597 resultados para stack


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The thesis deals with the background, development and description of a mathematical stock control methodology for use within an oil and chemical blending company, where demand and replenishment lead-times are generally non-stationary. The stock control model proper relies on, as input, adaptive forecasts of demand determined for an economical forecast/replenishment period precalculated on an individual stock-item basis. The control procedure is principally that of the continuous review, reorder level type, where the reorder level and reorder quantity 'float', that is, each changes in accordance with changes in demand. Two versions of the Methodology are presented; a cost minimisation version and a service level version. Realising the importance of demand forecasts, four recognised variations of the Trigg and Leach adaptive forecasting routine are examined. A fifth variation, developed, is proposed as part of the stock control methodology. The results of testing the cost minimisation version of the Methodology with historical data, by means of a computerised simulation, are presented together with a description of the simulation used. The performance of the Methodology is in addition compared favourably to a rule-of-thumb approach considered by the Company as an interim solution for reducing stack levels. The contribution of the work to the field of scientific stock control is felt to be significant for the following reasons:- (I) The Methodology is designed specifically for use with non-stationary demand and for this reason alone appears to be unique. (2) The Methodology is unique in its approach and the cost-minimisation version is shown to work successfully with the demand data presented. (3) The Methodology and the thesis as a whole fill an important gap between complex mathematical stock control theory and practical application. A brief description of a computerised order processing/stock monitoring system, designed and implemented as a pre-requisite for the Methodology's practical operation, is presented as an appendix.

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The use of high birefringence fiber interrogating interferometer for optical sensing applications was discussed. The method is of low cost and permits simple adjustment of the optical path difference and has much lower sensitivity to environmental perturbation. The polarization-maintaining (PM) fiber interferometer adopted a heterodyne approach using interferometric wavelength shift detection. The study showed that the inclusion of power amplifier driving a multi-element piezoelectric stack will enable the bandwidth to be pushed up into the kHz regime.

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Models are central tools for modern scientists and decision makers, and there are many existing frameworks to support their creation, execution and composition. Many frameworks are based on proprietary interfaces, and do not lend themselves to the integration of models from diverse disciplines. Web based systems, or systems based on web services, such as Taverna and Kepler, allow composition of models based on standard web service technologies. At the same time the Open Geospatial Consortium has been developing their own service stack, which includes the Web Processing Service, designed to facilitate the executing of geospatial processing - including complex environmental models. The current Open Geospatial Consortium service stack employs Extensible Markup Language as a default data exchange standard, and widely-used encodings such as JavaScript Object Notation can often only be used when incorporated with Extensible Markup Language. Similarly, no successful engagement of the Web Processing Service standard with the well-supported technologies of Simple Object Access Protocol and Web Services Description Language has been seen. In this paper we propose a pure Simple Object Access Protocol/Web Services Description Language processing service which addresses some of the issues with the Web Processing Service specication and brings us closer to achieving a degree of interoperability between geospatial models, and thus realising the vision of a useful 'model web'.

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In this paper, we discuss how discriminative training can be applied to the hidden vector state (HVS) model in different task domains. The HVS model is a discrete hidden Markov model (HMM) in which each HMM state represents the state of a push-down automaton with a finite stack size. In previous applications, maximum-likelihood estimation (MLE) is used to derive the parameters of the HVS model. However, MLE makes a number of assumptions and unfortunately some of these assumptions do not hold. Discriminative training, without making such assumptions, can improve the performance of the HVS model by discriminating the correct hypothesis from the competing hypotheses. Experiments have been conducted in two domains: the travel domain for the semantic parsing task using the DARPA Communicator data and the Air Travel Information Services (ATIS) data and the bioinformatics domain for the information extraction task using the GENIA corpus. The results demonstrate modest improvements of the performance of the HVS model using discriminative training. In the travel domain, discriminative training of the HVS model gives a relative error reduction rate of 31 percent in F-measure when compared with MLE on the DARPA Communicator data and 9 percent on the ATIS data. In the bioinformatics domain, a relative error reduction rate of 4 percent in F-measure is achieved on the GENIA corpus.

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We propose a hybrid generative/discriminative framework for semantic parsing which combines the hidden vector state (HVS) model and the hidden Markov support vector machines (HM-SVMs). The HVS model is an extension of the basic discrete Markov model in which context is encoded as a stack-oriented state vector. The HM-SVMs combine the advantages of the hidden Markov models and the support vector machines. By employing a modified K-means clustering method, a small set of most representative sentences can be automatically selected from an un-annotated corpus. These sentences together with their abstract annotations are used to train an HVS model which could be subsequently applied on the whole corpus to generate semantic parsing results. The most confident semantic parsing results are selected to generate a fully-annotated corpus which is used to train the HM-SVMs. The proposed framework has been tested on the DARPA Communicator Data. Experimental results show that an improvement over the baseline HVS parser has been observed using the hybrid framework. When compared with the HM-SVMs trained from the fully-annotated corpus, the hybrid framework gave a comparable performance with only a small set of lightly annotated sentences. © 2008. Licensed under the Creative Commons.

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Web APIs have gained increasing popularity in recent Web service technology development owing to its simplicity of technology stack and the proliferation of mashups. However, efficiently discovering Web APIs and the relevant documentations on the Web is still a challenging task even with the best resources available on the Web. In this paper we cast the problem of detecting the Web API documentations as a text classification problem of classifying a given Web page as Web API associated or not. We propose a supervised generative topic model called feature latent Dirichlet allocation (feaLDA) which offers a generic probabilistic framework for automatic detection of Web APIs. feaLDA not only captures the correspondence between data and the associated class labels, but also provides a mechanism for incorporating side information such as labelled features automatically learned from data that can effectively help improving classification performance. Extensive experiments on our Web APIs documentation dataset shows that the feaLDA model outperforms three strong supervised baselines including naive Bayes, support vector machines, and the maximum entropy model, by over 3% in classification accuracy. In addition, feaLDA also gives superior performance when compared against other existing supervised topic models.

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A Bragg grating fast tunable filter prototype working over a linear tuning range of 45 nm with a maximum tuning speed of 21 nm/ms has been realized. The tunable filter system is based on two piezoelectric stack actuators moving a mechanical device thus compressing an apodized fiber Bragg grating. The filter allows both traction and compression and can work in transmission and in reflection. It is designed to work with a channel spacing of 100 GHz according to the ITU specifications for wavelength division multiplexing systems.

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The growing use of a variety of information systems in crisis management both by non-governmental organizations (NGOs) and emergency management agencies makes the challenges of information sharing and interoperability increasingly important. The use of semantic web technologies is a growing area and is a technology stack specifically suited to these challenges. This paper presents a review of ontologies, vocabularies and taxonomies that are useful in crisis management systems. We identify the different subject areas relevant to crisis management based on a review of the literature. The different ontologies and vocabularies available are analysed in terms of their coverage, design and usability. We also consider the use cases for which they were designed and the degree to which they follow a variety of standards. While providing comprehensive ontologies for the crisis domain is not feasible or desirable there is considerable scope to develop ontologies for the subject areas not currently covered and for the purposes of interoperability.

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We have investigated the microstructure and bonding of two biomass-based porous carbon chromatographic stationary phase materials (alginic acid-derived Starbon® and calcium alginate-derived mesoporous carbon spheres (AMCS) and a commercial porous graphitic carbon (PGC), using high resolution transmission electron microscopy, electron energy loss spectroscopy (EELS), N2 porosimetry and X-ray photoelectron spectroscopy (XPS). The planar carbon sp -content of all three material types is similar to that of traditional nongraphitizing carbon although, both biomass-based carbon types contain a greater percentage of fullerene character (i.e. curved graphene sheets) than a non-graphitizing carbon pyrolyzed at the same temperature. This is thought to arise during the pyrolytic breakdown of hexauronic acid residues into C5 intermediates. Energy dispersive X-ray and XPS analysis reveals a homogeneous distribution of calcium in the AMCS and a calcium catalysis mechanism is discussed. That both Starbon® and AMCS, with high-fullerene character, show chromatographic properties similar to those of a commercial PGC material with extended graphitic stacks, suggests that, for separations at the molecular level, curved fullerene- like and planar graphitic sheets are equivalent in PGC chromatography. In addition, variation in the number of graphitic layers suggests that stack depth has minimal effect on the retention mechanism in PGC chromatography. © 2013 Elsevier Ltd. All rights reserved.

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Jones v Kernott [2011] UKSC 53 (SC) Stack v Dowden [2007] UKHL 17; [2007] 2 A.C. 432 (HL). Casenote explores the implications of the ruling in Jones v Kernott by the Supreme Court and assesses its implications for English Property Law. Building on the commonwealth experience the casenote calls for the intorduction of a statutory scheme so as to allow courts to reallocate property rights to unmarried cohabitants in the event of relationship breakdown.

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In this dissertation, I examine both theoretically and empirically the relationship between stock prices and income distribution using an endogenous growth model with social status impatience.^ The theoretical part looks into how status impatience and current economic status jointly determine time preference, savings, future economic status, stock prices, growth and wealth distribution in the steady state. This work builds on Burgstaller and Karayalcin (1996).^ More specifically, I look at (i) the effects of the distribution of status impatience levels on the distribution of steady state assets, incomes and consumption and (ii) the effects of changes in relative levels of status impatience on stock prices. Therefore, from (i) and (ii), I derive the correlation between stock prices, incomes and asset distribution. Also, the analysis of the stack market is undertaken in the presence of adjustment costs to investments.^ The empirical chapter looks at (i) the correlation between income inequality and long run economic growth on the one hand and (ii) the correlation between stock market prices and income inequality on the other. The role of stock prices and social status is examined to better understand the forces that enable a country to grow overtime and to determine why output per capita varies across countries. The data are from Summers and Heston (1988), Barro and Wolf (1989), Alesina and Rodrik (1994), Global financial Database (1997) and the World Bank. Data for social status are collected through a primary sample survey on the internet. Twenty-five developed and developing countries are included in the sample.^ The model developed in this study was specified as a system of simultaneous equations, in which per capita growth rate and income inequality were endogenous variables. Additionally, stock price index and social status measures were also incorporated. The results indicate that income inequality is inversely related to economic growth. In addition, increase in income inequality arising from higher stock prices constrains growth. Moreover, where social status is determined by income levels, it influences long run growth. Therefore, these results support findings of Persson and Tabellini (1994) and Alesina and Rodrik (1994). ^

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Due to the increasing demand for high power and reliable miniaturized energy storage devices, the development of micro-supercapacitors or electrochemical micro-capacitors have attracted much attention in recent years. This dissertation investigates several strategies to develop on-chip micro-supercapacitors with high power and energy density. Micro-supercapacitors based on interdigitated carbon micro-electrode arrays are fabricated through carbon microelectromechanical systems (C-MEMS) technique which is based on carbonization of patterned photoresist. To improve the capacitive behavior, electrochemical activation is performed on carbon micro-electrode arrays. The developed micro-supercapacitors show specific capacitances as high as 75 mFcm-2 at a scan rate of 5 mVs -1 after electrochemical activation for 30 minutes. The capacitance loss is less than 13% after 1000 cyclic voltammetry (CV) cycles. These results indicate that electrochemically activated C-MEMS micro-electrode arrays are promising candidates for on-chip electrochemical micro-capacitor applications. The energy density of micro-supercapacitors was further improved by conformal coating of polypyrrole (PPy) on C-MEMS structures. In these types of micro-devices the three dimensional (3D) carbon microstructures serve as current collectors for high energy density PPy electrodes. The electrochemical characterizations of these micro-supercapacitors show that they can deliver a specific capacitance of about 162.07 mFcm-2 and a specific power of 1.62mWcm -2 at a 20 mVs-1 scan rate. Addressing the need for high power micro-supercapacitors, the application of graphene as electrode materials for micro-supercapacitor was also investigated. The present study suggests a novel method to fabricate graphene-based micro-supercapacitors with thin film or in-plane interdigital electrodes. The fabricated micro-supercapacitors show exceptional frequency response and power handling performance and could effectively charge and discharge at rates as high as 50 Vs-1. CV measurements show that the specific capacitance of the micro-supercapacitor based on reduced graphene oxide and carbon nanotube composites is 6.1 mFcm -2 at scan rate of 0.01Vs-1. At a very high scan rate of 50 Vs-1, a specific capacitance of 2.8 mFcm-2 (stack capacitance of 3.1 Fcm-3) is recorded. This unprecedented performance can potentially broaden the future applications of micro-supercapacitors.

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Storage is a central part of computing. Driven by exponentially increasing content generation rate and a widening performance gap between memory and secondary storage, researchers are in the perennial quest to push for further innovation. This has resulted in novel ways to "squeeze" more capacity and performance out of current and emerging storage technology. Adding intelligence and leveraging new types of storage devices has opened the door to a whole new class of optimizations to save cost, improve performance, and reduce energy consumption. In this dissertation, we first develop, analyze, and evaluate three storage extensions. Our first extension tracks application access patterns and writes data in the way individual applications most commonly access it to benefit from the sequential throughput of disks. Our second extension uses a lower power flash device as a cache to save energy and turn off the disk during idle periods. Our third extension is designed to leverage the characteristics of both disks and solid state devices by placing data in the most appropriate device to improve performance and save power. In developing these systems, we learned that extending the storage stack is a complex process. Implementing new ideas incurs a prolonged and cumbersome development process and requires developers to have advanced knowledge of the entire system to ensure that extensions accomplish their goal without compromising data recoverability. Futhermore, storage administrators are often reluctant to deploy specific storage extensions without understanding how they interact with other extensions and if the extension ultimately achieves the intended goal. We address these challenges by using a combination of approaches. First, we simplify the storage extension development process with system-level infrastructure that implements core functionality commonly needed for storage extension development. Second, we develop a formal theory to assist administrators deploy storage extensions while guaranteeing that the given high level goals are satisfied. There are, however, some cases for which our theory is inconclusive. For such scenarios we present an experimental methodology that allows administrators to pick an extension that performs best for a given workload. Our evaluation demostrates the benefits of both the infrastructure and the formal theory.

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A prototype 3-dimensional (3D) anode, based on multiwall carbon nanotubes (MWCNTs), for Li-ion batteries (LIBs), with potential use in Electric Vehicles (EVs) was investigated. The unique 3D design of the anode allowed much higher areal mass density of MWCNTs as active materials, resulting in more amount of Li+ ion intake, compared to that of a conventional 2D counterpart. Furthermore, 3D amorphous Si/MWCNTs hybrid structure offered enhancement in electrochemical response (specific capacity 549 mAhg–1 ). Also, an anode stack was fabricated to further increase the areal or volumetric mass density of MWCNTs. An areal mass density of the anode stack 34.9 mg/cm2 was attained, which is 1,342% higher than the value for a single layer 2.6 mg/cm2. Furthermore, the binder-assisted and hot-pressed anode stack yielded the average reversible, stable gravimetric and volumetric specific capacities of 213 mAhg–1 and 265 mAh/cm3, respectively (at 0.5C). Moreover, a large-scale patterned novel flexible 3D MWCNTs-graphene-polyethylene terephthalate (PET) anode structure was prepared. It generated a reversible specific capacity of 153 mAhg–1 at 0.17C and cycling stability of 130 mAhg –1 up to 50 cycles at 1.7C.

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Late Pliocene changes in the advection of Mediterranean Outflow Water (MOW) derivates were reconstructed at northeast Atlantic DSDP/ODP sites 548 and 982 and compared to records of WMDW at West Mediterranean Site 978. Neodymium isotope (epsilon-Nd) values more positive than ~10.5/~ 11 reflect diluted MOW derivates that spread almost continuously into the northeast Atlantic from 3.7 to 2.55 Ma, reaching Rockall Plateau Site 982 from 3.63 to 2.75 Ma. From 3.4 to 3.3 Ma average MOW temperature and salinity increased by 2°-4 °C and ~1 psu both at proximal Site 548 and distal Site 982. The rise implies a rise in flow strength, coeval with a long-term rise in both west Mediterranean Sea surface salinity by almost 2 psu and average bottom water salinity (BWS) by ~1 psu, despite inherent uncertainties in BWS estimates. The changes were linked with major Mediterranean aridification and a drop in African monsoon humidity. In contrast to model expectations, the rise in MOW salt discharge after 3.4 Ma did not translate into improved ventilation of North Atlantic Deep Water, since it possibly was too small to significantly influence Atlantic Meridional Overturning Circulation. Right after ~2.95 Ma, with the onset of major Northern Hemisphere Glaciation, long-term average bottom water temperature (BWT) and BWS at Site 548 dropped abruptly by ~5 °C and ~1-2 psu, in contrast to more distal Site 982, where BWT and BWS continued to oscillate at estimates of ~2 °C and 1.5-2.5 psu higher than today until ~2.6 Ma. We relate the small-scale changes both to a reduced MOW flow and to enhanced dilution by warm waters of a strengthened North Atlantic Current temporarily replacing MOW derivates at Rockall Plateau.