Threshold models: It presents the experiments conducted to test the response threshold model with the objective to analyze the system performance index, for the problem of the distribution of heterogeneous multitasks in multi-robot systems; also has been introduced additive noise in the number of pending loads and has been generated dynamic tasks over time. Learning automata methods: It describes the experiments to test the learning automata-based probabilistic algorithms. The approach was tested to evaluate the system performance index with additive noise and with dynamic tasks generation for the same problem of the distribution of heterogeneous multi-tasks in multi-robot systems. Ant colony optimization: The goal of the experiments presented is to test the ant colony optimization-based deterministic algorithms, to achieve the distribution of heterogeneous multi-tasks in multi-robot systems. In the experiments performed, the system performance index is evaluated by introducing additive noise and dynamic tasks generation over time.

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This paper focuses on the general problem of coordinating of multi-robot systems, more specifically, it addresses the self-election of heterogeneous and specialized tasks by autonomous robots. In this regard, it has proposed experimenting with two different techniques based chiefly on selforganization and emergence biologically inspired, by applying response threshold models as well as ant colony optimization. Under this approach it can speak of multi-tasks selection instead of multi-tasks allocation, that means, as the agents or robots select the tasks instead of being assigned a task by a central controller. The key element in these algorithms is the estimation of the stimuli and the adaptive update of the thresholds. This means that each robot performs this estimate locally depending on the load or the number of pending tasks to be performed. It has evaluated the robustness of the algorithms, perturbing the number of pending loads to simulate the robot’s error in estimating the real number of pending tasks and also the dynamic generation of loads through time. The paper ends with a critical discussion of experimental results.

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This paper focuses on the general problem of coordinating multiple robots. More specifically, it addresses the self-selection of heterogeneous specialized tasks by autonomous robots. In this paper we focus on a specifically distributed or decentralized approach as we are particularly interested in a decentralized solution where the robots themselves autonomously and in an individual manner, are responsible for selecting a particular task so that all the existing tasks are optimally distributed and executed. In this regard, we have established an experimental scenario to solve the corresponding multi-task distribution problem and we propose a solution using two different approaches by applying Response Threshold Models as well as Learning Automata-based probabilistic algorithms. We have evaluated the robustness of the algorithms, perturbing the number of pending loads to simulate the robot’s error in estimating the real number of pending tasks and also the dynamic generation of loads through time. The paper ends with a critical discussion of experimental results.

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Isolated electrical systems lack electrical interconnection to other networks and are usually placed in geographically isolated areas—mainly islands or locations in developing countries. Until recently, only diesel generators were able to assure a safe and reliable supply in exchange for very high costs for fuel transportation and system operation. Transmission system operators (TSOs) are increasingly seeking to replace traditional energy models based on large groups of conventional generation units with mixed solutions where diesel groups are held as backup generation and important advantages are provided by renewable energy sources. The grid codes determine the technical requirements to be fulfilled by the generators connected in any electrical network, but regulations applied to isolated grids are more demanding. In technical literature it is rather easy to find and compare grid codes for interconnected electrical systems. However, the existing literature is incomplete and sparse regarding isolated grids. This paper aims to review the current state of isolated systems and grid codes applicable to them, specifying points of comparison and defining the guidelines to be followed by the upcoming regulations.

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The search for new energy models arises as a necessity to have a sustainable power supply. The inclusion of distributed generation sources (DG) allows to reduce the cost of facilities, increase the security of the grid or alleviate problems of congestion through the redistribution of power flows. In remote microgrids it is needed in a particular way a safe and reliable supply, which can cover the demand for a low cost; due to this, distributed generation is an alternative that is being widely introduced in these grids. But the remote microgrids are especially weak grids because of their small size, low voltage level, reduced network mesh and distribution lines with a high ratio R/X. This ratio affects the coupling between grid voltages and phase shifts, and stability becomes an issue of greater importance than in interconnected systems. To ensure the appropriate behavior of generation sources inserted in remote microgrids -and, in general, any electrical equipment-, it is essential to have devices for testing and certification. These devices must, not only faithfully reproduce disturbances occurring in remote microgrids, but also to behave against the equipment under test (EUT) as a real weak grid. This also makes the device commercially competitive. To meet these objectives and based on the aforementioned, it has been designed, built and tested a voltage disturbances generator, in order to provide a simple, versatile, full and easily scalable device to manufacturers and laboratories in the sector.

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Conductive nanoparticles, especially elongated ones such as carbon nanotubes, dramatically modify the electrical behavior of liquid crystal cells. These nanoparticles are known to reorient with liquid crystals in electric fields, causing significant variations of conductivity at minute concentrations of tens or hundreds ppm. The above notwithstanding, impedance spectroscopy of doped cells in the frequency range customarily employed by liquid crystal devices, 100 Hz?10 kHz, shows a relatively simple resistor/capacitor response where the components of the cell can be univocally assigned to single components of the electrical equivalent circuit. However, widening the frequency range up to 1 MHz or beyond reveals a complex behavior that cannot be explained with the same simple EEC. Moreover, the system impedance varies with the application of electric fields, their effect remaining after removing the field. Carbon nanotubes are reoriented together with liquid crystal reorientation when applying voltage, but barely reoriented back upon liquid crystal relaxation once the voltage is removed. Results demonstrate a remarkable variation in the impedance of the dielectric blend formed by liquid crystal and carbon nanotubes, the irreversible orientation of the carbon nanotubes and possible permanent contacts between electrodes.

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Earthquake zones in the upper crust are usually more conductive than the surrounding rocks, and electrical geophysical measurements can be used to map these zones. Magnetotelluric (MT) measurements across fault zones that are parallel to the coast and not too far away can also give some important information about the lower crustal zone. This is because the long-period electric currents coming from the ocean gradually leak into the mantle, but the lower crust is usually very resistive and very little leakage takes place. If a lower crustal zone is less resistive it will be a leakage zone, and this can be seen because the MT phase will change as the ocean currents leave the upper crust. The San Andreas Fault is parallel to the ocean boundary and close enough to have a lot of extra ocean currents crossing the zone. The Loma Prieta zone, after the earthquake, showed a lot of ocean electric current leakage, suggesting that the lower crust under the fault zone was much more conductive than normal. It is hard to believe that water, which is responsible for the conductivity, had time to get into the lower crustal zone, so it was probably always there, but not well connected. If this is true, then the poorly connected water would be at a pressure close to the rock pressure, and it may play a role in modifying the fluid pressure in the upper crust fault zone. We also have telluric measurements across the San Andreas Fault near Palmdale from 1979 to 1990, and beginning in 1985 we saw changes in the telluric signals on the fault zone and east of the fault zone compared with the signals west of the fault zone. These measurements were probably seeing a better connection of the lower crust fluids taking place, and this may result in a fluid flow from the lower crust to the upper crust. This could be a factor in changing the strength of the upper crust fault zone.