Immerhin eine Grenze ... Das polnisch-litauische Grenzgebiet: von sozialistischer Bruderschaft bis Schengen

Das Thema der heutigen Beziehungen zwischen der Bevölkerung im litauisch-polnischen Grenzgebiet ist wenig erforscht. Für polnische und litauische Autoren scheinen die interethnischen Beziehungen und gegenseitige Wahrnehmung von größerem Interesse zu sein, sowohl innerhalb eines Staates, als auch grenzüberschreitend. Dennoch fehlen Studien, die sich nur auf das Grenzgebiet beziehen und gleichzeitig den Sachstand beiderseits der Grenze erforschen. In der vorliegenden Fallstudie wird am Beispiel des polnischen-litauischen Grenzgebiets dargestellt, inwieweit die Erinnerungen an ein geschlossenes Grenzregime lokale grenzüberschreitende Kontakte verhindert, auch nach der Aufhebung aller formellen Einschränkungen und fast bei jeglichem Fehlen topographischer Hürden (Flüsse, Gebirge). Zuerst wird das polnisch-litauische Grenzgebiet anhand statistischer Daten (inkl. ethnische Zusammensetzung) präsentiert. Anschließend wird ein geschichtlicher Überblick gegeben und das einstige Grenzregime zwischen der Sowjetunion (UdSSR) und der Volksrepublik Polen geschildert. Dann wird skizziert, wie sich die Grenze selbst und die Kontakte lokaler Einwohner im Laufe der letzten zwei Jahrzehnte entwickelt haben. Das betrifft u.a. auf folgende Themenbereiche: Handel, Infrastruktur, Transport, grenzüberschreitende Zusammenarbeit auf kommunaler Ebene und kultureller Austausch. Es werden auch einige nicht genutzte Möglichkeiten aufgezeigt: gewisse "Brücken" im weitesten Sinne des Wortes, die in vielen anderen Grenzgebieten bei einer derartigen Freizügigkeit (wie im Schengen-Raum) entstehen, nicht jedoch im polnisch-litauischen Grenzgebiet. (Autorenreferat)The mutual links of the population in the border region between Poland and Lithuania have not yet been sufficiently examined. The Polish and Lithuanian authors seem to focus more on the interethnic relations and mutual perception of the Poles and Lithuanians, be it within the same state or over the border. More detailed studies related to the borderland itself, especially those examining the situation on the both sides of the border, are rather scarce. The following case study presents the Polish-Lithuanian borderland as an example of how the legacy of a closed border regime may hamper the cross-border contacts even after eliminating all formal barriers and despite the favourable topography of the border (i.e. no natural obstacles such as rivers or mountains). The study begins with a presentation of the Polish-Lithuanian borderland on the basis of statistical data, including the ethnic composition, followed by a historical overview and description of the border regime between the former Soviet Union and its satellite state, the Polish People's Republic. The next part is dedicated to the development of the border regime and the cross-border contacts of the population within the last two decades. Special focus is granted to the following issues: cross-border shopping, infrastructure, transports, co-operation of the local authorities, cultural exchange. Some unused potential for possible co-operation will also be shown, i.e. some "bridges" in the broad sense which can be identified in many other border regions given the same grade of border openness (given the Schengen area as benchmark), and which are still missing in the Polish-Lithuanian borderland. (author's abstract

Real-time event classification in field sport videos

The paper presents a novel approach to real-time event detection in sports broadcasts. We present how the same underlying audio-visual feature extraction algorithm based on new global image descriptors is robust across a range of different sports alleviating the need to tailor it to a particular sport. In addition, we propose and evaluate three different classifiers in order to detect events using these features: a feed-forward neural network, an Elman neural network and a decision tree. Each are investigated and evaluated in terms of their usefulness for real-time event classification. We also propose a ground truth dataset together with an annotation technique for performance evaluation of each classifier useful to others interested in this problem

Nine-Axis IMU sensor fusion using the AHRS algorithm and neural networks

This paper presents data processing method for Attitude Heading and Reference System (AHRS) based on Artificial Neural Networks (ANN). The system consist of MEMS (Micro Electro-Mechanical Systems) based on Inertial Measurement Unit (IMU) consisting of tri-axis gyroscopes, accelerometers and magnetometers providing three dimensional linear accelerations and angular rates. Training data was generated by simulation fusion of samples collected during the flight of Quadcopter. The presented results shows proper functioning of the neural network. Moreover, the presented system provide the possibility to easily add other sensors e.g. GPS, in order to achieve better performance

Anti-corrosive siloxane coatings for improved long-term performance of supercapacitors with an aqueous electrolyte

This paper reports on the impact that the corrosion of the stainless steel current collectors has on the performance fade of a symmetric, carbon/carbon electrochemical capacitor, operating with an aqueous electrolyte (1M Na2SO4). The results obtained by applying electrochemical ageing protocols (voltage-holding tests) confirm that the current collector of the positive electrode undergoes tremendous degradation during 200 h in the charged state. To prevent the detrimental impact of the corrosion, a hydrophobic siloxane coating has been successfully applied. In the case of siloxane-protected current collectors that are subjected to identical ageing protocols, no significant deterioration in the electrochemical capacitor performance was observed. The siloxane coating reduces the electrochemical corrosion rate of 316L stainless steel significantly, as the potentiodynamic polarization tests and the electrochemical impedance spectroscopy results show. The presence of the coating is demonstrated by the water contact angle measurements, atomic force microscopy and energy-dispersive X-ray spectroscopy analysis

Multi-agent system based on Artificial Neural Network for terrain exploration

In the presented paper Multi Agent System (MAS) with automatic formation selection based on the Artificial Neural Networks (ANN) is described. Presented system aims at testing the collective behavior of robots in unknown territory, their ability to cooperate in case where information and communication are extremely limited. As an example of MAS usage, the task of searching the experimental area to find a specific point is presented

Neural controller implementation in embedded system with use of FPGA coprocessor

In this paper we propose implementation of neural control system as embedded system with coprocessor in extensible processing platform

Gradient method of learning for stochastic kinetic model of neuron

In this paper we are focusing on the kinetic extension [4] of classic model of Hodgkin and Huxley [2]. We are showing the descent gradient method used in the learning process of neuron, which is described with stochastic kinetic model. In comparison with [1] we use only 3 weights instead of 9: gNa; gK and gL: We show that this model behaves equally accurate as the model of Hodgkin and Huxley with slighter system description

Time synchronization in distributed sensor network

Time synchronization in a distributed sensor network is a key issue. Data from the sensors are properly synchronized are very good material for further analysis. In the paper a network of medical sensors is presented. It is important to obtain a properly synchronized data from the sensors. This guarantee that the data can be processed to detect correlation between different signals. For the purpose of accurate time synchronization, the simple and efficient algorithm is presented

Nine-Axis IMU sensor fusion using the AHRS algorithm and neural networks

This paper presents data processing method for Attitude Heading and Reference System (AHRS) based on Artificial Neural Networks (ANN). The system consist of MEMS (Micro Electro-Mechanical Systems) based on Inertial Measurement Unit (IMU) consisting of tri-axis gyroscopes, accelerometers and magnetometers providing three dimensional linear accelerations and angular rates. Training data was generated by simulation fusion of samples collected during the flight of Quadcopter. The presented results shows proper functioning of the neural network. Moreover, the presented system provide the possibility to easily add other sensors e.g. GPS, in order to achieve better performance

On backreaction effects in geometrical destabilisation of inflation

International audienceWe study the geometrical instability arising in multi-field models of inflation with negatively-curved field space. We analyse how the homogeneous background evolves in presence of geometrical destabilisation, and show that, in simple models, a kinematical backreaction effect takes place that shuts off the instability. We also follow the evolution of the unstable scalar fluctuations and show that, in most situations, they must remain in the perturbative regime in order to satisfy observational constraints. We conclude that, in the simplest models of geometrical destabilisation, inflation does not end prematurely, but rather proceeds along a modified, sidetracked, field-space trajectory