Early Monks and Monasteries in the Holyland

Μη διαθέσιμη περίληψηno abstrac

The impact of eigenvalue locality on the convergence behavior of the PSD method for two-cyclic matrices

AbstractIn this paper, we analyse the convergence of the preconditioned simultaneous displacement (PSD) method applied to linear systems of the form Au=b where A is a two-cyclic matrix. Convergence conditions and optimum values of the parameters of the method are determined in the cases where the eigenvalues of the associated Jacobi iteration matrix are either all real or all imaginary. It is shown that the convergence behavior of the PSD method is greatly affected by the locality of the eigenvalues of the associated Jacobi iteration matrix. In particular, it is shown that when these eigenvalues are real the PSD method degenerates into the extrapolated Gauss–Seidel method whereas when they are imaginary its convergence is increased by an order of magnitude and becomes equivalent to the extrapolated SOR method. Finally, a comparison with the SSOR method reveals that the PSD method possesses a better convergence behavior in all cases

Das ArbeiterInnenlied im Kontext der österreichischen ArbeiterInnenbewegung

Die vorliegende Arbeit versucht das ArbeiterInnenlied im Kontext der österreichischen ArbeiterInnenbewegung zu untersuchen. Dabei wird der Frage nachgegangen, welche Funktion das ArbeiterInnenlied im politischen Kontext einnimmt und welche Wandlungen es durchläuft. Im ersten Teil der Arbeit wird versucht, das ArbeiterInnenlied zu definieren und es abzugrenzen. Im zweiten Teil der Arbeit wird das Umfeld der ArbeiterInnenliedbewegung, also der ArbeiterInnenmusikorganisationen und ihre Entwicklung untersucht und dargestellt. Ein besonderer Schwerpunkt wird auch auf die heutige Bedeutung von ArbeiterInnenlieder gelegt, die durch eine Umfrage unter jungen, in der Sozialistischen Jugend organisierten Menschen ermittelt wird. Im dritten Teil werden ArbeiterInnenlieder anhand von fünf historischen Schwerpunkten untersucht: Der Revolution 1848, Hymnen der österreichischen Sozialdemokratie, Adaptionen und Einflüsse auf die ArbeiterInnenliedbewegung, Lieder gegen Unterdrückung und Untersuchungen zur Proletenpassion. Die vorliegende Arbeit zeigt, dass das ArbeiterInnenlied für die österreichische Sozialdemokratie immer noch bedeutend ist und dass das Singen von Liedern aus dem ArbeiterInnenliedgut für die österreichische ArbeiterInnenbewegung zum politischen Alltag dazugehört

Μελέτη σχέσης κυτταρικής επικοινωνίας και ανοσίας

Στην παρούσα διπλωματική εργασία αναπτύσσονται κυτταρικά μοντέλα προσομοίωσης, με σκοπό την μελέτη βιολογικών φαινομένων όπως η κυτταρική επικοινωνία (μέσω ανταλλαγής χημικών ουσιών), η επίτευξη ανοσίας σε ένα σύστημα που εμπεριέχει κύτταρα με ανοσοποιητική δράση, η εμφάνιση ανοσολογικής απόκρισης και η συμπεριφορά της έναντι διαφορετικών νοσογόνων παραγόντων όπως τοξικές ουσίες, ενδοκυττάρια παράσιτα και εξωκυττάρια παράσιτα. Εξετάζεται επίσης η εμφάνιση πιο πολύπλοκων συμπεριφορών στο σύστημα όπως η ανοσολογική μνήμη και η αυτο-άνοση αντίδραση. Η σχεδίαση όλων των μοντέλων έγινε με βάση τις αρχές των εξατομικευμένων μοντέλων προσομοίωσης (Agent Based Models) και η γλώσσα προγραμματισμού που χρησιμοποιήθηκε για την υλοποίηση τους ήταν η JAVA.In the context of this thesis, cellular simulation models are developed, in order to study biological phenomena such as cellular communication (through exchange of chemical substances between cells), the occurrence of immunity inside a system that contains immune cells, the emergence of an immunological response and its behavior against various disease agents such as toxic substances, intracellular parasites and extracellular parasites. In addition, the emergence of more complex system behaviors is studied, like immunological memory and an autoimmune response. The creation of all the models was based on the principles of Agent Based Model design and the programming language that was used for the implementation of the models was JAVA

Design and manufacture of an optimised side-shifted PPM 2 EMAT array for use in mobile robotic localisation

Guided wave Electro Magnetic Acoustic Transducers (EMATs) offer an elegant method for structural inspection and localisation relative to geometric features, such as welds. This paper presents a Lorentz force EMAT construction framework, where a numerical model has been developed for optimising Printed Circuit Board (PCB) coil parameters as well as a methodology for optimising magnet array parameters to a user’s needs. This framework was validated experimentally to show its effectiveness through comparison to an industry built EMAT. The framework was then used to design and manufacture a Side-Shifted Unidirectional Periodic Permanent Magnet (PPM) EMAT for use on a mobile robotic system, which uses guided waves for ranging to build internal maps of a given subject, identifying welded sections, defects and other structural elements. The unidirectional transducer setup was shown to operate in simulation and was then manufactured to compare to the bidirectional transmitter and two-receiver configurations on a localisation system. The unidirectional setup was shown to have clear benefits over the bidirectional setup for mapping an unknown environment using guided waves as there were no dead spots of mapping where signal direction could not be interpreted. Additionally, overall package size was significantly reduced, which in turn allows more measurements to be taken within confined spaces and increases robotic crawler mobility

The effect of complex corrosion profiles on remaining wall thickness quantification using shear horizontal guided waves

Corrosion of plate and pipe structures is a major concern to many key industries, including power, maritime, and oil and gas. When there is a need to inspect large areas quickly or when access to the structure is limited, guided wave testing is often preferred over bulk wave measurements. In this work, shear horizontal guided waves are employed for wall thickness quantification. Specifically, the interaction of modes SH1 and SH0 with complex corrosion defects is investigated. The guided wave mode are selectively generated using a phased array-based approach. A pair of identical phased array probes are positioned before and after the simulated corrosion profile, to monitor the reflected and transmitted waves. The targeted mode is excited selectively using a 32-element 3 mm pitch array and guided wave modes are decomposed after a 2DFFT is performed. The cut-off frequency technique using mode SH1 is shown to be adequate when smooth wall thinning defects are considered. When sharp pits are present, mode SH0 proved sufficient to determine the pits depth

Non-contact ultrasonic-based Bayesian mapping for robotic structural inspection

The state-of-the-art robotic ultrasonic inspection of large structural assets such as oil and gas storage tanks is carried out on a point-by-point scheme, where an ultrasonic probe with a mobile platform is scanned over every point on the component. Point-by-point inspection, which generates a huge amount of data, is time-consuming for inspecting large structural and industrial assets. One way to achieve a more efficient inspection of large structures is to take advantage of ultrasonic guided waves (UGW) suitable for mid-range inspection. Unlike the point-by-point scheme, guided waves can also be used to inspect and detect defects such as corrosions in inaccessible regions (e.g., corrosion under pipe supports). In this ongoing research project, we are working towards simultaneous localisation and mapping (SLAM) of thick structures (~10mm) under inspection using ultrasonic guided waves, in particular shear horizontal (SH) wave modes generated using electromagnetic acoustic transducers (EMATs). In other words, we use guided waves to simultaneously localise the robot and map the geometrical features such as defects and boundaries. We present results on the sensitivity of different guided wave modes for weld detection. We then demonstrate the application of guided wave robotic occupancy grid mapping (GW-OGM) to map internal defects and the unknown structure's edges/boundaries. Both pseudo-pulse-echo and pitch-catch measurement setups are used for this purpose, in which one transducer acts as a transmitter and the other one as a receiver. The former mode is used to localise welded joints, which can be eventually exploited for robot localisation. The latter mode is used for defect identification and characterisation. Defect information such as the depth of defect can be used for predicting the remaining useful life of the component. Furthermore, to create a rich ultrasonic mapping of structures by characterising defects on the fly as the robot navigates the structural assets, we have taken advantage of a machine learning approach to estimate the depth of the corrosion-like defects. Phase-based handcrafted features are extracted and fed into the Gaussian process regression model to estimate the defects' depths using the calibrated simulated data set

Crawler-based automated non-contact ultrasonic inspection of large structural assets

This paper presents an update on the progress of developing a crawler-based automated non-contact ultrasonic inspection system for the evaluation of large structural assets. The system presented is a significant improvement on current robotic NDT crawlers and aims to greatly reduce the time of inspection by creating an internal feature map of the subject in a Simultaneous Localisation And Mapping (SLAM) style method instead of using a lawnmower scanning style where all areas are scanned regardless if they contain features or are featureless. This map will be generated through rapid automated path planning and scanning and will show the location of potential areas of interest, where then, the appropriate method of inspection can be used for a high detailed evaluation. Current and ongoing work presented is as follows; the use of guided waves as the sensory input of an occupancy grid map; evaluating guided wave modes to find the mode most appropriate for this system; minimum thickness estimation using machine learning; improving the transducer setup using a unidirectional transmitter