905 resultados para Data storage
Resumo:
We report on a new vector model of an erbium-doped fibre laser mode locked with carbon nanotubes. This model goes beyond the limitations of the previously used models based on either coupled nonlinear Schrödinger or Ginzburg-Landau equations. Unlike the previous models, it accounts for the vector nature of the interaction between an optical field and an erbium-doped active medium, slow relaxation dynamics of erbium ions, linear birefringence in a fibre, linear and circular birefringence of a laser cavity caused by in-cavity polarization controller and light-induced anisotropy caused by elliptically polarized pump field. Interplay of aforementioned factors changes coherent coupling of two polarization modes at a long time scale and so results in a new family of vector solitons (VSs) with fast and slowly evolving states of polarization. The observed VSs can be of interest in secure communications, trapping and manipulation of atoms and nanoparticles, control of magnetization in data storage devices and many other areas.
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This work is the first work using patterned soft underlayers in multilevel three-dimensional vertical magnetic data storage systems. The motivation stems from an exponentially growing information stockpile, and a corresponding need for more efficient storage devices with higher density. The world information stockpile currently exceeds 150EB (ExaByte=1x1018Bytes); most of which is in analog form. Among the storage technologies (semiconductor, optical and magnetic), magnetic hard disk drives are posed to occupy a big role in personal, network as well as corporate storage. However; this mode suffers from a limit known as the Superparamagnetic limit; which limits achievable areal density due to fundamental quantum mechanical stability requirements. There are many viable techniques considered to defer superparamagnetism into the 100's of Gbit/in2 such as: patterned media, Heat-Assisted Magnetic Recording (HAMR), Self Organized Magnetic Arrays (SOMA), antiferromagnetically coupled structures (AFC), and perpendicular magnetic recording. Nonetheless, these techniques utilize a single magnetic layer; and can thusly be viewed as two-dimensional in nature. In this work a novel three-dimensional vertical magnetic recording approach is proposed. This approach utilizes the entire thickness of a magnetic multilayer structure to store information; with potential areal density well into the Tbit/in2 regime. ^ There are several possible implementations for 3D magnetic recording; each presenting its own set of requirements, merits and challenges. The issues and considerations pertaining to the development of such systems will be examined, and analyzed using empirical and numerical analysis techniques. Two novel key approaches are proposed and developed: (1) Patterned soft underlayer (SUL) which allows for enhanced recording of thicker media, (2) A combinatorial approach for 3D media development that facilitates concurrent investigation of various film parameters on a predefined performance metric. A case study is presented using combinatorial overcoats of Tantalum and Zirconium Oxides for corrosion protection in magnetic media. ^ Feasibility of 3D recording is demonstrated, and an emphasis on 3D media development is emphasized as a key prerequisite. Patterned SUL shows significant enhancement over conventional "un-patterned" SUL, and shows that geometry can be used as a design tool to achieve favorable field distribution where magnetic storage and magnetic phenomena are involved. ^
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Moving objects database systems are the most challenging sub-category among Spatio-Temporal database systems. A database system that updates in real-time the location information of GPS-equipped moving vehicles has to meet even stricter requirements. Currently existing data storage models and indexing mechanisms work well only when the number of moving objects in the system is relatively small. This dissertation research aimed at the real-time tracking and history retrieval of massive numbers of vehicles moving on road networks. A total solution has been provided for the real-time update of the vehicles' location and motion information, range queries on current and history data, and prediction of vehicles' movement in the near future. ^ To achieve these goals, a new approach called Segmented Time Associated to Partitioned Space (STAPS) was first proposed in this dissertation for building and manipulating the indexing structures for moving objects databases. ^ Applying the STAPS approach, an indexing structure of associating a time interval tree to each road segment was developed for real-time database systems of vehicles moving on road networks. The indexing structure uses affordable storage to support real-time data updates and efficient query processing. The data update and query processing performance it provides is consistent without restrictions such as a time window or assuming linear moving trajectories. ^ An application system design based on distributed system architecture with centralized organization was developed to maximally support the proposed data and indexing structures. The suggested system architecture is highly scalable and flexible. Finally, based on a real-world application model of vehicles moving in region-wide, main issues on the implementation of such a system were addressed. ^
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Experimental and theoretical studies regarding noise processes in various kinds of AlGaAs/GaAs heterostructures with a quantum well are reported. The measurement processes, involving a Fast Fourier Transform and analog wave analyzer in the frequency range from 10 Hz to 1 MHz, a computerized data storage and processing system, and cryostat in the temperature range from 78 K to 300 K are described in detail. The current noise spectra are obtained with the “three-point method”, using a Quan-Tech and avalanche noise source for calibration. ^ The properties of both GaAs and AlGaAs materials and field effect transistors, based on the two-dimensional electron gas in the interface quantum well, are discussed. Extensive measurements are performed in three types of heterostructures, viz., Hall structures with a large spacer layer, modulation-doped non-gated FETs, and more standard gated FETs; all structures are grown by MBE techniques. ^ The Hall structures show Lorentzian generation-recombination noise spectra with near temperature independent relaxation times. This noise is attributed to g-r processes in the 2D electron gas. For the TEGFET structures, we observe several Lorentzian g-r noise components which have strongly temperature dependent relaxation times. This noise is attributed to trapping processes in the doped AlGaAs layer. The trap level energies are determined from an Arrhenius plot of log (τT2) versus 1/T as well as from the plateau values. The theory to interpret these measurements and to extract the defect level data is reviewed and further developed. Good agreement with the data is found for all reported devices. ^
Resumo:
Moving objects database systems are the most challenging sub-category among Spatio-Temporal database systems. A database system that updates in real-time the location information of GPS-equipped moving vehicles has to meet even stricter requirements. Currently existing data storage models and indexing mechanisms work well only when the number of moving objects in the system is relatively small. This dissertation research aimed at the real-time tracking and history retrieval of massive numbers of vehicles moving on road networks. A total solution has been provided for the real-time update of the vehicles’ location and motion information, range queries on current and history data, and prediction of vehicles’ movement in the near future. To achieve these goals, a new approach called Segmented Time Associated to Partitioned Space (STAPS) was first proposed in this dissertation for building and manipulating the indexing structures for moving objects databases. Applying the STAPS approach, an indexing structure of associating a time interval tree to each road segment was developed for real-time database systems of vehicles moving on road networks. The indexing structure uses affordable storage to support real-time data updates and efficient query processing. The data update and query processing performance it provides is consistent without restrictions such as a time window or assuming linear moving trajectories. An application system design based on distributed system architecture with centralized organization was developed to maximally support the proposed data and indexing structures. The suggested system architecture is highly scalable and flexible. Finally, based on a real-world application model of vehicles moving in region-wide, main issues on the implementation of such a system were addressed.
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The main objective of the project was to develop a geochemical method for exploration of ores associated with granitic rocks. Fe and Mn oxidates were sampled in streambeds and lakes from 129 localities in Southeastern Norway. 65 of these localities are situated in the northern Oslo Graben. The samples were examined mineralogically and chemically by a variety of methods. Geochemical maps of the element content in oxidates show regional distribution patterns for several elements. Sampling and analysis of oxidates can be used in exploration for mineralizations such as the Skrukkelia Mo-deposit in the northern Oslo Graben. New anomalies (especially for Zn and W) have been detected. Appendix I contains a description of samples, chemical and mineralogical determinations performed on the samples, backscattered electron image-, X-ray image- and scanning electron image pictures of the oxidate preparates. Appendix II contains spectral plots, point analysis with the microprobe, X-ray diffractograms, analytical results, correlation coefficient matrix, scatterplots, frequency distributions and information on data storage. Appendix III containS maps of the element content in oxidates.
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Location systems have become increasingly part of people's lives. For outdoor environments, GPS appears as standard technology, widely disseminated and used. However, people usually spend most of their daily time in indoor environments, such as: hospitals, universities, factories, buildings, etc. In these environments, GPS does not work properly causing an inaccurate positioning. Currently, to perform the location of people or objects in indoor environments no single technology could reproduce for indoors the same result achieved by GPS for outdoors environments. Due to this, it is necessary to consider use of information from multiple sources using diferent technologies. Thus, this work aims to build an Adaptable Platform for Indoor location. Based on this goal, the IndoLoR platform is proposed. This platform aims to allow information reception from diferent sources, data processing, data fusion, data storage and data retrieval for the indoor location context.
Resumo:
Location systems have become increasingly part of people's lives. For outdoor environments, GPS appears as standard technology, widely disseminated and used. However, people usually spend most of their daily time in indoor environments, such as: hospitals, universities, factories, buildings, etc. In these environments, GPS does not work properly causing an inaccurate positioning. Currently, to perform the location of people or objects in indoor environments no single technology could reproduce for indoors the same result achieved by GPS for outdoors environments. Due to this, it is necessary to consider use of information from multiple sources using diferent technologies. Thus, this work aims to build an Adaptable Platform for Indoor location. Based on this goal, the IndoLoR platform is proposed. This platform aims to allow information reception from diferent sources, data processing, data fusion, data storage and data retrieval for the indoor location context.
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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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Simulating the efficiency of business processes could reveal crucial bottlenecks for manufacturing companies and could lead to significant optimizations resulting in decreased time to market, more efficient resource utilization, and larger profit. While such business optimization software is widely utilized by larger companies, SMEs typically do not have the required expertise and resources to efficiently exploit these advantages. The aim of this work is to explore how simulation software vendors and consultancies can extend their portfolio to SMEs by providing business process optimization based on a cloud computing platform. By executing simulation runs on the cloud, software vendors and associated business consultancies can get access to large computing power and data storage capacity on demand, run large simulation scenarios on behalf of their clients, analyze simulation results, and advise their clients regarding process optimization. The solution is mutually beneficial for both vendor/consultant and the end-user SME. End-user companies will only pay for the service without requiring large upfront costs for software licenses and expensive hardware. Software vendors can extend their business towards the SME market with potentially huge benefits.
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The large upfront investments required for game development pose a severe barrier for the wider uptake of serious games in education and training. Also, there is a lack of well-established methods and tools that support game developers at preserving and enhancing the games’ pedagogical effectiveness. The RAGE project, which is a Horizon 2020 funded research project on serious games, addresses these issues by making available reusable software components that aim to support the pedagogical qualities of serious games. In order to easily deploy and integrate these game components in a multitude of game engines, platforms and programming languages, RAGE has developed and validated a hybrid component-based software architecture that preserves component portability and interoperability. While a first set of software components is being developed, this paper presents selected examples to explain the overall system’s concept and its practical benefits. First, the Emotion Detection component uses the learners’ webcams for capturing their emotional states from facial expressions. Second, the Performance Statistics component is an add-on for learning analytics data processing, which allows instructors to track and inspect learners’ progress without bothering about the required statistics computations. Third, a set of language processing components accommodate the analysis of textual inputs of learners, facilitating comprehension assessment and prediction. Fourth, the Shared Data Storage component provides a technical solution for data storage - e.g. for player data or game world data - across multiple software components. The presented components are exemplary for the anticipated RAGE library, which will include up to forty reusable software components for serious gaming, addressing diverse pedagogical dimensions.
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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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Lappeenrannan teknillinen yliopisto tutkii pientasajännitesähkön käyttöä. Yliopisto on rakennuttanut Järvi-Suomen Energia Oy:n ja Suur-Savon Sähkö Oy:n kanssa yhteistyössä kokeellisen pientasajännitesähköverkon, jolla pystytään tarjoamaan kenttäolosuhteet pienjännitetutkimukselle todellisilla asiakkailla ja todentaa LVDC-teknologiaa ja muita älykkään sähköverkon toimintoja kenttäolosuhteissa. Verkon tasajänniteyhteys on rakennettu 20 kV sähkönjakeluverkon ja neljän kuluttajan välille. 20 kV keskijännite suunnataan tasamuuntamolla ±750 V pientasajännitteeksi ja uudestaan 400/230 V vaihtojännitteeksi kuluttajien läheisyydessä. Tämän kandidaatintyön tarkoituksena on luoda yliopistolle tietokanta pientasajännitesähköverkosta kertyvälle tiedolle ja mittaustuloksille. Tietokanta nähtiin tarpeelliseksi luoda, jotta pienjänniteverkon mittaustuloksia pystytään myöhemmin tarkastelemaan yhdessä ja yhtenäisessä muodossa. Yhdeksi tutkimuskysymykseksi muodostui, kuinka järjestää ja visualisoida kaikki verkosta palvelimille kertyvä mittausdata. Työssä on huomioitu myös kolme tietokantaa mahdollisesti hyödyntävää käyttäjäryhmää: kotitalousasiakkaat, sähköverkkoyhtiöt ja tutkimuslaboratorio, sekä pohdittu tietokannan hyötyä ja merkitystä näille käyttäjille. Toiseksi tutkimuskysymykseksi muodostuikin, mikä kaikesta tietokantaan talletetusta datasta olisi oleellisen tärkeää ottaa talteen näiden asiakkaiden kannalta, ja kuinka nämä voisivat hakea tietoa tietokannasta. Työn tutkimusmenetelmät perustuvat jo valmiiksi olemassa olevaan mittausdataan. Työtä varten on käytetty sekä painettua että sähköisessä muodossa olevaa kirjallisuutta. Työn tuloksena on saatu luotua tietokanta MySQL Workbench -ohjelmistolla, sekä mittausdatan keräys- ja käsittelyohjelmat Python-ohjelmointikielellä. Lisäksi on luotu erillinen MATLAB-rajapinta tiedon visualisoimista varten, jolla havainnollistetaan kolmen asiakasryhmän mittausdataa. Tietokanta ja sen tiedon visualisointi antavat kuluttajalle mahdollisuuden ymmärtää paremmin omaa sähkönkäyttöään, sekä sähköverkkoyhtiöille ja tutkimuslaboratorioille muun muassa tietoa sähkön laadusta ja verkon kuormituksesta.
Resumo:
O presente trabalho tem como propósito responder a questão "qual o interesse estratégico de empresas do distrito de Aveiro se internacionalizarem para os Países Africanos de Língua Oficial Portuguesa (PALOP) e/ ou Brasil - Ceará?". O objeto de estudo surgiu após a integração num estágio curricular na AIDA - Associação Industrial do Distrito de Aveiro - e levou à revisão da literatura dos temas estratégia e internacionalização, assim como ao trabalho de campo (6 entrevistas a colaboradoras da AIDA), proporcionando as componentes conceptual e empírica. Verificou-se que o setor de atividade é fundamental para o sucesso das empresas nas missões. Designadamente, bastantes empresas ligadas ao setor metalomecânico, que tendem a recorrer a estes mercados dos PALOP e/ ou Brasil - Ceará, alcançaram, em muitos casos, o sucesso - isto é, a concretização de negócios com novos clientes e / ou o investimento direto nesses países. O contributo do presente trabalho reside também na perspetiva, resultante de um inquérito desenvolido no âmbito do estágio no Gabinete de Relações Exteriores da AIDA, de que ainda que se verifique uma janela de oportunidade para algumas das empresas nos referidos mercados (PALOP e Brasil - Ceará), entende-se que, para o sucesso efetivo destas empresas, outras formas de empreender poderiam ser colocadas em prática, nomeadamente alianças estratégicas entre pequenas e médias empresas (PME) de setores semelhantes, a nível local (Portugal), para competirem a nível internacional com os respetivos líderes de mercado. Desta forma, sugere-se lutar pela competitividade não só nos PALOP mas também nos mercados desenvolvidos, tais como Alemanha, Estados Unidos da América e/ ou países escandinavos - pois somente com clientes exigentes e com a pressão de concorrentes fortes poder-se-ão criar indústrias desenvolvidas e capazes de competir ao mais elevado nível e pelos melhores clientes, com poder de compra e fontes de inovação (Porter, 1990). Estas lições parecem, por ezes, esquecidas, mas segundo Gibbs (2007) um dos propósitos da investigação é também o de lembrar o que foi esquecido e/ ou ignorado. As entrevistas realizadas ofereceram contributo na medida em que proporcionam a compreensão dos motivos para as empresas portuguesas escolherem estes mercados, das razões para o sucesso ou insucesso nos PALOP e/ ou Brasil - Ceará, do investimento e esforço por parte das entidades não-governamentais portuguesas em internacionalizar empresas do setor da metalomecânica, das forças e fraquezas das missões empresariais, de que aspetos fazem da AIDA um agente de mudança e das áreas em que poderia haver maior diligência por parte da AIDA.São também sugeridas recomendações a associação, entre outras, a inclusão das questões culturais de cada país nos estudos de mercado não só sobre PALOP e Brasil - Ceará, mas também nos estudos de mercado do distrito de Aveiro, assim como de Portugal, para fazer divulgação a potenciais importadores; melhoria de processos, implementando-se um software de gestão/ partilha de conhecimento das várias oportunidades de negócio, rentabilizando o processo de estabelecimento de interesse em realizar negócio, no âmbito do EEN (Entelprise Eumpe Netwrk); intervenção na plataforma do IAPMEI por informáticos habilitados; e armazenamento de dados em cloud storage - um serviço do género da Dropbox, de modo a rentabilizar o tempo dispendido, assim como a tornar as pastas acedidas via intranet mais pequenas.
Resumo:
Terrestrial remote sensing imagery involves the acquisition of information from the Earth's surface without physical contact with the area under study. Among the remote sensing modalities, hyperspectral imaging has recently emerged as a powerful passive technology. This technology has been widely used in the fields of urban and regional planning, water resource management, environmental monitoring, food safety, counterfeit drugs detection, oil spill and other types of chemical contamination detection, biological hazards prevention, and target detection for military and security purposes [2-9]. Hyperspectral sensors sample the reflected solar radiation from the Earth surface in the portion of the spectrum extending from the visible region through the near-infrared and mid-infrared (wavelengths between 0.3 and 2.5 µm) in hundreds of narrow (of the order of 10 nm) contiguous bands [10]. This high spectral resolution can be used for object detection and for discriminating between different objects based on their spectral xharacteristics [6]. However, this huge spectral resolution yields large amounts of data to be processed. For example, the Airbone Visible/Infrared Imaging Spectrometer (AVIRIS) [11] collects a 512 (along track) X 614 (across track) X 224 (bands) X 12 (bits) data cube in 5 s, corresponding to about 140 MBs. Similar data collection ratios are achieved by other spectrometers [12]. Such huge data volumes put stringent requirements on communications, storage, and processing. The problem of signal sbspace identification of hyperspectral data represents a crucial first step in many hypersctral processing algorithms such as target detection, change detection, classification, and unmixing. The identification of this subspace enables a correct dimensionality reduction (DR) yelding gains in data storage and retrieval and in computational time and complexity. Additionally, DR may also improve algorithms performance since it reduce data dimensionality without losses in the useful signal components. The computation of statistical estimates is a relevant example of the advantages of DR, since the number of samples required to obtain accurate estimates increases drastically with the dimmensionality of the data (Hughes phnomenon) [13].