711 resultados para real shocks panel data


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Current research into the process of engineering design is extending the use of computers towards the acquisition, representation and application of design process knowledge in addition to the existing storage and manipulation of product-based models of design objects. This is a difficult task because the design of mechanical systems is a complex, often unpredictable process involving ill-structured problem solving skills and large amounts of knowledge, some which may be of an incomplete and subjective nature. Design problems require the integration of a variety of modes of working such as numerical, graphical, algorithmic or heuristic and demand products through synthesis, analysis and evaluation activities.

This report presents the results of a feasibility study into the blackboard approach and discusses the development of an initial prototype system that will enable an alphanumeric design dialogue between a designer and an expert to be analysed in a formal way, thus providing real-life protocol data on which to base the blackboard message structures.

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When searching for characteristic subpatterns in potentially noisy graph data, it appears self-evident that having multiple observations would be better than having just one. However, it turns out that the inconsistencies introduced when different graph instances have different edge sets pose a serious challenge. In this work we address this challenge for the problem of finding maximum weighted cliques. We introduce the concept of most persistent soft-clique. This is subset of vertices, that 1) is almost fully or at least densely connected, 2) occurs in all or almost all graph instances, and 3) has the maximum weight. We present a measure of clique-ness, that essentially counts the number of edge missing to make a subset of vertices into a clique. With this measure, we show that the problem of finding the most persistent soft-clique problem can be cast either as: a) a max-min two person game optimization problem, or b) a min-min soft margin optimization problem. Both formulations lead to the same solution when using a partial Lagrangian method to solve the optimization problems. By experiments on synthetic data and on real social network data we show that the proposed method is able to reliably find soft cliques in graph data, even if that is distorted by random noise or unreliable observations. Copyright 2012 by the author(s)/owner(s).

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Copyright © 2014, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. This paper presents the beginnings of an automatic statistician, focusing on regression problems. Our system explores an open-ended space of statistical models to discover a good explanation of a data set, and then produces a detailed report with figures and natural- language text. Our approach treats unknown regression functions non- parametrically using Gaussian processes, which has two important consequences. First, Gaussian processes can model functions in terms of high-level properties (e.g. smoothness, trends, periodicity, changepoints). Taken together with the compositional structure of our language of models this allows us to automatically describe functions in simple terms. Second, the use of flexible nonparametric models and a rich language for composing them in an open-ended manner also results in state- of-the-art extrapolation performance evaluated over 13 real time series data sets from various domains.

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依据可信计算机系统评测标准(TCSEC)要求,提出一种使用信道容量指标的安全实时数据库中数据竞争信道的限制方法(CUCCMM),给出了限制过程中信道容量度量算法和限制参数计算方法。为了保证系统的信道容量限制标准的准确执行,提出了一种基于多概率的并发控制协议选择策略(MPBPSP)。实验结果证明CUCCMM方法可以有效地、准确地实施对隐蔽信道容量的限制,并且通过使用MPBPSP策略显著降低了信道限制操作对系统实时性能的影响。

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This study examines the link between the economic growth and the environmental quality. Based on a panel data set, a N-shaped Environmental Kuzents Curve has been found for the sample period: a cubic relationship between per capita GDP and emissions of sulphur dioxide (SO2). We also find that energy consumption is an important determinant of environmental degradation. The empirical results suggest that we should promote environmental protection as soon as possible.

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An information system for inductively coupled plasma atomic emission spectrometry (TCP-BES) in MS Windows environment was developed based on the previous work in the laboratory. The system contains the data of about 28 000 spectral lines and a function of ICP spectral simulation,so it would be very helpful for line selection. The system also contains the Kalman filter and factor analysis programmes written with MS Visual Basic(version 4.0), which can be used for spectral interference correction and peak position optimization. A large amount of real spectral scanning data of rare earth elements were included in the system for user's references. All these characteristics made the system more useful and practical.

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Seismic While Drilling (SWD) is a new wellbore seismic technique. It uses the vibrations produced by a drill-bit while drilling as a downhole seismic energy source. The continuous signals generated by the drill bit are recorded by a pilot sensor attached to the top of the drill-string. Seismic wave receivers positioned in the earth near its surface receive the seismic waves both directly and reflection from the geologic formations. The pilot signal is cross-correlated with the receiver signals to compute travel-times of the arrivals (direct arrival and reflected arrival) and attenuate incoherent noise. No downhole intrusmentation is required to obtain the data and the data recording does not interfere with the drilling process. These characteristics offer a method by which borehole seismic data can be acquired, processed, and interpreted while drilling. As a Measure-While-Drill technique. SWD provides real-time seismic data for use at the well site . This can aid the engineer or driller by indicating the position of the drill-bit and providing a look at reflecting horizons yet to be encountered by the drill-bit. Furthermore, the ease with which surface receivers can be deployed makes multi-offset VSP economically feasible. First, this paper is theoretically studying drill-bit wavefield, interaction mode between drill-bit and formation below drill-bit , the new technique of modern signal process was applied to seismic data, the seismic body wave radiation pattern of a working roller-cone drill-bit can be characterized by theoretical modeling. Then , a systematical analysis about the drill-bit wave was done, time-distance equation of seismic wave traveling was established, the process of seismic while drilling was simulated using the computer software adaptive modeling of SWD was done . In order to spread this technique, I have made trial SWD modeling during drilling. the paper sketches out the procedure for trial SWD modeling during drilling , the involved instruments and their functions, and the trial effect. Subsurface condition ahead of the drill-bit can be predicted drillstring velocity was obtained by polit sensor autocorrelation. Reference decovolution, the drillstring multiples in the polit signal are removed by reference deconvolution, the crosscorrelation process enhance the signal-to-noise power ratio, lithologies. Final, SWD provides real-time seismic data for use at the well site well trajectory control exploratory well find out and preserve reservoirs. intervel velocity was computed by the traveltime The results of the interval velocity determination reflects the pore-pressure present in the subsurface units ahead of the drill-bit. the presences of fractures in subsurface formation was detected by shear wave. et al.

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In the practical seismic profile multiple reflections tend to impede the task of even the experienced interpreter in deducing information from the reflection data. Surface multiples are usually much stronger, more broadband, and more of a problem than internal multiples because the reflection coefficient at the water surface is much larger than the reflection coefficients found in the subsurface. For this reason most attempts to remove multiples from marine data focus on surface multiples, as will I. A surface-related multiple attenuation method can be formulated as an iterative procedure. In this essay a fully data-driven approach which is called MPI —multiple prediction through inversion (Wang, 2003) is applied to a real marine seismic data example. This is a pretty promising scheme for predicting a relative accurate multiple model by updating the multiple model iteratively, as we usually do in a linearized inverse problem. The prominent characteristic of MPI method lie in that it eliminate the need for an explicit surface operator which means it can model the multiple wavefield without any knowledge of surface and subsurface structures even a source signature. Another key feature of this scheme is that it can predict multiples not only in time but also in phase and in amplitude domain. According to the real data experiments it is shown that this scheme for multiple prediction can be made very efficient if a good initial estimate of the multiple-free data set can be provided in the first iteration. In the other core step which is multiple subtraction we use an expanded multi-channel matching filter to fulfil this aim. Compared to a normal multichannel matching filter where an original seismic trace is matched by a group of multiple-model traces, in EMCM filter a seismic trace is matched by not only a group of the ordinary multiple-model traces but also their adjoints generated mathematically. The adjoints of a multiple-model trace include its first derivative, its Hilbert transform and the derivative of the Hilbert transform. The third chapter of the thesis is the application for the real data using the previous methods we put forward from which we can obviously find the effectivity and prospect of the value in use. For this specific case I have done three group experiments to test the effectiveness of MPI method, compare different subtraction results with fixed filter length but different window length, invest the influence of the initial subtraction result for MPI method. In terms of the real data application, we do fine that the initial demultiple estimate take on a great deal of influence for the MPI method. Then two approaches are introduced to refine the intial demultiple estimate which are first arrival and masking filter respectively. In the last part some conclusions are drawn in terms of the previous results I have got.

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3D wave equation prestack depth migration is the effective tool for obtaining the exact imaging result of complex geology structures. It's a part of the 3D seismic data processing. 3D seismic data processing belongs to high dimension signal processing, and there are some difficult problems to do with. They are: How to process high dimension operators? How to improve the focusing? and how to construct the deconvolution operator? The realization of 3D wave equation prestack depth migration, not only realized the leap from poststack to prestack, but also provided the important means to solve the difficult problems in high dimension signal processing. In this thesis, I do a series research especially for the solve of the difficult problems around the 3D wave equation prestack depth migration and using it as a mean. So this thesis service for the realization of 3D wave equation prestack depth migration for one side and improve the migration effect for another side. This thesis expatiates in five departs. Summarizes the main contents as the follows: In the first part, I have completed the projection from 3D data point area to low dimension are using de big matrix transfer and trace rearrangement, and realized the liner processing of high dimension signal. Firstly, I present the mathematics expression of 3D seismic data and the mean according to physics, present the basic ideal of big matrix transfer and describe the realization of five transfer models for example. Secondly, I present the basic ideal and rules for the rearrange and parallel calculate of 3D traces, and give a example. In the conventional DMO focusing method, I recall the history of DM0 process firstly, give the fundamental of DMO process and derive the equation of DMO process and it's impulse response. I also prove the equivalence between DMO and prestack time migration, from the kinematic character of DMO. And derive the relationship between DMO base on wave equation and prestack time migration. Finally, I give the example of DMO process flow and synthetic data of theoretical models. In the wave equation prestak depth migration, I firstly recall the history of migration from time to depth, from poststack to prestack and from 2D to 3D. And conclude the main migration methods, point out their merit and shortcoming. Finally, I obtain the common image point sets using the decomposed migration program code.In the residual moveout, I firstly describe the Viterbi algorithm based on Markov process and compound decision theory and how to solve the shortest path problem using Viterbi algorithm. And based on this ideal, I realized the residual moveout of post 3D wave equation prestack depth migration. Finally, I give the example of residual moveout of real 3D seismic data. In the migration Green function, I firstly give the concept of migration Green function and the 2D Green function migration equation for the approximate of far field. Secondly, I prove the equivalence of wave equation depth extrapolation algorithms. And then I derive the equation of Green function migration. Finally, I present the response and migration result of Green function for point resource, analyze the effect of migration aperture to prestack migration result. This research is benefit for people to realize clearly the effect of migration aperture to migration result, and study on the Green function deconvolution to improve the focusing effect of migration.

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Thomas, Dennis, Henley, Andrew, 'Public service employment and the public-private wage differential in British regions', Regional Studies (2001) 35(3) pp.229-240 RAE2008

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This paper proposes a novel protocol which uses the Internet Domain Name System (DNS) to partition Web clients into disjoint sets, each of which is associated with a single DNS server. We define an L-DNS cluster to be a grouping of Web Clients that use the same Local DNS server to resolve Internet host names. We identify such clusters in real-time using data obtained from a Web Server in conjunction with that server's Authoritative DNS―both instrumented with an implementation of our clustering algorithm. Using these clusters, we perform measurements from four distinct Internet locations. Our results show that L-DNS clustering enables a better estimation of proximity of a Web Client to a Web Server than previously proposed techniques. Thus, in a Content Distribution Network, a DNS-based scheme that redirects a request from a web client to one of many servers based on the client's name server coordinates (e.g., hops/latency/loss-rates between the client and servers) would perform better with our algorithm.

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A combined 2D, 3D approach is presented that allows for robust tracking of moving people and recognition of actions. It is assumed that the system observes multiple moving objects via a single, uncalibrated video camera. Low-level features are often insufficient for detection, segmentation, and tracking of non-rigid moving objects. Therefore, an improved mechanism is proposed that integrates low-level (image processing), mid-level (recursive 3D trajectory estimation), and high-level (action recognition) processes. A novel extended Kalman filter formulation is used in estimating the relative 3D motion trajectories up to a scale factor. The recursive estimation process provides a prediction and error measure that is exploited in higher-level stages of action recognition. Conversely, higher-level mechanisms provide feedback that allows the system to reliably segment and maintain the tracking of moving objects before, during, and after occlusion. The 3D trajectory, occlusion, and segmentation information are utilized in extracting stabilized views of the moving object that are then used as input to action recognition modules. Trajectory-guided recognition (TGR) is proposed as a new and efficient method for adaptive classification of action. The TGR approach is demonstrated using "motion history images" that are then recognized via a mixture-of-Gaussians classifier. The system was tested in recognizing various dynamic human outdoor activities: running, walking, roller blading, and cycling. Experiments with real and synthetic data sets are used to evaluate stability of the trajectory estimator with respect to noise.

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Complex systems, from environmental behaviour to electronics reliability, can now be monitored with Wireless Sensor Networks (WSN), where multiple environmental sensors are deployed in remote locations. This ensures aggregation and reading of data, at lower cost and lower power consumption. Because miniaturisation of the sensing system is hampered by the fact that discrete sensors and electronics consume board area, the development of MEMS sensors offers a promising solution. At Tyndall, the fabrication flow of multiple sensors has been made compatible with CMOS circuitry to further reduce size and cost. An ideal platform on which to host these MEMS environmental sensors is the Tyndall modular wireless mote. This paper describes the development and test of the latest sensors incorporating temperature, humidity, corrosion, and gas. It demonstrates their deployment on the Tyndall platform, allowing real-time readings, data aggregation and cross-correlation capabilities. It also presents the design of the next generation sensing platform using the novel 10mm wireless cube developed by Tyndall.

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Recent empirical findings suggest that the long-run dependence in U.S. stock market volatility is best described by a slowly mean-reverting fractionally integrated process. The present study complements this existing time-series-based evidence by comparing the risk-neutralized option pricing distributions from various ARCH-type formulations. Utilizing a panel data set consisting of newly created exchange traded long-term equity anticipation securities, or leaps, on the Standard and Poor's 500 stock market index with maturity times ranging up to three years, we find that the degree of mean reversion in the volatility process implicit in these prices is best described by a Fractionally Integrated EGARCH (FIEGARCH) model. © 1999 Elsevier Science S.A. All rights reserved.

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There is a general presumption in the literature and among policymakers that immigrant remittances play the same role in economic development as foreign direct investment and other capital flows, but this is an open question. We develop a model of remittances based on the economics of the family that implies that remittances are not profit-driven, but are compensatory transfers, and should have a negative correlation with GDP growth. This is in contrast to the positive correlation of profit-driven capital flows with GDP growth. We test this implication of our model using a new panel data set on remittances and find a robust negative correlation between remittances and GDP growth. This indicates that remittances may not be intended to serve as a source of capital for economic development. © 2005 International Monetary Fund.