930 resultados para System Computing


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Background Access to health care can be described along four dimensions: geographic accessibility, availability, financial accessibility and acceptability. Geographic accessibility measures how physically accessible resources are for the population, while availability reflects what resources are available and in what amount. Combining these two types of measure into a single index provides a measure of geographic (or spatial) coverage, which is an important measure for assessing the degree of accessibility of a health care network. Results This paper describes the latest version of AccessMod, an extension to the Geographical Information System ArcView 3.×, and provides an example of application of this tool. AccessMod 3 allows one to compute geographic coverage to health care using terrain information and population distribution. Four major types of analysis are available in AccessMod: (1) modeling the coverage of catchment areas linked to an existing health facility network based on travel time, to provide a measure of physical accessibility to health care; (2) modeling geographic coverage according to the availability of services; (3) projecting the coverage of a scaling-up of an existing network; (4) providing information for cost effectiveness analysis when little information about the existing network is available. In addition to integrating travelling time, population distribution and the population coverage capacity specific to each health facility in the network, AccessMod can incorporate the influence of landscape components (e.g. topography, river and road networks, vegetation) that impact travelling time to and from facilities. Topographical constraints can be taken into account through an anisotropic analysis that considers the direction of movement. We provide an example of the application of AccessMod in the southern part of Malawi that shows the influences of the landscape constraints and of the modes of transportation on geographic coverage. Conclusion By incorporating the demand (population) and the supply (capacities of heath care centers), AccessMod provides a unifying tool to efficiently assess the geographic coverage of a network of health care facilities. This tool should be of particular interest to developing countries that have a relatively good geographic information on population distribution, terrain, and health facility locations.

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Die voranschreitende Entwicklung von Konzepten und Systemen zur Nutzung digitaler Informationen im industriellen Umfeld eröffnet verschiedenste Möglichkeiten zur Optimierung der Informationsverarbeitung und damit der Prozesseffektivität und -effizienz. Werden die relevanten Daten zu Produkten oder Prozessen jedoch lediglich in digitaler Form zur Verfügung gestellt, fällt ein Eingriff des Menschen in die virtuelle Welt immer schwerer. Auf Grundlage dessen wird am Beispiel der RFIDTechnologie dargestellt, inwiefern digitale Informationen durch die Verwendung von in den Arbeitsablauf integrierten Systemen für den Menschen nutzbar werden. Durch die Entwicklung eines Systems zur papierlosen Produktion und Logistik werden exemplarisch Einsatzszenarien zur Unterstützung des Mitarbeiters in Montageprozessen sowie zur Vermeidung von Fehlern in der Kommissionierung aufgezeigt. Dazu findet neben einer am Kopf getragenen Datenbrille zur Visualisierung der Informationen ein mobiles RFID-Lesegerät Anwendung, mit Hilfe dessen die digitalen Transponderdaten ohne zusätzlichen Aufwand für den Anwender genutzt werden können.

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Recent advancements in cloud computing have enabled the proliferation of distributed applications, which require management and control of multiple services. However, without an efficient mechanism for scaling services in response to changing environmental conditions and number of users, application performance might suffer, leading to Service Level Agreement (SLA) violations and inefficient use of hardware resources. We introduce a system for controlling the complexity of scaling applications composed of multiple services using mechanisms based on fulfillment of SLAs. We present how service monitoring information can be used in conjunction with service level objectives, predictions, and correlations between performance indicators for optimizing the allocation of services belonging to distributed applications. We validate our models using experiments and simulations involving a distributed enterprise information system. We show how discovering correlations between application performance indicators can be used as a basis for creating refined service level objectives, which can then be used for scaling the application and improving the overall application's performance under similar conditions.

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Cloud Computing enables provisioning and distribution of highly scalable services in a reliable, on-demand and sustainable manner. However, objectives of managing enterprise distributed applications in cloud environments under Service Level Agreement (SLA) constraints lead to challenges for maintaining optimal resource control. Furthermore, conflicting objectives in management of cloud infrastructure and distributed applications might lead to violations of SLAs and inefficient use of hardware and software resources. This dissertation focusses on how SLAs can be used as an input to the cloud management system, increasing the efficiency of allocating resources, as well as that of infrastructure scaling. First, we present an extended SLA semantic model for modelling complex service-dependencies in distributed applications, and for enabling automated cloud infrastructure management operations. Second, we describe a multi-objective VM allocation algorithm for optimised resource allocation in infrastructure clouds. Third, we describe a method of discovering relations between the performance indicators of services belonging to distributed applications and then using these relations for building scaling rules that a CMS can use for automated management of VMs. Fourth, we introduce two novel VM-scaling algorithms, which optimally scale systems composed of VMs, based on given SLA performance constraints. All presented research works were implemented and tested using enterprise distributed applications.

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Advancements in cloud computing have enabled the proliferation of distributed applications, which require management and control of multiple services. However, without an efficient mechanism for scaling services in response to changing workload conditions, such as number of connected users, application performance might suffer, leading to violations of Service Level Agreements (SLA) and possible inefficient use of hardware resources. Combining dynamic application requirements with the increased use of virtualised computing resources creates a challenging resource Management context for application and cloud-infrastructure owners. In such complex environments, business entities use SLAs as a means for specifying quantitative and qualitative requirements of services. There are several challenges in running distributed enterprise applications in cloud environments, ranging from the instantiation of service VMs in the correct order using an adequate quantity of computing resources, to adapting the number of running services in response to varying external loads, such as number of users. The application owner is interested in finding the optimum amount of computing and network resources to use for ensuring that the performance requirements of all her/his applications are met. She/he is also interested in appropriately scaling the distributed services so that application performance guarantees are maintained even under dynamic workload conditions. Similarly, the infrastructure Providers are interested in optimally provisioning the virtual resources onto the available physical infrastructure so that her/his operational costs are minimized, while maximizing the performance of tenants’ applications. Motivated by the complexities associated with the management and scaling of distributed applications, while satisfying multiple objectives (related to both consumers and providers of cloud resources), this thesis proposes a cloud resource management platform able to dynamically provision and coordinate the various lifecycle actions on both virtual and physical cloud resources using semantically enriched SLAs. The system focuses on dynamic sizing (scaling) of virtual infrastructures composed of virtual machines (VM) bounded application services. We describe several algorithms for adapting the number of VMs allocated to the distributed application in response to changing workload conditions, based on SLA-defined performance guarantees. We also present a framework for dynamic composition of scaling rules for distributed service, which used benchmark-generated application Monitoring traces. We show how these scaling rules can be combined and included into semantic SLAs for controlling allocation of services. We also provide a detailed description of the multi-objective infrastructure resource allocation problem and various approaches to satisfying this problem. We present a resource management system based on a genetic algorithm, which performs allocation of virtual resources, while considering the optimization of multiple criteria. We prove that our approach significantly outperforms reactive VM-scaling algorithms as well as heuristic-based VM-allocation approaches.

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Aims. We extend the results of planetary formation synthesis by computing the long-term evolution of synthetic systems from the clearing of the gas disk into the dynamical evolution phase. Methods. We use the symplectic integrator SyMBA to numerically integrate the orbits of planets for 100 Myr, using populations from previous studies as initial conditions. Results. We show that within the populations studied, mass and semimajor axis distributions experience only minor changes from post-formation evolution. We also show that, depending upon their initial distribution, planetary eccentricities can statistically increase or decrease as a result of gravitational interactions. We find that planetary masses and orbital spacings provided by planet formation models do not result in eccentricity distributions comparable to observed exoplanet eccentricities, requiring other phenomena, such as stellar fly-bys, to account for observed eccentricities.

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Embedded context management in resource-constrained devices (e.g. mobile phones, autonomous sensors or smart objects) imposes special requirements in terms of lightness for data modelling and reasoning. In this paper, we explore the state-of-the-art on data representation and reasoning tools for embedded mobile reasoning and propose a light inference system (LIS) aiming at simplifying embedded inference processes offering a set of functionalities to avoid redundancy in context management operations. The system is part of a service-oriented mobile software framework, conceived to facilitate the creation of context-aware applications—it decouples sensor data acquisition and context processing from the application logic. LIS, composed of several modules, encapsulates existing lightweight tools for ontology data management and rule-based reasoning, and it is ready to run on Java-enabled handheld devices. Data management and reasoning processes are designed to handle a general ontology that enables communication among framework components. Both the applications running on top of the framework and the framework components themselves can configure the rule and query sets in order to retrieve the information they need from LIS. In order to test LIS features in a real application scenario, an ‘Activity Monitor’ has been designed and implemented: a personal health-persuasive application that provides feedback on the user’s lifestyle, combining data from physical and virtual sensors. In this case of use, LIS is used to timely evaluate the user’s activity level, to decide on the convenience of triggering notifications and to determine the best interface or channel to deliver these context-aware alerts.d

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Managing large medical image collections is an increasingly demanding important issue in many hospitals and other medical settings. A huge amount of this information is daily generated, which requires robust and agile systems. In this paper we present a distributed multi-agent system capable of managing very large medical image datasets. In this approach, agents extract low-level information from images and store them in a data structure implemented in a relational database. The data structure can also store semantic information related to images and particular regions. A distinctive aspect of our work is that a single image can be divided so that the resultant sub-images can be stored and managed separately by different agents to improve performance in data accessing and processing. The system also offers the possibility of applying some region-based operations and filters on images, facilitating image classification. These operations can be performed directly on data structures in the database.

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The European Credit Transfer and Accumulation System (ECTS) is the credit system for higher education used in the European Higher Education Area (EHEA), which involves all the countries engaged in the Bologna Process. This paper describes a study which is part of the project of the Bologna Experts Team-Spain and was carried out with the following aims: 1) designing some procedures for the assessment of transferable competences; and 2) testing some basic psychometric features that an assessment device with some consequences for the subjects being evaluated needs to prove. We will focus on the degrees of Computing. The sample of students (20) includes first year students from the Technical University of Madrid. In this paper, we will report some results of data analyses carried out to this moment on reliability and validity of the task designed to measure problem solving.

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Industrial applications of computer vision sometimes require detection of atypical objects that occur as small groups of pixels in digital images. These objects are difficult to single out because they are small and randomly distributed. In this work we propose an image segmentation method using the novel Ant System-based Clustering Algorithm (ASCA). ASCA models the foraging behaviour of ants, which move through the data space searching for high data-density regions, and leave pheromone trails on their path. The pheromone map is used to identify the exact number of clusters, and assign the pixels to these clusters using the pheromone gradient. We applied ASCA to detection of microcalcifications in digital mammograms and compared its performance with state-of-the-art clustering algorithms such as 1D Self-Organizing Map, k-Means, Fuzzy c-Means and Possibilistic Fuzzy c-Means. The main advantage of ASCA is that the number of clusters needs not to be known a priori. The experimental results show that ASCA is more efficient than the other algorithms in detecting small clusters of atypical data.

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This article evaluates an authentication technique for mobiles based on gestures. Users create a remindful identifying gesture to be considered as their in-air signature. This work analyzes a database of 120 gestures of different vulnerability, obtaining an Equal Error Rate (EER) of 9.19% when robustness of gestures is not verified. Most of the errors in this EER come from very simple and easily forgeable gestures that should be discarded at enrollment phase. Therefore, an in-air signature robustness verification system using Linear Discriminant Analysis is proposed to infer automatically whether the gesture is secure or not. Different configurations have been tested obtaining a lowest EER of 4.01% when 45.02% of gestures were discarded, and an optimal compromise of EER of 4.82% when 19.19% of gestures were automatically rejected.

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The &-Prolog system, a practical implementation of a parallel execution niodel for Prolog exploiting strict and non-strict independent and-parallelism, is described. Both automatic and manual parallelization of programs is supported. This description includes a summary of the system's language and architecture, some details of its execution model (based on the RAP-WAM model), and data on its performance on sequential workstations and shared memory multiprocessors, which is compared to that of current Prolog systems. The results to date show significant speed advantages over state-of-the-art sequential systems.

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Multi-user videoconferencing systems offer communication between more than two users, who are able to interact through their webcams, microphones and other components. The use of these systems has been increased recently due to, on the one hand, improvements in Internet access, networks of companies, universities and houses, whose available bandwidth has been increased whilst the delay in sending and receiving packets has decreased. On the other hand, the advent of Rich Internet Applications (RIA) means that a large part of web application logic and control has started to be implemented on the web browsers. This has allowed developers to create web applications with a level of complexity comparable to traditional desktop applications, running on top of the Operating Systems. More recently the use of Cloud Computing systems has improved application scalability and involves a reduction in the price of backend systems. This offers the possibility of implementing web services on the Internet with no need to spend a lot of money when deploying infrastructures and resources, both hardware and software. Nevertheless there are not many initiatives that aim to implement videoconferencing systems taking advantage of Cloud systems. This dissertation proposes a set of techniques, interfaces and algorithms for the implementation of videoconferencing systems in public and private Cloud Computing infrastructures. The mechanisms proposed here are based on the implementation of a basic videoconferencing system that runs on the web browser without any previous installation requirements. To this end, the development of this thesis starts from a RIA application with current technologies that allow users to access their webcams and microphones from the browser, and to send captured data through their Internet connections. Furthermore interfaces have been implemented to allow end users to participate in videoconferencing rooms that are managed in different Cloud provider servers. To do so this dissertation starts from the results obtained from the previous techniques and backend resources were implemented in the Cloud. A traditional videoconferencing service which was implemented in the department was modified to meet typical Cloud Computing infrastructure requirements. This allowed us to validate whether Cloud Computing public infrastructures are suitable for the traffic generated by this kind of system. This analysis focused on the network level and processing capacity and stability of the Cloud Computing systems. In order to improve this validation several other general considerations were taken in order to cover more cases, such as multimedia data processing in the Cloud, as research activity has increased in this area in recent years. The last stage of this dissertation is the design of a new methodology to implement these kinds of applications in hybrid clouds reducing the cost of videoconferencing systems. Finally, this dissertation opens up a discussion about the conclusions obtained throughout this study, resulting in useful information from the different stages of the implementation of videoconferencing systems in Cloud Computing systems. RESUMEN Los sistemas de videoconferencia multiusuario permiten la comunicación entre más de dos usuarios que pueden interactuar a través de cámaras de video, micrófonos y otros elementos. En los últimos años el uso de estos sistemas se ha visto incrementado gracias, por un lado, a la mejora de las redes de acceso en las conexiones a Internet en empresas, universidades y viviendas, que han visto un aumento del ancho de banda disponible en dichas conexiones y una disminución en el retardo experimentado por los datos enviados y recibidos. Por otro lado también ayudó la aparación de las Aplicaciones Ricas de Internet (RIA) con las que gran parte de la lógica y del control de las aplicaciones web comenzó a ejecutarse en los mismos navegadores. Esto permitió a los desarrolladores la creación de aplicaciones web cuya complejidad podía compararse con la de las tradicionales aplicaciones de escritorio, ejecutadas directamente por los sistemas operativos. Más recientemente el uso de sistemas de Cloud Computing ha mejorado la escalabilidad y el abaratamiento de los costes para sistemas de backend, ofreciendo la posibilidad de implementar servicios Web en Internet sin la necesidad de grandes desembolsos iniciales en las áreas de infraestructuras y recursos tanto hardware como software. Sin embargo no existen aún muchas iniciativas con el objetivo de realizar sistemas de videoconferencia que aprovechen las ventajas del Cloud. Esta tesis doctoral propone un conjunto de técnicas, interfaces y algoritmos para la implentación de sistemas de videoconferencia en infraestructuras tanto públicas como privadas de Cloud Computing. Las técnicas propuestas en la tesis se basan en la realización de un servicio básico de videoconferencia que se ejecuta directamente en el navegador sin la necesidad de instalar ningún tipo de aplicación de escritorio. Para ello el desarrollo de esta tesis parte de una aplicación RIA con tecnologías que hoy en día permiten acceder a la cámara y al micrófono directamente desde el navegador, y enviar los datos que capturan a través de la conexión de Internet. Además se han implementado interfaces que permiten a usuarios finales la participación en salas de videoconferencia que se ejecutan en servidores de proveedores de Cloud. Para ello se partió de los resultados obtenidos en las técnicas anteriores de ejecución de aplicaciones en el navegador y se implementaron los recursos de backend en la nube. Además se modificó un servicio ya existente implementado en el departamento para adaptarlo a los requisitos típicos de las infraestructuras de Cloud Computing. Alcanzado este punto se procedió a analizar si las infraestructuras propias de los proveedores públicos de Cloud Computing podrían soportar el tráfico generado por los sistemas que se habían adaptado. Este análisis se centró tanto a nivel de red como a nivel de capacidad de procesamiento y estabilidad de los sistemas. Para los pasos de análisis y validación de los sistemas Cloud se tomaron consideraciones más generales para abarcar casos como el procesamiento de datos multimedia en la nube, campo en el que comienza a haber bastante investigación en los últimos años. Como último paso se ideó una metodología de implementación de este tipo de aplicaciones para que fuera posible abaratar los costes de los sistemas de videoconferencia haciendo uso de clouds híbridos. Finalmente en la tesis se abre una discusión sobre las conclusiones obtenidas a lo largo de este amplio estudio, obteniendo resultados útiles en las distintas etapas de implementación de los sistemas de videoconferencia en la nube.

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One of the advantages of social networks is the possibility to socialize and personalize the content created or shared by the users. In mobile social networks, where the devices have limited capabilities in terms of screen size and computing power, Multimedia Recommender Systems help to present the most relevant content to the users, depending on their tastes, relationships and profile. Previous recommender systems are not able to cope with the uncertainty of automated tagging and are knowledge domain dependant. In addition, the instantiation of a recommender in this domain should cope with problems arising from the collaborative filtering inherent nature (cold start, banana problem, large number of users to run, etc.). The solution presented in this paper addresses the abovementioned problems by proposing a hybrid image recommender system, which combines collaborative filtering (social techniques) with content-based techniques, leaving the user the liberty to give these processes a personal weight. It takes into account aesthetics and the formal characteristics of the images to overcome the problems of current techniques, improving the performance of existing systems to create a mobile social networks recommender with a high degree of adaptation to any kind of user.

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Embedded context management in resource-constrained devices (e.g. mobile phones, autonomous sensors or smart objects) imposes special requirements in terms of lightness for data modelling and reasoning. In this paper, we explore the state-of-the-art on data representation and reasoning tools for embedded mobile reasoning and propose a light inference system (LIS) aiming at simplifying embedded inference processes offering a set of functionalities to avoid redundancy in context management operations. The system is part of a service-oriented mobile software framework, conceived to facilitate the creation of context-aware applications?it decouples sensor data acquisition and context processing from the application logic. LIS, composed of several modules, encapsulates existing lightweight tools for ontology data management and rule-based reasoning, and it is ready to run on Java-enabled handheld devices. Data management and reasoning processes are designed to handle a general ontology that enables communication among framework components. Both the applications running on top of the framework and the framework components themselves can configure the rule and query sets in order to retrieve the information they need from LIS. In order to test LIS features in a real application scenario, an ?Activity Monitor? has been designed and implemented: a personal health-persuasive application that provides feedback on the user?s lifestyle, combining data from physical and virtual sensors. In this case of use, LIS is used to timely evaluate the user?s activity level, to decide on the convenience of triggering notifications and to determine the best interface or channel to deliver these context-aware alerts.