987 resultados para Policy parameters


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AERA Distinguished Lecture, Annual Meetings of the American Educational Research Association, New Orleans, 8 April 2011. How well does educational policy, innovation and science cross borders? What are the parameters of a generalisable cultural science of education? What constitutes a principled policy 'borrowing'?

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This special issue presents an excellent opportunity to study applied epistemology in public policy. This is an important task because the arena of public policy is the social domain in which macro conditions for ‘knowledge work’ and ‘knowledge industries’ are defined and created. We argue that knowledge-related public policy has become overly concerned with creating the politico-economic parameters for the commodification of knowledge. Our policy scope is broader than that of Fuller (1988), who emphasizes the need for a social epistemology of science policy. We extend our focus to a range of policy documents that include communications, science, education and innovation policy (collectively called knowledge-related public policy in acknowledgement of the fact that there is no defined policy silo called ‘knowledge policy’), all of which are central to policy concerned with the ‘knowledge economy’ (Rooney and Mandeville, 1998). However, what we will show here is that, as Fuller (1995) argues, ‘knowledge societies’ are not industrial societies permeated by knowledge, but that knowledge societies are permeated by industrial values. Our analysis is informed by an autopoietic perspective. Methodologically, we approach it from a sociolinguistic position that acknowledges the centrality of language to human societies (Graham, 2000). Here, what we call ‘knowledge’ is posited as a social and cognitive relationship between persons operating on and within multiple social and non-social (or, crudely, ‘physical’) environments. Moreover, knowing, we argue, is a sociolinguistically constituted process. Further, we emphasize that the evaluative dimension of language is most salient for analysing contemporary policy discourses about the commercialization of epistemology (Graham, in press). Finally, we provide a discourse analysis of a sample of exemplary texts drawn from a 1.3 million-word corpus of knowledge-related public policy documents that we compiled from local, state, national and supranational legislatures throughout the industrialized world. Our analysis exemplifies a propensity in policy for resorting to technocratic, instrumentalist and anti-intellectual views of knowledge in policy. We argue that what underpins these patterns is a commodity-based conceptualization of knowledge, which is underpinned by an axiology of narrowly economic imperatives at odds with the very nature of knowledge. The commodity view of knowledge, therefore, is flawed in its ignorance of the social systemic properties of knowing’.

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Access to transport systems and the connection to such systems provided to essential economic and social activities are critical to determine households' transportation disadvantage levels. In spite of the developments in better identifying transportation disadvantaged groups, the lack of effective policies resulted in the continuum of the issue as a significant problem. This paper undertakes a pilot case investigation as test bed for a new approach developed to reduce transportation policy shortcomings. The approach, ‘disadvantage-impedance index’, aims to ease transportation disadvantages by employing representative parameters to measure the differences between policy alternatives run in a simulation environment. Implemented in the Japanese town of Arao, the index uses trip-making behaviour and resident stated preference data. The results of the index reveal that even a slight improvement in accessibility and travel quality indicators makes a significant difference in easing disadvantages. The index, integrated into a four-step model, proves to be highly robust and useful in terms of quick diagnosis in capturing effective actions, and developing potentially efficient policies.

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This article explains the essence of the context-sensitive parameters and dimensions in play at the time of an intervention, through the application of Rog’s (2012) model of contextual parameters. Rog’s model offers evaluators a structured approach to examine an intervention. The initial study provided a systematic way to clarify the scope, variables, timing, and appropriate evaluation methodology to evaluate the implementation of a government policy. Given that the government implementation of an educational intervention under study did not follow the experimental research approach, nor the double cycle of action research approach, the application of Rog’s model provided an in-depth understanding of the context-sensitive environment; it is from this clear purpose that the broader evaluation was conducted. Overall, when governments or institutions implement policy to invoke educational change (and this intervention is not guided by an appropriate evaluation approach), then program evaluation is achievable post-implementation. In this situation, Rog’s (2012) model of contextual parameters is a useful way to achieve clarity of purpose to guide the program evaluation.

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In a framework of Intellectual Capital (IC), the effects and interactions of a Worksite Fitness Program (WFP) policy was studied with a multidisciplinary approach. In a preliminary study, indicators for physical activity (PAI), physical fitness (PFI), activity in WFP on a regular (WFPI) and on a events basis (WFPE) were created in line with positive findings regarding the associations between physical activity and fitness patterns and sick leave, perceived health, and self-assessed work ability. The intensity of physical activity was found to be the most important variable to predict positive associations with the above mentioned wellness parameters. In four case study follow-up settings, the effects and interactions of physical activity and fitness patterns and the company’s WFP-policy on different elements of IC were studied. Qualitative methods were applied in constructing indicators and a descriptive IC measure for each case company. In cross-sectional and follow-up settings, several findings with respect to IC were found regarding physical activity in general and activity in WFP in particular. Findings were relatively strong in health and wellness related indicators in Human Capital, where, as also in Structural Capital indicators such as the company climate and employee-superior relationship, revealed positive associations. Physical activity patterns were found to act in minor role in Relational Capital. Overall, WFP was seen to be an integrated part of Structural Capital. From the viewpoint of Worksite Fitness Program as a phenomenon, this study positioned WFP as an active element of Intellectual Capital. The literature in the field of WFP emphasizes the role of WFP as an instrument to activate employees in physical activity, and thus promote their health and wellbeing. With the wider perspective the active and long range WFP policy can support a company’s Structural and Relational Capital in line with the fundamental role it has on Human Capital.

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In underlay cognitive radio (CR), a secondary user (SU) can transmit concurrently with a primary user (PU) provided that it does not cause excessive interference at the primary receiver (PRx). The interference constraint fundamentally changes how the SU transmits, and makes link adaptation in underlay CR systems different from that in conventional wireless systems. In this paper, we develop a novel, symbol error probability (SEP)-optimal transmit power adaptation policy for an underlay CR system that is subject to two practically motivated constraints, namely, a peak transmit power constraint and an interference outage probability constraint. For the optimal policy, we derive its SEP and a tight upper bound for MPSK and MQAM constellations when the links from the secondary transmitter (STx) to its receiver and to the PRx follow the versatile Nakagami-m fading model. We also characterize the impact of imperfectly estimating the STx-PRx link on the SEP and the interference. Extensive simulation results are presented to validate the analysis and evaluate the impact of the constraints, fading parameters, and imperfect estimates.

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We propose a simulation-based algorithm for computing the optimal pricing policy for a product under uncertain demand dynamics. We consider a parameterized stochastic differential equation (SDE) model for the uncertain demand dynamics of the product over the planning horizon. In particular, we consider a dynamic model that is an extension of the Bass model. The performance of our algorithm is compared to that of a myopic pricing policy and is shown to give better results. Two significant advantages with our algorithm are as follows: (a) it does not require information on the system model parameters if the SDE system state is known via either a simulation device or real data, and (b) as it works efficiently even for high-dimensional parameters, it uses the efficient smoothed functional gradient estimator.

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[EN] The main objective of this project is to analyze Cuban public health policy and the Millennium Development Goals, especially those linked to the issue of health, presenting their potential and strengths with a well-defined time horizon (2000-2015). The Millennium Development Goals are the international consensus on development and was signed as an international minimum agreement, with which began the century. The MDGs promote various goals and targets, with the corresponding monitoring indicators, which should be achieved by all countries for the present year. Health is an area that is at the center of the Millennium Development Goals, which reinforce each other to get a true human development itself. The research was done through theoretical frameworks of social production of health and disease, social justice and the power structure. A retrospective analysis of Cuban economic and social context is performed in order to study whether health-related MDGs are likely to be completed by the deadline on the island and likewise, the main parameters related to health compared with those of the neighboring countries in the Americas.

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Although it is widely believed that reinforcement learning is a suitable tool for describing behavioral learning, the mechanisms by which it can be implemented in networks of spiking neurons are not fully understood. Here, we show that different learning rules emerge from a policy gradient approach depending on which features of the spike trains are assumed to influence the reward signals, i.e., depending on which neural code is in effect. We use the framework of Williams (1992) to derive learning rules for arbitrary neural codes. For illustration, we present policy-gradient rules for three different example codes - a spike count code, a spike timing code and the most general "full spike train" code - and test them on simple model problems. In addition to classical synaptic learning, we derive learning rules for intrinsic parameters that control the excitability of the neuron. The spike count learning rule has structural similarities with established Bienenstock-Cooper-Munro rules. If the distribution of the relevant spike train features belongs to the natural exponential family, the learning rules have a characteristic shape that raises interesting prediction problems.

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Jackson, R. (2007). Language, Policy and the Construction of a Torture Culture in the War on Terrorism. Review of International Studies. 33(3), pp.353-371 RAE2008

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Pavements and bridges are subject to a continuous degradation due to traffic aggressiveness, ageing and environmental factors. A rational transport policy requires the monitoring of this transport infrastructure in order to provide adequate maintenance and guarantee the required levels of transport service and safety. This paper investigates the use of an instrumented vehicle fitted with accelerometers on its axles to monitor the dynamics of bridges. A simplified quarter carbridge interaction model is used in theoretical simulations and the natural frequency of the bridge is extracted from the spectra of the vehicle accelerations. The accuracy is better at lower speeds and for smooth road profiles. The structural damping of the bridge was also monitored for smooth and rough road profiles. The magnitude of peaks in the power spectral density of the vehicle accelerations decreased with increasing bridge damping and this decrease was easier to detect the smoother the road profile.

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Highway structures such as bridges are subject to continuous degradation primarily due to ageing and environmental factors. A rational transport policy requires the monitoring of this transport infrastructure to provide adequate maintenance and guarantee the required levels of transport service and safety. In Europe, this is now a legal requirement - a European Directive requires all member states of the European Union to implement a Bridge Management System. However, the process is expensive, requiring the installation of sensing equipment and data acquisition electronics on the bridge. This paper investigates the use of an instrumented vehicle fitted with accelerometers on its axles to monitor the dynamic behaviour of bridges as an indicator of its structural condition. This approach eliminates the need for any on-site installation of measurement equipment. A simplified half-car vehicle-bridge interaction model is used in theoretical simulations to test the possibility of extracting the dynamic parameters of the bridge from the spectra of the vehicle accelerations. The effect of vehicle speed, vehicle mass and bridge span length on the detection of the bridge dynamic parameters are investigated. The algorithm is highly sensitive to the condition of the road profile and simulations are carried out for both smooth and rough profiles

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Voting records indicate that dissents in monetary policy committees are frequent and predictability regressions show that they help forecast future policy decisions. In order to study whether the latter relation is causal, we construct a model of committee decision making and dissent where members' decisions are not a function of past dissents. The model is estimated using voting data from the Bank of England and the Riksbank. Stochastic simulations show that the decision-making frictions in our model help account for the predictive power of current dissents. The effect of insti- tutional characteristics and structural parameters on dissent rates is examined using simulations as well.

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This paper proposes a high-level reinforcement learning (RL) control system for solving the action selection problem of an autonomous robot. Although the dominant approach, when using RL, has been to apply value function based algorithms, the system here detailed is characterized by the use of direct policy search methods. Rather than approximating a value function, these methodologies approximate a policy using an independent function approximator with its own parameters, trying to maximize the future expected reward. The policy based algorithm presented in this paper is used for learning the internal state/action mapping of a behavior. In this preliminary work, we demonstrate its feasibility with simulated experiments using the underwater robot GARBI in a target reaching task