913 resultados para Modern Power Theories


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A long-held assumption in entrepreneurship research is that normal (i.e., Gaussian) distributions characterize variables of interest for both theory and practice. We challenge this assumption by examining more than 12,000 nascent, young, and hyper-growth firms. Results reveal that variables which play central roles in resource-, cognition-, action-, and environment-based entrepreneurship theories exhibit highly skewed power law distributions, where a few outliers account for a disproportionate amount of the distribution's total output. Our results call for the development of new theory to explain and predict the mechanisms that generate these distributions and the outliers therein. We offer a research agenda, including a description of non-traditional methodological approaches, to answer this call.

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This book focuses on how evolutionary computing techniques benefit engineering research and development tasks by converting practical problems of growing complexities into simple formulations, thus largely reducing development efforts. This book begins with an overview of the optimization theory and modern evolutionary computing techniques, and goes on to cover specific applications of evolutionary computing to power system optimization and control problems.

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This paper is the second in a two-part series that maps continuities and ruptures in conceptions of power and traces their effects in educational discourse on 'the child'. It delineates two post-Newtonian intellectual trajectories through which concepts of 'power' arrived at the theorization of 'the child': the paradoxical bio-physical inscriptions of human-ness that accompanied mechanistic worldviews and the explanations for social motion in political philosophy. The intersection of pedagogical theories with 'the child' and 'power' is further traced from the latter 1800s to the present, where a Foucaultian analytics of power-as-effects is reconsidered in regard to histories of motion. The analysis culminates in an examination of post-Newtonian (dis)continuities in the theorization of power, suggesting some productive paradoxes that inhabit turn of the 21st-century conceptualizations of the social.

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Our present-day understanding of fundamental constituents of matter and their interactions is based on the Standard Model of particle physics, which relies on quantum gauge field theories. On the other hand, the large scale dynamical behaviour of spacetime is understood via the general theory of relativity of Einstein. The merging of these two complementary aspects of nature, quantum and gravity, is one of the greatest goals of modern fundamental physics, the achievement of which would help us understand the short-distance structure of spacetime, thus shedding light on the events in the singular states of general relativity, such as black holes and the Big Bang, where our current models of nature break down. The formulation of quantum field theories in noncommutative spacetime is an attempt to realize the idea of nonlocality at short distances, which our present understanding of these different aspects of Nature suggests, and consequently to find testable hints of the underlying quantum behaviour of spacetime. The formulation of noncommutative theories encounters various unprecedented problems, which derive from their peculiar inherent nonlocality. Arguably the most serious of these is the so-called UV/IR mixing, which makes the derivation of observable predictions especially hard by causing new tedious divergencies, to which our previous well-developed renormalization methods for quantum field theories do not apply. In the thesis I review the basic mathematical concepts of noncommutative spacetime, different formulations of quantum field theories in the context, and the theoretical understanding of UV/IR mixing. In particular, I put forward new results to be published, which show that also the theory of quantum electrodynamics in noncommutative spacetime defined via Seiberg-Witten map suffers from UV/IR mixing. Finally, I review some of the most promising ways to overcome the problem. The final solution remains a challenge for the future.

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Democratic Legitimacy and the Politics of Rights is a research in normative political theory, based on comparative analysis of contemporary democratic theories, classified roughly as conventional liberal, deliberative democratic and radical democratic. Its focus is on the conceptual relationship between alternative sources of democratic legitimacy: democratic inclusion and liberal rights. The relationship between rights and democracy is studied through the following questions: are rights to be seen as external constraints to democracy or as objects of democratic decision making processes? Are individual rights threatened by public participation in politics; do constitutionally protected rights limit the inclusiveness of democratic processes? Are liberal values such as individuality, autonomy and liberty; and democratic values such as equality, inclusion and popular sovereignty mutually conflictual or supportive? Analyzing feminist critique of liberal discourse, the dissertation also raises the question about Enlightenment ideals in current political debates: are the universal norms of liberal democracy inherently dependent on the rationalist grand narratives of modernity and incompatible with the ideal of diversity? Part I of the thesis introduces the sources of democratic legitimacy as presented in the alternative democratic models. Part II analyses how the relationship between rights and democracy is theorized in them. Part III contains arguments by feminists and radical democrats against the tenets of universalist liberal democratic models and responds to that critique by partly endorsing, partly rejecting it. The central argument promoted in the thesis is that while the deconstruction of modern rationalism indicates that rights are political constructions as opposed to externally given moral constraints to politics, this insight does not delegitimize the politics of universal rights as an inherent part of democratic institutions. The research indicates that democracy and universal individual rights are mutually interdependent rather than oppositional; and that democracy is more dependent on an unconditional protection of universal individual rights when it is conceived as inclusive, participatory and plural; as opposed to robust majoritarian rule. The central concepts are: liberalism, democracy, legitimacy, deliberation, inclusion, equality, diversity, conflict, public sphere, rights, individualism, universalism and contextuality. The authors discussed are e.g. John Rawls, Jürgen Habermas, Seyla Benhabib, Iris Young, Chantal Mouffe and Stephen Holmes. The research focuses on contemporary political theory, but the more classical work of John S. Mill, Benjamin Constant, Isaiah Berlin and Hannah Arendt is also included.

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Provision of modern energy services for cooking (with gaseous fuels)and lighting (with electricity) is an essential component of any policy aiming to address health, education or welfare issues; yet it gets little attention from policy-makers. Secure, adequate, low-cost energy of quality and convenience is core to the delivery of these services. The present study analyses the energy consumption pattern of Indian domestic sector and examines the urban-rural divide and income energy linkage. A comprehensive analysis is done to estimate the cost for providing modern energy services to everyone by 2030. A public-private partnership-driven business model, with entrepreneurship at the core, is developed with institutional, financing and pricing mechanisms for diffusion of energy services. This approach, termed as EMPOWERS (entrepreneurship model for provision of wholesome energy-related basic services), if adopted, can facilitate large-scale dissemination of energy-efficient and renewable technologies like small-scale biogas/biofuel plants, and distributed power generation technologies to provide clean, safe, reliable and sustainable energy to rural households and urban poor. It is expected to integrate the processes of market transformation and entrepreneurship development involving government, NGOs, financial institutions and community groups as stakeholders. (C) 2009 Elsevier Ltd. All rights reserved.

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This study investigates the implications of the introduction of electric lighting systems, building technologies, and theories of worker efficiency on the deep spatial and environmental transformations that occurred within the corporate workplace during the twentieth century. Examining the shift from daylighting strategies to largely artificially lit workplace environments, this paper argues that electric lighting significantly contributed to the architectural rationalization of both office work and the modern office environment. Contesting the historical and critical marginalization of lighting within the discourse of the modern built environment, this study calls for a reassessment of the role of artificial lighting in the development of the modern corporate workplace. Keywords: daylighting, fluorescent lighting, rationalization, workplace design

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This study examines different ways in which the concept of media pluralism has been theorized and used in contemporary media policy debates. Access to a broad range of different political views and cultural expressions is often regarded as a self-evident value in both theoretical and political debates on media and democracy. Opinions on the meaning and nature of media pluralism as a theoretical, political or empirical concept, however, are many, and it can easily be adjusted to different political purposes. The study aims to analyse the ambiguities surrounding the concept of media pluralism in two ways: by deconstructing its normative roots from the perspective of democratic theory, and by examining its different uses, definitions and underlying rationalities in current European media policy debates. The first part of the study examines the values and assumptions behind the notion of media pluralism in the context of different theories of democracy and the public sphere. The second part then analyses and assesses the deployment of the concept in contemporary European policy debates on media ownership and public service media. Finally, the study critically evaluates various attempts to create empirical indicators for measuring media pluralism and discusses their normative implications and underlying rationalities. The analysis of contemporary policy debates indicates that the notion of media pluralism has been too readily reduced to an empty catchphrase or conflated with consumer choice and market competition. In this narrow technocratic logic, pluralism is often unreflectively associated with quantitative data in a way that leaves unexamined key questions about social and political values, democracy, and citizenship. The basic argument advanced in the study is that media pluralism needs to be rescued from its depoliticized uses and re-imagined more broadly as a normative value that refers to the distribution of communicative power in the public sphere. Instead of something that could simply be measured through the number of media outlets available, the study argues that media pluralism should be understood in terms of its ability to challenge inequalities in communicative power and create a more democratic public sphere.

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Modern-day economics is increasingly biased towards believing that institutions matter for growth, an argument that has been further enforced by the recent economic crisis. There is also a wide consensus on what these growth-promoting institutions should look like, and countries are periodically ranked depending on how their institutional structure compares with the best-practice institutions, mostly in place in the developing world. In this paper, it is argued that ”non-desirable” or “second-best” institutions can be beneficial for fostering investment and thus providing a starting point for sustained growth, and that what matters is the appropriateness of institutions to the economy’s distance to the frontier or current phase of development. Anecdotal evidence from Japan and South-Korea is used as a motivation for studying the subject and a model is presented to describe this phenomenon. In the model, the rigidity or non-rigidity of the institutions is described by entrepreneurial selection. It is assumed that entrepreneurs are the ones taking part in the imitation and innovation of technologies, and that decisions on whether or not their projects are refinanced comes from capitalists. The capitalists in turn have no entrepreneurial skills and act merely as financers of projects. The model has two periods, and two kinds of entrepreneurs: those with high skills and those with low skills. The society’s choice of whether an imitation or innovation – based strategy is chosen is modeled as the trade-off between refinancing a low-skill entrepreneur or investing in the selection of the entrepreneurs resulting in a larger fraction of high-skill entrepreneurs with the ability to innovate but less total investment. Finally, a real-world example from India is presented as an initial attempt to test the theory. The data from the example is not included in this paper. It is noted that the model may be lacking explanatory power due to difficulties in testing the predictions, but that this should not be seen as a reason to disregard the theory – the solution might lie in developing better tools, not better just better theories. The conclusion presented is that institutions do matter. There is no one-size-fits-all-solution when it comes to institutional arrangements in different countries, and developing countries should be given space to develop their own institutional structures that cater to their specific needs.

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Road transportation, as an important requirement of modern society, is presently hindered by restrictions in emission legislations as well as the availability of petroleum fuels, and as a consequence, the fuel cost. For nearly 270 years, we burned our fossil cache and have come to within a generation of exhausting the liquid part of it. Besides, to reduce the greenhouse gases, and to obey the environmental laws of most countries, it would be necessary to replace a significant number of the petroleum-fueled internal-combustion-engine vehicles (ICEVs) with electric cars in the near future. In this article, we briefly describe the merits and demerits of various proposed electrochemical systems for electric cars, namely the storage batteries, fuel cells and electrochemical supercapacitors, and determine the power and energy requirements of a modern car. We conclude that a viable electric car could be operated with a 50 kW polymer-electrolyte fuel cell stack to provide power for cruising and climbing, coupled in parallel with a 30 kW supercapacitor and/or battery bank to deliver additional short-term burst-power during acceleration.

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The presence of software bloat in large flexible software systems can hurt energy efficiency. However, identifying and mitigating bloat is fairly effort intensive. To enable such efforts to be directed where there is a substantial potential for energy savings, we investigate the impact of bloat on power consumption under different situations. We conduct the first systematic experimental study of the joint power-performance implications of bloat across a range of hardware and software configurations on modern server platforms. The study employs controlled experiments to expose different effects of a common type of Java runtime bloat, excess temporary objects, in the context of the SPECPower_ssj2008 workload. We introduce the notion of equi-performance power reduction to characterize the impact, in addition to peak power comparisons. The results show a wide variation in energy savings from bloat reduction across these configurations. Energy efficiency benefits at peak performance tend to be most pronounced when bloat affects a performance bottleneck and non-bloated resources have low energy-proportionality. Equi-performance power savings are highest when bloated resources have a high degree of energy proportionality. We develop an analytical model that establishes a general relation between resource pressure caused by bloat and its energy efficiency impact under different conditions of resource bottlenecks and energy proportionality. Applying the model to different "what-if" scenarios, we predict the impact of bloat reduction and corroborate these predictions with empirical observations. Our work shows that the prevalent software-only view of bloat is inadequate for assessing its power-performance impact and instead provides a full systems approach for reasoning about its implications.

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Conventionally, street entrepreneurs were either seen as a residue from a pre-modern era that is gradually disappearing (modernisation theory), or an endeavour into which marginalised populations are driven out of necessity in the absence of alternative ways of securing a livelihood (structuralist theory). In recent years, however, participa-tioninstreetentrepreneurshiphas beenre-read eitherasa rationaleconomicchoice(neo-liberal theory) or as conducted for cultural reasons (post-modern theory). The aim of this paper is to evaluate critically these competing explanations for participation in street entrepreneurship. To do this, face-to-face interviews were conducted with 871 street entrepreneurs in the Indian city of Bangalore during 2010 concerning their reasons for participation in street entrepreneurship. The finding is that no one explanation suffices. Some 12 % explain their participation in street entrepreneurship as necessity-driven, 15 % as traditional ancestral activity, 56 % as a rational economic choice and 17 % as pursued for social or lifestyle reasons. The outcome is a call to combine these previously rival explanations in order to develop a richer and more nuanced theorisation of the multifarious motives for street entrepreneurship in emerging market economies.

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The dissertation studies the general area of complex networked systems that consist of interconnected and active heterogeneous components and usually operate in uncertain environments and with incomplete information. Problems associated with those systems are typically large-scale and computationally intractable, yet they are also very well-structured and have features that can be exploited by appropriate modeling and computational methods. The goal of this thesis is to develop foundational theories and tools to exploit those structures that can lead to computationally-efficient and distributed solutions, and apply them to improve systems operations and architecture.

Specifically, the thesis focuses on two concrete areas. The first one is to design distributed rules to manage distributed energy resources in the power network. The power network is undergoing a fundamental transformation. The future smart grid, especially on the distribution system, will be a large-scale network of distributed energy resources (DERs), each introducing random and rapid fluctuations in power supply, demand, voltage and frequency. These DERs provide a tremendous opportunity for sustainability, efficiency, and power reliability. However, there are daunting technical challenges in managing these DERs and optimizing their operation. The focus of this dissertation is to develop scalable, distributed, and real-time control and optimization to achieve system-wide efficiency, reliability, and robustness for the future power grid. In particular, we will present how to explore the power network structure to design efficient and distributed market and algorithms for the energy management. We will also show how to connect the algorithms with physical dynamics and existing control mechanisms for real-time control in power networks.

The second focus is to develop distributed optimization rules for general multi-agent engineering systems. A central goal in multiagent systems is to design local control laws for the individual agents to ensure that the emergent global behavior is desirable with respect to the given system level objective. Ideally, a system designer seeks to satisfy this goal while conditioning each agent’s control on the least amount of information possible. Our work focused on achieving this goal using the framework of game theory. In particular, we derived a systematic methodology for designing local agent objective functions that guarantees (i) an equivalence between the resulting game-theoretic equilibria and the system level design objective and (ii) that the resulting game possesses an inherent structure that can be exploited for distributed learning, e.g., potential games. The control design can then be completed by applying any distributed learning algorithm that guarantees convergence to the game-theoretic equilibrium. One main advantage of this game theoretic approach is that it provides a hierarchical decomposition between the decomposition of the systemic objective (game design) and the specific local decision rules (distributed learning algorithms). This decomposition provides the system designer with tremendous flexibility to meet the design objectives and constraints inherent in a broad class of multiagent systems. Furthermore, in many settings the resulting controllers will be inherently robust to a host of uncertainties including asynchronous clock rates, delays in information, and component failures.

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In the quest for a descriptive theory of decision-making, the rational actor model in economics imposes rather unrealistic expectations and abilities on human decision makers. The further we move from idealized scenarios, such as perfectly competitive markets, and ambitiously extend the reach of the theory to describe everyday decision making situations, the less sense these assumptions make. Behavioural economics has instead proposed models based on assumptions that are more psychologically realistic, with the aim of gaining more precision and descriptive power. Increased psychological realism, however, comes at the cost of a greater number of parameters and model complexity. Now there are a plethora of models, based on different assumptions, applicable in differing contextual settings, and selecting the right model to use tends to be an ad-hoc process. In this thesis, we develop optimal experimental design methods and evaluate different behavioral theories against evidence from lab and field experiments.

We look at evidence from controlled laboratory experiments. Subjects are presented with choices between monetary gambles or lotteries. Different decision-making theories evaluate the choices differently and would make distinct predictions about the subjects' choices. Theories whose predictions are inconsistent with the actual choices can be systematically eliminated. Behavioural theories can have multiple parameters requiring complex experimental designs with a very large number of possible choice tests. This imposes computational and economic constraints on using classical experimental design methods. We develop a methodology of adaptive tests: Bayesian Rapid Optimal Adaptive Designs (BROAD) that sequentially chooses the "most informative" test at each stage, and based on the response updates its posterior beliefs over the theories, which informs the next most informative test to run. BROAD utilizes the Equivalent Class Edge Cutting (EC2) criteria to select tests. We prove that the EC2 criteria is adaptively submodular, which allows us to prove theoretical guarantees against the Bayes-optimal testing sequence even in the presence of noisy responses. In simulated ground-truth experiments, we find that the EC2 criteria recovers the true hypotheses with significantly fewer tests than more widely used criteria such as Information Gain and Generalized Binary Search. We show, theoretically as well as experimentally, that surprisingly these popular criteria can perform poorly in the presence of noise, or subject errors. Furthermore, we use the adaptive submodular property of EC2 to implement an accelerated greedy version of BROAD which leads to orders of magnitude speedup over other methods.

We use BROAD to perform two experiments. First, we compare the main classes of theories for decision-making under risk, namely: expected value, prospect theory, constant relative risk aversion (CRRA) and moments models. Subjects are given an initial endowment, and sequentially presented choices between two lotteries, with the possibility of losses. The lotteries are selected using BROAD, and 57 subjects from Caltech and UCLA are incentivized by randomly realizing one of the lotteries chosen. Aggregate posterior probabilities over the theories show limited evidence in favour of CRRA and moments' models. Classifying the subjects into types showed that most subjects are described by prospect theory, followed by expected value. Adaptive experimental design raises the possibility that subjects could engage in strategic manipulation, i.e. subjects could mask their true preferences and choose differently in order to obtain more favourable tests in later rounds thereby increasing their payoffs. We pay close attention to this problem; strategic manipulation is ruled out since it is infeasible in practice, and also since we do not find any signatures of it in our data.

In the second experiment, we compare the main theories of time preference: exponential discounting, hyperbolic discounting, "present bias" models: quasi-hyperbolic (α, β) discounting and fixed cost discounting, and generalized-hyperbolic discounting. 40 subjects from UCLA were given choices between 2 options: a smaller but more immediate payoff versus a larger but later payoff. We found very limited evidence for present bias models and hyperbolic discounting, and most subjects were classified as generalized hyperbolic discounting types, followed by exponential discounting.

In these models the passage of time is linear. We instead consider a psychological model where the perception of time is subjective. We prove that when the biological (subjective) time is positively dependent, it gives rise to hyperbolic discounting and temporal choice inconsistency.

We also test the predictions of behavioral theories in the "wild". We pay attention to prospect theory, which emerged as the dominant theory in our lab experiments of risky choice. Loss aversion and reference dependence predicts that consumers will behave in a uniquely distinct way than the standard rational model predicts. Specifically, loss aversion predicts that when an item is being offered at a discount, the demand for it will be greater than that explained by its price elasticity. Even more importantly, when the item is no longer discounted, demand for its close substitute would increase excessively. We tested this prediction using a discrete choice model with loss-averse utility function on data from a large eCommerce retailer. Not only did we identify loss aversion, but we also found that the effect decreased with consumers' experience. We outline the policy implications that consumer loss aversion entails, and strategies for competitive pricing.

In future work, BROAD can be widely applicable for testing different behavioural models, e.g. in social preference and game theory, and in different contextual settings. Additional measurements beyond choice data, including biological measurements such as skin conductance, can be used to more rapidly eliminate hypothesis and speed up model comparison. Discrete choice models also provide a framework for testing behavioural models with field data, and encourage combined lab-field experiments.