893 resultados para Print on demand
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Objective. To measure the demand for primary care and its associated factors by building and estimating a demand model of primary care in urban settings.^ Data source. Secondary data from 2005 California Health Interview Survey (CHIS 2005), a population-based random-digit dial telephone survey, conducted by the UCLA Center for Health Policy Research in collaboration with the California Department of Health Services, and the Public Health Institute between July 2005 and April 2006.^ Study design. A literature review was done to specify the demand model by identifying relevant predictors and indicators. CHIS 2005 data was utilized for demand estimation.^ Analytical methods. The probit regression was used to estimate the use/non-use equation and the negative binomial regression was applied to the utilization equation with the non-negative integer dependent variable.^ Results. The model included two equations in which the use/non-use equation explained the probability of making a doctor visit in the past twelve months, and the utilization equation estimated the demand for primary conditional on at least one visit. Among independent variables, wage rate and income did not affect the primary care demand whereas age had a negative effect on demand. People with college and graduate educational level were associated with 1.03 (p < 0.05) and 1.58 (p < 0.01) more visits, respectively, compared to those with no formal education. Insurance was significantly and positively related to the demand for primary care (p < 0.01). Need for care variables exhibited positive effects on demand (p < 0.01). Existence of chronic disease was associated with 0.63 more visits, disability status was associated with 1.05 more visits, and people with poor health status had 4.24 more visits than those with excellent health status. ^ Conclusions. The average probability of visiting doctors in the past twelve months was 85% and the average number of visits was 3.45. The study emphasized the importance of need variables in explaining healthcare utilization, as well as the impact of insurance, employment and education on demand. The two-equation model of decision-making, and the probit and negative binomial regression methods, was a useful approach to demand estimation for primary care in urban settings.^
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Available on demand as hard copy or computer file from Cornell University Library.
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Available on demand as hard copy or computer file from Cornell University Library.
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Available on demand as hard copy or computer file from Cornell University Library.
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Available on demand as hard copy or computer file from Cornell University Library.
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Available on demand as hard copy or computer file from Cornell University Library.
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Available on demand as hard copy or computer file from Cornell University.
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Available on demand as hard copy or computer file from Cornell University Library.
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Available on demand as hard copy or computer file from Cornell University Library.
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Simulating the efficiency of business processes could reveal crucial bottlenecks for manufacturing companies and could lead to significant optimizations resulting in decreased time to market, more efficient resource utilization, and larger profit. While such business optimization software is widely utilized by larger companies, SMEs typically do not have the required expertise and resources to efficiently exploit these advantages. The aim of this work is to explore how simulation software vendors and consultancies can extend their portfolio to SMEs by providing business process optimization based on a cloud computing platform. By executing simulation runs on the cloud, software vendors and associated business consultancies can get access to large computing power and data storage capacity on demand, run large simulation scenarios on behalf of their clients, analyze simulation results, and advise their clients regarding process optimization. The solution is mutually beneficial for both vendor/consultant and the end-user SME. End-user companies will only pay for the service without requiring large upfront costs for software licenses and expensive hardware. Software vendors can extend their business towards the SME market with potentially huge benefits.
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Exit, Voice and Political Change: Evidence from Swedish Mass Migration to the United States. During the Age of Mass Migration, 30 million Europeans immigrated to the United States. We study the long-term political effects of this large-scale migration episode on origin communities using detailed historical data from Sweden. To instrument for emigration, we exploit severe local frost shocks that sparked an initial wave of emigration, interacted with within-country travel costs. Because Swedish emigration was highly path dependent, the initial shocks strongly predict total emigration over 50 years. Our estimates show that emigration substantially increased membership in local labor organizations, the strongest political opposition groups at the time. Furthermore, emigration caused greater strike participation, and mobilized voter turnout and support for left-wing parties in national elections. Emigration also had formal political effects, as measured by welfare expenditures and adoption of inclusive political institutions. Together, our findings indicate that large-scale emigration can achieve long-lasting effects on the political equilibrium in origin communities. Mass Migration and Technological Innovation at the Origin. This essay studies the effects of migration on technological innovations in origin communities. Using historical data from Sweden, we find that large-scale emigration caused a long-run increase in patent innovations in origin municipalities. Our IV estimate shows that a ten percent increase in emigration entails a 7 percent increase in a muncipality’s number of patents. Weighting patents by a measure of their economic value, the positive effects are further increased. Discussing possible mechanisms, we suggest that low skilled labor scarcity may be an explanation for these results. Richer (and Holier) Than Thou? The Impact of Relative Income Improvements on Demand for Redistribution. We use a tailor-made survey on a Swedish sample to investigate how individuals' relative income affects their demand for redistribution. We first document that a majority misperceive their position in the income distribution and believe that they are poorer, relative to others, than they actually are. We then inform a subsample about their true relative income, and find that individuals who are richer than they initially thought demand less redistribution. This result is driven by individuals with prior right-of-center political preferences who view taxes as distortive and believe that effort, rather than luck, drives individual economic success. Wealth, home ownership and mobility. Rent controls on housing have long been thought to reduce labor mobility and allocative efficiency. We study a policy that allowed renters to purchase their rent-controlled apartments at below market prices, and examine the effects of home ownership and wealth on mobility. Treated individuals have a substantially higher likelihood of moving to a new home in a given year. The effect corresponds to a 30 percent increase from the control group mean. The size of the wealth shock predicts lower mobility, while the positive average effect can be explained by tenants switching from the previous rent-controlled system to market-priced condominiums. By contrast, we do not find that the increase in residential mobility leads to a greater probability of moving to a new place of work.
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Doing Kyd reads Thomas Kyd's The Spanish Tragedy, the box-office and print success of its time, as the play that established the revenge genre in England and served as a 'pattern and precedent' for the golden generation of early modern playwrights, from Marlowe and Shakespeare to Middleton, Webster and Ford. Interdisciplinary in approach and accessible in style, this collection is crucial in two respects: firstly, it has a wide spectrum, addressing readers with interests in the play from its early impact as the first sixteenth-century revenge tragedy, to its afterlife in print, on the stage, in screen adaptation and bibliographical studies. Secondly, the collection appears at a time when Kyd and his play are back in the spotlight, through renewed critical interest, several new stage productions between 2009 and 2013, and its firm presence in higher-education curriculum for English and drama.
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This paper focuses on computational models development and its applications on demand response, within smart grid scope. A prosumer model is presented and the corresponding economic dispatch problem solution is analyzed. The prosumer solar radiation production and energy consumption are forecasted by artificial neural networks. The existing demand response models are studied and a computational tool based on fuzzy clustering algorithm is developed and the results discussed. Consumer energy management applications within the InovGrid pilot project are presented. Computation systems are developed for the acquisition, monitoring, control and supervision of consumption data provided by smart meters, allowing the incorporation of consumer actions on their electrical energy management. An energy management system with integration of smart meters for energy consumers in a smart grid is developed.
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A great challenge exists today: how to reach youth (a.k.a. the iYGeneration) who consume multiple media concurrently, who can access information on demand, and who have intertwined virtual social media networks in their lives. Our research finds that Australian youth multi-task and rarely use traditional media, although significant differences between males and females, as well as late tweens and 20-somethings, exist. Technology convergence facilitates two-way dialogue, allowing growing social interactions to occur in their technological environments. Our findings show that in order for marketing communication professionals to effectively communicate with this market, it is crucial to know exactly how the iYGeneration use media, which media they use, and when they use it.
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The programming and retasking of sensor nodes could benefit greatly from the use of a virtual machine (VM) since byte code is compact, can be loaded on demand, and interpreted on a heterogeneous set of devices. The challenge is to ensure good programming tools and a small footprint for the virtual machine to meet the memory constraints of typical WSN platforms. To this end we propose Darjeeling, a virtual machine modelled after the Java VM and capable of executing a substantial subset of the Java language, but designed specifically to run on 8- and 16-bit microcontrollers with 2 - 10 KB of RAM. The Darjeeling VM uses a 16- rather than a 32-bit architecture, which is more efficient on the targeted platforms. Darjeeling features a novel memory organisation with strict separation of reference from non-reference types which eliminates the need for run-time type inspection in the underlying compacting garbage collector. Darjeeling uses a linked stack model that provides light-weight threads, and supports synchronisation. The VM has been implemented on three different platforms and was evaluated with micro benchmarks and a real-world application. The latter includes a pure Java implementation of the collection tree routing protocol conveniently programmed as a set of cooperating threads, and a reimplementation of an existing environmental monitoring application. The results show that Darjeeling is a viable solution for deploying large-scale heterogeneous sensor networks. Copyright 2009 ACM.