979 resultados para customer-order-driven


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This thesis discusses the design of a system to use wave energy to pump oxygen-rich surface water towards the bottom of the sea. A simple device, called OXYFLUX, is proposed in a scale model and tested in a wave flume in order to validate its supposed theoretical functioning. Once its effectiveness has been demonstrated, a overset mesh, CFD model has been developed and validated by means of the physical model results. Both numerical and physical results show how wave height affects the behavior of the device. Wave heights lower than about 0.5 m overtop the floater and fall into it. As the wave height increases, phase shift between water surface and vertical displacement of the device also increases its influence on the functioning mechanism. In these situations, with wave heights between 0.5 and 0.9 m, the downward flux is due to the higher head established in the water column inside the device respect to the outside wave field. Furthermore, as the wave height grows over 0.9 m, water flux inverts the direction thanks to depression caused by the wave crest pass over the floater. In this situation the wave crest goes over the float but does not go into it and it draws water from the bottom to the surface through the device pipe. By virtue of these results a new shape of the floater has been designed and tested in CFD model. Such new geometry is based on the already known Lazzari’s profile and it aims to grab as much water as possible from the wave crest during the emergence of the floater from the wave field. Results coming from the new device are compared with the first ones in order to identify differences between the two shapes and their possible areas of application.

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A significant cost for foundations is the design and installation of piles when they are required due to poor ground conditions. Not only is it important that piles be designed properly, but also that the installation equipment and total cost be evaluated. To assist in the evaluation of piles a number of methods have been developed. In this research three of these methods were investigated, which were developed by the Federal Highway Administration, the US Corps of Engineers and the American Petroleum Institute (API). The results from these methods were entered into the program GRLWEAPTM to assess the pile drivability and to provide a standard base for comparing the three methods. An additional element of this research was to develop EXCEL spreadsheets to implement these three methods. Currently the Army Corps and API methods do not have publicly available software and must be performed manually, which requires that data is taken off of figures and tables, which can introduce error in the prediction of pile capacities. Following development of the EXCEL spreadsheet, they were validated with both manual calculations and existing data sets to ensure that the data output is correct. To evaluate the three pile capacity methods data was utilized from four project sites from North America. The data included site geotechnical data along with field determined pile capacities. In order to achieve a standard comparison of the data, the pile capacities and geotechnical data from the three methods were entered into GRLWEAPTM. The sites consisted of both cohesive and cohesionless soils; where one site was primarily cohesive, one was primarily cohesionless, and the other two consisted of inter-bedded cohesive and cohesionless soils. Based on this limited set of data the results indicated that the US Corps of Engineers method more closely compared with the field test data, followed by the API method to a lesser degree. The DRIVEN program compared favorably in cohesive soils, but over predicted in cohesionless material.

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In manual order picking systems, order pickers walk or drive through a distribution warehouse in order to collect items which are requested by (internal or external) customers. In order to perform these operations efficiently, it is usually required that customer orders are combined into (more substantial) picking orders of limited size. The Order Batching Problem considered in this paper deals with the question of how a given set of customer orders should be combined such that the total length of all tours is minimized which are necessary to collect all items. The authors introduce two metaheuristic approaches for the solution of this problem: the first one is based on Iterated Local Search; the second on Ant Colony Optimization. In a series of extensive numerical experiments, the newly developed approaches are benchmarked against classic solution methods. It is demonstrated that the proposed methods are not only superior to existing methods but provide solutions which may allow distribution warehouses to be operated significantly more efficiently.

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Nicht nur die vielfältigen funktionsbezogenen Anforderungen von Produkten und Bauteilen, sondern vor allem die heutigen Marktbedürfnisse stellen große Herausforderungen für aktuelle Fertigungstechnologien dar. Hierbei bildet die kontinuierlich steigende Variantenvielfalt bei gleichzeitiger Senkung der Stückzahlen je Variante die differenzierten Kundenwünsche ab. Diese Entwicklungen begünstigen die Perspektiven des Laserstrahlschmelzens im Allgemeinen sowie seiner speziellen Anwendungsgebiete Rapid Prototyping, Rapid Tooling und Rapid Manufac-turing. In den Branchen der Medizintechnik und der Gummi- und Kunststoffverarbeitung ist bereits seit einiger Zeit eine dynamische Entwicklung erkennbar. Besonders in der Medizintechnik wird der immer breitere Einsatz des Laserstrahlschmelzens durch die hohe Innovationsfähigkeit des Verfahrens und ein verbesserstes Qualitäts-management vorangetrieben. Aufgrund der zunehmenden Forderungen nach individualisierten und individuellen Produkten werden bereits heute patientenangepasste Implantate mit dem Laserstrahlschmelzverfahren gefertigt. Erwarten die Marktteilnehmer eine weiterhin steigende Nachfrage nach solchen Produkten? Wie muss das Verfah-ren verbessert werden, um seine Prozessstabilität zu erhöhen? Wo liegen die zukünftigen Herausforderungen in der Strahlschmelztechnologie? Um diese und weitere Fragen zu klären hat das Fraunhofer Institut für Produkti-onsanlagen und Konstruktionstechnik (IPK) eine Markt- und Trendanalyse für das Laserstrahlschmelzen durchge-führt.

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Dike swarms consisting of tens to thousands of subparallel dikes are commonly observed at Earth's surface, raising the possibility of simultaneous propagation of two or more dikes at various stages of a swarm's development. The behavior of multiple propagating dikes differs from that of a single dike owing to the interacting stress fields associated with each dike. We analyze an array of parallel, periodically spaced dikes that grow simultaneously from an overpressured source into a semi-infinite, linear elastic host rock. To simplify the analysis, we assume steady state (constant velocity) magma flow and dike propagation. We use a perturbation method to analyze the coupled, nonlinear problem of multiple dike propagation and magma transport. The stress intensity factor at the dike tips and the opening displacements of the dike surfaces are calculated. The numerical results show that dike spacing has a profound effect on the behavior of dike propagation. The stress intensity factors at the tips of parallel dikes decrease with a decrease in dike spacing and are significantly smaller than that for a single dike with the same length. The reduced stress intensity factor indicates that, compared to a single dike, propagation of parallel dikes is more likely to be arrested under otherwise the same conditions. It also implies that fracture toughness of the host rock in a high confining pressure environment may not be as high as inferred from the propagation of a single dike. Our numerical results suggest fracture toughness values on the order of 100 MPa root m. The opening displacements for parallel dikes are smaller than that for a single dike, which results in higher magma pressure gradients in parallel dikes and lower flux of magma transport.

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We study the strength of the electroweak phase transition in models with two light Higgs doublets and a light SU(3)c triplet by means of lattice simulations in a dimensionally reduced effective theory. In the parameter region considered the transition on the lattice is significantly stronger than indicated by a 2-loop perturbative analysis. Within some ultraviolet uncertainties, the finding applies to MSSM with a Higgs mass mh ≈ 126 GeV and shows that the parameter region useful for electroweak baryogenesis is enlarged. In particular (even though only dedicated analyses can quantify the issue), the tension between LHC constraints after the 7 TeV and 8 TeV runs and frameworks where the electroweak phase transition is driven by light stops, seems to be relaxed.

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Offset printing is a common method to produce large amounts of printed matter. We consider a real-world offset printing process that is used to imprint customer-specific designs on napkin pouches. The production equipment used gives rise to various technological constraints. The planning problem consists of allocating designs to printing-plate slots such that the given customer demand for each design is fulfilled, all technological and organizational constraints are met and the total overproduction and setup costs are minimized. We formulate this planning problem as a mixed-binary linear program, and we develop a multi-pass matching-based savings heuristic. We report computational results for a set of problem instances devised from real-world data.

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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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Ocean acidification (OA) is expected to drive the transition of coral reef ecosystems from net calcium carbonate (CaCO3) precipitating to net dissolving within the next century. Although permeable sediments represent the largest reservoir of CaCO3 in coral reefs, the dissolution of shallow CaCO3 sands under future pCO2 levels has not been measured under natural conditions. In situ, advective chamber incubations under elevated pCO2 (~800 µatm) shifted the sediments from net precipitating to net dissolving. Pore water advection more than doubled dissolution rates (1.10 g CaCO3/m**2/day) when compared to diffusive conditions (0.42 g CaCO3/m**2 /day). Sediment dissolution could reduce net ecosystem calcification rates of the Heron Island lagoon by 8% within the next century, which is equivalent to a 25% reduction in the global average calcification rate of coral lagoons. The dissolution of CaCO3 sediments needs to be taken into account in order to address how OA will impact the net accretion of coral reefs under future predicted increases in CO2.

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Surface tension induced convection in a liquid bridge held between two parallel, coaxial, solid disks is considered. The surface tension gradient is produced by a small temperature gradient parallel Co the undisturbed surface. The study is performed by using a mathematical regular perturbation approach based on a small parameter, e, which measures the deviation of the imposed temperature field from its mean value. The first order velocity field is given by a Stokes-type problem (viscous terms are dominant) with relatively simple boundary conditions. The first order temperature field is that imposed from the end disks on a liquid bridge immersed in a non-conductive fluid. Radiative effects are supposed to be negligible. The second order temperature field, which accounts for convective effects, is split into three components, one due to the bulk motion, and the other two to the distortion of the free surface. The relative importance of these components in terms of the heat transfer to or from the end disks is assessed

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In this introductory chapter we put in context and give a brief outline of the work that we thoroughly present in the rest of the dissertation. We consider this work divided in two main parts. The first part is the Firenze Framework, a knowledge level description framework rich enough to express the semantics required for describing both semantic Web services and semantic Grid services. We start by defining what the Semantic Grid is and its relation with the Semantic Web; and the possibility of their convergence since both initiatives have become mainly service-oriented. We also introduce the main motivators of the creation of this framework, one is to provide a valid description framework that works at knowledge level; the other to provide a description framework that takes into account the characteristics of Grid services in order to be able to describe them properly. The other part of the dissertation is devoted to Vega, an event-driven architecture that, by means of proposed knowledge level description framework, is able to achieve high scale provisioning of knowledge-intensive services. In this introductory chapter we portrait the anatomy of a generic event-driven architecture, and we briefly enumerate their main characteristics, which are the reason that make them our choice.

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Several activities in service oriented computing, such as automatic composition, monitoring, and adaptation, can benefit from knowing properties of a given service composition before executing them. Among these properties we will focus on those related to execution cost and resource usage, in a wide sense, as they can be linked to QoS characteristics. In order to attain more accuracy, we formulate execution costs / resource usage as functions on input data (or appropriate abstractions thereof) and show how these functions can be used to make better, more informed decisions when performing composition, adaptation, and proactive monitoring. We present an approach to, on one hand, synthesizing these functions in an automatic fashion from the definition of the different orchestrations taking part in a system and, on the other hand, to effectively using them to reduce the overall costs of non-trivial service-based systems featuring sensitivity to data and possibility of failure. We validate our approach by means of simulations of scenarios needing runtime selection of services and adaptation due to service failure. A number of rebinding strategies, including the use of cost functions, are compared.

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Some basic ideas are presented for the construction of robust, computationally efficient reduced order models amenable to be used in industrial environments, combined with somewhat rough computational fluid dynamics solvers. These ideas result from a critical review of the basic principles of proper orthogonal decomposition-based reduced order modeling of both steady and unsteady fluid flows. In particular, the extent to which some artifacts of the computational fluid dynamics solvers can be ignored is addressed, which opens up the possibility of obtaining quite flexible reduced order models. The methods are illustrated with the steady aerodynamic flow around a horizontal tail plane of a commercial aircraft in transonic conditions, and the unsteady lid-driven cavity problem. In both cases, the approximations are fairly good, thus reducing the computational cost by a significant factor.

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It is easy to get frustrated at spoken conversational agents (SCAs), perhaps because they seem to be callous. By and large, the quality of human-computer interaction is affected due to the inability of the SCAs to recognise and adapt to user emotional state. Now with the mass appeal of artificially-mediated communication, there has been an increasing need for SCAs to be socially and emotionally intelligent, that is, to infer and adapt to their human interlocutors’ emotions on the fly, in order to ascertain an affective, empathetic and naturalistic interaction. An enhanced quality of interaction would reduce users’ frustrations and consequently increase their satisfactions. These reasons have motivated the development of SCAs towards including socio-emotional elements, turning them into affective and socially-sensitive interfaces. One barrier to the creation of such interfaces has been the lack of methods for modelling emotions in a task-independent environment. Most emotion models for spoken dialog systems are task-dependent and thus cannot be used “as-is” in different applications. This Thesis focuses on improving this, in which it concerns computational modeling of emotion, personality and their interrelationship for task-independent autonomous SCAs. The generation of emotion is driven by needs, inspired by human’s motivational systems. The work in this Thesis is organised in three stages, each one with its own contribution. The first stage involved defining, integrating and quantifying the psychological-based motivational and emotional models sourced from. Later these were transformed into a computational model by implementing them into software entities. The computational model was then incorporated and put to test with an existing SCA host, a HiFi-control agent. The second stage concerned automatic prediction of affect, which has been the main challenge towards the greater aim of infusing social intelligence into the HiFi agent. In recent years, studies on affect detection from voice have moved on to using realistic, non-acted data, which is subtler. However, it is more challenging to perceive subtler emotions and this is demonstrated in tasks such as labelling and machine prediction. In this stage, we attempted to address part of this challenge by considering the roles of user satisfaction ratings and conversational/dialog features as the respective target and predictors in discriminating contentment and frustration, two types of emotions that are known to be prevalent within spoken human-computer interaction. The final stage concerned the evaluation of the emotional model through the HiFi agent. A series of user studies with 70 subjects were conducted in a real-time environment, each in a different phase and with its own conditions. All the studies involved the comparisons between the baseline non-modified and the modified agent. The findings have gone some way towards enhancing our understanding of the utility of emotion in spoken dialog systems in several ways; first, an SCA should not express its emotions blindly, albeit positive. Rather, it should adapt its emotions to user states. Second, low performance in an SCA may be compensated by the exploitation of emotion. Third, the expression of emotion through the exploitation of prosody could better improve users’ perceptions of an SCA compared to exploiting emotions through just lexical contents. Taken together, these findings not only support the success of the emotional model, but also provide substantial evidences with respect to the benefits of adding emotion in an SCA, especially in mitigating users’ frustrations and ultimately improving their satisfactions. Resumen Es relativamente fácil experimentar cierta frustración al interaccionar con agentes conversacionales (Spoken Conversational Agents, SCA), a menudo porque parecen ser un poco insensibles. En general, la calidad de la interacción persona-agente se ve en cierto modo afectada por la incapacidad de los SCAs para identificar y adaptarse al estado emocional de sus usuarios. Actualmente, y debido al creciente atractivo e interés de dichos agentes, surge la necesidad de hacer de los SCAs unos seres cada vez más sociales y emocionalmente inteligentes, es decir, con capacidad para inferir y adaptarse a las emociones de sus interlocutores humanos sobre la marcha, de modo que la interacción resulte más afectiva, empática y, en definitiva, natural. Una interacción mejorada en este sentido permitiría reducir la posible frustración de los usuarios y, en consecuencia, mejorar el nivel de satisfacción alcanzado por los mismos. Estos argumentos justifican y motivan el desarrollo de nuevos SCAs con capacidades socio-emocionales, dotados de interfaces afectivas y socialmente sensibles. Una de las barreras para la creación de tales interfaces ha sido la falta de métodos de modelado de emociones en entornos independientes de tarea. La mayoría de los modelos emocionales empleados por los sistemas de diálogo hablado actuales son dependientes de tarea y, por tanto, no pueden utilizarse "tal cual" en diferentes dominios o aplicaciones. Esta tesis se centra precisamente en la mejora de este aspecto, la definición de modelos computacionales de las emociones, la personalidad y su interrelación para SCAs autónomos e independientes de tarea. Inspirada en los sistemas motivacionales humanos en el ámbito de la psicología, la tesis propone un modelo de generación/producción de la emoción basado en necesidades. El trabajo realizado en la presente tesis está organizado en tres etapas diferenciadas, cada una con su propia contribución. La primera etapa incluyó la definición, integración y cuantificación de los modelos motivacionales de partida y de los modelos emocionales derivados a partir de éstos. Posteriormente, dichos modelos emocionales fueron plasmados en un modelo computacional mediante su implementación software. Este modelo computacional fue incorporado y probado en un SCA anfitrión ya existente, un agente con capacidad para controlar un equipo HiFi, de alta fidelidad. La segunda etapa se orientó hacia el reconocimiento automático de la emoción, aspecto que ha constituido el principal desafío en relación al objetivo mayor de infundir inteligencia social en el agente HiFi. En los últimos años, los estudios sobre reconocimiento de emociones a partir de la voz han pasado de emplear datos actuados a usar datos reales en los que la presencia u observación de emociones se produce de una manera mucho más sutil. El reconocimiento de emociones bajo estas condiciones resulta mucho más complicado y esta dificultad se pone de manifiesto en tareas tales como el etiquetado y el aprendizaje automático. En esta etapa, se abordó el problema del reconocimiento de las emociones del usuario a partir de características o métricas derivadas del propio diálogo usuario-agente. Gracias a dichas métricas, empleadas como predictores o indicadores del grado o nivel de satisfacción alcanzado por el usuario, fue posible discriminar entre satisfacción y frustración, las dos emociones prevalentes durante la interacción usuario-agente. La etapa final corresponde fundamentalmente a la evaluación del modelo emocional por medio del agente Hifi. Con ese propósito se llevó a cabo una serie de estudios con usuarios reales, 70 sujetos, interaccionando con diferentes versiones del agente Hifi en tiempo real, cada uno en una fase diferente y con sus propias características o capacidades emocionales. En particular, todos los estudios realizados han profundizado en la comparación entre una versión de referencia del agente no dotada de ningún comportamiento o característica emocional, y una versión del agente modificada convenientemente con el modelo emocional propuesto. Los resultados obtenidos nos han permitido comprender y valorar mejor la utilidad de las emociones en los sistemas de diálogo hablado. Dicha utilidad depende de varios aspectos. En primer lugar, un SCA no debe expresar sus emociones a ciegas o arbitrariamente, incluso aunque éstas sean positivas. Más bien, debe adaptar sus emociones a los diferentes estados de los usuarios. En segundo lugar, un funcionamiento relativamente pobre por parte de un SCA podría compensarse, en cierto modo, dotando al SCA de comportamiento y capacidades emocionales. En tercer lugar, aprovechar la prosodia como vehículo para expresar las emociones, de manera complementaria al empleo de mensajes con un contenido emocional específico tanto desde el punto de vista léxico como semántico, ayuda a mejorar la percepción por parte de los usuarios de un SCA. Tomados en conjunto, los resultados alcanzados no sólo confirman el éxito del modelo emocional, sino xv que constituyen además una evidencia decisiva con respecto a los beneficios de incorporar emociones en un SCA, especialmente en cuanto a reducir el nivel de frustración de los usuarios y, en última instancia, mejorar su satisfacción.

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Advances in electronics nowadays facilitate the design of smart spaces based on physical mash-ups of sensor and actuator devices. At the same time, software paradigms such as Internet of Things (IoT) and Web of Things (WoT) are motivating the creation of technology to support the development and deployment of web-enabled embedded sensor and actuator devices with two major objectives: (i) to integrate sensing and actuating functionalities into everyday objects, and (ii) to easily allow a diversity of devices to plug into the Internet. Currently, developers who are applying this Internet-oriented approach need to have solid understanding about specific platforms and web technologies. In order to alleviate this development process, this research proposes a Resource-Oriented and Ontology-Driven Development (ROOD) methodology based on the Model Driven Architecture (MDA). This methodology aims at enabling the development of smart spaces through a set of modeling tools and semantic technologies that support the definition of the smart space and the automatic generation of code at hardware level. ROOD feasibility is demonstrated by building an adaptive health monitoring service for a Smart Gym.