911 resultados para concepts of power


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In this paper, we discuss the issues related to word recognition in born-digital word images. We introduce a novel method of power-law transformation on the word image for binarization. We show the improvement in image binarization and the consequent increase in the recognition performance of OCR engine on the word image. The optimal value of gamma for a word image is automatically chosen by our algorithm with fixed stroke width threshold. We have exhaustively experimented our algorithm by varying the gamma and stroke width threshold value. By varying the gamma value, we found that our algorithm performed better than the results reported in the literature. On the ICDAR Robust Reading Systems Challenge-1: Word Recognition Task on born digital dataset, as compared to the recognition rate of 61.5% achieved by TH-OCR after suitable pre-processing by Yang et. al. and 63.4% by ABBYY Fine Reader (used as baseline by the competition organizers without any preprocessing), we achieved 82.9% using Omnipage OCR applied on the images after being processed by our algorithm.

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This paper presents an analysis of an organic Rankine cycle (ORC) with dry cooling system aided by an earth-coupled passive cooling system. Several organic fluids were considered as working fluids in the ORC in the temperature range of 125-200 degrees C. An earth-air-heat-exchanger (EMU) is studied for a location in the United States (Las Vegas) and another in India (New Delhi), to pre cool the ambient air before entering an air-cooled condenser (ACC). It was observed that the efficiency of the system improved by 1-3% for the system located in Las Vegas and fluctuations associated with temperature variations of the ambient air were also reduced when the EAHE system was used. A ground-coupled heat pump (GCHP) is also studied for these locations where cooling water is pre cooled in an underground buried pipe before entering a condenser heat exchanger in a closed loop. The area of the buried pipe and the condenser size are calculated per kW of power generation for various working fluids.

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The dissertation is concerned with the mathematical study of various network problems. First, three real-world networks are considered: (i) the human brain network (ii) communication networks, (iii) electric power networks. Although these networks perform very different tasks, they share similar mathematical foundations. The high-level goal is to analyze and/or synthesis each of these systems from a “control and optimization” point of view. After studying these three real-world networks, two abstract network problems are also explored, which are motivated by power systems. The first one is “flow optimization over a flow network” and the second one is “nonlinear optimization over a generalized weighted graph”. The results derived in this dissertation are summarized below.

Brain Networks: Neuroimaging data reveals the coordinated activity of spatially distinct brain regions, which may be represented mathematically as a network of nodes (brain regions) and links (interdependencies). To obtain the brain connectivity network, the graphs associated with the correlation matrix and the inverse covariance matrix—describing marginal and conditional dependencies between brain regions—have been proposed in the literature. A question arises as to whether any of these graphs provides useful information about the brain connectivity. Due to the electrical properties of the brain, this problem will be investigated in the context of electrical circuits. First, we consider an electric circuit model and show that the inverse covariance matrix of the node voltages reveals the topology of the circuit. Second, we study the problem of finding the topology of the circuit based on only measurement. In this case, by assuming that the circuit is hidden inside a black box and only the nodal signals are available for measurement, the aim is to find the topology of the circuit when a limited number of samples are available. For this purpose, we deploy the graphical lasso technique to estimate a sparse inverse covariance matrix. It is shown that the graphical lasso may find most of the circuit topology if the exact covariance matrix is well-conditioned. However, it may fail to work well when this matrix is ill-conditioned. To deal with ill-conditioned matrices, we propose a small modification to the graphical lasso algorithm and demonstrate its performance. Finally, the technique developed in this work will be applied to the resting-state fMRI data of a number of healthy subjects.

Communication Networks: Congestion control techniques aim to adjust the transmission rates of competing users in the Internet in such a way that the network resources are shared efficiently. Despite the progress in the analysis and synthesis of the Internet congestion control, almost all existing fluid models of congestion control assume that every link in the path of a flow observes the original source rate. To address this issue, a more accurate model is derived in this work for the behavior of the network under an arbitrary congestion controller, which takes into account of the effect of buffering (queueing) on data flows. Using this model, it is proved that the well-known Internet congestion control algorithms may no longer be stable for the common pricing schemes, unless a sufficient condition is satisfied. It is also shown that these algorithms are guaranteed to be stable if a new pricing mechanism is used.

Electrical Power Networks: Optimal power flow (OPF) has been one of the most studied problems for power systems since its introduction by Carpentier in 1962. This problem is concerned with finding an optimal operating point of a power network minimizing the total power generation cost subject to network and physical constraints. It is well known that OPF is computationally hard to solve due to the nonlinear interrelation among the optimization variables. The objective is to identify a large class of networks over which every OPF problem can be solved in polynomial time. To this end, a convex relaxation is proposed, which solves the OPF problem exactly for every radial network and every meshed network with a sufficient number of phase shifters, provided power over-delivery is allowed. The concept ofpower over-delivery” is equivalent to relaxing the power balance equations to inequality constraints.

Flow Networks: In this part of the dissertation, the minimum-cost flow problem over an arbitrary flow network is considered. In this problem, each node is associated with some possibly unknown injection, each line has two unknown flows at its ends related to each other via a nonlinear function, and all injections and flows need to satisfy certain box constraints. This problem, named generalized network flow (GNF), is highly non-convex due to its nonlinear equality constraints. Under the assumption of monotonicity and convexity of the flow and cost functions, a convex relaxation is proposed, which always finds the optimal injections. A primary application of this work is in the OPF problem. The results of this work on GNF prove that the relaxation on power balance equations (i.e., load over-delivery) is not needed in practice under a very mild angle assumption.

Generalized Weighted Graphs: Motivated by power optimizations, this part aims to find a global optimization technique for a nonlinear optimization defined over a generalized weighted graph. Every edge of this type of graph is associated with a weight set corresponding to the known parameters of the optimization (e.g., the coefficients). The motivation behind this problem is to investigate how the (hidden) structure of a given real/complex valued optimization makes the problem easy to solve, and indeed the generalized weighted graph is introduced to capture the structure of an optimization. Various sufficient conditions are derived, which relate the polynomial-time solvability of different classes of optimization problems to weak properties of the generalized weighted graph such as its topology and the sign definiteness of its weight sets. As an application, it is proved that a broad class of real and complex optimizations over power networks are polynomial-time solvable due to the passivity of transmission lines and transformers.

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The Trench Insulated Gate Bipolar Transistor (IGBT) is the most promising structure for the next generation of power semiconductor devices with wide applications ranging from motor control (1-4 kV) to HVDC (6.5 kV). Here we present for the first time an optimum design of a 1.4kV Trench IGBT using a new, fully integrated optimisation system comprising process and device simulators and the RSM optimiser. The use of this new TCAD system has contributed largely to realizing devices with characteristics far superior to the previous DMOS generation of IGBTs. Full experimental results on 1.4kV Trench IGBTs which are in excellent agreement with the TCAD predictions are reported.

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15 years ago the vertical SuperJunction (SJ) concept conceived for SJ power MOSFETs was the last, major breakthrough in the field of silicon power devices. Today, the SuperJunction MOSFET technologies have reached a mature stage characterized by gradual performance improvements. SuperJunction Insulated Gate Bipolar Transistors (SJ IGBTs) could interrupt this stagnation holding promise to revitalize voltage classes from 600 up to 1200 V. Such SJ IGBTs surpass by a very significant margin their SJ MOSFET counterparts both in terms of power handling capability, on-state and turn-off losses, all at the same time. On the higher end of the voltage class, SJ IGBTs would top the performance of 1.2 kV IGBTs by a similar margin. © 2012 IEEE.

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This paper describes a methodology that enables fast and reasonably accurate prediction of the reliability of power electronic modules featuring IGBTs and p-i-n diodes, by taking into account thermo-mechanical failure mechanisms of the devices and their associated packaging. In brief, the proposed simulation framework performs two main tasks which are tightly linked together: (i) the generation of the power devices' transient thermal response for realistic long load cycles and (ii) the prediction of the power modules' lifetime based on the obtained temperature profiles. In doing so the first task employs compact, physics-based device models, power losses lookup tables and polynomials and combined material-failure and thermal modelling, while the second task uses advanced reliability tests for failure mode and time-to-failure estimation. The proposed technique is intended to be utilised as a design/optimisation tool for reliable power electronic converters, since it allows easy and fast investigation of the effects that changes in circuit topology or devices' characteristics and packaging have on the reliability of the employed power electronic modules. © 2012 IEEE.

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This work presents simplified 242mAm-fueled nuclear battery concept design featuring direct fission products energy conversion and passive heat rejection. Optimization of the battery operating characteristics and dimensions was performed. The calculations of power conversion efficiency under thermal and nuclear design constraints showed that 5.6 W e/kg power density can be achieved, which corresponds to conversion efficiency of about 4%. A system with about 190 cm outer radius translates into 17.8 MT mass per 100 kW e. Total power scales linearly with the outer surface area of the battery through which the residual heat is rejected. Tradeoffs between the battery lifetime, mass, dimensions, power rating, and conversion efficiency are presented and discussed. The battery can be used in a wide variety of interplanetary missions with power requirements in the kW to MW range. Copyright © 2007 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

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The effect of the bandgap narrowing (BGN) on performance of power devices is investigated in detail in this paper. The analysis reveals that the change in the energy band structure caused by BGN can strongly affect the conductivity modulation of the bipolar devices resulting in a completely different performance. This is due to the modified injection efficiency under high-level injection conditions. Using a comprehensive analysis of the injection efficiency in a p-n junction, an analytical model for this phenomenon is developed. BGN model tuning has been proved to be essential in accurately predicting the performance of a lateral insulated-gate bipolar transistor (IGBT). Other devices such as p-i-n diodes or punch-through IGBTs are significantly affected by the BGN, while others, such as field-stop IGBTs or power MOSFETs, are only marginally affected. © 2013 IEEE.

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With the proliferation of mobile wireless communication and embedded systems, the energy efficiency becomes a major design constraint. The dissipated energy is often referred as the product of power dissipation and the input-output delay. Most of electronic design automation techniques focus on optimising only one of these parameters either power or delay. Industry standard design flows integrate systematic methods of optimising either area or timing while for power consumption optimisation one often employs heuristics which are characteristic to a specific design. In this work we answer three questions in our quest to provide a systematic approach to joint power and delay Optimisation. The first question of our research is: How to build a design flow which incorporates academic and industry standard design flows for power optimisation? To address this question, we use a reference design flow provided by Synopsys and integrate in this flow academic tools and methodologies. The proposed design flow is used as a platform for analysing some novel algorithms and methodologies for optimisation in the context of digital circuits. The second question we answer is: Is possible to apply a systematic approach for power optimisation in the context of combinational digital circuits? The starting point is a selection of a suitable data structure which can easily incorporate information about delay, power, area and which then allows optimisation algorithms to be applied. In particular we address the implications of a systematic power optimisation methodologies and the potential degradation of other (often conflicting) parameters such as area or the delay of implementation. Finally, the third question which this thesis attempts to answer is: Is there a systematic approach for multi-objective optimisation of delay and power? A delay-driven power and power-driven delay optimisation is proposed in order to have balanced delay and power values. This implies that each power optimisation step is not only constrained by the decrease in power but also the increase in delay. Similarly, each delay optimisation step is not only governed with the decrease in delay but also the increase in power. The goal is to obtain multi-objective optimisation of digital circuits where the two conflicting objectives are power and delay. The logic synthesis and optimisation methodology is based on AND-Inverter Graphs (AIGs) which represent the functionality of the circuit. The switching activities and arrival times of circuit nodes are annotated onto an AND-Inverter Graph under the zero and a non-zero-delay model. We introduce then several reordering rules which are applied on the AIG nodes to minimise switching power or longest path delay of the circuit at the pre-technology mapping level. The academic Electronic Design Automation (EDA) tool ABC is used for the manipulation of AND-Inverter Graphs. We have implemented various combinatorial optimisation algorithms often used in Electronic Design Automation such as Simulated Annealing and Uniform Cost Search Algorithm. Simulated Annealing (SMA) is a probabilistic meta heuristic for the global optimization problem of locating a good approximation to the global optimum of a given function in a large search space. We used SMA to probabilistically decide between moving from one optimised solution to another such that the dynamic power is optimised under given delay constraints and the delay is optimised under given power constraints. A good approximation to the global optimum solution of energy constraint is obtained. Uniform Cost Search (UCS) is a tree search algorithm used for traversing or searching a weighted tree, tree structure, or graph. We have used Uniform Cost Search Algorithm to search within the AIG network, a specific AIG node order for the reordering rules application. After the reordering rules application, the AIG network is mapped to an AIG netlist using specific library cells. Our approach combines network re-structuring, AIG nodes reordering, dynamic power and longest path delay estimation and optimisation and finally technology mapping to an AIG netlist. A set of MCNC Benchmark circuits and large combinational circuits up to 100,000 gates have been used to validate our methodology. Comparisons for power and delay optimisation are made with the best synthesis scripts used in ABC. Reduction of 23% in power and 15% in delay with minimal overhead is achieved, compared to the best known ABC results. Also, our approach is also implemented on a number of processors with combinational and sequential components and significant savings are achieved.

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The work presented in this thesis covers four major topics of research related to the grid integration of wave energy. More specifically, the grid impact of a wave farm on the power quality of its local network is investigated. Two estimation methods were developed regarding the flicker level Pst generated by a wave farm in relation to its rated power as well as in relation to the impedance angle ψk of the node in the grid to which it is connected. The electrical design of a typical wave farm design is also studied in terms of minimum rating for three types of costly pieces of equipment, namely the VAr compensator, the submarine cables and the overhead line. The power losses dissipated within the farm's electrical network are also evaluated. The feasibility of transforming a test site into a commercial site of greater rated power is investigated from the perspective of power quality and of cables and overhead line thermal loading. Finally, the generic modelling of ocean devices, referring here to both wave and tidal current devices, is investigated.

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Great demand in power optimized devices shows promising economic potential and draws lots of attention in industry and research area. Due to the continuously shrinking CMOS process, not only dynamic power but also static power has emerged as a big concern in power reduction. Other than power optimization, average-case power estimation is quite significant for power budget allocation but also challenging in terms of time and effort. In this thesis, we will introduce a methodology to support modular quantitative analysis in order to estimate average power of circuits, on the basis of two concepts named Random Bag Preserving and Linear Compositionality. It can shorten simulation time and sustain high accuracy, resulting in increasing the feasibility of power estimation of big systems. For power saving, firstly, we take advantages of the low power characteristic of adiabatic logic and asynchronous logic to achieve ultra-low dynamic and static power. We will propose two memory cells, which could run in adiabatic and non-adiabatic mode. About 90% dynamic power can be saved in adiabatic mode when compared to other up-to-date designs. About 90% leakage power is saved. Secondly, a novel logic, named Asynchronous Charge Sharing Logic (ACSL), will be introduced. The realization of completion detection is simplified considerably. Not just the power reduction improvement, ACSL brings another promising feature in average power estimation called data-independency where this characteristic would make power estimation effortless and be meaningful for modular quantitative average case analysis. Finally, a new asynchronous Arithmetic Logic Unit (ALU) with a ripple carry adder implemented using the logically reversible/bidirectional characteristic exhibiting ultra-low power dissipation with sub-threshold region operating point will be presented. The proposed adder is able to operate multi-functionally.

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This thesis comprises close textual analyses of Chicana author Helena María Viramontes' two published novels, Under the Feet of Jesus (1995) and Their Dogs Came With Them (2007). These analyses fall under three broad frameworks: space, time and body. Chapter One engages with the first of these frameworks, space, and explores concepts of cognitive mapping and heteroptopias. Chapter Two, which looks at time, employs theories of intertextuality and the palimpsest, while Chapter Three looks at the interrrelationship between mythology and images of the body in the texts. This study emerges five years after the publication of Viramontes' last novel, Their Dogs Came With Them, but offers fresh insight into the contribution of the author to both the Chicano literary tradition and also the U.S. canon through her critique of hegemonic power structures that suppress not only the voices of lower class ethnic citizens but also of ethnic writers. In particular, her work chastises the paucity of attention given to ethnic women writers in the U.S. This thesis reaffirms Viramontes' position as one of the most important writers living and writing in the U.S. today. It corroborates her work as a contestation against ethnic and gender suppression, and applauds the craftsmanship of her narrative style that delicately but decisively exposes the socio-political wrongs that occur in ocntemporary U.S. society.

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This thesis traces a genealogy of the discourse of mathematics education reform in Ireland at the beginning of the twenty first century at a time when the hegemonic political discourse is that of neoliberalism. It draws on the work of Michel Foucault to identify the network of power relations involved in the development of a single case of curriculum reform – in this case Project Maths. It identifies the construction of an apparatus within the fields of politics, economics and education, the elements of which include institutions like the OECD and the Government, the bureaucracy, expert groups and special interest groups, the media, the school, the State, state assessment and international assessment. Five major themes in educational reform emerge from the analysis: the arrival of neoliberal governance in Ireland; the triumph of human capital theory as the hegemonic educational philosophy here; the dominant role of OECD/PISA and its values in the mathematics education discourse in Ireland; the fetishisation of western scientific knowledge and knowledge as commodity; and the formation of a new kind of subjectivity, namely the subjectivity of the young person as a form of human-capital-to-be. In particular, it provides a critical analysis of the influence of OECD/PISA on the development of mathematics education policy here – especially on Project Maths curriculum, assessment and pedagogy. It unpacks the arguments in favour of curriculum change and lays bare their ideological foundations. This discourse contextualises educational change as occurring within a rapidly changing economic environment where the concept of the State’s economic aspirations and developments in science, technology and communications are reshaping both the focus of business and the demands being put on education. Within this discourse, education is to be repurposed and its consequences measured against the paradigm of the Knowledge Economy – usually characterised as the inevitable or necessary future of a carefully defined present.

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© Emerald Group Publishing Limited.Purpose – The purpose of this paper is to introduce the global value chain (GVC) approach to understand the relationship between multinational enterprises (MNEs) and the changing patterns of global trade, investment and production, and its impact on economic and social upgrading. It aims to illuminate how GVCs can advance our understanding about MNEs and rising power (RP) firms and their impact on economic and social upgrading in fragmented and dispersed global production systems. Design/methodology/approach – The paper reviews theGVCliterature focusing on two conceptual elements of the GVC approach, governance and upgrading, and highlights three key recent developments in GVCs: concentration, regionalization and synergistic governance. Findings – The paper underscores the complicated role of GVCs in shaping economic and social upgrading for emerging economies, RP firms and developing country firms in general. Rising geographic and organizational concentration in GVCs leads to the uneven distribution of upgrading opportunities in favor of RP firms, and yet economic upgrading may be elusive even for the most established suppliers because of power asymmetry with global buyers. Shifting end markets and the regionalization of value chains can benefit RP firms by presenting alternative markets for upgrading. Yet, without further upgrading, such benefits may be achieved at the expense of social downgrading. Finally, the ineffectiveness of private standards to achieve social upgrading has led to calls for synergistic governance through the cooperation of private, public and social actors, both global and local. Originality/value – The paper illuminates how the GVC approach and its key concepts can contribute to the critical international business and RP firms literature by examining the latest dynamics in GVCs and their impacts on economic and social development in developing countries.