Advanced detection in Lorentz microscopy: pixelated detection in differential phase contrast scanning transmission electron microscopy

Modern devices require fundamental length scales to be analysed in a maximum detail to enable research of new types of phenomena and design new materials. In this thesis, an advancement in Lorentz microscopy will be presented where the focus was placed not only onto resolution in spatial space but also onto resolution in reciprocal space. This allows greater sensitivity to measurements of the integrated magnetic induction within thin samples. This was achieved by a novel approach to the data acquisition, where instead of a segmented (annular) detector, a pixelated detector was used to measure the deflection of the scanning transmission microscopy (STEM) probe due to the in-plane integrated magnetic induction. Computer vision algorithms were researched to find an efficient, noise-robust way to register the deflection of the STEM probe. This enabled a novel approach to data analysis, where a scatter of the 2D integrated induction (a bivariate histogram) is used to show the distribution of the magnetic induction vector. The experimental results are supported by simulations, where a model of a thin polycrystalline sample causes a shift of the simulated beam due to phase modulations. The results of the detection in both the simulation and experiment showed that cross-correlation based processing can efficiently separate the low spatial frequencies (from the in-plane magnetic induction), and high spatial frequencies (from the structure of the polycrystalline sample). This work will enable quantitative analysis of a greater number of thin magnetic samples, for which the current methods are hampered by the diffraction contrast. This will be particularly helpful for the study low moment, out of plane, magnetised thin films. Currently such systems are of great interest due to the tunability of their magnetic properties and the novel magnetic structures present within them. This work also provides an important step for computational methods in transmission electron microscopy, as this is one of the first examples of 4D data acquisition of processing in STEM (where two dimensions represent the spatial scanning dimensions and other two the reciprocal space). Imaging methods developed in this thesis were applied to the topic of skyrmions in a thin layer of a FeGe cubic helimagnet, where the very fine detail of the structure of their in-plane integrated magnetic induction was shown to contain a distorted modulations of its profile. This was compared to a simple three harmonic frequency model, which was altered to fit some characteristics of the imaged magnetic skyrmions. In this work, for the first time, a direct comparison of differential phase contrast and electron holography will be shown for a simple experiment in which the integrated electric field between two needles was measured in free space in the same microscope. Although it was concluded that both methods are equivalent, some small discrepancies of measured values were present due to a long range electric field in electron holography and/or drift of the beam in between scans in STEM

Magnetic Nanomaterials

The constant search for innovative magnetic materials increasingly leads to the creation of highly engineered systems built in different forms (films, wires, particles), structured on the nanoscale in at least one spatial direction, and often characterized by the coexistence of two or more phases that are magnetically and/or structurally different. In magnetic systems, the nanometric structural characteristics of the constituent elements, together with the type and strength of the magnetic interactions between them, determine the overall magnetic behavior and can lead to the appearance of unexpected and amazing magnetic phenomena. Indeed, the study of the magnetic properties of nanomaterials continues to arouse great interest for their intriguing fundamental properties and prospective technological applications. This Special Issue contributes to broadening the knowledge on magnetic nanomaterials, demonstrating the breadth and richness of this research field as well as the growing need to address it through an interdisciplinary approach. The papers collected in this book (two reviews and eight regular articles) report cutting-edge studies on the production and characterization of a variety of novel magnetic nanomaterials (nanoparticles, nanocomposites, thin films and multilayers), which have the potential to play a key role in different technologically advanced sectors, such as biotechnology, nanomedicine, energy, spintronics, data storage, and sensors

Recent Advances in Signal Processing

The signal processing task is a very critical issue in the majority of new technological inventions and challenges in a variety of applications in both science and engineering fields. Classical signal processing techniques have largely worked with mathematical models that are linear, local, stationary, and Gaussian. They have always favored closed-form tractability over real-world accuracy. These constraints were imposed by the lack of powerful computing tools. During the last few decades, signal processing theories, developments, and applications have matured rapidly and now include tools from many areas of mathematics, computer science, physics, and engineering. This book is targeted primarily toward both students and researchers who want to be exposed to a wide variety of signal processing techniques and algorithms. It includes 27 chapters that can be categorized into five different areas depending on the application at hand. These five categories are ordered to address image processing, speech processing, communication systems, time-series analysis, and educational packages respectively. The book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity

Tracing back the source of contamination

From the time a contaminant is detected in an observation well, the question of where and when the contaminant was introduced in the aquifer needs an answer. Many techniques have been proposed to answer this question, but virtually all of them assume that the aquifer and its dynamics are perfectly known. This work discusses a new approach for the simultaneous identification of the contaminant source location and the spatial variability of hydraulic conductivity in an aquifer which has been validated on synthetic and laboratory experiments and which is in the process of being validated on a real aquifer

Speech Recognition

Chapters in the first part of the book cover all the essential speech processing techniques for building robust, automatic speech recognition systems: the representation for speech signals and the methods for speech-features extraction, acoustic and language modeling, efficient algorithms for searching the hypothesis space, and multimodal approaches to speech recognition. The last part of the book is devoted to other speech processing applications that can use the information from automatic speech recognition for speaker identification and tracking, for prosody modeling in emotion-detection systems and in other speech processing applications that are able to operate in real-world environments, like mobile communication services and smart homes

Handbook of Mathematical Geosciences

This Open Access handbook published at the IAMG's 50th anniversary, presents a compilation of invited path-breaking research contributions by award-winning geoscientists who have been instrumental in shaping the IAMG. It contains 45 chapters that are categorized broadly into five parts (i) theory, (ii) general applications, (iii) exploration and resource estimation, (iv) reviews, and (v) reminiscences covering related topics like mathematical geosciences, mathematical morphology, geostatistics, fractals and multifractals, spatial statistics, multipoint geostatistics, compositional data analysis, informatics, geocomputation, numerical methods, and chaos theory in the geosciences

Abstracts on Radio Direction Finding (1899 - 1995)

The files on this record represent the various databases that originally composed the CD-ROM issue of "Abstracts on Radio Direction Finding" database, which is now part of the Dudley Knox Library's Abstracts and Selected Full Text Documents on Radio Direction Finding (1899 - 1995) Collection. (See Calhoun record https://calhoun.nps.edu/handle/10945/57364 for further information on this collection and the bibliography). Due to issues of technological obsolescence preventing current and future audiences from accessing the bibliography, DKL exported and converted into the three files on this record the various databases contained in the CD-ROM. The contents of these files are: 1) RDFA_CompleteBibliography_xls.zip [RDFA_CompleteBibliography.xls: Metadata for the complete bibliography, in Excel 97-2003 Workbook format; RDFA_Glossary.xls: Glossary of terms, in Excel 97-2003 Workbookformat; RDFA_Biographies.xls: Biographies of leading figures, in Excel 97-2003 Workbook format]; 2) RDFA_CompleteBibliography_csv.zip [RDFA_CompleteBibliography.TXT: Metadata for the complete bibliography, in CSV format; RDFA_Glossary.TXT: Glossary of terms, in CSV format; RDFA_Biographies.TXT: Biographies of leading figures, in CSV format]; 3) RDFA_CompleteBibliography.pdf: A human readable display of the bibliographic data, as a means of double-checking any possible deviations due to conversion

NASA Workshop on Distributed Parameter Modeling and Control of Flexible Aerospace Systems

Although significant advances have been made in modeling and controlling flexible systems, there remains a need for improvements in model accuracy and in control performance. The finite element models of flexible systems are unduly complex and are almost intractable to optimum parameter estimation for refinement using experimental data. Distributed parameter or continuum modeling offers some advantages and some challenges in both modeling and control. Continuum models often result in a significantly reduced number of model parameters, thereby enabling optimum parameter estimation. The dynamic equations of motion of continuum models provide the advantage of allowing the embedding of the control system dynamics, thus forming a complete set of system dynamics. There is also increased insight provided by the continuum model approach