857 resultados para GDP Interpolation
Resumo:
This paper uses examples from the history and practices of multi-national and large companies in the oil, chemical and asbestos industries to examine their legal and illegal despoiling and destruction of the environment and impact on human and non-human life. The discussion draws on the literature on green criminology and state-corporate crime and considers measures and arrangements that might mitigate or prevent such damaging acts. This paper is part of ongoing work on green criminology and crimes of the economy. It places these actions and crimes in the context of a global neo-liberal economic system and considers and critiques the distorting impact of the GDP model of ‘economic health’ and its consequences for the environment.
Resumo:
Many model-based investigation techniques, such as sensitivity analysis, optimization, and statistical inference, require a large number of model evaluations to be performed at different input and/or parameter values. This limits the application of these techniques to models that can be implemented in computationally efficient computer codes. Emulators, by providing efficient interpolation between outputs of deterministic simulation models, can considerably extend the field of applicability of such computationally demanding techniques. So far, the dominant techniques for developing emulators have been priors in the form of Gaussian stochastic processes (GASP) that were conditioned with a design data set of inputs and corresponding model outputs. In the context of dynamic models, this approach has two essential disadvantages: (i) these emulators do not consider our knowledge of the structure of the model, and (ii) they run into numerical difficulties if there are a large number of closely spaced input points as is often the case in the time dimension of dynamic models. To address both of these problems, a new concept of developing emulators for dynamic models is proposed. This concept is based on a prior that combines a simplified linear state space model of the temporal evolution of the dynamic model with Gaussian stochastic processes for the innovation terms as functions of model parameters and/or inputs. These innovation terms are intended to correct the error of the linear model at each output step. Conditioning this prior to the design data set is done by Kalman smoothing. This leads to an efficient emulator that, due to the consideration of our knowledge about dominant mechanisms built into the simulation model, can be expected to outperform purely statistical emulators at least in cases in which the design data set is small. The feasibility and potential difficulties of the proposed approach are demonstrated by the application to a simple hydrological model.
Resumo:
Construction delay has been a protracted problem for the Malaysian construction industry. Recent report showed that 80% of public sector projects are behind schedule. This underachieving time performance has led to many problems including public complaints, loss of reputation and revenue for the government and a slump in the industry’s GDP contribution. Research in the area of project delay has mushroomed worldwide with attempts to place mitigation plans, but delay remains a global phenomenon. There is now an urgent need for revolutionizing construction practices and past research, backed up with few successful cases suggests that Supply Chain Management (SCM) could prove beneficial to reduce or eliminate delays in construction. SCM which originated from the automotive manufacturing industry promotes a more collaborative approach to construction management and has recently gained attention of the construction industry. However every country, including Malaysia, would certainly have disparities of their own compared to others being it from the cultural point of view, nature of problems, locality or improvements needed. Therefore, this paper will present part of a Ph.D. research which aims at illustrating the Malaysian construction industry experts’ perception of the Malaysian public sector project delay, provide insight into these dilemmas, highlights the problems with current practices, its effects and the improvements needed. Subsequently, this paper would propose ratification to the problems using SCM. A semi-structured interview has been conducted to practitioners with at least 20 years’ experience in the industry. The findings showed that Malaysia may be unique compared to other countries and that by considering a number of additional factors, SCM could prove beneficial to increase efficiency of the Malaysian public sector projects.
Resumo:
We present two unconditional secure protocols for private set disjointness tests. In order to provide intuition of our protocols, we give a naive example that applies Sylvester matrices. Unfortunately, this simple construction is insecure as it reveals information about the intersection cardinality. More specifically, it discloses its lower bound. By using the Lagrange interpolation, we provide a protocol for the honest-but-curious case without revealing any additional information. Finally, we describe a protocol that is secure against malicious adversaries. In this protocol, a verification test is applied to detect misbehaving participants. Both protocols require O(1) rounds of communication. Our protocols are more efficient than the previous protocols in terms of communication and computation overhead. Unlike previous protocols whose security relies on computational assumptions, our protocols provide information theoretic security. To our knowledge, our protocols are the first ones that have been designed without a generic secure function evaluation. More important, they are the most efficient protocols for private disjointness tests in the malicious adversary case.
Resumo:
Spatially-explicit modelling of grassland classes is important to site-specific planning for improving grassland and environmental management over large areas. In this study, a climate-based grassland classification model, the Comprehensive and Sequential Classification System (CSCS) was integrated with spatially interpolated climate data to classify grassland in Gansu province, China. The study area is characterized by complex topographic features imposed by plateaus, high mountains, basins and deserts. To improve the quality of the interpolated climate data and the quality of the spatial classification over this complex topography, three linear regression methods, namely an analytic method based on multiple regression and residues (AMMRR), a modification of the AMMRR method through adding the effect of slope and aspect to the interpolation analysis (M-AMMRR) and a method which replaces the IDW approach for residue interpolation in M-AMMRR with an ordinary kriging approach (I-AMMRR), for interpolating climate variables were evaluated. The interpolation outcomes from the best interpolation method were then used in the CSCS model to classify the grassland in the study area. Climate variables interpolated included the annual cumulative temperature and annual total precipitation. The results indicated that the AMMRR and M-AMMRR methods generated acceptable climate surfaces but the best model fit and cross validation result were achieved by the I-AMMRR method. Twenty-six grassland classes were classified for the study area. The four grassland vegetation classes that covered more than half of the total study area were "cool temperate-arid temperate zonal semi-desert", "cool temperate-humid forest steppe and deciduous broad-leaved forest", "temperate-extra-arid temperate zonal desert", and "frigid per-humid rain tundra and alpine meadow". The vegetation classification map generated in this study provides spatial information on the locations and extents of the different grassland classes. This information can be used to facilitate government agencies' decision-making in land-use planning and environmental management, and for vegetation and biodiversity conservation. The information can also be used to assist land managers in the estimation of safe carrying capacities which will help to prevent overgrazing and land degradation.
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A sub‒domain smoothed Galerkin method is proposed to integrate the advantages of mesh‒free Galerkin method and FEM. Arbitrarily shaped sub‒domains are predefined in problems domain with mesh‒free nodes. In each sub‒domain, based on mesh‒free Galerkin weak formulation, the local discrete equation can be obtained by using the moving Kriging interpolation, which is similar to the discretization of the high‒order finite elements. Strain smoothing technique is subsequently applied to the nodal integration of sub‒domain by dividing the sub‒domain into several smoothing cells. Moreover, condensation of DOF can also be introduced into the local discrete equations to improve the computational efficiency. The global governing equations of present method are obtained on the basis of the scheme of FEM by assembling all local discrete equations of the sub‒domains. The mesh‒free properties of Galerkin method are retained in each sub‒domain. Several 2D elastic problems have been solved on the basis of this newly proposed method to validate its computational performance. These numerical examples proved that the newly proposed sub‒domain smoothed Galerkin method is a robust technique to solve solid mechanics problems based on its characteristics of high computational efficiency, good accuracy, and convergence.
Resumo:
We present efficient protocols for private set disjointness tests. We start from an intuition of our protocols that applies Sylvester matrices. Unfortunately, this simple construction is insecure as it reveals information about the cardinality of the intersection. More specifically, it discloses its lower bound. By using the Lagrange interpolation we provide a protocol for the honest-but-curious case without revealing any additional information. Finally, we describe a protocol that is secure against malicious adversaries. The protocol applies a verification test to detect misbehaving participants. Both protocols require O(1) rounds of communication. Our protocols are more efficient than the previous protocols in terms of communication and computation overhead. Unlike previous protocols whose security relies on computational assumptions, our protocols provide information theoretic security. To our knowledge, our protocols are first ones that have been designed without a generic secure function evaluation. More importantly, they are the most efficient protocols for private disjointness tests for the malicious adversary case.
Resumo:
When the acronym of ëBRICí was coined in 2001 by Jim OíNeill of Goldman Sachs, it was expected that economic growth rates in India, Brazil and Russia would eventually catch up with that of China. However, China has continued to outperform the other economies in the group, even after it was renamed ëBRICSí to reflect the inclusion of South Africa in 2010. The focus of this chapter is on one of the BRICS economies, namely India. Its aim is to examine from an economic perspective, why Indiaís performance has not lived up to expectations, and comment on the key challenges it faces in meeting them. We begin with some descriptive statistics regarding the progress of the Indian economy since 1990. While it has been growing at a rapid rate since the reforms it introduced in the1990s, there has been a slowdown in its overall GDP growth rates since 2008. The rate of growth experienced in the period 2003ñ07 was an average of 10.5 per cent. However, since the recession following the Global Financial Crisis (GFC) of 2008, the growth rate has fallen. From the period 2008ñ12 it has only registered an average growth rate of 6.5 per cent (World Bank, 2013). This chapter suggests that one of the major factors underpinning this slowdown is the performance of Indiaís agricultural sector. The importance of the agricultural sector is highlighted by the following stylized facts.
Resumo:
Condensation technique of degree of freedom is first proposed to improve the computational efficiency of meshfree method with Galerkin weak form for elastic dynamic analysis. In the present method, scattered nodes without connectivity are divided into several subsets by cells with arbitrary shape. Local discrete equation is established over each cell by using moving Kriging interpolation, in which the nodes that located in the cell are used for approximation. Then local discrete equations can be simplified by condensation of degree of freedom, which transfers equations of inner nodes to equations of boundary nodes based on cells. The global dynamic system equations are obtained by assembling all local discrete equations and are solved by using the standard implicit Newmark’s time integration scheme. In the scheme of present method, the calculation of each cell is carried out by meshfree method, and local search is implemented in interpolation. Numerical examples show that the present method has high computational efficiency and good accuracy in solving elastic dynamic problems.
Resumo:
The Construction industry accounts for a tenth of global GDP. Still, challenges such as slow adoption of new work processes, islands of information, and legal disputes, remain frequent, industry-wide occurrences despite various attempts to address them. In response, IT-based approaches have been adopted to explore collaborative ways of executing construction projects. Building Information Modelling (BIM) is an exemplar of integrative technologies whose 3D-visualisation capabilities have fostered collaboration especially between clients and design teams. Yet, the ways in which specification documents are created and used in capturing clients' expectations based on industry standards have remained largely unchanged since the 18th century. As a result, specification-related errors are still common place in an industry where vast amounts of information are consumed as well as produced in the course project implementation in the built environment. By implication, processes such as cost planning which depend on specification-related information remain largely inaccurate even with the use of BIM-based technologies. This paper briefly distinguishes between non-BIM-based and BIM-based specifications and reports on-going efforts geared towards the latter. We review exemplars aimed at extending Building Information Models to specification information embedded within the objects in a product library and explore a viable way of reasoning about a semi-automated process of specification using our product library.
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Loop detectors are widely used on the motorway networks where they provide point speed and traffic volumes. Models have been proposed for temporal and spatial generalization of speed for average travel time estimation. Advancement in technology provides complementary data sources such as Bluetooth MAC Scanner (BMS), detecting the MAC ID of the Bluetooth devices transported by the traveller. Matching the data from two BMS stations provides individual vehicle travel time. Generally, on the motorways loops are closely spaced, whereas BMS are placed few kilometres apart. In this research, we fuse BMSs and loops data to define the trajectories of the Bluetooth vehicles. The trajectories are utilised to estimate the travel time statistics between any two points along the motorway. The proposed model is tested using simulation and validated with real data from Pacific motorway, Brisbane. Comparing the model with the linear interpolation based trajectory provides significant improvements.
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According to 2011 Australian Census figures, embedded creative employees (creative employees not working in the core Creative Industries) make up 2 per cent (or a total of 17 635) of manufacturing industry employees. The average for all industries is 1.6 per cent. In the 2011–2012 financial year the manufacturing industry formed 7.3 per cent of Australia’s gross domestic product (GDP), contributing approximately AU$106.5 billion to the economy (Department of Industry, Innovation, Science, Research and Tertiary Education 2013). Manufacturing is central to innovation, accounting for over one-quarter of all business expenditure in R&D in 2010–2011, representing around AU$4.8 billion invested in R&D (ibid.). Facing challenges such as sustainability concerns, ever-increasing offshore production and the global financial crisis, the Australian manufacturing industry needs to remain relevant and competitive to succeed. Innovation is one way to do this. Given the contribution of the manufacturing industry to the Australian economy, and the above-average portion of embedded creatives in manufacturing, it is important to consider what exactly embedded creatives add to the industry. This chapter, inspired by the Getting Creative in Healthcare report (Pagan, Higgs and Cunningham 2008), examines the contribution of embedded creatives to innovation in the manufacturing industry via case studies and supplemental data.
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We discuss algorithms for combining sequential prediction strategies, a task which can be viewed as a natural generalisation of the concept of universal coding. We describe a graphical language based on Hidden Markov Models for defining prediction strategies, and we provide both existing and new models as examples. The models include efficient, parameterless models for switching between the input strategies over time, including a model for the case where switches tend to occur in clusters, and finally a new model for the scenario where the prediction strategies have a known relationship, and where jumps are typically between strongly related ones. This last model is relevant for coding time series data where parameter drift is expected. As theoretical contributions we introduce an interpolation construction that is useful in the development and analysis of new algorithms, and we establish a new sophisticated lemma for analysing the individual sequence regret of parameterised models.
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We first classify the state-of-the-art stream authentication problem in the multicast environment and group them into Signing and MAC approaches. A new approach for authenticating digital streams using Threshold Techniques is introduced. The new approach main advantages are in tolerating packet loss, up to a threshold number, and having a minimum space overhead. It is most suitable for multicast applications running over lossy, unreliable communication channels while, in same time, are pertain the security requirements. We use linear equations based on Lagrange polynomial interpolation and Combinatorial Design methods.
Resumo:
A new test of hypothesis for classifying stationary time series based on the bias-adjusted estimators of the fitted autoregressive model is proposed. It is shown theoretically that the proposed test has desirable properties. Simulation results show that when time series are short, the size and power estimates of the proposed test are reasonably good, and thus this test is reliable in discriminating between short-length time series. As the length of the time series increases, the performance of the proposed test improves, but the benefit of bias-adjustment reduces. The proposed hypothesis test is applied to two real data sets: the annual real GDP per capita of six European countries, and quarterly real GDP per capita of five European countries. The application results demonstrate that the proposed test displays reasonably good performance in classifying relatively short time series.