5,941 research outputs found

    Geodetic monitoring of complex shaped infrastructures using Ground-Based InSAR

    Get PDF
    In the context of climate change, alternatives to fossil energies need to be used as much as possible to produce electricity. Hydroelectric power generation through the utilisation of dams stands out as an exemplar of highly effective methodologies in this endeavour. Various monitoring sensors can be installed with different characteristics w.r.t. spatial resolution, temporal resolution and accuracy to assess their safe usage. Among the array of techniques available, it is noteworthy that ground-based synthetic aperture radar (GB-SAR) has not yet been widely adopted for this purpose. Despite its remarkable equilibrium between the aforementioned attributes, its sensitivity to atmospheric disruptions, specific acquisition geometry, and the requisite for phase unwrapping collectively contribute to constraining its usage. Several processing strategies are developed in this thesis to capitalise on all the opportunities of GB-SAR systems, such as continuous, flexible and autonomous observation combined with high resolutions and accuracy. The first challenge that needs to be solved is to accurately localise and estimate the azimuth of the GB-SAR to improve the geocoding of the image in the subsequent step. A ray tracing algorithm and tomographic techniques are used to recover these external parameters of the sensors. The introduction of corner reflectors for validation purposes confirms a significant error reduction. However, for the subsequent geocoding, challenges persist in scenarios involving vertical structures due to foreshortening and layover, which notably compromise the geocoding quality of the observed points. These issues arise when multiple points at varying elevations are encapsulated within a singular resolution cell, posing difficulties in pinpointing the precise location of the scattering point responsible for signal return. To surmount these hurdles, a Bayesian approach grounded in intensity models is formulated, offering a tool to enhance the accuracy of the geocoding process. The validation is assessed on a dam in the black forest in Germany, characterised by a very specific structure. The second part of this thesis is focused on the feasibility of using GB-SAR systems for long-term geodetic monitoring of large structures. A first assessment is made by testing large temporal baselines between acquisitions for epoch-wise monitoring. Due to large displacements, the phase unwrapping can not recover all the information. An improvement is made by adapting the geometry of the signal processing with the principal component analysis. The main case study consists of several campaigns from different stations at Enguri Dam in Georgia. The consistency of the estimated displacement map is assessed by comparing it to a numerical model calibrated on the plumblines data. It exhibits a strong agreement between the two results and comforts the usage of GB-SAR for epoch-wise monitoring, as it can measure several thousand points on the dam. It also exhibits the possibility of detecting local anomalies in the numerical model. Finally, the instrument has been installed for continuous monitoring for over two years at Enguri Dam. An adequate flowchart is developed to eliminate the drift happening with classical interferometric algorithms to achieve the accuracy required for geodetic monitoring. The analysis of the obtained time series confirms a very plausible result with classical parametric models of dam deformations. Moreover, the results of this processing strategy are also confronted with the numerical model and demonstrate a high consistency. The final comforting result is the comparison of the GB-SAR time series with the output from four GNSS stations installed on the dam crest. The developed algorithms and methods increase the capabilities of the GB-SAR for dam monitoring in different configurations. It can be a valuable and precious supplement to other classical sensors for long-term geodetic observation purposes as well as short-term monitoring in cases of particular dam operations

    A Spark Of Emotion: The Impact of Electrical Facial Muscle Activation on Emotional State and Affective Processing

    Get PDF
    Facial feedback, which involves the brain receiving information about the activation of facial muscles, has the potential to influence our emotional states and judgments. The extent to which this applies is still a matter of debate, particularly considering a failed replication of a seminal study. One factor contributing to the lack of replication in facial feedback effects may be the imprecise manipulation of facial muscle activity in terms of both degree and timing. To overcome these limitations, this thesis proposes a non-invasive method for inducing precise facial muscle contractions, called facial neuromuscular electrical stimulation (fNMES). I begin by presenting a systematic literature review that lays the groundwork for standardising the use of fNMES in psychological research, by evaluating its application in existing studies. This review highlights two issues, the lack of use of fNMES in psychology research and the lack of parameter reporting. I provide practical recommendations for researchers interested in implementing fNMES. Subsequently, I conducted an online experiment to investigate participants' willingness to participate in fNMES research. This experiment revealed that concerns over potential burns and involuntary muscle movements are significant deterrents to participation. Understanding these anxieties is critical for participant management and expectation setting. Subsequently, two laboratory studies are presented that investigated the facial FFH using fNMES. The first study showed that feelings of happiness and sadness, and changes in peripheral physiology, can be induced by stimulating corresponding facial muscles with 5–seconds of fNMES. The second experiment showed that fNMES-induced smiling alters the perception of ambiguous facial emotions, creating a bias towards happiness, and alters neural correlates of face processing, as measured with event-related potentials (ERPs). In summary, the thesis presents promising results for testing the facial feedback hypothesis with fNMES and provides practical guidelines and recommendations for researchers interested in using fNMES for psychological research

    Climate Change and Critical Agrarian Studies

    Full text link
    Climate change is perhaps the greatest threat to humanity today and plays out as a cruel engine of myriad forms of injustice, violence and destruction. The effects of climate change from human-made emissions of greenhouse gases are devastating and accelerating; yet are uncertain and uneven both in terms of geography and socio-economic impacts. Emerging from the dynamics of capitalism since the industrial revolution — as well as industrialisation under state-led socialism — the consequences of climate change are especially profound for the countryside and its inhabitants. The book interrogates the narratives and strategies that frame climate change and examines the institutionalised responses in agrarian settings, highlighting what exclusions and inclusions result. It explores how different people — in relation to class and other co-constituted axes of social difference such as gender, race, ethnicity, age and occupation — are affected by climate change, as well as the climate adaptation and mitigation responses being implemented in rural areas. The book in turn explores how climate change – and the responses to it - affect processes of social differentiation, trajectories of accumulation and in turn agrarian politics. Finally, the book examines what strategies are required to confront climate change, and the underlying political-economic dynamics that cause it, reflecting on what this means for agrarian struggles across the world. The 26 chapters in this volume explore how the relationship between capitalism and climate change plays out in the rural world and, in particular, the way agrarian struggles connect with the huge challenge of climate change. Through a huge variety of case studies alongside more conceptual chapters, the book makes the often-missing connection between climate change and critical agrarian studies. The book argues that making the connection between climate and agrarian justice is crucial

    Photocatalysis in the Wastewater Treatment

    Get PDF
    The use of photocatalysis for wastewater treatment is an important area of research, which is not yet fully exploited at an industrial level and has significant potential in the disposal of many industrial effluents, particularly the effluents that are difficult to treat by conventional treatment processes. This reprint tries to know the latest advances in the field of wastewater treatment by photocatalysis. In this sense, it is worth mentioning the treatments based on photolysis, TiO2/solar light, oxidants/ultraviolet irradiation, oxidants/catalyst/ultraviolet irradiation, etc. In addition, the reprint describes catalyst manufacturing methods and reaction mechanisms

    3D Innovations in Personalized Surgery

    Get PDF
    Current practice involves the use of 3D surgical planning and patient-specific solutions in multiple surgical areas of expertise. Patient-specific solutions have been endorsed for several years in numerous publications due to their associated benefits around accuracy, safety, and predictability of surgical outcome. The basis of 3D surgical planning is the use of high-quality medical images (e.g., CT, MRI, or PET-scans). The translation from 3D digital planning toward surgical applications was developed hand in hand with a rise in 3D printing applications of multiple biocompatible materials. These technical aspects of medical care require engineers’ or technical physicians’ expertise for optimal safe and effective implementation in daily clinical routines.The aim and scope of this Special Issue is high-tech solutions in personalized surgery, based on 3D technology and, more specifically, bone-related surgery. Full-papers or highly innovative technical notes or (systematic) reviews that relate to innovative personalized surgery are invited. This can include optimization of imaging for 3D VSP, optimization of 3D VSP workflow and its translation toward the surgical procedure, or optimization of personalized implants or devices in relation to bone surgery

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

    Get PDF
    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    On the path integration system of insects: there and back again

    Get PDF
    Navigation is an essential capability of animate organisms and robots. Among animate organisms of particular interest are insects because they are capable of a variety of navigation competencies solving challenging problems with limited resources, thereby providing inspiration for robot navigation. Ants, bees and other insects are able to return to their nest using a navigation strategy known as path integration. During path integration, the animal maintains a running estimate of the distance and direction to its nest as it travels. This estimate, known as the `home vector', enables the animal to return to its nest. Path integration was the technique used by sea navigators to cross the open seas in the past. To perform path integration, both sailors and insects need access to two pieces of information, their direction and their speed of motion over time. Neurons encoding the heading and speed have been found to converge on a highly conserved region of the insect brain, the central complex. It is, therefore, believed that the central complex is key to the computations pertaining to path integration. However, several questions remain about the exact structure of the neuronal circuit that tracks the animal's heading, how it differs between insect species, and how the speed and direction are integrated into a home vector and maintained in memory. In this thesis, I have combined behavioural, anatomical, and physiological data with computational modelling and agent simulations to tackle these questions. Analysis of the internal compass circuit of two insect species with highly divergent ecologies, the fruit fly Drosophila melanogaster and the desert locust Schistocerca gregaria, revealed that despite 400 million years of evolutionary divergence, both species share a fundamentally common internal compass circuit that keeps track of the animal's heading. However, subtle differences in the neuronal morphologies result in distinct circuit dynamics adapted to the ecology of each species, thereby providing insights into how neural circuits evolved to accommodate species-specific behaviours. The fast-moving insects need to update their home vector memory continuously as they move, yet they can remember it for several hours. This conjunction of fast updating and long persistence of the home vector does not directly map to current short, mid, and long-term memory accounts. An extensive literature review revealed a lack of available memory models that could support the home vector memory requirements. A comparison of existing behavioural data with the homing behaviour of simulated robot agents illustrated that the prevalent hypothesis, which posits that the neural substrate of the path integration memory is a bump attractor network, is contradicted by behavioural evidence. An investigation of the type of memory utilised during path integration revealed that cold-induced anaesthesia disrupts the ability of ants to return to their nest, but it does not eliminate their ability to move in the correct homing direction. Using computational modelling and simulated agents, I argue that the best explanation for this phenomenon is not two separate memories differently affected by temperature but a shared memory that encodes both the direction and distance. The results presented in this thesis shed some more light on the labyrinth that researchers of animal navigation have been exploring in their attempts to unravel a few more rounds of Ariadne's thread back to its origin. The findings provide valuable insights into the path integration system of insects and inspiration for future memory research, advancing path integration techniques in robotics, and developing novel neuromorphic solutions to computational problems

    Relation-Oriented: Toward Knowledge-Aligned Causal AI

    Full text link
    In machine learning, we naturally apply an Observation-Oriented principle, in which observational variables preexist and set the stage for constructing relationships. While sufficient for traditional models, the integration of AI with big data exposes the misalignment between the observational models and our actual comprehension. Contrarily, humans shape cognitive entities defined by relationships, enabling us to formulate knowledge across temporal and hyper-dimensional spaces, rather than being confined to observational constructs. From an innovative Relation-Oriented perspective, this study examines the roots of this misalignment within our current modeling paradigm, illuminated by intuitive examples from computer vision and health informatics. We also introduce the relation-defined representation learning methodology as a practical implementation of Relation-Oriented modeling, supported by extensive experimental validation

    High Voltage DC-biased Oil Type Medium Frequency Transformer; A Green Solution for Series DC Wind Park Concept

    Get PDF
    The electric energy generated by remote offshore wind parks is transported to the consumers using high voltage submarine cables. On the generation site, such transmissions are realized today by collecting the energy produced by several wind turbines in a bulky and expensive transformer placed on a dedicated platform. An alternative solution has been proposed recently, which allows to reduce the installation and maintenance costs by eliminating such a platform. It is suggested to equip each wind turbine in the wind park by an individual DC/DC converter and connect them in series to reach the DC voltage level required for an efficient HVDC energy transportation to the shore. The DC/DC converter is supposed to be a Dual Active Bridge (DAB) converter, which can be made reasonably small to be placed on the wind turbine tower or even in its nacelle. The key element of the converter defining its size and mass is a special transformer, which operates at voltages comprising a high (switching) frequency component superimposed on a high DC offset voltage. DC insulation design of such a transformer and investigation of the effects of a high DC insulation level on the other electromagnetic properties of the transformer is the subject of the present research.In order to verify the concept a prototype of the transformer was built, and its evaluation presented. The unit has been manufactured for the rated power of 50 kW and rated voltages 0.4/5 kV including DC offset of 125 kV and square-shaped oscillations with the frequency of 5 kHz. The magnetic system was made of ferrite material and consisted of 10 shell-type core segments. The magnetic properties have been verified by measuring magnetization and losses at various frequencies in the range 1-10 kHz to cover the operational range of the DAB. The types and dimensions of the windings and their conductors were chosen to minimize the proximity and eddy current effects at higher frequencies. To reduce the size of the transformer and to allow for its efficient cooling, the active part was immersed in oil and cellulose-based materials (paper and pressboard) were used to build the high voltage insulation system. The principles for dimensioning the insulation of the transformer are discussed. The criteria used for selecting insulating distances were based on the consideration of the electric field strength obtained from FEM simulations and using the non-linear Maxwell-Wagner model accounting for local variations of the electric field caused by accumulation of interfacial charges induced by DC stresses. The properties of the materials needed for the calculations were obtained by measuring their dielectric constants and electric conductivities. The methodology used for the measurements conducted for conventional mineral oil and eco-friendly biodegradable transformer oils and, respectively, for oil-impregnated paper/pressboard, is presented. The methodologies used for obtaining parameters of the built transformer prototype needed for its integration in the power electric circuit of the DAB are introduced. A method developed for accurate calculations of the leakage inductance for the shell-type multi core transformers with circular windings is described. Two innovative methods for evaluations of parasitic capacitances based on high frequency equivalent circuits of the transformer are presented. The results of their verifications against performed Frequency Response Analysis measurements and FEM calculations as well as their accuracy are discussed.Thermal performance of the developed transformer prototype is analysed based on the results of computer simulations of heat transfer in its active part under rated load. Identified hot spots and solutions for their elimination are presented.Finally, the expected dimensions, weight, and efficiency of an actual DC/DC converter with the rated parameters corresponding to a 6 MW, 1.8 kV real wind turbine having a 250 kV offset DC voltage are estimated assuming that the developed transformer prototype is scalable. It is shown that the proposed solution allows for installing the full-scale converter having 2.2 Tons in weight and 1.8 m3 in volume on the bottom of the wind turbine’s tower
    • …
    corecore