Through-the-wall Imaging (TWI) is crucial for various applications such as law enforcement, rescue missions and defense. TWI methods aim to provide detailed information of spaces that cannot be seen directly. Current state-of-the-art TWI systems utilise ultra-wideband (UWB) signals to simultaneously achieve wall penetration and high resolution. These TWI systems transmit signals and mathematically back-project the reflected signals received to image the scenario of interest. However, these systems are diffraction-limited and encounter problems due to multipath signals in the presence of multiple scatterers. Time reversal (TR) methods have become popular for remote sensing because they can take advantage of multipath signals to achieve superresolution (resolution that beats the diffraction limit). The Decomposition Of the Time-Reversal Operator (DORT in its French acronym) and MUltiple SIgnal Classification (MUSIC) methods are both TR techniques which involve taking the Singular Value Decomposition (SVD) of the Multistatic Data Matrix (MDM) which contains the signals received from the target(s) to be located. The DORT and MUSIC imaging methods have generated a lot of interests due to their robustness and ability to locate multiple targets. However these TR-based methods encounter problems when the targets are behind an obstruction, particularly when the properties of the obstruction is unknown as is often the case in TWI applications. This dissertation introduces a novel total sub-MDM algorithm that uses the highly acclaimed MUSIC method to image targets hidden behind an obstruction and achieve superresolution. The algorithm utilises spatio-temporal windows to divide the full-MDM into sub-MDMs. The summation of all images obtained from each sub-MDM give a clearer image of a scenario than we can obtain using the full-MDM. Furthermore, we propose a total sub-differential MDM algorithm that uses the MUSIC method to obtain images of moving targets that are hiddenbehind an obstructing material.

Denna studie undersöker läsbarheten i ledargenren i morgontidningarna DN och SvD med hjälp av läsbarhetsfaktorerna; meningslängd, bisatsfrekvens, personliga pronomen och personord, LIX samt OVIX. Hypotesen som prövas i uppsatsen är att ledargenren, liksom skriftspråket i allmänhet, har gått mot ett allt ”enklare” och mer läsbart språk med mer inslag av talspråklighet. En annan hypotes är att DN som är en liberal tidning har ett enklare språk än SvD som är konservativ/moderat. Materialet består av sammanlagt 12 ledartexter från åren 2004, 2008 och 2012. Undersökningen är av kvantitativ natur och resultatet relateras till tidigare undersökningar om ledargenren.     Undersökningens resultat ger stöd åt ovanstående hypoteser, då läsbarhetsfaktorerna visar på att ledargenren har fått ett mer läsbart skriftspråk, samt att DN är den tidning med mest läsbara ledare. Trots att ledargenren har blivit enklare, är den fortfarande en svår genre att läsa i förhållande till de flesta andra genrer. Ledargenren visar således även en hög skriftspråklighet.

Arbetet handlar om hur olika tidningar i Sverige framställer nazistregimen i Tyskland före och under andra världskriget i sina rubriker. Syftet är att ta reda på vilka skillnader och likheter som finns mellan lokala tidningar, tidningarna själva över tid, lokala tidningar över tid, lokal respektive rikstidning och lokal respektive rikstidning över tid. Materialet som ligger till grund för undersökningen är fyra lokala tidningar samt en rikstidning. Därutöver har vi konstruerat en analysmodell med inspiration från Asp (2011) mediernas betydelse, valet 2010och Lundgren (1999) Nyheter- att läsa tidningstext. Undersökningen visar på att det finns skillnader och även likheter mellan de olika lokaltidningarna. Dessutom påvisar undersökningen att det finns skillnader över tid mellan vissa lokaltidningar och att vissa lokaltidningar också förändrar sig över tid. Undersökningen påvisar också skillnader mellan lokaltidningar och rikstidningen.

Throughout this project, we perform a multivariate analysis of the parameters of a long short-term memory (LSTM) system for handwritten digit recognition in order to understand the model’s behaviour. In particular, we are interested in explaining how this behaviour precipitate from its parameters, and what in the network is responsible for the model arriving at a certain decision. This problem is often referred to as the interpretability problem, and falls under scope of Explainable AI (XAI). The motivation is to make AI systems more transparent, so that we can establish trust between humans. For this purpose, we make use of the MNIST dataset, which has been successfully used in the past for tackling digit recognition problem. Moreover, the balance and the simplicity of the data makes it an appropriate dataset for carrying out this research. We start by investigating the linear output layer of the LSTM, which is directly associated with the models’ predictions. The analysis includes several experiments, where we apply various methods from linear algebra such as principal component analysis (PCA) and singular value decomposition (SVD), to interpret the parameters of the network. For example, we experiment with different setups of low-rank approximations of the weight output matrix, in order to see the importance of each singular vector for each class of the digits. We found out that cutting off the fifth left and right singular vectors the model practically losses its ability to predict eights. Finally, we present a framework for analysing the parameters of the hidden layer, along with our implementation of an LSTM based variational autoencoder that serves this purpose. / I det här projektet utför vi en multivariatanalys av parametrarna för ett long short-term memory system (LSTM) för igenkänning av handskrivna siffror för att förstå modellens beteende. Vi är särskilt intresserade av att förklara hur detta uppträdande kommer ur parametrarna, och vad i nätverket som ligger bakom den modell som kommer fram till ett visst beslut. Detta problem kallas ofta för interpretability problem och omfattas av förklarlig AI (XAI). Motiveringen är att göra AI-systemen öppnare, så att vi kan skapa förtroende mellan människor. I detta syfte använder vi MNIST-datamängden, som tidigare framgångsrikt har använts för att ta itu med problemet med igenkänning av siffror. Dessutom gör balansen och enkelheten i uppgifterna det till en lämplig uppsättning uppgifter för att utföra denna forskning. Vi börjar med att undersöka det linjära utdatalagret i LSTM, som är direkt kopplat till modellernas förutsägelser. Analysen omfattar flera experiment, där vi använder olika metoder från linjär algebra, som principalkomponentanalys (PCA) och singulärvärdesfaktorisering (SVD), för att tolka nätverkets parametrar. Vi experimenterar till exempel med olika uppsättningar av lågrangordnade approximationer av viktutmatrisen för att se vikten av varje enskild vektor för varje klass av siffrorna. Vi upptäckte att om man skär av den femte vänster och högervektorn förlorar modellen praktiskt taget sin förmåga att förutsäga siffran åtta. Slutligen lägger vi fram ett ramverk för analys av parametrarna för det dolda lagret, tillsammans med vårt genomförande av en LSTM-baserad variational autoencoder som tjänar detta syfte.

<p dir="ltr">Acoustic holography is a powerful tool in the visualization of sound fields and sound sources. It provides engineers and researchers clear insights into sound fields as well as their sound sources. Some widely-used methods include Nearfield Acoustical Holography (NAH), Statistically Optimized Nearfield Acoustic Holography (SONAH) and the Equivalent Source Method (ESM). SONAH and ESM were developed specifically to tackle the intrinsic deficiency of the Fourier-based NAH which requires that the sound field fall to negligible levels at the edges of the measurement aperture, a requirement rarely met in practice. Besides the aforementioned methods, the Inverse Boundary Element Method (IBEM) can be used, given sufficient measurements and computational resources. As useful as they are in visualizing the sound field, none of these methods can provide direct guidance on potential design modifications of the observed structure in order to unequivocally reduce sound power radiation. Acoustic radiation mode analysis has previously been primarily associated with active noise control applications. Since the radiation modes radiate sound power independently, it is only necessary to modify the surface vibration patterns so that they do not couple well with the radiation modes in order to guarantee a reduction of the radiated sound power. Since the radiation modes are orthogonal and complete, they can be used as the basis functions through which the source surface vibration can be described. Therefore, an acoustic holography method based on the acoustic radiation modes will enable the sound power ranking of the modal components of the surface vibration pattern, and in turn, point out the component(s) which should be targeted in order to reduce the overall sound power. However, use of the acoustic radiation modes in the inverse procedure comes with a price: the detailed geometry of the object to be measured must be obtained, thus enabling the calculation of acoustic radiation modes and the modal pressures. But this is not an issue for original equipment manufacturers given that almost all prototypes are now designed with CAD, as is the case with the engine example to be described next.</p><p dir="ltr">In modern engine design, downsizing and reducing weight while still providing an increased amount of power has been a general trend in recent decades. Traditionally, an engine design with superior NVH performance usually comes with a heavier, thus sturdier structure. Therefore, modern engine design requires that NVH be considered in the very early design stage to avoid modifications of engine structures at the last minute, when very few changes can be made. NVH design optimization of engine components has become more practical due to the development of computer software and hardware. However, there is still a need for smarter algorithms to draw a direct relationship between the design and the radiated sound power. At the moment, techniques based on modal acoustic transfer vectors (MATVs) have gained popularity in design optimization for their good performance in sound pressure prediction. Since MATVs are derived based on structural modes, they are not independent with respect to radiated sound power. In contrast, as noted, acoustic radiation modes are an orthogonal set of velocity distributions on the structure’s surface that contribute to the radiated sound power independently. As a result, it is beneficial to describe structural vibration in terms of acoustic radiation modes in order to identify the velocity distributions that contribute the majority of the radiated sound power. Measures can then be taken to modify the identified vibration patterns to reduce their magnitudes, which will in turn result in an unequivocal reduction of the radiated sound power. A workflow of the structural optimization procedure is proposed in this dissertation.</p><p dir="ltr">While acoustic radiation modes have great efficiencies in describing radiated acoustic power, the computation of acoustic radiation modes can be time consuming. In the last chapter of this thesis, a novel way of calculating acoustic radiation modes is proposed, which differs from the traditional singular value decomposition of the power radiation resistance matrix, and which is more efficient than previously proposed procedures. </p><p><br></p>

Les décompositions parcimonieuses décrivent un signal comme une combinaison d'un petit nombre de formes de base, appelées atomes. Le dictionnaire d'atomes, crucial pour l'efficacité de la décomposition, peut résulter d'un choix a priori (ondelettes, Gabor, ...) qui fixe la structure du dictionnaire, ou d'un apprentissage à partir d'exemples représentatifs du signal. Nous proposons ici un cadre hybride combinant des contraites structurelles et une approche par apprentissage. Les dictionnaires ainsi structurés apportent une meilleure adaptation aux propriétés du signal et permettent de traiter des volumes importants de données. Nous exposons les concepts et les outils qui étayent cette approche, notamment l'adaptation des algorithmes Matching Pursuit et K-SVD à des dictionnaires d'atomes constitués de motifs linéairement déformables, via une propriété d'adjonction. Nous présentons également des résultats de séparation de signaux monocanaux dans le cadre proposé.

Approved for public release, distribution is unlimited / This study continues a previous face recognition investigation using uncooled infrared technology. The database developed in an earlier study is further expanded to include 50 volunteers with 30 facial images from each subject. The automatic image reduction method reduces the pixel size of each image from 160 120 to 60 45 . The study reexamines two linear classification methods: the Principal Component Analysis (PCA) and Fisher Linear Discriminant Analysis (LDA). Both PCA and LDA apply eigenvectors and eigenvalues concepts. In addition, the Singular Value Decomposition based Snapshot method is applied to decrease the computational load. The K-fold Cross Validation is applied to estimate classification performances. Results indicate that the best PCA-based method (using all eigenvectors) produces an average classification performance equal to 79.22%. Incorporated with PCA for dimension reduction, the LDA-based method achieves 94.58% accuracy in average classification performance. Additional testing on unfocused images produces no significant impact on the overall classification performance. Overall results again confirm uncooled IR imaging can be used to identify individual subjects in a constrained indoor environment. / Lieutenant, United States Navy

Nous proposons de construire un atlas numérique 3D contenant les caractéristiques moyennes et les variabilités de la morphologie d’un organe. Nos travaux seront appliqués particulièrement à la construction d'un atlas numérique 3D de la totalité de la cornée humaine incluant la surface antérieure et postérieure à partir des cartes topographiques fournies par le topographe Orbscan II. Nous procédons tout d'abord par normalisation de toute une population de cornées. Dans cette étape, nous nous sommes basés sur l'algorithme de recalage ICP (iterative closest point) pour aligner simultanément les surfaces antérieures et postérieures d'une population de cornée vers les surfaces antérieure et postérieure d'une cornée de référence. En effet, nous avons élaboré une variante de l'algorithme ICP adapté aux images (cartes) de cornées qui tient compte de changement d'échelle pendant le recalage et qui se base sur la recherche par voisinage via la distance euclidienne pour établir la correspondance entre les points. Après, nous avons procédé pour la construction de l'atlas cornéen par le calcul des moyennes des élévations de surfaces antérieures et postérieures recalées et leurs écarts-types associés. Une population de 100 cornées saines a été utilisée pour construire l'atlas cornéen normal. Pour visualiser l’atlas, on a eu recours à des cartes topographiques couleurs similairement à ce qu’offrent déjà les systèmes topographiques actuels. Enfin, des observations ont été réalisées sur l'atlas cornéen reflétant sa précision et permettant de développer une meilleure connaissance de l’anatomie cornéenne. / We propose to build a 3D digital atlas which contains the average characteristics and variability of the morphology of an organ. In particular our work consists in the construction of a 3D digital atlas of the entire human cornea including anterior and posterior surfaces. The atlas was built using topographies provided by the Orbscan II system. First, we normalized the given population of corneas using a variant of the ICP (iterative closest point) algorithm for shape registration to fit simultaneously the anterior and posterior surfaces with the anterior and posterior surfaces of a reference cornea. Indeed, we developed a specific algorithm for corneas topographies that considers scaling during registration and which is based on neighborhood search via the Euclidean distance to find the correspondence between points. After that, we built the corneal atlas by averaging elevations of anterior and posterior surfaces and by calculating their associated standard deviations. A population of 100 healthy corneas was used to construct the normal corneal atlas. To illustrate the atlas, we used topographic color maps like those already offered by existing topographic systems. Finally, observations were made on the corneal atlas that reflects its precision and allows to develop a better understanding of corneal anatomy.

Cette thèse doctorale aborde divers aspects méthodologiques de l’analyse de levés électromagnétiques aéroportés en domaine temporel (TDEM) pour une interprétation détaillée à finalités géologique et hydrogéologique. Ce travail s’est appuyé sur un levé réalisé dans la région de Courtenay (Nord-Est de la région Centre) caractérisée par un plateau de craie karstifié (karst des Trois Fontaines) recouvert par des argiles d’altération et des alluvions. Tout d’abord, une méthode de filtrage des données TDEM utilisant la Décomposition en Valeurs Singulières (SVD) a été développée. L’adaptation rigoureuse de cette technique aux mesures TDEM a permis de séparer avec succès les bruits, qui ont pu être cartographiés, et le « signal géologique », diminuant grandement le temps nécessaire à leur traitement. De plus, la méthode s’est avérée efficace pour obtenir, rapidement, des informations géologiques préliminaires sur la zone. Ensuite, une analyse croisée entre le modèle de résistivité obtenu en inversant les données filtrées et les forages disponibles a été effectuée. Celle-ci a mené à une amélioration de la connaissance géologique et hydrogéologique de la zone. Une figure d’ondulation, séparant deux dépôts de craie, et le réseau de failles en subsurface ont pu être imagés, apportant un cadre géologique au karst des Trois Fontaines. Enfin, une nouvelle méthode combinant l’information aux forages et les pentes issues du modèle de résistivité EM a permis d’obtenir un modèle d‟une précision inégalée du toit de la craie. L’ensemble de ces travaux fournit un cadre solide pour de futures études géo-environnementales utilisant des données TDEM aéroportées, et ce, même en zone anthropisée. / This PhD thesis addresses various methodological aspects of the analysis of airborne Time Domain ElectroMagnetic (TDEM) surveys for a detailed interpretation in geological and hydrogeological purposes. This work was based on a survey conducted in the region of Courtenay (north-east of the Région Centre, France) characterized by a plateau of karstified chalk (karst des Trois Fontaines) covered by weathering clays and alluvium. First, a TDEM data filtering method using the Singular Value Decomposition (SVD) was developed. The rigorous adaptation of this technique to TDEM data has successfully separated the noise, which was mapped, and the “geological signal”, greatly reducing the time required for processing. Furthermore, the method has proved to be effective to obtain quick preliminary geological information on the area. Then, a cross analysis between the resistivity model obtained by inverting the filtered data and the available boreholes was conducted. This has led to the improvement of the geological and hydrogeological knowledge of the area. An undulating feature, separating two chalk deposits, and a fault network were imaged in subsurface, providing a geological framework for the Trois Fontaines karst. Finally, a new 3D modelling method combining the information at boreholes and the slopes derived from the EM resistivity model yielded an accurate model of the top of the chalk. All of this work provides a solid framework for future geo-environmental studies using airborne TDEM data, even in anthropized area.

Artificial intelligence (AI) has over the past years become a hot topic for discussion in Sweden, as the technology presents exciting unique possibilities and challenges for the country and its citizens. Coverage of AI in Swedish news media presents imagined scenarios with both current and future AI that contribute to myths about how the technology is able to radically transform life, that spring out of a central digital sublime. Through a mixed-method study of 55 newspaper items about AI from Svenska Dagbladet from 2017 to 2018, the thesis studies what evident AI myths occur in coverage and how such discourses spring out digital sublime regarding AI. A total of four AI myths are found in news media coverage that revolve around existing and future intelligent computers, robots, machines and perceptions with them. Myths and hopes and concerns with them point to digital sublime regarding AI as a force of intelligent digitization that promises to empower a sublime citizen, economy, and welfare state. Emotional values with sublime AI are understood to reflect a general Swedish techno-optimism as digital artefacts have allowed Sweden to become prosperous.