No abstract is provided for this article.
This paper exposes problems of the commonly used technique of splitting the available data in neural spatial interaction modelling into training, validation, and test sets that are held fixed and warns about drawing too strong conclusions from such static splits. Using a bootstrapping procedure, we compare the uncertainty in the solution stemming from the data splitting with model specific uncertainties such as parameter initialization. Utilizing the Austrian interregional telecommunication traffic data and the differential evolution method for solving the parameter estimation task for a fixed topology of the network model [ i.e. J = 9] this paper illustrates that the variation due to different resamplings is significantly larger than the variation due to different parameter initializations. This result implies that it is important to not over-interpret a model, estimated on one specific static split of the data.
Quite recently research on small firms and business formation has become an increasingly important focus of academic and policy discussions in most advanced economies. With the declining mobility of industry, the emphasis in regional policy in recent years has shifted towards developing the indigenous potential of the regions.
This article outlines the general architecture of a knowledge based GISystem that has the potential to intelligently support decision making in a GIS environment. The efficient and effective integration of spatial data, spatial analytic procedures and models, procedural and declarative knowledge is through fuzzy logic, expert systems and neural network technologies. A specific focus of the discussion is on the expert system and neural network components of the system, technologies which had been relatively unknown in the GIS community at the time this chapter was written.
Classification of terrain cover from satellite radar imagery represents an area of considerable current interest and research. Most satellite sensors used for land applications are of the imaging type. They record data in a variety of spectral channels and at a variety of ground resolutions. Spectral pattern recognition refers to classification procedures utilizing pixel-by-pixel spectral information as the basis for automated land cover classification. A number of methods have been developed in the past to classify pixels [resolution cells] from multispectral imagery to a priori given land cover categories. Their ability to provide land cover information with high classification accuracies is significant for work where accurate and reliable thematic information is needed. The current trend towards the use of more spectral bands on satellite instruments, such as visible and infrared imaging spectrometers, and finer pixel and grey level resolutions will offer more precise possibilities for accurate identification. But as the complexity of the data grows, so too does the need for more powerful tools to analyse them. It is the major objective of this study to analyse the capabilities and applicability of the neural pattern recognition system, called fuzzy ARTMAP, to generate high quality classifications of urban land cover using remotely sensed images. Fuzzy ARTMAP synthesizes fuzzy logic and Adaptive Resonance Theory (ART) by exploiting the formal similarity between the computations of fuzzy subsethood and the dynamics of category choice, search and learning. The paper describes design features, system dynamics and simulation algorithms of this learning system, which is trained and tested for classification (8 a priori given classes) of a multispectral image of a Landsat-5 Thematic Mapper scene (270 x 360 pixels) from the City of Vienna on a pixel-by-pixel basis. Fuzzy ARTMAP performance is compared with that of an error-based learning system based upon the multi-layer perceptron, and the Gaussian maximum likelihood classifier as conventional statistical benchmark on the same database. Both neural classifiers outperform the conventional classifier in terms of classification accuracy. Fuzzy ARTMAP leads to out-of-sample classification accuracies, very close to maximum performance, while the multi-layer perceptron - like the conventional classifier - shows difficulties to distinguish between some land use categories. (authors' abstract)
Two alternative methodological approaches (the IPFP based and the intramax procedures) to the problem of pattern identification in spatial interaction data are compared and evaluated in this paper. After a general discussion of the major characteristics and shortcomings of these methodologies, the paper presents the findings of a case study relying on telecommunication data measured by the Austrian PTT in 1991, in terms of erlangs. The results clearly illustrate the superiority of the intramax approach in the context of medium-sized and relatively centralised flow systems.
. During the last thirty years there has been much research effort in regional science devoted to modeling interactions over geographic space. Theoretical approaches for studying these phenomena have been modified considerably. This paper suggests a new modeling approach, based upon a general nested sigmoid neural network model. Its feasibility is illustrated in the context of modeling interregional telecommunication traffic in Austria, and its performance is evaluated in comparison with the classical regression approach of the gravity type. The application of this neural network approach may be viewed as a three‐stage process. The first stage refers to the identification of an appropriate network from the family of two‐layered feedforward networks with 3 input nodes, one layer of (sigmoidal) intermediate nodes and one (sigmoidal) output node (logistic activation function). There is no general procedure to address this problem. We solved this issue experimentally. The input‐output dimensions have been chosen in order to make the comparison with the gravity model as close as possible. The second stage involves the estimation of the network parameters of the selected neural network model. This is performed via the adaptive setting of the network parameters (training, estimation) by means of the application of a least mean squared error goal and the error back propagating technique, a recursive learning procedure using a gradient search to minimize the error goal. Particular emphasis is laid on the sensitivity of the network performance to the choice of the initial network parameters, as well as on the problem of overfitting. The final stage of applying the neural network approach refers to the testing of the interregional teletraffic flows predicted. Prediction quality is analyzed by means of two performance measures, average relative variance and the coefficient of determination, as well as by the use of residual analysis. The analysis shows that the neural network model approach outperforms the classical regression approach to modeling telecommunication traffic in Austria.
Artificial intelligence (Al) has received an explosion of interest during the last five years in various fields. There is no longer any question that expert systems and neural networks will be of central importance for developing the next generation of more intelligent geographic information systems. Such knowledge based geographic information systems will especially play a key role in spatial decision and policy analysis related to issues such as environmental monitoring and management, land use planning, motor vehicle navigation and distribution logistics. This paper sketches briefly the major characteristics of conventional geographic information systems, and then looks at some of the potentials of Al principles and techniques in a GIS environment where emphasis is laid on expert systems and artificial neural networks technologies and techniques.
No abstract is provided for this article.
No abstract is provided for this article.
The relationship between innovation, networks and localities is of central concern for many nations. However, despite increasing interest in the components of this research triangle, efforts in these fields are hampered by a lackofconceptual and empirical insights. This volume brings together contributions from a distinguished group of scholars working in different but related disciplines, and aims to provide a fresh look at this research triangle. The objective is to offer a concise overview of current developments and insights derived from recent studies in Europe and North America. All of the contributions are based on original research undertaken in the various regions and nations and are published here for the first time. We are grateful to all those who have contributed to this volume for their willingness to participate in the project. Without their co-operation this book would not have been possible. We should like, in addition, to thank Angela Spence for her careful linguistic editing and assistance in co-ordinating the production of the camera ready copy. Lastly, but not least, we wish to express our gratitude for support from our home institutions, and in particular the Austrian Academy of Sciences (Institute for Urban and Regional Research), the Austrian Ministry for Science and Transport, the Styrian Government (Section for Science and Research) and the Federation of Austrian Industry in Styria for the financial backing received. April 1999 Manfred M.
End caps are intended to prevent nail migration (push-out) in elastic stable intramedullary nailing. The aim of this study was to investigate the force at failure with and without end caps, and whether different insertion angles of nails and end caps would alter that force at failure. Simulated oblique fractures of the diaphysis were created in 15 artificial paediatric femurs. Titanium Elastic Nails with end caps were inserted at angles of 45°, 55° and 65° in five specimens for each angle to create three study groups. Biomechanical testing was performed with axial compression until failure. An identical fracture was created in four small adult cadaveric femurs harvested from two donors (both female, aged 81 and 85 years, height 149 cm and 156 cm, respectively). All femurs were tested without and subsequently with end caps inserted at 45°. In the artificial femurs, maximum force was not significantly different between the three groups (p = 0.613). Push-out force was significantly higher in the cadaveric specimens with the use of end caps by an up to sixfold load increase (830 N, standard deviation (SD) 280 vs 150 N, SD 120, respectively; p = 0.007). These results indicate that the nail and end cap insertion angle can be varied within 20° without altering construct stability and that the risk of elastic stable intramedullary nailing push-out can be effectively reduced by the use of end caps.
The chromosome numbers ofVeronica beccabunga subsp.abscondita (2n=18),V. anagallis-aquatica subsp.lysimachioides (2n=18),V. anagallis-aquatica subsp.michau
Correction to: Rechtliche Verantwortung/Verpflichtungen des Nuklearmediziners bei der Radiosynoviorthese und Radionuklidtherapie von KnochenmetastasenDer Nuklearmediziner 2013; 36(01): 53-63DOI: 10.1055/s-0033-1333707
The existence of a popliteal Baker's cyst was regarded as a contraindication for radiosynoviorthesis of the knee joint since decades. A so-called "ventile mechanism" was discussed leading to a significant concentration of the intraarticularly applied, high energy beta emitting radiopharmaceutical yttrium-90-colloid in the cyst. This cyst arises from a bursa beneath the tendon of the medial head of the gastrocnemius muscle, normally communicating with the knee joint space. Since the cyst wall is much thinner than the knee joint capsule, a radiogenic rupture of the cyst was feared, leading to severe radiogenic necroses of the surrounding soft tissue. Due to this potential hazard, knee joint ultrasound is mandatory prior to radiosynoviorthesis to check for any popliteal cysts. New studies however decline the risk of a radiogenic cyst rupture after an appropriately performed radiosynoviorthesis of the knee joint.In case of a preexistent cyst rupture, the risk of a radiogenic tissue damage remains an issue and magnetic resonance imaging (MRI) is the method of choice to exclude this potential hazard. However, MRI sometimes leads to equivocal results. Scintigraphy of the knee joint after intraarticular application of Tc-99m-nanocolloid offers the possibility to check for the integrity of the Baker's cyst in these patients to be sure that radiosynoviorthesis will not lead to a relevant extraarticular leakage with soft tissue necroses. This study describes the procedure of intracavitary distribution scintigraphy by means of representative case reports.Die popliteale Bakerzyste galt lange Zeit als Kontraindikation bei der Durchführung einer Radiosynoviorthese (RSO). Insbesondere bei einem vorliegenden „Ventilmechanismus“ der Zyste fürchtete man eine vermehrte Anreicherung des intraartikulär injizierten Radiopharmazeutikums Yttrium-90-Kolloid in der Zyste, die aus einer mit der Kniegelenkhöhle kommunizierenden Bursa unter dem medialen Kopf des M. gastrocnemius bei chronischer Arthritis mit Ergussneigung entstehen kann. Aufgrund der im Vergleich zur Kniegelenkkapsel deutlich dünneren Zystenwand wurde die Gefahr einer radiogenen Zystenruptur mit konsekutiver Freisetzung des hoch energetischen Betastrahlers in die umgebenden Weichteile und einer dadurch hervorgerufenen Weichteilnekrose diskutiert. Daher ist vor der Kniegelenk-RSO zwingend die sonografische Abklärung einer möglichen Bakerzyste erforderlich. Neue Studien zeigen hingegen keinen Hinweis auf die Gefahr einer Zystenruptur durch eine lege artis durchgeführte Kniegelenk-RSO.Bei bereits präexistierender Zystenwandruptur ist jedoch die Gefahr eines unkontrollierten Austritts des Radiopharmazeutikums mit nachfolgender Radionekrose auch weiterhin gegeben. Die Magnetresonanztomografie (MRT) ist die Methode der Wahl, um eine solche Zystenruptur im Vorfeld auszuschließen, liefert aber nicht immer zuverlässige Befunde. In derartigen Fällen ist die Binnenraumszintigrafie unter Verwendung von Tc-99m-Nanokolloid geeignet, die Integrität der Bakerzyste nachzuweisen und einen möglichen Aktivitätsaustritt aus der Zyste mit hinreichender Sicherheit auszuschließen. Die vorliegende Arbeit erläutert diese Methode an repräsentativen Fallbeispielen.
Geographical Information Systems (GIS) provide an enhanced environment for spatial data processing. The ability of geographic information systems to handle and analyse spatially referenced data may be seen as a major characteristic which distinguishes GIS from information systems developed to serve the needs of business data processing as well as from CAD systems or other systems whose primary objective is map production. This book, which contains contributions from a wide-ranging group of international scholars, demonstrates the progress which has been achieved so far at the interface of GIS technology and spatial analysis and planning. The various contributions bring together theoretical and conceptual, technical and applied issues. Topics covered include the design and use of GIS and spatial models, AI tools for spatial modelling in GIS, spatial statistical analysis and GIS, GIS and dynamic modelling, GIS in urban planning and policy making, information systems for policy evaluation, and spatial decision support systems.
