980 resultados para operational systems
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Pipeline systems play a key role in the petroleum business. These operational systems provide connection between ports and/or oil fields and refineries (upstream), as well as between these and consumer markets (downstream). The purpose of this work is to propose a novel MINLP formulation based on a continuous time representation for the scheduling of multiproduct pipeline systems that must supply multiple consumer markets. Moreover, it also considers that the pipeline operates intermittently and that the pumping costs depend on the booster stations yield rates, which in turn may generate different flow rates. The proposed continuous time representation is compared with a previously developed discrete time representation [Rejowski, R., Jr., & Pinto, J. M. (2004). Efficient MILP formulations and valid cuts for multiproduct pipeline scheduling. Computers and Chemical Engineering, 28, 1511] in terms of solution quality and computational performance. The influence of the number of time intervals that represents the transfer operation is studied and several configurations for the booster stations are tested. Finally, the proposed formulation is applied to a larger case, in which several booster configurations with different numbers of stages are tested. (C) 2007 Elsevier Ltd. All rights reserved.
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A variety of operational systems are vulnerable to disruption by solar disturbances brought to the Earth by the solar wind. Of particular importance to navigation systems are energetic charged particles which can generate temporary malfunctions and permanent damage in satellites. Modern spacecraft technology may prove to be particularly at risk during the next maximum of the solar cycle. In addition, the associated ionospheric disturbances cause phase shifts of transionospheric and ionosphere-reflected signals, giving positioning errors and loss of signal for GPS and Loran-C positioning systems and for over-the-horizon radars. We now have sufficient understanding of the solar wind, and how it interacts with the Earth's magnetic field, to predict statistically the likely effects on operational systems over the next solar cycle. We also have a number of advanced ways of detecting and tracking these disturbances through space but we cannot, as yet, provide accurate forecasts of individual disturbances that could be used to protect satellites and to correct errors. In addition, we have recently discovered long-term changes in the Sun, which mean that the number and severity of the disturbances to operational systems are increasing.
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Floods are the most frequent of natural disasters, affecting millions of people across the globe every year. The anticipation and forecasting of floods at the global scale is crucial to preparing for severe events and providing early awareness where local flood models and warning services may not exist. As numerical weather prediction models continue to improve, operational centres are increasingly using the meteorological output from these to drive hydrological models, creating hydrometeorological systems capable of forecasting river flow and flood events at much longer lead times than has previously been possible. Furthermore, developments in, for example, modelling capabilities, data and resources in recent years have made it possible to produce global scale flood forecasting systems. In this paper, the current state of operational large scale flood forecasting is discussed, including probabilistic forecasting of floods using ensemble prediction systems. Six state-of-the-art operational large scale flood forecasting systems are reviewed, describing similarities and differences in their approaches to forecasting floods at the global and continental scale. Currently, operational systems have the capability to produce coarse-scale discharge forecasts in the medium-range and disseminate forecasts and, in some cases, early warning products, in real time across the globe, in support of national forecasting capabilities. With improvements in seasonal weather forecasting, future advances may include more seamless hydrological forecasting at the global scale, alongside a move towards multi-model forecasts and grand ensemble techniques, responding to the requirement of developing multi-hazard early warning systems for disaster risk reduction.
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Doctoral Thesis in Information Systems and Technologies Area of Engineering and Manag ement Information Systems
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Esta dissertação incide sobre a problemática da construção de um data warehouse para a empresa AdClick que opera na área de marketing digital. O marketing digital é um tipo de marketing que utiliza os meios de comunicação digital, com a mesma finalidade do método tradicional que se traduz na divulgação de bens, negócios e serviços e a angariação de novos clientes. Existem diversas estratégias de marketing digital tendo em vista atingir tais objetivos, destacando-se o tráfego orgânico e tráfego pago. Onde o tráfego orgânico é caracterizado pelo desenvolvimento de ações de marketing que não envolvem quaisquer custos inerentes à divulgação e/ou angariação de potenciais clientes. Por sua vez o tráfego pago manifesta-se pela necessidade de investimento em campanhas capazes de impulsionar e atrair novos clientes. Inicialmente é feita uma abordagem do estado da arte sobre business intelligence e data warehousing, e apresentadas as suas principais vantagens as empresas. Os sistemas business intelligence são necessários, porque atualmente as empresas detêm elevados volumes de dados ricos em informação, que só serão devidamente explorados fazendo uso das potencialidades destes sistemas. Nesse sentido, o primeiro passo no desenvolvimento de um sistema business intelligence é concentrar todos os dados num sistema único integrado e capaz de dar apoio na tomada de decisões. É então aqui que encontramos a construção do data warehouse como o sistema único e ideal para este tipo de requisitos. Nesta dissertação foi elaborado o levantamento das fontes de dados que irão abastecer o data warehouse e iniciada a contextualização dos processos de negócio existentes na empresa. Após este momento deu-se início à construção do data warehouse, criação das dimensões e tabelas de factos e definição dos processos de extração e carregamento dos dados para o data warehouse. Assim como a criação das diversas views. Relativamente ao impacto que esta dissertação atingiu destacam-se as diversas vantagem a nível empresarial que a empresa parceira neste trabalho retira com a implementação do data warehouse e os processos de ETL para carregamento de todas as fontes de informação. Sendo que algumas vantagens são a centralização da informação, mais flexibilidade para os gestores na forma como acedem à informação. O tratamento dos dados de forma a ser possível a extração de informação a partir dos mesmos.
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Today it is easy to find a lot of tools to define data migration schemas among different types of information systems. Data migration processes use to be implemented on a very diverse range of applications, ranging from conventional operational systems to data warehousing platforms. The implementation of a data migration process often involves a serious planning, considering the development of conceptual migration schemas at early stages. Such schemas help architects and engineers to plan and discuss the most adequate way to migrate data between two different systems. In this paper we present and discuss a way for enriching data migration conceptual schemas in BPMN using a domain-specific language, demonstrating how to convert such enriched schemas to a first correspondent physical representation (a skeleton) in a conventional ETL implementation tool like Kettle.
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The MAP-i Doctoral Programme in Informatics, of the Universities of Minho, Aveiro and Porto
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Työn tavoittena oli selvittää, miten tietovarastointi voi tukea yrityksessä tapahtuvaa päätöksentekoa. Tietovarastokomponenttien ja –prosessien kuvauksen jälkeen on käsitelty tietovarastoprojektin eri vaiheita. Esitettyä teoriaa sovellettiin käytäntöön globaalissa metalliteollisuusyrityksessä, jossa tietovarastointikonseptia testattiin. Testauksen perusteella arvioitiin olemassa olevan tiedon tilaa sekä kahden käytetyn ohjelmiston toimivuutta tietovarastoinnissa. Yrityksen operatiivisten järjestelmien tiedon laadun todettiin olevan tutkituilta osin epäyhtenäistä ja puutteellista. Siksi tiedon suora yrityslaajuinen hyödyntäminen luotettavien ja hyvälaatuisten raporttien luonnissa on vaikeaa. Lisäksi eri yksiköiden välillä havaittiin epäyhtenäisyyttä käytettyjen liiketoiminnan käsitteiden sekä järjestelmien käyttötapojen suhteen. Testauksessa käytetyt ohjelmistot suoriutuivat perustietovarastoinnista hyvin, vaikkakin joitain rajoituksia ja erikoisuuksia ilmenikin. Työtä voidaan pitää ennen varsinaista tietovarastoprojektia tehtävänä esitutkimuksena. Jatkotoimenpiteinä ehdotetaan testauksen jatkamista nykyisillä työkaluilla kohdistaen tavoitteet konkreettisiin tuloksiin. Tiedon laadun tärkeyttä tulee korostaa koko organisaatiossa ja olemassa olevan tiedon laatua pitää parantaa tulevaisuudessa.
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Työn tavoite oli löytää malli, joka mahdollistaisi kaikkien tilaus- toimitusprosessin operatiivisten järjestelmien integroimisen keskenään siten, että niitä voidaan hyödyntää valmistuksen ohjaukseen. Vaneritehtaissa ei ole keskitettyä tietojärjestelmää, joten tavoiteasetanta edellytti vaneritehtaan tietoverkon rakentamiseen liittyvän ongelmakentän periaatteellista ratkaisua.Koska tilaus- toimitusprosessi, tuotantoa lukuunottamatta, oli kohdeyrityksessä katettu tietojärjestelmillä, loivat nämä jo olemassa olevat järjestelmät reunaehdot ratkaisulle myös tuotannon tietoverkon kehittämisessä. Työssä etsittiin ja kiinnitettiin avaimet, joilla tuote- sekä henkilötieto saadaan identifioitua keskenään integroiduissa järjestelmissä niin, että informaatioketju ei katkea siirryttäessä järjestelmästä toiseen.Työssä ratkaistiin tietoverkon liityntä tuotantolaitteisiin valvomotuotteen avulla. Liittymisratkaisuja esiteltiin neljä. Nämä mallit kattavat suurimman osan vaneritehtaassa eteen tulevista tapauksista. Näiden lisäksi päädyttiin suosittamaan erään mekaanisen metsäteollisuuden laitetoimittajan luomaa tiedonkeruu- ja tuotannonsuunnitteluohjelmistoa, joka valmiina ratkaisuna edesauttaa tietoverkon nopeaa implementointia.
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Data management consists of collecting, storing, and processing the data into the format which provides value-adding information for decision-making process. The development of data management has enabled of designing increasingly effective database management systems to support business needs. Therefore as well as advanced systems are designed for reporting purposes, also operational systems allow reporting and data analyzing. The used research method in the theory part is qualitative research and the research type in the empirical part is case study. Objective of this paper is to examine database management system requirements from reporting managements and data managements perspectives. In the theory part these requirements are identified and the appropriateness of the relational data model is evaluated. In addition key performance indicators applied to the operational monitoring of production are studied. The study has revealed that the appropriate operational key performance indicators of production takes into account time, quality, flexibility and cost aspects. Especially manufacturing efficiency has been highlighted. In this paper, reporting management is defined as a continuous monitoring of given performance measures. According to the literature review, the data management tool should cover performance, usability, reliability, scalability, and data privacy aspects in order to fulfill reporting managements demands. A framework is created for the system development phase based on requirements, and is used in the empirical part of the thesis where such a system is designed and created for reporting management purposes for a company which operates in the manufacturing industry. Relational data modeling and database architectures are utilized when the system is built for relational database platform.
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As soluções informáticas de Customer Relationship Management (CRM) e os sistemas de suporte à informação, designados por Business Intelligence (BI), permitem a recolha de dados e a sua transformação em informação e em conhecimento, vital para diferenciação das organizações num Mundo globalizado e em constante mudança. A construção de um Data Warehouse corporativo é fundamental para as organizações que utilizam vários sistemas operacionais de modo a ser possível a agregação da informação. A Fundação INATEL – uma fundação privada de interesse público, 100% estatal – é um exemplo deste tipo de organização. Com uma base de dados de clientes superior a 250.000, atuando em áreas tão diferentes como sejam o Turismo, a Cultura e o Desporto, sustentado em mais de 25 sistemas informáticos autónomos. A base de estudo deste trabalho é a procura de identificação dos benefícios da implementação de um CRM Analítico na Fundação INATEL. Apresentando-se assim uma metodologia para a respetiva implementação e sugestão de um modelo de dados para a obtenção de uma visão única do cliente, acessível a toda a organização, de modo a garantir a total satisfação e consequente fidelização à marca INATEL. A disponibilização desta informação irá proporcionar um posicionamento privilegiado da Fundação INATEL e terá um papel fundamental na sua sustentabilidade económica.
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The assimilation of Doppler radar radial winds for high resolution NWP may improve short term forecasts of convective weather. Using insects as the radar target, it is possible to provide wind observations during convective development. This study aims to explore the potential of these new observations, with three case studies. Radial winds from insects detected by 4 operational weather radars were assimilated using 3D-Var into a 1.5 km resolution version of the Met Office Unified Model, using a southern UK domain and no convective parameterization. The effect on the analysis wind was small, with changes in direction and speed up to 45° and 2 m s−1 respectively. The forecast precipitation was perturbed in space and time but not substantially modified. Radial wind observations from insects show the potential to provide small corrections to the location and timing of showers but not to completely relocate convergence lines. Overall, quantitative analysis indicated the observation impact in the three case studies was small and neutral. However, the small sample size and possible ground clutter contamination issues preclude unequivocal impact estimation. The study shows the potential positive impact of insect winds; future operational systems using dual polarization radars which are better able to discriminate between insects and clutter returns should provided a much greater impact on forecasts.
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Data assimilation algorithms are a crucial part of operational systems in numerical weather prediction, hydrology and climate science, but are also important for dynamical reconstruction in medical applications and quality control for manufacturing processes. Usually, a variety of diverse measurement data are employed to determine the state of the atmosphere or to a wider system including land and oceans. Modern data assimilation systems use more and more remote sensing data, in particular radiances measured by satellites, radar data and integrated water vapor measurements via GPS/GNSS signals. The inversion of some of these measurements are ill-posed in the classical sense, i.e. the inverse of the operator H which maps the state onto the data is unbounded. In this case, the use of such data can lead to significant instabilities of data assimilation algorithms. The goal of this work is to provide a rigorous mathematical analysis of the instability of well-known data assimilation methods. Here, we will restrict our attention to particular linear systems, in which the instability can be explicitly analyzed. We investigate the three-dimensional variational assimilation and four-dimensional variational assimilation. A theory for the instability is developed using the classical theory of ill-posed problems in a Banach space framework. Further, we demonstrate by numerical examples that instabilities can and will occur, including an example from dynamic magnetic tomography.
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In the two last decades of the past century, following the consolidation of the Internet as the world-wide computer network, applications generating more robust data flows started to appear. The increasing use of videoconferencing stimulated the creation of a new form of point-to-multipoint transmission called IP Multicast. All companies working in the area of software and the hardware development for network videoconferencing have adjusted their products as well as developed new solutionsfor the use of multicast. However the configuration of such different solutions is not easy done, moreover when changes in the operational system are also requirede. Besides, the existing free tools have limited functions, and the current comercial solutions are heavily dependent on specific platforms. Along with the maturity of IP Multicast technology and with its inclusion in all the current operational systems, the object-oriented programming languages had developed classes able to handle multicast traflic. So, with the help of Java APIs for network, data bases and hipertext, it became possible to the develop an Integrated Environment able to handle multicast traffic, which is the major objective of this work. This document describes the implementation of the above mentioned environment, which provides many functions to use and manage multicast traffic, functions which existed only in a limited way and just in few tools, normally the comercial ones. This environment is useful to different kinds of users, so that it can be used by common users, who want to join multimedia Internet sessions, as well as more advenced users such engineers and network administrators who may need to monitor and handle multicast traffic