895 resultados para Vehicle Operating Performance Modeling.


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National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.

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National Highway Traffic Safety Administration, Washington, D.C.

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National Highway Traffic Safety Administration, Office of State Vehicle Programs, Washington, D.C.

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National Highway Traffic Safety Administration, Office of Passenger Vehicle Research, Washington, D.C.

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National Highway Traffic Safety Administration, Office of Passenger Vehicle Research, Washington, D.C.

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Pavement performance is one of the most important components of the pavement management system. Prediction of the future performance of a pavement section is important in programming maintenance and rehabilitation needs. Models for predicting pavement performance have been developed on the basis of traffic and age. The purpose of this research is to extend the use of a relatively new approach to performance prediction in pavement performance modeling using adaptive logic networks (ALN). Adaptive logic networks have recently emerged as an effective alternative to artificial neural networks for machine learning tasks. ^ The ALN predictive methodology is applicable to a wide variety of contexts including prediction of roughness based indices, composite rating indices and/or individual pavement distresses. The ALN program requires key information about a pavement section, including the current distress indexes, pavement age, climate region, traffic and other variables to predict yearly performance values into the future. ^ This research investigates the effect of different learning rates of the ALN in pavement performance modeling. It can be used at both the network and project level for predicting the long term performance of a road network. Results indicate that the ALN approach is well suited for pavement performance prediction modeling and shows a significant improvement over the results obtained from other artificial intelligence approaches. ^

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The rapid growth of virtualized data centers and cloud hosting services is making the management of physical resources such as CPU, memory, and I/O bandwidth in data center servers increasingly important. Server management now involves dealing with multiple dissimilar applications with varying Service-Level-Agreements (SLAs) and multiple resource dimensions. The multiplicity and diversity of resources and applications are rendering administrative tasks more complex and challenging. This thesis aimed to develop a framework and techniques that would help substantially reduce data center management complexity.^ We specifically addressed two crucial data center operations. First, we precisely estimated capacity requirements of client virtual machines (VMs) while renting server space in cloud environment. Second, we proposed a systematic process to efficiently allocate physical resources to hosted VMs in a data center. To realize these dual objectives, accurately capturing the effects of resource allocations on application performance is vital. The benefits of accurate application performance modeling are multifold. Cloud users can size their VMs appropriately and pay only for the resources that they need; service providers can also offer a new charging model based on the VMs performance instead of their configured sizes. As a result, clients will pay exactly for the performance they are actually experiencing; on the other hand, administrators will be able to maximize their total revenue by utilizing application performance models and SLAs. ^ This thesis made the following contributions. First, we identified resource control parameters crucial for distributing physical resources and characterizing contention for virtualized applications in a shared hosting environment. Second, we explored several modeling techniques and confirmed the suitability of two machine learning tools, Artificial Neural Network and Support Vector Machine, to accurately model the performance of virtualized applications. Moreover, we suggested and evaluated modeling optimizations necessary to improve prediction accuracy when using these modeling tools. Third, we presented an approach to optimal VM sizing by employing the performance models we created. Finally, we proposed a revenue-driven resource allocation algorithm which maximizes the SLA-generated revenue for a data center.^

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Franchising is an important form of organizational control. Possible benefits of franchising include its ability to reduce agency costs that increase with costly monitoring, and provide incentives for the use of local information by onsite managers. However, these benefits may come at a cost, as franchisees may reduce quality by choosing to free ride. While many studies have investigated the reasons for franchising, few studies have documented the impacts of franchising on unit level operating performance. Using time-series data from a number of lodging properties that were converted to franchisee control from company control, this study documents the performance impacts of franchising. The analysis reveals that conversion results in a modest decline in financial performance and an immediate sharp decline in quality.

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This research is part of the field of organizational studies, focusing on organizational purchase behavior and, specifically, trust interorganizational at the purchases. This topic is current and relevant by addressing the development of good relations between buyer-supplier that increases the exchange of information, increases the length of relationship, reduces the hierarchical controls and improves performance. Furthermore, although there is a vast literature on trust, the scientific work that deal specifically at the trust interorganizational still need further research to synthesize and validate the variables that generate this phenomenon. In this sense, this investigation is to explain the antecedents of trust interorganizational by the relationship between the variable operational performance, organizational characteristics, shared values and interpersonal relationships on purchases by manufacturing industries, in order to develop a robust literature, most consensual, that includes the current sociological and economic, considering the effect of interpersonal relationships in this phenomenon. This proposal is configured in a new vision of the antecedents of interorganizational trust, described as significant quantitative from models Morgan and Hunt (1994), Doney and Cannon (1997), Zhao and Cavusgil (2006) and Nyaga, Whipple, Lynch (2011), as well as qualitative analysis of Tacconi et al. (2011). With regard to methodological aspects, the study assumes the form of a descriptive, survey type, and causal trace theoretical and empirical. As for his nature, the investigation, explicative character, has developed a quantitative approach with the use of exploratory factor analysis and structural equation modeling SEM, with the use of IBM software SPSS Amos 18.0, using the method of maximum verisimilitude, and supported by technical bootstraping. The unit of analysis was the buyer-supplier relationship, in which the object under investigation was the supplier organization in view of the purchasing company. 237 valid questionnaires were collected among key informants, using a simple random sampling developed in manufacturing industries (SIC 10-33), located in the city of Natal and in the region of Natal. The first results of descriptive analysis demonstrate the phenomenon of interorganizational trust, in which purchasing firms believe, feel secure about the supplier. This demonstration showed high levels of intensity, predominantly among the vendors that supply the company with materials that are used directly in the production process. The exploratory and confirmatory factor analysis, performed on each variable alone, generated a set of observable and unobservable variables more consistent, giving rise to a model, that needed to be further specified. This again specify model consists of trajectories was positive, with a good fit, with a composite reliability and variance extracted satisfactory, and demonstrates convergent and discriminant validity, in which the factor loadings are significant and strong explanatory power. Given the findings that reinforce the model again specify data, suggesting a high probability that this model may be more suited for the study population, the results support the explanation that interorganizational trust depends on purchases directly from interpersonal relationships, sharing value and operating performance and indirectly of personal relationships, social networks, organizational characteristics, physical and relational aspect of performance. It is concluded that this trust can be explained by a set of interactions between these three determinants, where the focus is on interpersonal relationships, with the largest path coefficient for the factor under study

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This research is part of the field of organizational studies, focusing on organizational purchase behavior and, specifically, trust interorganizational at the purchases. This topic is current and relevant by addressing the development of good relations between buyer-supplier that increases the exchange of information, increases the length of relationship, reduces the hierarchical controls and improves performance. Furthermore, although there is a vast literature on trust, the scientific work that deal specifically at the trust interorganizational still need further research to synthesize and validate the variables that generate this phenomenon. In this sense, this investigation is to explain the antecedents of trust interorganizational by the relationship between the variable operational performance, organizational characteristics, shared values and interpersonal relationships on purchases by manufacturing industries, in order to develop a robust literature, most consensual, that includes the current sociological and economic, considering the effect of interpersonal relationships in this phenomenon. This proposal is configured in a new vision of the antecedents of interorganizational trust, described as significant quantitative from models Morgan and Hunt (1994), Doney and Cannon (1997), Zhao and Cavusgil (2006) and Nyaga, Whipple, Lynch (2011), as well as qualitative analysis of Tacconi et al. (2011). With regard to methodological aspects, the study assumes the form of a descriptive, survey type, and causal trace theoretical and empirical. As for his nature, the investigation, explicative character, has developed a quantitative approach with the use of exploratory factor analysis and structural equation modeling SEM, with the use of IBM software SPSS Amos 18.0, using the method of maximum verisimilitude, and supported by technical bootstraping. The unit of analysis was the buyer-supplier relationship, in which the object under investigation was the supplier organization in view of the purchasing company. 237 valid questionnaires were collected among key informants, using a simple random sampling developed in manufacturing industries (SIC 10-33), located in the city of Natal and in the region of Natal. The first results of descriptive analysis demonstrate the phenomenon of interorganizational trust, in which purchasing firms believe, feel secure about the supplier. This demonstration showed high levels of intensity, predominantly among the vendors that supply the company with materials that are used directly in the production process. The exploratory and confirmatory factor analysis, performed on each variable alone, generated a set of observable and unobservable variables more consistent, giving rise to a model, that needed to be further specified. This again specify model consists of trajectories was positive, with a good fit, with a composite reliability and variance extracted satisfactory, and demonstrates convergent and discriminant validity, in which the factor loadings are significant and strong explanatory power. Given the findings that reinforce the model again specify data, suggesting a high probability that this model may be more suited for the study population, the results support the explanation that interorganizational trust depends on purchases directly from interpersonal relationships, sharing value and operating performance and indirectly of personal relationships, social networks, organizational characteristics, physical and relational aspect of performance. It is concluded that this trust can be explained by a set of interactions between these three determinants, where the focus is on interpersonal relationships, with the largest path coefficient for the factor under study

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The rapid growth of virtualized data centers and cloud hosting services is making the management of physical resources such as CPU, memory, and I/O bandwidth in data center servers increasingly important. Server management now involves dealing with multiple dissimilar applications with varying Service-Level-Agreements (SLAs) and multiple resource dimensions. The multiplicity and diversity of resources and applications are rendering administrative tasks more complex and challenging. This thesis aimed to develop a framework and techniques that would help substantially reduce data center management complexity. We specifically addressed two crucial data center operations. First, we precisely estimated capacity requirements of client virtual machines (VMs) while renting server space in cloud environment. Second, we proposed a systematic process to efficiently allocate physical resources to hosted VMs in a data center. To realize these dual objectives, accurately capturing the effects of resource allocations on application performance is vital. The benefits of accurate application performance modeling are multifold. Cloud users can size their VMs appropriately and pay only for the resources that they need; service providers can also offer a new charging model based on the VMs performance instead of their configured sizes. As a result, clients will pay exactly for the performance they are actually experiencing; on the other hand, administrators will be able to maximize their total revenue by utilizing application performance models and SLAs. This thesis made the following contributions. First, we identified resource control parameters crucial for distributing physical resources and characterizing contention for virtualized applications in a shared hosting environment. Second, we explored several modeling techniques and confirmed the suitability of two machine learning tools, Artificial Neural Network and Support Vector Machine, to accurately model the performance of virtualized applications. Moreover, we suggested and evaluated modeling optimizations necessary to improve prediction accuracy when using these modeling tools. Third, we presented an approach to optimal VM sizing by employing the performance models we created. Finally, we proposed a revenue-driven resource allocation algorithm which maximizes the SLA-generated revenue for a data center.

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Choosing a financially strong insurance company is important when buying health insurance. You want the company to still be in business when you have claims, which can be 20 to 30 years from now. Insurance companies selling insurance in Iowa have met the minimum legal standards to be licensed by the State of Iowa Insurance Division. This licensure doesn’t mean the company has a high financial stability rating. Several independent rating agencies evaluate the financial stability of insurance companies. The rating for an individual insurance company is an opinion as to its financial strength and ability to pay claims in the future. When evaluating a company, a rating agency may consider a company's balance sheet strength, operating performance and business management and strategies.

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The paper argues that the market signifficantly overvalues firms with severely underfunded pension plans. These companies earn lower stock returns than firms with healthier pension plans for at least five years after the first emergence of the underfunding. The low returns are not explained by risk, price momentum, earnings momentum, or accruals. Further, the evidence suggests that investors do not anticipate the impact of the pension liability on future earnings, and they are surprised when the negative implications of underfunding ultimately materialize. Finally, underfunded firms have poor operating performance, and they earn low returns, although they are value companies.

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RESUMEN La energia eolica se considera una forma indirecta de energia solar. Entre el 1 y 2% de la energia proveniente del sol se convierte en viento, debido al movimiento del aire ocasionado por el desigual calentamiento de la superficie terrestre. La energia cinetica del viento puede transformarse en energia util, tanto mecanica como electrica. La energia eolica, transformada en energia mecanica ha sido historicamente aprovechada, pero su uso para la generacion de energia electrica es mas reciente, en respuesta a la crisis del petroleo y a los impactos ambientales derivados del uso de combustibles. El objetivo principal de este trabajo es hacer un analisis de viabilidad desde un punto de vista tecnico y economico de un parque eolico situado en el municipio de Barasoain (Navarra). Desde el punto de vista tecnico se han estudiado los aspectos constructivos del parque considerando sus diferentes infraestructuras de obra civil y electrica asi como los niveles de recurso eolico. En el ambito economico y financiero se han analizado los aspectos y ratios mas relevantes que definen un proyecto de estas caracteristicas asi como el modelo de financiacion elegida basada en el Project- Finance. Entre las conclusiones mas destacadas de este proyecto cabe destacar la contribucion de la construccion del parque al desarrollo social y economico de la zona donde queda ubicado contribuyendo a la creacion de puestos de trabajo, tanto en la fase de construccion como de explotacion y una perfecta armonia con condicionantes medioambientales de la zona. El analisis tecnico realizado nos indica la viabilidad tecnica del parque tanto desde el punto de vista de recurso eolico como la idoneidad para poder evacuar la energia producida. Por otro lado, los resultados obtenidos cumplen perfectamente con los estandares requeridos por los financiadores de los parques y resultando ser muy atractivos para sus accionistas

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Portable (roll-out) stop signs are used at school crossings in over 300 cities in Iowa. Their use conforms to the Code of Iowa, although it is not consistent with the provisions of the Manual on Uniform Traffic Control Devices adopted for nationwide application. A survey indicated that most users in Iowa believe that portable stop signs provide effective protection at school crossings, and favor their continued use. Other non-uniform signs that fold or rotate to display a STOP message only during certain hours are used at school crossings in over 60 cities in Iowa. Their use does not conform to either the Code of Iowa or the Manual on Uniform Traffic Control Devices. Users of these devices also tend to favor their continued use. A survey of other states indicated that use of temporary devices similar to those used in Iowa is not generally sanctioned. Some unsanctioned use apparently occurs in several states, however. A different type of portable stop sign for school crossings is authorized and widely used in one state. Portable stop signs similar to those used in Iowa are authorized in another state, although their use is quite limited. A few reports in the literature reviewed for this research discussed the use of portable stop signs. The authors of these reports uniformly recommended against the use of portable or temporary traffic control devices. Various reasons for this recommendation were given, although data to support the recommendation were not offered. As part of this research, field surveys were conducted at 54 locations in 33 communities where temporary stop control devices were in use at school crossings. Research personnel observed the obedience to stop control and measured the vehicular delay incurred. Stopped delay averaged 1.89 seconds/entering vehicle. Only 36.6 percent of the vehicles were observed to come to a complete stop at the study locations controlled by temporary stop control devices. However, this level of obedience does not differ from that observed at intersections controlled by permanent stop signs. Accident experience was compiled for 76 intersections in 33 communities in Iowa where temporary stop signs were used and, for comparative purposes, at 76 comparable intersections having other forms of control or operating without stop control. There were no significant differences in accident experience An economic analysis of vehicle operating costs, delay costs, and other costs indicated that temporary stop control generated costs only about 12 percent as great as permanent stop control for a street having a school crossing. Midblock pedestrian-actuated signals were shown to be cost effective in comparison with temporary stop signs under the conditions of use assumed. Such signals could be used effectively at a number of locations where temporary stop signs are being used. The results of this research do not provide a basis for recommending that use of portable stop signs be prohibited. However, erratic patterns of use of these devices and inadequate designs suggest that improved standards for their use are needed. Accordingly, nine recommendations are presented to enhance the efficiency of vehicular flow at school crossings, without causing a decline in the level of pedestrian protection being afforded.