Transport and infrastructure in Poland: the current state and projects for the future

The paper illustrates the current state of the transport infrastructure in Poland, with special attention to the road, rail and airport infrastructure. It highlights the recent trends in freight and passenger transport and discusses the project for improving and updating the transport networks. Though some improvements are taking place, funds availability remains the main problem for the enhancing of the current poor state of the transport infrastructure

natural gradient flow in the mixture geometry of a discrete exponential family

In this paper, we study Amari's natural gradient flows of real functions defined on the densities belonging to an exponential family on a finite sample space. Our main example is the minimization of the expected value of a real function defined on the sample space. In such a case, the natural gradient flow converges to densities with reduced support that belong to the border of the exponential family. We have suggested in previous works to use the natural gradient evaluated in the mixture geometry. Here, we show that in some cases, the differential equation can be extended to a bigger domain in such a way that the densities at the border of the exponential family are actually internal points in the extended problem. The extension is based on the algebraic concept of an exponential variety. We study in full detail a toy example and obtain positive partial results in the important case of a binary sample space

FAULT DETECTION IN HEAVY DUTY WHEELS BY ADVANCED VIBRATION PROCESSING TECHNIQUES AND NUMERICAL MODELLING

The research work reported in this thesis aims at developing a methodology and a procedure for the condition monitoring and diagnostics of heavy-duty wheels based on vibration measurements at the end of the production line. The early detection of manufacturing anomalies is necessary to sensibly reduce the time/money lost due to possible problems that can rise up during the operating phases. Heavy-duty wheels are used in applications as automatic vehicles and motor trucks and are mainly composed of a polyurethane tread glued to a cast iron hub. The adhesive application between tread and hub is the most critical assembly phase, since it is completely made by an operator and a contamination of the link area between polyurethane and cast iron may happen. Furthermore the presence of rust on the hub surface can contribute to worsen the adherence interface and to reduce the operating life. As the author is aware, studies by other researchers concerning the fault detection in heavy-duty wheels are not present in literature. In order to develop a detection procedure, several wheels with different types of faults have been manufactured “ad hoc” with anomalies similar to real ones. Such anomalies consist of incorrectly adherence zones between tread and hub as well as localized or distributed rust on the hub surface. Numerous experimental tests have been carried out in order to identify the vibration effects of these defects as a function of fault type and dimensions. The thesis concerns the detection and diagnostic capability of different vibration processing techniques using well-suited indicators and determining pass/fail decision thresholds through the Tukey’s non-statistical method. Contemporary, an accurate dynamic analysis of this mechanical system has been conducted - both experimentally through modal analysis techniques and numerically through finite element method - in order to establish the influence of the dynamic properties of the system components (namely heavy-duty wheel, support, frame of the test set up) on the measured vibratory signal. Based on this dynamic characterization, a multibody model of the system has been developed: the heavy-duty wheel is considered as rigid and the yielding part is focused in the contact patch between wheel and drum. A non-linear elastic contact algorithm is adopted, based on stiffness properties previously extracted from static tests conducted on both material specimens and complete components. The model makes it possible to reproduce the vibration effects of the defects and to simulate signal modifications due to different component materials and design. as Synchronous Average and Cyclostationarity Analysis

Natural Wake-Sleep Algorithm

The benefits of using the natural gradient are well known in a wide range of optimization problems. However, for the training of common neural networks the resulting increase in computational complexity sets a limitation to its practical application. Helmholtz Machines are a particular type of generative model composed of two Sigmoid Belief Networks (SBNs), acting as an encoder and a decoder, commonly trained using the Wake-Sleep (WS) algorithm and its reweighted version RWS. For SBNs, it has been shown how the locality of the connections in the graphical structure induces sparsity in the Fisher information matrix. The resulting block diagonal structure can be efficiently exploited to reduce the computational complexity of the Fisher matrix inversion and thus compute the natural gradient exactly, without the need of approximations. We present a geometric adaptation of well-known methods from the literature, introducing the Natural Wake-Sleep (NWS) and the Natural Reweighted Wake-Sleep (NRWS) algorithms. We present an experimental analysis of the novel geometrical algorithms based on the convergence speed and the value of the log-likelihood, both with respect to the number of iterations and the time complexity and demonstrating improvements on these aspects over their respective non-geometric baselines.Comment: 19 pages, 9 figure

anomalous origin of left main coronary artery from the right coronary artery echocardiographic diagnosis

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Identifying efficient Nitrate reduction strategies in the Upper Danube

Nitrogen losses in the form of Nitrate (N-NO3) from point and diffuse sources of pollution are recognized to be the leading cause of water body impairment throughout Europe. Implementation of conservation programs is perceived as being crucial for restoring and protecting the good ecological status of freshwater bodies. The success of conservation programs depends on the efficient identification of management solutions with respect to the envisaged environmental and economic objectives. This is a complex task, especially considering that costs and effectiveness of conservation strategies depend on their locations. We applied a multi-objective, spatially explicit analysis tool, the R-SWAT-DM framework, to search for efficient, spatially-targeted solution of Nitrate abatement in the Upper Danube Basin. The Soil Water Assessment Tool (SWAT) model served as the nonpoint source pollution estimator for current conditions as well as for scenarios with modified agricultural practices and waste water treatment upgrading. A spatially explicit optimization analysis that considered point and diffuse sources of Nitrate was performed to search for strategies that could achieve largest pollution abatement at minimum cost. The set of optimal spatial conservation strategies identified in the Basin indicated that it could be possible to reduce Nitrate loads by more than 50% while simultaneously provide a higher income