No abstract is provided for this article.
No abstract is provided for this article.
Past focus in the panel gravity literature has been on multidimensional fixed effects specifications in an effort to accommodate heterogeneity. After introducing conventional multidimensional fixed effects, we find evidence of cross-sectional dependence in flows. We propose a simultaneous dependence gravity model that allows for network dependence in flows, along with computationally efficient Markov Chain Monte Carlo estimation methods that produce a Monte Carlo integration estimate of log-marginal likelihood useful for model comparison. Application of the model to a panel of trade flows points to network spillover effects, suggesting the presence of network dependence and biased estimates from conventional trade flow specifications. The most important sources of network dependence were found to be membership in trade organizations, historical colonial ties, common currency and spatial proximity of countries.
Meeting future energy demands with more efficient, lower emission, and safe energy technologies has top priority in the medium term. Consumer‐friendly energy concepts, integrated into regional and supraregional energy supply structures, represent further elements. These will make important contributions to resource‐conserving and environmentally compatible power supplies utilizing local energy sources including renewable resources. Supplying energy to large areas involves additional tasks, from compensation of large amounts of fluctuating energy to the transport of fluctuating energy to the transport of renewable energy over long distances. Solar dish, parabolic section, and tower power generating plant have considerable economic and CO 2 ‐reduction potential in sunny countries, such as in the Mediterranean region, However, the costs of solar‐thermal electricity generation have to be reduced by a factor of 1.5 to 2. Fuel cell systems can attain particular significance as efficient low‐emission energy conversion systems in power plant and automative engineering once their technical and economic potential can be realized.
No abstract is provided for this article.
This paper attempts to develop a mathematically rigid framework for minimizing the cross‐entropy function in an error backpropagating framework. In doing so, we derive the backpropagation formulae for evaluating the partial derivatives in a computationally efficient way. Various techniques of optimizing the multiple‐class cross‐entropy error function to train single hidden layer neural network classifiers with softmax output transfer functions are investigated on a real‐world multispectral pixel‐by‐pixel classification problem that is of fundamental importance in remote sensing. These techniques include epoch‐based and batch versions of backpropagation of gradient descent, PR‐conjugate gradient, and BPGS quasi‐Newton errors. The method of choice depends upon the nature of the learning task and whether one wants to optimize learning for speed or classification performance. It was found that, comparatively considered, gradient descent error backpropagation provided the best and most stable out‐of‐sample performance results across batch and epoch‐based modes of operation. If the goal is to maximize learning speed and a sacrifice in classification accuracy is acceptable, then PR‐conjugate gradient error backpropagation tends to be superior. If the training set is very large, stochastic epoch‐based versions of local optimizers should be chosen utilizing a larger rather than a smaller epoch size to avoid unacceptable instabilities in the classification results.
Fifty-nine PCA cups and 61 hydroxyapatite-coated RM cups were included in a prospective randomised study with a mean follow up of 5.2 years. Clinical evalu
No abstract is provided for this article.
No abstract is provided for this article.
The need to account for spatial autocorrelation is well known in spatial analysis. Many spatial statistics and spatial econometric texts detail the way spatial autocorrelation can be identified and modelled in the case of object and field data. The literature on spatial autocorrelation is much less developed in the case of spatial interaction data. The focus of interest in this paper is on the problem of spatial autocorrelation in a spatial interaction context. The paper aims to illustrate that eigenfunction-based spatial filtering offers a powerful methodology that can efficiently account for spatial autocorrelation effects within a Poisson spatial interaction model context that serves the purpose to identify and measure spatial separation effects to interregional knowledge spillovers as captured by patent citations among high-technology-firms in Europe.
The paper examines the application of the concept of economic efficiency to organizational issues of collective information processing in decision making. Information processing is modeled in the framework of the dynamic parallel processing model of associative computation with an endogenous setup cost of the processors. The model is extended to include the specific features of collective information processing in the team of decision makers which may lead to an error in data analysis. In such a model, the conditions for efficient organization of information processing are defined and the architecture of the efficient structures is considered. We show that specific features of collective decision making procedures require a broader framework for judging organizational efficiency than has traditionally been adopted. In particular, and contrary to the results available in economic literature, we show that there is no unique architecture for efficient information processing structures, but a number of various efficient forms. The results indicate that technological progress resulting in faster data processing ( ceteris paribus ) will lead to more regular information processing structures. However, if the relative cost of the delay in data analysis increases significantly, less regular structures could be efficient. Copyright © 2007 John Wiley & Sons, Ltd.
The explosion of activities and requirements associated with the production, processing and transfer of information is increasingly being matched by a profileration and diversification of new telecommunication media for transmitting information, including text processing and transmission services such as facsimile transmission, videotex, teleconference services, electronic mail etc. Nevertheless, the telephone is still - by far - the most important telecommunication service. The paper results from ESF-research undertaken within the Network on European Communication and Transport Activity Research (NECTAR) and relates to telephone communication undertaken for the Netherlands by Rietveld and Jansen (1990) and Switzerland by Rossera (1990). The current study focuses on the Austrian case and relies on data measured by the Austrian PTT in 1991, in terms of erlangs, an internationally widely used and reliable measure of telecommunication contact intensity. The data refer to the total telecommunication traffic on the public network. Due to technical reasons oral communication can not be distinguished from other services such as data transmission, transfer of documents and text (facsimile) etc. But the demand for such new telecommunication services is still at a very modest level in Austria. The paper addresses two major issues. First an attempt is made to explore the factors influencing the spatial pattern of domestic telephone traffic in Austria. The econometric approach applied to this problem belongs to the class of spatial interaction models explaining a telephone communication flow from a region i to a region j by three types of factors, factors associated with the region of origin, factors associated with the region of destination and factors associated with origin-destination pairs (separation factors). In using the spatial interaction modelling approach in telephone traffic analysis various choices need to be made about how the above mentioned factors should be defined. To have confidence in the model results it is desirable that its interpretation is insensitive to the particular choices made. Whether this is so, will be investigated for several potential sources of variation in model performance.
In den „Thesen“ wird für eine Änderung der gegenwärtig in unserem Staat verfolgten Energiepolitik plädiert. Dafür sprechen nicht zuletzt auch ökologische Gründe. Es wäre allerdings eine unzulässige...
The ‘systems of innovation’ approach has emerged during the last decade as a way of studying of innovation processes as an endogenous part of the economy. The approach is not a formal theory, but a conceptual framework — a framework still in its...
