921 resultados para Data Storage Solutions


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The promise of Wireless Sensor Networks (WSNs) is the autonomous collaboration of a collection of sensors to accomplish some specific goals which a single sensor cannot offer. Basically, sensor networking serves a range of applications by providing the raw data as fundamentals for further analyses and actions. The imprecision of the collected data could tremendously mislead the decision-making process of sensor-based applications, resulting in an ineffectiveness or failure of the application objectives. Due to inherent WSN characteristics normally spoiling the raw sensor readings, many research efforts attempt to improve the accuracy of the corrupted or "dirty" sensor data. The dirty data need to be cleaned or corrected. However, the developed data cleaning solutions restrict themselves to the scope of static WSNs where deployed sensors would rarely move during the operation. Nowadays, many emerging applications relying on WSNs need the sensor mobility to enhance the application efficiency and usage flexibility. The location of deployed sensors needs to be dynamic. Also, each sensor would independently function and contribute its resources. Sensors equipped with vehicles for monitoring the traffic condition could be depicted as one of the prospective examples. The sensor mobility causes a transient in network topology and correlation among sensor streams. Based on static relationships among sensors, the existing methods for cleaning sensor data in static WSNs are invalid in such mobile scenarios. Therefore, a solution of data cleaning that considers the sensor movements is actively needed. This dissertation aims to improve the quality of sensor data by considering the consequences of various trajectory relationships of autonomous mobile sensors in the system. First of all, we address the dynamic network topology due to sensor mobility. The concept of virtual sensor is presented and used for spatio-temporal selection of neighboring sensors to help in cleaning sensor data streams. This method is one of the first methods to clean data in mobile sensor environments. We also study the mobility pattern of moving sensors relative to boundaries of sub-areas of interest. We developed a belief-based analysis to determine the reliable sets of neighboring sensors to improve the cleaning performance, especially when node density is relatively low. Finally, we design a novel sketch-based technique to clean data from internal sensors where spatio-temporal relationships among sensors cannot lead to the data correlations among sensor streams.

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The increasing amount of available semistructured data demands efficient mechanisms to store, process, and search an enormous corpus of data to encourage its global adoption. Current techniques to store semistructured documents either map them to relational databases, or use a combination of flat files and indexes. These two approaches result in a mismatch between the tree-structure of semistructured data and the access characteristics of the underlying storage devices. Furthermore, the inefficiency of XML parsing methods has slowed down the large-scale adoption of XML into actual system implementations. The recent development of lazy parsing techniques is a major step towards improving this situation, but lazy parsers still have significant drawbacks that undermine the massive adoption of XML. Once the processing (storage and parsing) issues for semistructured data have been addressed, another key challenge to leverage semistructured data is to perform effective information discovery on such data. Previous works have addressed this problem in a generic (i.e. domain independent) way, but this process can be improved if knowledge about the specific domain is taken into consideration. This dissertation had two general goals: The first goal was to devise novel techniques to efficiently store and process semistructured documents. This goal had two specific aims: We proposed a method for storing semistructured documents that maps the physical characteristics of the documents to the geometrical layout of hard drives. We developed a Double-Lazy Parser for semistructured documents which introduces lazy behavior in both the pre-parsing and progressive parsing phases of the standard Document Object Model's parsing mechanism. The second goal was to construct a user-friendly and efficient engine for performing Information Discovery over domain-specific semistructured documents. This goal also had two aims: We presented a framework that exploits the domain-specific knowledge to improve the quality of the information discovery process by incorporating domain ontologies. We also proposed meaningful evaluation metrics to compare the results of search systems over semistructured documents.

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In order to become better prepared to support Research Data Management (RDM) practices in sciences and engineering, Queen’s University Library, together with the University Research Services, conducted a research study of all ranks of faculty members, as well as postdoctoral fellows and graduate students at the Faculty of Engineering & Applied Science, Departments of Chemistry, Computer Science, Geological Sciences and Geological Engineering, Mathematics and Statistics, Physics, Engineering Physics & Astronomy, School of Environmental Studies, and Geography & Planning in the Faculty of Arts and Science.

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Development of Internet-of-Services will be hampered by heterogeneous Internet-of-Things infrastructures, such as inconsistency in communicating with participating objects, connectivity between them, topology definition & data transfer, access via cloud computing for data storage etc. Our proposed solutions are applicable to a random topology scenario that allow establishing of multi-operational sensor networks out of single networks and/or single service networks with the participation of multiple networks; thus allowing virtual links to be created and resources to be shared. The designed layers are context-aware, application-oriented, and capable of representing physical objects to a management system, along with discovery of services. The reliability issue is addressed by deploying IETF supported IEEE 802.15.4 network model for low-rate wireless personal networks. Flow- sensor succeeded better results in comparison to the typical - sensor from reachability, throughput, energy consumption and diversity gain viewpoint and through allowing the multicast groups into maximum number, performances can be improved.

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Thesis (Ph.D.)--University of Washington, 2016-08

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Scientific research is increasingly data-intensive, relying more and more upon advanced computational resources to be able to answer the questions most pressing to our society at large. This report presents findings from a brief descriptive survey sent to a sample of 342 leading researchers at the University of Washington (UW), Seattle, Washington in 2010 and 2011 as the first stage of the larger National Science Foundation project “Interacting with Cyberinfrastructure in the Face of Changing Science.” This survey assesses these researcher’s use of advanced computational resources, data, and software in their research. We present high-level findings that describe UW researchers’: demographics, interdisciplinarity, research groups, data use, software and computational use—including software development and use, data storage and transfer activities, and collaboration tools, and computing resources. These findings offer insights into the state of computational resources in use during this time period as well as offering a look at the data intensiveness of UW researchers.

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Early definitions of Smart Building focused almost entirely on the technology aspect and did not suggest user interaction at all. Indeed, today we would attribute it more to the concept of the automated building. In this sense, control of comfort conditions inside buildings is a problem that is being well investigated, since it has a direct effect on users’ productivity and an indirect effect on energy saving. Therefore, from the users’ perspective, a typical environment can be considered comfortable, if it’s capable of providing adequate thermal comfort, visual comfort and indoor air quality conditions and acoustic comfort. In the last years, the scientific community has dealt with many challenges, especially from a technological point of view. For instance, smart sensing devices, the internet, and communication technologies have enabled a new paradigm called Edge computing that brings computation and data storage closer to the location where it is needed, to improve response times and save bandwidth. This has allowed us to improve services, sustainability and decision making. Many solutions have been implemented such as smart classrooms, controlling the thermal condition of the building, monitoring HVAC data for energy-efficient of the campus and so forth. Though these projects provide to the realization of smart campus, a framework for smart campus is yet to be determined. These new technologies have also introduced new research challenges: within this thesis work, some of the principal open challenges will be faced, proposing a new conceptual framework, technologies and tools to move forward the actual implementation of smart campuses. Keeping in mind, several problems known in the literature have been investigated: the occupancy detection, noise monitoring for acoustic comfort, context awareness inside the building, wayfinding indoor, strategic deployment for air quality and books preserving.

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Today, the contribution of the transportation sector on greenhouse gases is evident. The fast consumption of fossil fuels and its impact on the environment has given a strong impetus to the development of vehicles with better fuel economy. Hybrid electric vehicles fit into this context with different targets, starting from the reduction of emissions and fuel consumption, but also for performance and comfort enhancement. Vehicles exist with various missions; super sport cars usually aim to reach peak performance and to guarantee a great driving experience to the driver, but great attention must also be paid to fuel consumption. According to the vehicle mission, hybrid vehicles can differ in the powertrain configuration and the choice of the energy storage system. Lamborghini has recently invested in the development of hybrid super sport cars, due to performance and comfort reasons, with the possibility to reduce fuel consumption. This research activity has been conducted as a joint collaboration between the University of Bologna and the sportscar manufacturer, to analyze the impact of innovative energy storage solutions on the hybrid vehicle performance. Capacitors have been studied and modeled to analyze the pros and cons of such solution with respect to batteries. To this aim, a full simulation environment has been developed and validated to provide a concept design tool capable of precise results and able to foresee the longitudinal performance on regulated emission cycles and real driving conditions, with a focus on fuel consumption. In addition, the target of the research activity is to deepen the study of hybrid electric super sports cars in the concept development phase, focusing on defining the control strategies and the energy storage system’s technology that best suits the needs of the vehicles. This dissertation covers the key steps that have been carried out in the research project.

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Carotenoids are biosynthetic organic pigments that constitute an important class of one-dimensional pi-conjugated organic molecules with enormous potential for application in biophotonic devices. In this context, we studied the degenerate two-photon absorption (2PA) cross-section spectra of two carotenoid compounds (beta-carotene and beta-apo-8'-carotenal) employing the conventional and white-light-continuum Z-scan techniques and quantum chemistry calculations. Because carotenoids coexist at room temperature as a mixture of isomers, the 2PA spectra reported here are due to samples containing a distribution of isomers, presenting distinct conjugation length and conformation. We show that these compounds present a defined structure on the 2PA spectra, that peaks at 650 nm with an absorption cross-section of approximately 5000 GM, for both compounds. In addition, we observed a 2PA band at 990 nm for beta-apo-8'-carotenal, which was attributed to a overlapping of I(I)B(u) +-like and 2(I)Ag(-)-like states, which are strongly one- and two-photon allowed, respectively. Spectroscopic parameters of the electronic transitions to singlet-excited states, which are directly related to photophysical properties of these compounds, were obtained by fitting the 2PA spectra using the sum-over-states approach. The analysis and interpretations of the 2PA spectra of the investigated carotenoids were supported by theoretical predictions of one- and two-photon transitions carried out using the response functions formalism within the density functional theory framework, using the long-range corrected CAM-B3LYP functional. (C) 2011 American Institute of Physics. [doi:10.1063/1.3590157]

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The fast and reversible phase transition mechanism between crystalline and amorphous phases of Ge(2)Sb(2)Te(5) has been in debate for several years. Through employing first-principles density functional theory calculations, we identify a direct structural link between the metastable crystalline and amorphous phases. The phase transition is driven by the displacement of Ge atoms along the rocksalt [111] direction from stable octahedron to high energy unstable tetrahedron sites close to the intrinsic vacancy regions, which generates a high energy intermediate phase between metastable and amorphous phases. Due to the instability of Ge at the tetrahedron sites, the Ge atoms naturally shift away from those sites, giving rise to the formation of local-ordered fourfold motifs and the long-range structural disorder. Intrinsic vacancies, which originate from Sb(2)Te(3), lower the energy barrier for Ge displacements, and hence, their distribution plays an important role in the phase transition. The high energy intermediate configuration can be obtained experimentally by applying an intense laser beam, which overcomes the thermodynamic barrier from the octahedron to tetrahedron sites. The high figure of merit of Ge(2)Sb(2)Te(5) is achieved from the optimal combination of intrinsic vacancies provided by Sb(2)Te(3) and the instability of the tetrahedron sites provided by GeTe.

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UQ eSpace (http://espace.uq.edu.au/) is The University of Queensland's institutional digital repository. The poster outlines all the different ways academic staff and postgraduate students can make use of the repository.

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One of the challenges in scientific visualization is to generate software libraries suitable for the large-scale data emerging from tera-scale simulations and instruments. We describe the efforts currently under way at SDSC and NPACI to address these challenges. The scope of the SDSC project spans data handling, graphics, visualization, and scientific application domains. Components of the research focus on the following areas: intelligent data storage, layout and handling, using an associated “Floor-Plan” (meta data); performance optimization on parallel architectures; extension of SDSC’s scalable, parallel, direct volume renderer to allow perspective viewing; and interactive rendering of fractional images (“imagelets”), which facilitates the examination of large datasets. These concepts are coordinated within a data-visualization pipeline, which operates on component data blocks sized to fit within the available computing resources. A key feature of the scheme is that the meta data, which tag the data blocks, can be propagated and applied consistently. This is possible at the disk level, in distributing the computations across parallel processors; in “imagelet” composition; and in feature tagging. The work reflects the emerging challenges and opportunities presented by the ongoing progress in high-performance computing (HPC) and the deployment of the data, computational, and visualization Grids.

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Signal subspace identification is a crucial first step in many hyperspectral processing algorithms such as target detection, change detection, classification, and unmixing. The identification of this subspace enables a correct dimensionality reduction, yielding gains in algorithm performance and complexity and in data storage. This paper introduces a new minimum mean square error-based approach to infer the signal subspace in hyperspectral imagery. The method, which is termed hyperspectral signal identification by minimum error, is eigen decomposition based, unsupervised, and fully automatic (i.e., it does not depend on any tuning parameters). It first estimates the signal and noise correlation matrices and then selects the subset of eigenvalues that best represents the signal subspace in the least squared error sense. State-of-the-art performance of the proposed method is illustrated by using simulated and real hyperspectral images.

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Este trabalho foi realizado sob orientação do Prof. António Brandão Moniz para a disciplina “Factores Sociais da Inovação” do Mestrado Engenharia Informática realizado na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa (Portugal)

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Portugal joined the effort to create the EPOS infrastructure in 2008, and it became immediately apparent that a national network of Earth Sciences infrastructures was required to participate in the initiative. At that time, FCT was promoting the creation of a national infrastructure called RNG - Rede Nacional de Geofísica (National Geophysics Network). A memorandum of understanding had been agreed upon, and it seemed therefore straightforward to use RNG (enlarged to include relevant participants that were not RNG members) as the Portuguese partner to EPOS-PP. However, at the time of signature of the EPOS-PP contract with the European Commission (November 2010), RNG had not gained formal identity yet, and IST (one of the participants) signed the grant agreement on behalf of the Portuguese consortium. During 2011 no progress was made towards the formal creation of RNG, and the composition of the network – based on proposals submitted to a call issued in 2002 – had by then become obsolete. On February 2012, the EPOS national contact point was mandated by the representatives of the participating national infrastructures to request from FCT the recognition of a new consortium - C3G, Collaboratory for Geology, Geodesy and Geophysics - as the Portuguese partner to EPOS-PP. This request was supported by formal letters from the following institutions: ‐ LNEG. Laboratório Nacional de Energia e Geologia (National Geological Survey); ‐ IGP ‐ Instituto Geográfico Português (National Geographic Institute); ‐ IDL, Instituto Dom Luiz – Laboratório Associado ‐ CGE, Centro de Geofísica de Évora; ‐ FCTUC, Faculdade de Ciências e Tecnologia da Universidade de Coimbra; ‐ Instituto Superior de Engenharia de Lisboa; ‐ Instituto Superior Técnico; ‐ Universidade da Beira Interior. While Instituto de Meteorologia (Meteorological Institute, in charge of the national seismographic network) actively supports the national participation in EPOS, a letter of support was not feasible in view of the organic changes underway at the time. C3G aims at the integration and coordination, at national level, of existing Earth Sciences infrastructures, namely: ‐ seismic and geodetic networks (IM, IST, IDL, CGE); ‐ rock physics laboratories (ISEL); ‐ geophysical laboratories dedicated to natural resources and environmental studies; ‐ geological and geophysical data repositories; ‐ facilities for data storage and computing resources. The C3G - Collaboratory for Geology, Geodesy and Geophysics will be coordinated by Universidade da Beira Interior, whose Department of Informatics will host the C3G infrastructure.