986 resultados para Traction-engines


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Social scientists and other analysts have written about medicalization since at least the 1970s. Most of these studies depict the medical profession, interprofessional or organizational contests, or social movements and interest groups as the prime movers toward medicalization. This article contends that changes in medicine in the past two decades are altering the medicalization process. Using several case examples, I argue that three major changes in medical knowledge and organization have engendered an important shift in the engines that drive medicalization: biotechnology (especially the pharmaceutical industry and genetics), consumers, and managed care. Doctors are still gatekeepers for medical treatment, but their role has become more subordinate in the expansion or contraction of medicalization. Medicalization is now more driven by commercial and market interests than by professional claims-makers. The definitional center of medicalization remains constant, but the availability of new pharmaceutical and potential genetic treatments are increasingly drivers for new medical categories. This requires a shift in the sociological focus examining medicalization for the twenty-first century.

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In any internal combustion engine, the amount of heat rejected from the engine, and associated systems, is a result of the engine inefficiency. Successfully recovering a small proportion of this energy would therefore substantially improve the fuel economy.

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The adoption of each new level of automotive emissions legislation often requires the introduction of additional emissions reduction techniques or the development of existing emissions control systems. This, in turn, usually requires the implementation of new sensors and hardware which must subsequently be monitored by the on-board fault detection systems. The reliable detection and diagnosis of faults in these systems or sensors, which result in the tailpipe emissions rising above the progressively lower failure thresholds, provides enormous challenges for OBD engineers. This paper gives a review of the field of fault detection and diagnostics as used in the automotive industry. Previous work is discussed and particular emphasis is placed on the various strategies and techniques employed. Methodologies such as state estimation, parity equations and parameter estimation are explained with their application within a physical model diagnostic structure. The utilization of symptoms and residuals in the diagnostic process is also discussed. These traditional physical model based diagnostics are investigated in terms of their limitations. The requirements from the OBD legislation are also addressed. Additionally, novel diagnostic techniques, such as principal component analysis (PCA) are also presented as a potential method of achieving the monitoring requirements of current and future OBD legislation.

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The practical untenability of the quasi-static assumption makes any realistic engine intrinsically irreversible and its operating time finite, thus implying friction effects at short cycle times. An important technological goal is thus the design of maximally efficient engines working at the maximum possible power. We show that, by utilising shortcuts to adiabaticity in a quantum engine cycle, one can engineer a thermodynamic cycle working at finite power and zero friction. Our findings are illustrated using a harmonic oscillator undergoing a quantum Otto cycle.

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When orchestrating Web service workflows, the geographical placement of the orchestration engine (s) can greatly affect workflow performance. Data may have to be transferred across long geographical distances, which in turn increases execution time and degrades the overall performance of a workflow. In this paper, we present a framework that, given a DAG-based workflow specification, computes the optimal Amazon EC2 cloud regions to deploy the orchestration engines and execute a workflow. The framework incorporates a constraint model that solves the workflow deployment problem, which is generated using an automated constraint modelling system. The feasibility of the framework is evaluated by executing different sample workflows representative of scientific workloads. The experimental results indicate that the framework reduces the workflow execution time and provides a speed up of 1.3x-2.5x over centralised approaches.

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Tesis (Maestría en Ciencias con Orientación en Ingeniería Estructural) UANL, 2013.

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When publishing information on the web, one expects it to reach all the people that could be interested in. This is mainly achieved with general purpose indexing and search engines like Google which is the most used today. In the particular case of geographic information (GI) domain, exposing content to mainstream search engines is a complex task that needs specific actions. In many occasions it is convenient to provide a web site with a specially tailored search engine. Such is the case for on-line dictionaries (wikipedia, wordreference), stores (amazon, ebay), and generally all those holding thematic databases. Due to proliferation of these engines, A9.com proposed a standard interface called OpenSearch, used by modern web browsers to manage custom search engines. Geographic information can also benefit from the use of specific search engines. We can distinguish between two main approaches in GI retrieval information efforts: Classical OGC standardization on one hand (CSW, WFS filters), which are very complex for the mainstream user, and on the other hand the neogeographer’s approach, usually in the form of specific APIs lacking a common query interface and standard geographic formats. A draft ‘geo’ extension for OpenSearch has been proposed. It adds geographic filtering for queries and recommends a set of simple standard response geographic formats, such as KML, Atom and GeoRSS. This proposal enables standardization while keeping simplicity, thus covering a wide range of use cases, in both OGC and the neogeography paradigms. In this article we will analyze the OpenSearch geo extension in detail and its use cases, demonstrating its applicability to both the SDI and the geoweb. Open source implementations will be presented as well

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For fifty years, computer chess has pursued an original goal of Artificial Intelligence, to produce a chess-engine to compete at the highest level. The goal has arguably been achieved, but that success has made it harder to answer questions about the relative playing strengths of man and machine. The proposal here is to approach such questions in a counter-intuitive way, handicapping or stopping-down chess engines so that they play less well. The intrinsic lack of man-machine games may be side-stepped by analysing existing games to place computer engines as accurately as possible on the FIDE ELO scale of human play. Move-sequences may also be assessed for likelihood if computer-assisted cheating is suspected.

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Our ability to identify, acquire, store, enquire on and analyse data is increasing as never before, especially in the GIS field. Technologies are becoming available to manage a wider variety of data and to make intelligent inferences on that data. The mainstream arrival of large-scale database engines is not far away. The experience of using the first such products tells us that they will radically change data management in the GIS field.

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