930 resultados para Spatial Query Processing And Optimization


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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

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In the context of focal epilepsy, the simultaneous combination of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) holds a great promise as a technique by which the hemodynamic correlates of interictal spikes detected on scalp EEG can be identified. The fact that traditional EEG recordings have not been able to overcome the difficulty in correlating the ictal clinical symptoms to the onset in particular areas of the lobes, brings the need of mapping with more precision the epileptogenic cortical regions. On the other hand, fMRI suggested localizations more consistent with the ictal clinical manifestations detected. This study was developed in order to improve the knowledge about the way parameters involved in the physical and mathematical data, produced by the EEG/fMRI technique processing, would influence the final results. The evaluation of the accuracy was made by comparing the BOLD results with: the high resolution EEG maps; the malformative lesions detected in the T1 weighted MR images; and the anatomical localizations of the diagnosed symptomatology of each studied patient. The optimization of the set of parameters used, will provide an important contribution to the diagnosis of epileptogenic focuses, in patients included on an epilepsy surgery evaluation program. The results obtained allowed us to conclude that: by associating the BOLD effect with interictal spikes, the epileptogenic areas are mapped to localizations different from those obtained by the EEG maps representing the electrical potential distribution across the scalp (EEG); there is an important and solid bond between the variation of particular parameters (manipulated during the fMRI data processing) and the optimization of the final results, from which smoothing, deleted volumes, HRF (used to convolve with the activation design), and the shape of the Gamma function can be certainly emphasized.

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Time is embedded in any sensory experience: the movements of a dance, the rhythm of a piece of music, the words of a speaker are all examples of temporally structured sensory events. In humans, if and how visual cortices perform temporal processing remains unclear. Here we show that both primary visual cortex (V1) and extrastriate area V5/MT are causally involved in encoding and keeping time in memory and that this involvement is independent from low-level visual processing. Most importantly we demonstrate that V1 and V5/MT are functionally linked and temporally synchronized during time encoding whereas they are functionally independent and operate serially (V1 followed by V5/MT) while maintaining temporal information in working memory. These data challenge the traditional view of V1 and V5/MT as visuo-spatial features detectors and highlight the functional contribution and the temporal dynamics of these brain regions in the processing of time in millisecond range. The present project resulted in the paper entitled: 'How the visual brain encodes and keeps track of time' by Paolo Salvioni, Lysiann Kalmbach, Micah Murray and Domenica Bueti that is now submitted for publication to the Journal of Neuroscience.

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Orienting attention in space recruits fronto-parietal networks whose damage results in unilateral spatial neglect. However, attention orienting may also be governed by emotional and motivational factors; but it remains unknown whether these factors act through a modulation of the fronto-parietal attentional systems or distinct neural pathways. Here we asked whether attentional orienting is affected by learning about the reward value of targets in a visual search task, in a spatially specific manner, and whether these effects are preserved in right-brain damaged patients with left spatial neglect. We found that associating rewards with left-sided (but not right-sided) targets during search led to progressive exploration biases towards left space, in both healthy people and neglect patients. Such spatially specific biases occurred even without any conscious awareness of the asymmetric reward contingencies. These results show that reward-induced modulations of space representation are preserved despite a dysfunction of fronto-parietal networks associated with neglect, and therefore suggest that they may arise through spared subcortical networks directly acting on sensory processing and/or oculomotor circuits. These effects could be usefully exploited for potentiating rehabilitation strategies in neglect patients.

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The general goal of the present work was to study whether spatial perceptual asymmetry initially observed in linguistic dichotic listening studies is related to the linguistic nature of the stimuli and/or is modality-specific, as well as to investigate whether the spatial perceptual/attentional asymmetry changes as a function of age and sensory deficit via praxis. Several dichotic listening studies with linguistic stimuli have shown that the inherent perceptual right ear advantage (REA), which presumably results from the left lateralized linguistic functions (bottom-up processes), can be modified with executive functions (top-down control). Executive functions mature slowly during childhood, are well developed in adulthood, and decline as a function of ageing. In Study I, the purpose was to investigate with a cross-sectional experiment from a lifespan perspective the age-related changes in top-down control of REA for linguistic stimuli in dichotic listening with a forced-attention paradigm (DL). In Study II, the aim was to determine whether the REA is linguistic-stimulus-specific or not, and whether the lifespan changes in perceptual asymmetry observed in dichotic listening would exist also in auditory spatial attention tasks that put load on attentional control. In Study III, using visual spatial attention tasks, mimicking the auditory tasks applied in Study II, it was investigated whether or not the stimulus-non-specific rightward spatial bias found in auditory modality is a multimodal phenomenon. Finally, as it has been suggested that the absence of visual input in blind participants leads to improved auditory spatial perceptual and cognitive skills, the aim in Study IV was to determine, whether blindness modifies the ear advantage in DL. Altogether 180-190 right-handed participants between 5 and 79 years of age were studied in Studies I to III, and in Study IV the performance of 14 blind individuals was compared with that of 129 normally sighted individuals. The results showed that only rightward spatial bias was observed in tasks with intensive attentional load, independent of the type of stimuli (linguistic vs. non-linguistic) or the modality (auditory vs. visual). This multimodal rightward spatial bias probably results from a complex interaction of asymmetrical perceptual, attentional, and/or motor mechanisms. Most importantly, the strength of the rightward spatial bias changed as a function of age and augmented praxis due to sensory deficit. The efficiency of the performance in spatial attention tasks and the ability to overcome the rightward spatial bias increased during childhood, was at its best in young adulthood, and decreased as a function of ageing. Between the ages of 5 and 11 years probably at first develops movement and impulse control, followed by the gradual development of abilities to inhibit distractions and disengage attention. The errors especially in bilateral stimulus conditions suggest that a mild phenomenon resembling extinction can be observed throughout the lifespan, but especially the ability to distribute attention to multiple targets simultaneously decreases in the course of ageing. Blindness enhances the processing of auditory bilateral linguistic stimuli, the ability to overcome a stimulus-driven laterality effect related to speech sound perception, and the ability to direct attention to an appropriate spatial location. It was concluded that the ability to voluntarily suppress and inhibit the multimodal rightward spatial bias changes as a function of age and praxis due to sensory deficit and probably reflects the developmental level of executive functions.

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The iron and steelmaking industry is among the major contributors to the anthropogenic emissions of carbon dioxide in the world. The rising levels of CO2 in the atmosphere and the global concern about the greenhouse effect and climate change have brought about considerable investigations on how to reduce the energy intensity and CO2 emissions of this industrial sector. In this thesis the problem is tackled by mathematical modeling and optimization using three different approaches. The possibility to use biomass in the integrated steel plant, particularly as an auxiliary reductant in the blast furnace, is investigated. By pre-processing the biomass its heating value and carbon content can be increased at the same time as the oxygen content is decreased. As the compression strength of the preprocessed biomass is lower than that of coke, it is not suitable for replacing a major part of the coke in the blast furnace burden. Therefore the biomass is assumed to be injected at the tuyere level of the blast furnace. Carbon capture and storage is, nowadays, mostly associated with power plants but it can also be used to reduce the CO2 emissions of an integrated steel plant. In the case of a blast furnace, the effect of CCS can be further increased by recycling the carbon dioxide stripped top gas back into the process. However, this affects the economy of the integrated steel plant, as the amount of top gases available, e.g., for power and heat production is decreased. High quality raw materials are a prerequisite for smooth blast furnace operation. High quality coal is especially needed to produce coke with sufficient properties to ensure proper gas permeability and smooth burden descent. Lower quality coals as well as natural gas, which some countries have in great volumes, can be utilized with various direct and smelting reduction processes. The DRI produced with a direct reduction process can be utilized as a feed material for blast furnace, basic oxygen furnace or electric arc furnace. The liquid hot metal from a smelting reduction process can in turn be used in basic oxygen furnace or electric arc furnace. The unit sizes and investment costs of an alternative ironmaking process are also lower than those of a blast furnace. In this study, the economy of an integrated steel plant is investigated by simulation and optimization. The studied system consists of linearly described unit processes from coke plant to steel making units, with a more detailed thermodynamical model of the blast furnace. The results from the blast furnace operation with biomass injection revealed the importance of proper pre-processing of the raw biomass as the composition of the biomass as well as the heating value and the yield are all affected by the pyrolysis temperature. As for recycling of CO2 stripped blast furnace top gas, substantial reductions in the emission rates are achieved if the stripped CO2 can be stored. However, the optimal recycling degree together with other operation conditions is heavily dependent on the cost structure of CO2 emissions and stripping/storage. The economical feasibility related to the use of DRI in the blast furnace depends on the price ratio between the DRI pellets and the BF pellets. The high amount of energy needed in the rotary hearth furnace to reduce the iron ore leads to increased CO2 emissions.

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Spatial data representation and compression has become a focus issue in computer graphics and image processing applications. Quadtrees, as one of hierarchical data structures, basing on the principle of recursive decomposition of space, always offer a compact and efficient representation of an image. For a given image, the choice of quadtree root node plays an important role in its quadtree representation and final data compression. The goal of this thesis is to present a heuristic algorithm for finding a root node of a region quadtree, which is able to reduce the number of leaf nodes when compared with the standard quadtree decomposition. The empirical results indicate that, this proposed algorithm has quadtree representation and data compression improvement when in comparison with the traditional method.

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The increasing number of space debris in operating regions around the earth constitutes a real threat to space missions. The goal of the research is to establish appropriate scientific-technological conditions to prevent the destruction and/or impracticability of spacecraft in imminent collision in these regions. A definitive solution to this problem has not yet been reached with the degree of precision that the dynamics of spatial objects (vehicle and debris) requires mainly due to the fact that collisions occur in chains and fragmentation of these objects in the space environment. This fact threatens the space missions on time and with no prospects for a solution in the near future. We present an optimization process in finding the initial conditions (CIC) to collisions, considering the symmetry of the distributions of maximum relative positions between spatial objects with respect to the spherical angles. For this, we used the equations of the dynamics on the Clohessy-Witshire, representing a limit of validation that is highly computationally costly. We simulate different maximum relative positions values of the corresponding initial conditions given in terms of spherical angles. Our results showed that there are symmetries that significantly reduce operating costs, such that the search of the CIC is advantageously carried out up to 4 times the initial processing routine. Knowledge of CIC allows the propulsion system operating vehicle implement evasive maneuvers before impending collisions with space debris.

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Current commercial and academic OLAP tools do not process XML data that contains XLink. Aiming at overcoming this issue, this paper proposes an analytical system composed by LMDQL, an analytical query language. Also, the XLDM metamodel is given to model cubes of XML documents with XLink and to deal with syntactic, semantic and structural heterogeneities commonly found in XML documents. As current W3C query languages for navigating in XML documents do not support XLink, XLPath is discussed in this article to provide features for the LMDQL query processing. A prototype system enabling the analytical processing of XML documents that use XLink is also detailed. This prototype includes a driver, named sql2xquery, which performs the mapping of SQL queries into XQuery. To validate the proposed system, a case study and its performance evaluation are presented to analyze the impact of analytical processing over XML/XLink documents.

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The presented study carried out an analysis on rural landscape changes. In particular the study focuses on the understanding of driving forces acting on the rural built environment using a statistical spatial model implemented through GIS techniques. It is well known that the study of landscape changes is essential for a conscious decision making in land planning. From a bibliography review results a general lack of studies dealing with the modeling of rural built environment and hence a theoretical modelling approach for such purpose is needed. The advancement in technology and modernity in building construction and agriculture have gradually changed the rural built environment. In addition, the phenomenon of urbanization of a determined the construction of new volumes that occurred beside abandoned or derelict rural buildings. Consequently there are two types of transformation dynamics affecting mainly the rural built environment that can be observed: the conversion of rural buildings and the increasing of building numbers. It is the specific aim of the presented study to propose a methodology for the development of a spatial model that allows the identification of driving forces that acted on the behaviours of the building allocation. In fact one of the most concerning dynamic nowadays is related to an irrational expansion of buildings sprawl across landscape. The proposed methodology is composed by some conceptual steps that cover different aspects related to the development of a spatial model: the selection of a response variable that better describe the phenomenon under study, the identification of possible driving forces, the sampling methodology concerning the collection of data, the most suitable algorithm to be adopted in relation to statistical theory and method used, the calibration process and evaluation of the model. A different combination of factors in various parts of the territory generated favourable or less favourable conditions for the building allocation and the existence of buildings represents the evidence of such optimum. Conversely the absence of buildings expresses a combination of agents which is not suitable for building allocation. Presence or absence of buildings can be adopted as indicators of such driving conditions, since they represent the expression of the action of driving forces in the land suitability sorting process. The existence of correlation between site selection and hypothetical driving forces, evaluated by means of modeling techniques, provides an evidence of which driving forces are involved in the allocation dynamic and an insight on their level of influence into the process. GIS software by means of spatial analysis tools allows to associate the concept of presence and absence with point futures generating a point process. Presence or absence of buildings at some site locations represent the expression of these driving factors interaction. In case of presences, points represent locations of real existing buildings, conversely absences represent locations were buildings are not existent and so they are generated by a stochastic mechanism. Possible driving forces are selected and the existence of a causal relationship with building allocations is assessed through a spatial model. The adoption of empirical statistical models provides a mechanism for the explanatory variable analysis and for the identification of key driving variables behind the site selection process for new building allocation. The model developed by following the methodology is applied to a case study to test the validity of the methodology. In particular the study area for the testing of the methodology is represented by the New District of Imola characterized by a prevailing agricultural production vocation and were transformation dynamic intensively occurred. The development of the model involved the identification of predictive variables (related to geomorphologic, socio-economic, structural and infrastructural systems of landscape) capable of representing the driving forces responsible for landscape changes.. The calibration of the model is carried out referring to spatial data regarding the periurban and rural area of the study area within the 1975-2005 time period by means of Generalised linear model. The resulting output from the model fit is continuous grid surface where cells assume values ranged from 0 to 1 of probability of building occurrences along the rural and periurban area of the study area. Hence the response variable assesses the changes in the rural built environment occurred in such time interval and is correlated to the selected explanatory variables by means of a generalized linear model using logistic regression. Comparing the probability map obtained from the model to the actual rural building distribution in 2005, the interpretation capability of the model can be evaluated. The proposed model can be also applied to the interpretation of trends which occurred in other study areas, and also referring to different time intervals, depending on the availability of data. The use of suitable data in terms of time, information, and spatial resolution and the costs related to data acquisition, pre-processing, and survey are among the most critical aspects of model implementation. Future in-depth studies can focus on using the proposed model to predict short/medium-range future scenarios for the rural built environment distribution in the study area. In order to predict future scenarios it is necessary to assume that the driving forces do not change and that their levels of influence within the model are not far from those assessed for the time interval used for the calibration.

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A range of societal issues have been caused by fossil fuel consumption in the transportation sector in the United States (U.S.), including health related air pollution, climate change, the dependence on imported oil, and other oil related national security concerns. Biofuels production from various lignocellulosic biomass types such as wood, forest residues, and agriculture residues have the potential to replace a substantial portion of the total fossil fuel consumption. This research focuses on locating biofuel facilities and designing the biofuel supply chain to minimize the overall cost. For this purpose an integrated methodology was proposed by combining the GIS technology with simulation and optimization modeling methods. The GIS based methodology was used as a precursor for selecting biofuel facility locations by employing a series of decision factors. The resulted candidate sites for biofuel production served as inputs for simulation and optimization modeling. As a precursor to simulation or optimization modeling, the GIS-based methodology was used to preselect potential biofuel facility locations for biofuel production from forest biomass. Candidate locations were selected based on a set of evaluation criteria, including: county boundaries, a railroad transportation network, a state/federal road transportation network, water body (rivers, lakes, etc.) dispersion, city and village dispersion, a population census, biomass production, and no co-location with co-fired power plants. The simulation and optimization models were built around key supply activities including biomass harvesting/forwarding, transportation and storage. The built onsite storage served for spring breakup period where road restrictions were in place and truck transportation on certain roads was limited. Both models were evaluated using multiple performance indicators, including cost (consisting of the delivered feedstock cost, and inventory holding cost), energy consumption, and GHG emissions. The impact of energy consumption and GHG emissions were expressed in monetary terms to keep consistent with cost. Compared with the optimization model, the simulation model represents a more dynamic look at a 20-year operation by considering the impacts associated with building inventory at the biorefinery to address the limited availability of biomass feedstock during the spring breakup period. The number of trucks required per day was estimated and the inventory level all year around was tracked. Through the exchange of information across different procedures (harvesting, transportation, and biomass feedstock processing procedures), a smooth flow of biomass from harvesting areas to a biofuel facility was implemented. The optimization model was developed to address issues related to locating multiple biofuel facilities simultaneously. The size of the potential biofuel facility is set up with an upper bound of 50 MGY and a lower bound of 30 MGY. The optimization model is a static, Mathematical Programming Language (MPL)-based application which allows for sensitivity analysis by changing inputs to evaluate different scenarios. It was found that annual biofuel demand and biomass availability impacts the optimal results of biofuel facility locations and sizes.

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In coffee processing the fermentation stage is considered one of the critical operations by its impact on the final quality of the product. However, the level of control of the fermentation process on each farm is often not adequate; the use of sensorics for controlling coffee fermentation is not common. The objective of this work is to characterize the fermentation temperature in a fermentation tank by applying spatial interpolation and a new methodology of data analysis based on phase space diagrams of temperature data, collected by means of multi-distributed, low cost and autonomous wireless sensors. A real coffee fermentation was supervised in the Cauca region (Colombia) with a network of 24 semi-passive TurboTag RFID temperature loggers with vacuum plastic cover, submerged directly in the fermenting mass. Temporal evolution and spatial distribution of temperature is described in terms of the phase diagram areas which characterizes the cyclic behaviour of temperature and highlights the significant heterogeneity of thermal conditions at different locations in the tank where the average temperature of the fermentation was 21.2 °C, although there were temperature ranges of 4.6°C, and average spatial standard deviation of ±1.21ºC. In the upper part of the tank we found high heterogeneity of temperatures, the higher temperatures and therefore the higher fermentation rates. While at the bottom, it has been computed an area in the phase diagram practically half of the area occupied by the sensors of the upper tank, therefore this location showed higher temperature homogeneity