816 resultados para Will to Power


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Abstract: Nietzsche's Will-to-Power Ontology: An Interpretation of Beyond Good and Evil § 36 By: Mark Minuk Will-to-power is the central component of Nietzsche's philosophy, and passage 36 of Beyond Good and Evil is essential to coming to an understanding of it. 1 argue for and defend the thesis that will-to-power constitutes Nietzsche's ontology, and offer a new understanding of what that means. Nietzsche's ontology can be talked about as though it were a traditional substance ontology (i.e., a world made up of forces; a duality of conflicting forces described as 'towards which' and 'away from which'). However, 1 argue that what defines this ontology is an understanding of valuation as ontologically fundamental—^the basis of interpretation, and from which a substance ontology emerges. In the second chapter, I explain Nietzsche's ontology, as reflected in this passage, through a discussion of Heidegger's two ontological categories in Being and Time (readiness-to-hand, and present-at-hand). In a nutshell, it means that the world of our desires and passions (the most basic of which is for power) is ontologically more fundamental than the material world, or any other interpretation, which is to say, the material world emerges out of a world of our desires and passions. In the first chapter, I address the problematic form of the passage reflected in the first sentence. The passage is in a hypothetical style makes no claim to positive knowledge or truth, and, superficially, looks like Schopenhaurian position for the metaphysics of the will, which Nietzsche rejects. 1 argue that the hypothetical form of the passage is a matter of style, namely, the style of a free-spirit for whom the question of truth is reframed as a question of values. In the third and final chapter, 1 address the charge that Nietzsche's interpretation is a conscious anthropomorphic projection. 1 suggest that the charge rests on a distinction (between nature and man) that Nietzsche rejects. I also address the problem of the causality of the will for Nietzsche, by suggesting that an alternative, perspectival form of causality is possible.

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ABSTRACT: There has been a growing trend towards the use of biomass as a primary energy source, which now contributes over 54% of the European pulp and paper industry energy needs [1]. The remaining part comes from natural gas, which to a large extent serves as the major source of energy for numerous recovered fiber paper mills located in regions with limited available forest resources. The cost of producing electricity to drive paper machinery and generate heat for steam is increasing as world demand for fossil fuels increases. Additionally, recovered fiber paper mills are also significant producers of fibrous sludge and reject waste material that can contain high amounts of useful energy. Currently, a majority of these waste fractions is disposed of by landspreading, incineration, or landfill. Paper mills must also pay a gate fee to process their waste streams in this way and the result of this is a further increase in operating costs. This work has developed methods to utilize the waste fractions produced at recovered fiber paper mills for the onsite production of combined heat and power (CHP) using advanced thermal conversion methods (pyrolysis and gasification) that are well suited to relatively small scales of throughput. The electrical power created would either be used onsite to power the paper making process or alternatively exported to the national grid, and the surplus heat created could also be used onsite or exported to a local customer. The focus of this paper is to give a general overview of the project progress so far and will present the experimental results of the most successful thermal conversion trials carried out by this work to date. Application: The research provides both paper mills and energy providers with methodologies to condition their waste materials for conversion into useful energy. The research also opens up new markets for gasifier and pyrolysis equipment manufacturers and suppliers.

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Light Detection and Ranging (LIDAR) has great potential to assist vegetation management in power line corridors by providing more accurate geometric information of the power line assets and vegetation along the corridors. However, the development of algorithms for the automatic processing of LIDAR point cloud data, in particular for feature extraction and classification of raw point cloud data, is in still in its infancy. In this paper, we take advantage of LIDAR intensity and try to classify ground and non-ground points by statistically analyzing the skewness and kurtosis of the intensity data. Moreover, the Hough transform is employed to detected power lines from the filtered object points. The experimental results show the effectiveness of our methods and indicate that better results were obtained by using LIDAR intensity data than elevation data.

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Trees, shrubs and other vegetation are of continued importance to the environment and our daily life. They provide shade around our roads and houses, offer a habitat for birds and wildlife, and absorb air pollutants. However, vegetation touching power lines is a risk to public safety and the environment, and one of the main causes of power supply problems. Vegetation management, which includes tree trimming and vegetation control, is a significant cost component of the maintenance of electrical infrastructure. For example, Ergon Energy, the Australia’s largest geographic footprint energy distributor, currently spends over $80 million a year inspecting and managing vegetation that encroach on power line assets. Currently, most vegetation management programs for distribution systems are calendar-based ground patrol. However, calendar-based inspection by linesman is labour-intensive, time consuming and expensive. It also results in some zones being trimmed more frequently than needed and others not cut often enough. Moreover, it’s seldom practicable to measure all the plants around power line corridors by field methods. Remote sensing data captured from airborne sensors has great potential in assisting vegetation management in power line corridors. This thesis presented a comprehensive study on using spiking neural networks in a specific image analysis application: power line corridor monitoring. Theoretically, the thesis focuses on a biologically inspired spiking cortical model: pulse coupled neural network (PCNN). The original PCNN model was simplified in order to better analyze the pulse dynamics and control the performance. Some new and effective algorithms were developed based on the proposed spiking cortical model for object detection, image segmentation and invariant feature extraction. The developed algorithms were evaluated in a number of experiments using real image data collected from our flight trails. The experimental results demonstrated the effectiveness and advantages of spiking neural networks in image processing tasks. Operationally, the knowledge gained from this research project offers a good reference to our industry partner (i.e. Ergon Energy) and other energy utilities who wants to improve their vegetation management activities. The novel approaches described in this thesis showed the potential of using the cutting edge sensor technologies and intelligent computing techniques in improve power line corridor monitoring. The lessons learnt from this project are also expected to increase the confidence of energy companies to move from traditional vegetation management strategy to a more automated, accurate and cost-effective solution using aerial remote sensing techniques.

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Alan Jones's now infamous comment that women are destroying the joint' sparked a flurry of observations and interpretations in the national and international media and in the blogosphere about the motivations and meanings of such a statement. The overriding tone of this commentary was outrage - how dare an influential figure like Jones state with such blatant and provocative hostility that women are at best unsuitable for leadership and at worst, damaging our public and private institutions? The answers, as we have seen, are likely to be complex, but an alternative question could also be posed. Why the outrage? Public male figures have, throughout history, made derogatory, demeaning and sexist remarks about women, and the material effects of gender inequality continue to be felt- consider the gender pay gap and glass ceiling phenomenon for starters. So why did this particular comment ignite such widespread indignation and anger?

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This thesis presents novel vision based control solutions that enable fixed-wing Unmanned Aerial Vehicles to perform tasks of inspection over infrastructure including power lines, pipe lines and roads. This is achieved through the development of techniques that combine visual servoing with alternate manoeuvres that assist the UAV in both following and observing the feature from a downward facing camera. Control designs are developed through techniques of Image Based Visual Servoing to utilise sideslip through Skid-to-Turn and Forward-Slip manoeuvres. This allows the UAV to simultaneously track and collect data over the length of infrastructure, including straight segments and the transition where these meet.

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An analytical solution of the heat transfer problem with viscous dissipation for non-Newtonian fluids with power-law model in the thermal entrance region of a circular pipe and two parallel plates under constant heat flux conditions is obtained using eigenvalue approach by suitably replacing one of the boundary conditions by total energy balance equation. Analytical expressions for the wall and the bulk temperatures and the local Nusselt number are presented. The results are in close agreement with those obtained by implicit finite-difference scheme. It is found that the role of viscous dissipation on heat transfer is completely different for heating and cooling conditions at the wall. The results for the case of cooling at the wall are of interest in the design of the oil pipe line.

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As power systems grow in their size and interconnections, their complexity increases. Rising costs due to inflation and increased environmental concerns has made transmission, as well as generation systems be operated closer to design limits. Hence power system voltage stability and voltage control are emerging as major problems in the day-to-day operation of stressed power systems. For secure operation and control of power systems under normal and contingency conditions it is essential to provide solutions in real time to the operator in energy control center (ECC). Artificial neural networks (ANN) are emerging as an artificial intelligence tool, which give fast, though approximate, but acceptable solutions in real time as they mostly use the parallel processing technique for computation. The solutions thus obtained can be used as a guide by the operator in ECC for power system control. This paper deals with development of an ANN architecture, which provide solutions for monitoring, and control of voltage stability in the day-to-day operation of power systems.

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Power system is at the brink of change. Engineering needs, economic forces and environmental factors are the main drivers of this change. The vision is to build a smart electrical grid and a smarter market mechanism around it to fulfill mandates on clean energy. Looking at engineering and economic issues in isolation is no longer an option today; it needs an integrated design approach. In this thesis, I shall revisit some of the classical questions on the engineering operation of power systems that deals with the nonconvexity of power flow equations. Then I shall explore some issues of the interaction of these power flow equations on the electricity markets to address the fundamental issue of market power in a deregulated market environment. Finally, motivated by the emergence of new storage technologies, I present an interesting result on the investment decision problem of placing storage over a power network. The goal of this study is to demonstrate that modern optimization and game theory can provide unique insights into this complex system. Some of the ideas carry over to applications beyond power systems.

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Power consumption of a multi-GHz local clock driver is reduced by returning energy stored in the clock-tree load capacitance back to the on-chip power-distribution grid. We call this type of return energy recycling. To achieve a nearly square clock waveform, the energy is transferred in a non-resonant way using an on-chip inductor in a configuration resembling a full-bridge DC-DC converter. A zero-voltage switching technique is implemented in the clock driver to reduce dynamic power loss associated with the high switching frequencies. A prototype implemented in 90 nm CMOS shows a power savings of 35% at 4 GHz. The area needed for the inductor in this new clock driver is about 6% of a local clock region. © 2006 IEEE.