848 resultados para Online data processing.


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Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. These systems provide currently relatively few structure. We discuss in this paper, how association rule mining can be adopted to analyze and structure folksonomies, and how the results can be used for ontology learning and supporting emergent semantics. We demonstrate our approach on a large scale dataset stemming from an online system.

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In diesem Bericht werden die Ergebnisse und Fortschritte des Forschungsprojekts ADDOaction vorgestellt. Durch die Entwicklung in den letzten Jahrzehnten wurde das Internet zu einer wichtigen Infrastruktur für Geschäftsprozesse. Beliebige Anwendungen können als Dienste angeboten und übers Internet den Kunden online zur Verfügung gestellt werden. Eine flexible Dienstarchitektur ist dabei durch einen gewissen Grad an Dynamik gekennzeichnet, wo Dienste angepasst, ausgetauscht oder entfernt werden können und eventuell gleichzeitig von verschiedenen Anbietern bereitgestellt werden können. Dienste müssen dabei sowohl die funktionalen als auch die nicht-funktionalen Quality of Service (QoS) Anforderungen der Klienten erfüllen, um Kundenzufriedenheit garantieren zu können. Die Vielzahl der angebotenen Dienste und die unterschiedlichen Anforderungen der Klienten machen eine manuelle Entdeckung und ein manuelles Management der Dienste praktisch unmöglich. ADDOaction adressiert genau diese Probleme einer dienstorientierten Architektur und liefert innovative Lösungen von der automatischen Entdeckung von Diensten bis hin zur Überwachung und zum Management von Diensten zur Laufzeit.

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Vorgestellt wird eine weltweit neue Methode, Schnittstellen zwischen Menschen und Maschinen für individuelle Bediener anzupassen. Durch Anwenden von Abstraktionen evolutionärer Mechanismen wie Selektion, Rekombination und Mutation in der EOGUI-Methodik (Evolutionary Optimization of Graphical User Interfaces) kann eine rechnergestützte Umsetzung der Methode für Graphische Bedienoberflächen, insbesondere für industrielle Prozesse, bereitgestellt werden. In die Evolutionäre Optimierung fließen sowohl die objektiven, d.h. messbaren Größen wie Auswahlhäufigkeiten und -zeiten, mit ein, als auch das anhand von Online-Fragebögen erfasste subjektive Empfinden der Bediener. Auf diese Weise wird die Visualisierung von Systemen den Bedürfnissen und Präferenzen einzelner Bedienern angepasst. Im Rahmen dieser Arbeit kann der Bediener aus vier Bedienoberflächen unterschiedlicher Abstraktionsgrade für den Beispielprozess MIPS ( MIschungsProzess-Simulation) die Objekte auswählen, die ihn bei der Prozessführung am besten unterstützen. Über den EOGUI-Algorithmus werden diese Objekte ausgewählt, ggf. verändert und in einer neuen, dem Bediener angepassten graphischen Bedienoberfläche zusammengefasst. Unter Verwendung des MIPS-Prozesses wurden Experimente mit der EOGUI-Methodik durchgeführt, um die Anwendbarkeit, Akzeptanz und Wirksamkeit der Methode für die Führung industrieller Prozesse zu überprüfen. Anhand der Untersuchungen kann zu großen Teilen gezeigt werden, dass die entwickelte Methodik zur Evolutionären Optimierung von Mensch-Maschine-Schnittstellen industrielle Prozessvisualisierungen tatsächlich an den einzelnen Bediener anpaßt und die Prozessführung verbessert.

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Das Ziel der Dissertation war die Untersuchung des Computereinsatzes zur Lern- und Betreuungsunterstützung beim selbstgesteuerten Lernen in der Weiterbildung. In einem bisher konventionell durchgeführten Selbstlernkurs eines berufsbegleitenden Studiengangs, der an das Datenmanagement der Bürodatenverarbeitung heranführt, wurden die Kursunterlagen digitalisiert, die Betreuung auf eine online-basierte Lernbegleitung umgestellt und ein auf die neuen Lernmedien abgestimmtes Lernkonzept entwickelt. Dieses neue Lernkonzept wurde hinsichtlich der Motivation und der Akzeptanz von digitalen Lernmedien evaluiert. Die Evaluation bestand aus zwei Teilen: 1. eine formative, den Entwicklungsprozess begleitende Evaluation zur Optimierung der entwickelten Lernsoftware und des eingeführten Lernkonzeptes, 2. eine sowohl qualitative wie quantitative summative Evaluation der Entwicklungen. Ein zentraler Aspekt der Untersuchung war die freie Wahl der Lernmedien (multimediale Lernsoftware oder konventionelles Begleitbuch) und der Kommunikationsmedien (online-basierte Lernplattform oder die bisher genutzten Kommunikationskanäle: E-Mail, Telefon und Präsenztreffen). Diese Zweigleisigkeit erlaubte eine differenzierte Gegenüberstellung von konventionellen und innovativen Lernarrangements. Die Verbindung von qualitativen und quantitativen Vorgehensweisen, auf Grund derer die subjektiven Einstellungen der Probanden in das Zentrum der Betrachtung rückten, ließen einen Blickwinkel auf den Nutzen und die Wirkung der Neuen Medien in Lernprozessen zu, der es erlaubte einige in der Literatur als gängig angesehene Interpretationen in Frage zu stellen und neu zu diskutieren. So konnten durch eine Kategorisierung des Teilnehmerverhaltens nach online-typisch und nicht online-typisch die Ursache-Wirkungs-Beziehungen der in vielen Untersuchungen angeführten Störungen in Online-Seminaren verdeutlicht werden. In den untersuchten Kursen zeigte sich beispielsweise keine Abhängigkeit der Drop-out-Quote von den Lern- und Betreuungsformen und dass diese Quote mit dem neuen Lernkonzept nur geringfügig beeinflusst werden konnte. Die freie Wahl der Lernmedien führte zu einer gezielten Nutzung der multimedialen Lernsoftware, wodurch die Akzeptanz dieses Lernmedium stieg. Dagegen war die Akzeptanz der Lernenden gegenüber der Lernbegleitung mittels einer Online-Lernplattform von hoch bis sehr niedrig breit gestreut. Unabhängig davon reichte in allen Kursdurchgängen die Online-Betreuung nicht aus, so dass Präsenztreffen erbeten wurde. Hinsichtlich der Motivation war die Wirkung der digitalen Medien niedriger als erwartet. Insgesamt bieten die Ergebnisse Empfehlungen für die Planung und Durchführung von computerunterstützten, online-begleiteten Kursen.

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Presentation given at the Al-Azhar Engineering First Conference, AEC’89, Dec. 9-12 1989, Cairo, Egypt. The paper presented at AEC'89 suggests an infinite storage scheme divided into one volume which is online and an arbitrary number of off-line volumes arranged into a linear chain which hold records which haven't been accessed recently. The online volume holds the records in sorted order (e.g. as a B-tree) and contains shortest prefixes of keys of records already pushed offline. As new records enter, older ones are retired to the first volume which is going offline next. Statistical arguments are given for the rate at which an off-line volume needs to be fetched to reload a record which had been retired before. The rate depends on the distribution of access probabilities as a function of time. Applications are medical records, production records or other data which need to be kept for a long time for legal reasons.

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This thesis aims at empowering software customers with a tool to build software tests them selves, based on a gradual refinement of natural language scenarios into executable visual test models. The process is divided in five steps: 1. First, a natural language parser is used to extract a graph of grammatical relations from the textual scenario descriptions. 2. The resulting graph is transformed into an informal story pattern by interpreting structurization rules based on Fujaba Story Diagrams. 3. While the informal story pattern can already be used by humans the diagram still lacks technical details, especially type information. To add them, a recommender based framework uses web sites and other resources to generate formalization rules. 4. As a preparation for the code generation the classes derived for formal story patterns are aligned across all story steps, substituting a class diagram. 5. Finally, a headless version of Fujaba is used to generate an executable JUnit test. The graph transformations used in the browser application are specified in a textual domain specific language and visualized as story pattern. Last but not least, only the heavyweight parsing (step 1) and code generation (step 5) are executed on the server side. All graph transformation steps (2, 3 and 4) are executed in the browser by an interpreter written in JavaScript/GWT. This result paves the way for online collaboration between global teams of software customers, IT business analysts and software developers.

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Objetivo Identificar la prevalencia de síntomas osteomusculares, por segmentos y los factores de riesgo asociados, en los trabajadores de una empresa de Geomática, en Colombia en el año 2014. Metodología Se llevó a cabo un estudio descriptivo de corte transversal con una población de 169 trabajadores, distribuidos en 2 grupos, el grupo de campo que desarrolla actividades de topografía y el grupo de oficina donde se realizan procesamiento de datos en Geomática y actividades administrativas. A cada trabajador se le aplicó el cuestionario ERGOPAR que interroga la exposición o factores de riesgo y la presencia de síntomas osteomusculares. Resultados: El personal de oficina presenta mayor frecuencia de síntomas osteomusculares en el cuello 72%, la región lumbar 55%, los codos 17,7%, las manos y muñecas 57.3%. Presentándose con mayor frecuencia en las mujeres los síntomas en cuello 80% y manos 64%, mientras que los mayores porcentajes en personal de campo se presentan en las piernas 21%, las rodillas 26% y pies 11,5%. Se encontró asociación significativa entre la sedestación durante más de cuatro horas, con dolor en cuello (p=0.02) y dolor en región lumbar (p=0.03); inclinar el cuello hacia delante durante más de cuatro horas, con dolor en el cuello (p=0.006); repetir cada pocos segundos la flexión de muñecas (p=001) y utilizar los dedos de manera intensiva por más de 4 horas (p=0.01) con dolor en manos y las variables jornada laboral y puesto de trabajo con dolor en pies. Conclusiones La prevalencia de síntomas osteomusculares en los trabajadores de la empresa estudiada es alta. Dado que se encontró asociación significativa con las variables sociodemográficas y laborales. La alta prevalencia de sintomatología puede ser explicada por la exposición a carga física laboral, por posturas de trabajo, por movimientos repetitivos y características propias de género.

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The long-term stability, high accuracy, all-weather capability, high vertical resolution, and global coverage of Global Navigation Satellite System (GNSS) radio occultation (RO) suggests it as a promising tool for global monitoring of atmospheric temperature change. With the aim to investigate and quantify how well a GNSS RO observing system is able to detect climate trends, we are currently performing an (climate) observing system simulation experiment over the 25-year period 2001 to 2025, which involves quasi-realistic modeling of the neutral atmosphere and the ionosphere. We carried out two climate simulations with the general circulation model MAECHAM5 (Middle Atmosphere European Centre/Hamburg Model Version 5) of the MPI-M Hamburg, covering the period 2001–2025: One control run with natural variability only and one run also including anthropogenic forcings due to greenhouse gases, sulfate aerosols, and tropospheric ozone. On the basis of this, we perform quasi-realistic simulations of RO observables for a small GNSS receiver constellation (six satellites), state-of-the-art data processing for atmospheric profiles retrieval, and a statistical analysis of temperature trends in both the “observed” climatology and the “true” climatology. Here we describe the setup of the experiment and results from a test bed study conducted to obtain a basic set of realistic estimates of observational errors (instrument- and retrieval processing-related errors) and sampling errors (due to spatial-temporal undersampling). The test bed results, obtained for a typical summer season and compared to the climatic 2001–2025 trends from the MAECHAM5 simulation including anthropogenic forcing, were found encouraging for performing the full 25-year experiment. They indicated that observational and sampling errors (both contributing about 0.2 K) are consistent with recent estimates of these errors from real RO data and that they should be sufficiently small for monitoring expected temperature trends in the global atmosphere over the next 10 to 20 years in most regions of the upper troposphere and lower stratosphere (UTLS). Inspection of the MAECHAM5 trends in different RO-accessible atmospheric parameters (microwave refractivity and pressure/geopotential height in addition to temperature) indicates complementary climate change sensitivity in different regions of the UTLS so that optimized climate monitoring shall combine information from all climatic key variables retrievable from GNSS RO data.

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This paper is an initial work towards developing an e-Government benchmarking model that is user-centric. To achieve the goal then, public service delivery is discussed first including the transition to online public service delivery and the need for providing public services using electronic media. Two major e-Government benchmarking methods are critically discussed and the need to develop a standardized benchmarking model that is user-centric is presented. To properly articulate user requirements in service provision, an organizational semiotic method is suggested.

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For several years, online educational tools such as Blackboard have been used by Universities to foster collaborative learning in an online setting. Such tools tend to be implemented in a top-down fashion, with the institution providing the tool to the students and instructing them to use it. Recently, however, a more informal, bottom up approach is increasingly being employed by the students themselves in the form of social networks such as Facebook. With over 9,000 registered Facebook users at the beginning of this study, rising to over 12,000 at the University of Reading alone, Facebook is becoming the de facto social network of choice for higher education students in the UK, and there was increasing anecdotal evidence that students were actively learning via Facebook rather than through BlackBoard. To test the validity of these anecdotes, a questionnaire was sent to students, asking them about their learning experiences via BlackBoard and Facebook. The results show that students are making use of the tools available to them even when there is no formal academic content, and that increased use of a social networking tool is correlated with a reported increase in learning as a result of that use.

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GODIVA2 is a dynamic website that provides visual access to several terabytes of physically distributed, four-dimensional environmental data. It allows users to explore large datasets interactively without the need to install new software or download and understand complex data. Through the use of open international standards, GODIVA2 maintains a high level of interoperability with third-party systems, allowing diverse datasets to be mutually compared. Scientists can use the system to search for features in large datasets and to diagnose the output from numerical simulations and data processing algorithms. Data providers around Europe have adopted GODIVA2 as an INSPIRE-compliant dynamic quick-view system for providing visual access to their data.

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This chapter introduces the latest practices and technologies in the interactive interpretation of environmental data. With environmental data becoming ever larger, more diverse and more complex, there is a need for a new generation of tools that provides new capabilities over and above those of the standard workhorses of science. These new tools aid the scientist in discovering interesting new features (and also problems) in large datasets by allowing the data to be explored interactively using simple, intuitive graphical tools. In this way, new discoveries are made that are commonly missed by automated batch data processing. This chapter discusses the characteristics of environmental science data, common current practice in data analysis and the supporting tools and infrastructure. New approaches are introduced and illustrated from the points of view of both the end user and the underlying technology. We conclude by speculating as to future developments in the field and what must be achieved to fulfil this vision.

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Body area networks (BANs) are emerging as enabling technology for many human-centered application domains such as health-care, sport, fitness, wellness, ergonomics, emergency, safety, security, and sociality. A BAN, which basically consists of wireless wearable sensor nodes usually coordinated by a static or mobile device, is mainly exploited to monitor single assisted livings. Data generated by a BAN can be processed in real-time by the BAN coordinator and/or transmitted to a server-side for online/offline processing and long-term storing. A network of BANs worn by a community of people produces large amount of contextual data that require a scalable and efficient approach for elaboration and storage. Cloud computing can provide a flexible storage and processing infrastructure to perform both online and offline analysis of body sensor data streams. In this paper, we motivate the introduction of Cloud-assisted BANs along with the main challenges that need to be addressed for their development and management. The current state-of-the-art is overviewed and framed according to the main requirements for effective Cloud-assisted BAN architectures. Finally, relevant open research issues in terms of efficiency, scalability, security, interoperability, prototyping, dynamic deployment and management, are discussed.

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In recent years, there has been an increasing interest in the adoption of emerging ubiquitous sensor network (USN) technologies for instrumentation within a variety of sustainability systems. USN is emerging as a sensing paradigm that is being newly considered by the sustainability management field as an alternative to traditional tethered monitoring systems. Researchers have been discovering that USN is an exciting technology that should not be viewed simply as a substitute for traditional tethered monitoring systems. In this study, we investigate how a movement monitoring measurement system of a complex building is developed as a research environment for USN and related decision-supportive technologies. To address the apparent danger of building movement, agent-mediated communication concepts have been designed to autonomously manage large volumes of exchanged information. In this study, we additionally detail the design of the proposed system, including its principles, data processing algorithms, system architecture, and user interface specifics. Results of the test and case study demonstrate the effectiveness of the USN-based data acquisition system for real-time monitoring of movement operations.

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Environment monitoring applications using Wireless Sensor Networks (WSNs) have had a lot of attention in recent years. In much of this research tasks like sensor data processing, environment states and events decision making and emergency message sending are done by a remote server. A proposed cross layer protocol for two different applications where, reliability for delivered data, delay and life time of the network need to be considered, has been simulated and the results are presented in this paper. A WSN designed for the proposed applications needs efficient MAC and routing protocols to provide a guarantee for the reliability of the data delivered from source nodes to the sink. A cross layer based on the design given in [1] has been extended and simulated for the proposed applications, with new features, such as routes discovery algorithms added. Simulation results show that the proposed cross layer based protocol can conserve energy for nodes and provide the required performance such as life time of the network, delay and reliability.