873 publications from this institution
The aim of this chapter is to examine the new patterns and volumes of trade flows between Austria and the growing economies of Central and Eastern Europe. The modelling approach is sequential in nature and relies on two types of classic regional science models:...
This paper lies in the tradition of decomposition analysis of wage differentials based on the model set forth in Blinder (1973) and Oaxaca (1973), and aims to measure labour market discrimination against Roma in South East European countries (Albania, Bulgaria, Croatia, Serbia and Kosovo). We use microdata from 2004 UNDP household survey and a Bayesian approach, proposed by Keith and LeSage (2003), for the decomposition analysis of wage differentials. Statistical inference for both discrimination and characteristics effects estimates are based on Markov Chain Monte Carlo (MCMC) estimation. Variance estimates derived from this method of estimation are known to reflect the true posterior variance when a sufficiently large sample of MCMC draws is carried out. The results provide clear evidence for labour market discrimination against Roma in Albania and Kosovo, but not so in Bulgaria, Croatia, and Serbia. Nevertheless, there are significant differences in how individual characteristics are valued between Roma and non-Roma.
Both geographic information systems (GIS) and network analysis are burgeoning fields, characterised by rapid methodological and scientific advances in recent years. A geographic information system (GIS) is a digital computer application designed for the capture, storage, manipulation, analysis and display of geographic information. Geographic location is the element that distinguishes geographic information from all other types of information. Without location, data are termed to be non-spatial and would have little value within a GIS. Location is, thus, the basis for many benefits of GIS: the ability to map, the ability to measure distances and the ability to tie different kinds of information together because they refer to the same place (Longley et al., 2001). GIS-T, the application of geographic information science and systems to transportation problems, represents one of the most important application areas of GIS-technology today. While traditional GIS formulation's strengths are in mapping display and geodata processing, GIS-T requires new data structures to represent the complexities of transportation networks and to perform different network algorithms in order to fulfil its potential in the field of logistics and distribution logistics. This paper addresses these issues as follows. The section that follows discusses data models and design issues which are specifically oriented to GIS-T, and identifies several improvements of the traditional network data model that are needed to support advanced network analysis in a ground transportation context. These improvements include turn-tables, dynamic segmentation, linear referencing, traffic lines and non-planar networks. Most commercial GIS software vendors have extended their basic GIS data model during the past two decades to incorporate these innovations (Goodchild, 1998). The third section shifts attention to network routing problems that have become prominent in GIS-T: the travelling salesman problem, the vehicle routing problem and the shortest path problem with time windows, a problem that occurs as a subproblem in many time constrained routing and scheduling issues of practical importance. Such problems are conceptually simple, but mathematically complex and challenging. The focus is on theory and algorithms for solving these problems. The paper concludes with some final remarks.
No abstract is provided for this article.
No abstract is provided for this article.
Around 8 million people in Germany suffer from type 2 diabetes. One of the secondary and accompanying diseases is diabetic foot syndrome, which currently affects 250,000 patients. Therapeutic and preventive measures are designed to reduce the risk of foot wounds (ulcers). These include the detection of increased pressure values in the entire foot area. A pressure-measuring stocking can be used to continuously record pressure loads during activities of daily living. It is important to use skin-friendly, heat- and moisture-regulating textiles with very thin and soft sensors that do not create pressure points and are very comfortable to put on, take off and wear. Machine washing should be possible for daily cleaning. And the manufacturing costs must be low. The solution presented is the use of thin (1 mm) capacitive dielectric elastomer pressure sensors based on skin-compatible silicones, which are bonded at any position on the smart wool sock. The signal cables are knitted in elastically during stocking production and are connected to a removable radio electronics unit at the end of the stocking. The measurement data from up to 16 pressure sensors on the entire foot can thus be sent wirelessly to a mobile receiving device (e.g. smartphone) to warn patients of excessive pressure and inform the doctors treating them.
No abstract is provided for this article.
The focus is on cross-sectional dependence in panel trade flow models. We propose alternative specifications for modeling time invariant factors such as socio-cultural indicator variables, e.g., common language and currency. These are typically treated as a source of heterogeneity eliminated using fixed effects transformations, but we find evidence of cross-sectional dependence after eliminating country-specific and time-specific effects. These findings suggest use of alternative simultaneous dependence model specifications that accommodate cross-sectional dependence, which we set forth along with Bayesian estimation methods. Ignoring cross-sectional dependence implies biased estimates from panel trade flow models that rely on fixed effects.
Analyses of interaction patterns across geographical space have always been at the forefront of interest in the spatial sciences. Although a wide variety of contexts have been examined, in this paper we shall restrict our attention to those situations in which patterns of communication are affected by the existence or imposition of barriers. According to Nijkamp, Rietveld and Salomon (1990), obstacles in space or time that impede the smooth transfer or free movement of information-related goods can be regarded as barriers to communication. For our present exploratory purpose, significant discontinuities in the flow intensity of communications may signify the existence of barriers. Their effects on communication patterns are generally nonlinear and often stepwise in character. They may not approximate traditional frictions of distance - which are mostly continuous in character.
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 BFGS 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 generalization 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 generalisation 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 inacceptable instabilities in the generalization results. (authors' abstract)
No abstract is provided for this article.
This paper attempts to elaborate the theory of random utility maximizing discrete choice behaviour in the context of regional labour supply mobility. From a choice theoretic point of view, regional labour supply is considered as the result of a series of decisions. Assuming different probability choice structures underlying the complete residential location‐employment status‐workplace location choice problem, four different regional labour supply random utility based discrete choice models are derived and discussed in some detail.
No abstract is provided for this article.
No abstract is provided for this article.
Eine verbesserte Gattungsabgrenzung vonAsperula undGalium macht die Überstellung vonGalium purpureum notwendig:Asperula purpurea (L.)Ehrend., comb. no
This chapter describes how both geographic information systems (GIS) and network analysis are burgeoning fields that have been characterized by rapid methodological and scientific advances in recent years. A GIS is a digital computer application designed for the capture, storage, manipulation, analysis and display of geographic information. Geographic location is the element that distinguishes geographic information from all other types of information. Without location, data are termed to be non-spatial and would have little value within a GIS. Location is, thus, the basis for many benefits of GIS: the ability to map, the ability to measure distances, and the ability to tie different kinds of information together because they refer to the same place. GIS-T, the application of geographic information science and systems to transportation problems, represents one of the most important application areas of GIS technology today. While the strengths of stand GIS technology are in mapping display and goedata processing, GIS-T requires new data structure to represent the complexities of transportation networks and to perform different network algorithms in order to fulfill its potential in the field of logistics and distribution logistics.
