Biological signal processing can help us gain knowledge about biological complexity, as well as using this knowledge to engineer better systems. Three areas are identified as critical to understanding biology: 1) understanding DNA, 2) examining the overall biological function and 3) evaluating these systems in environmental (ie: turbulent) conditions. DNA is investigated for coding structure and redundancy, and a new tandem repeat region, an indicator of a neurodegenerative disease, is discovered. The linear algebraic framework can be used for further analysis and techniques. The work illustrates how signal processing is a tool to reverse engineer biological systems, and how our better understanding of biology can improve engineering designs. Then, the way a single-cell mobilizes in response to a chemical gradient, known as chemotaxis, is examined. Inspiration from receptor clustering in chemotaxis combined with a Hebbian learning method is shown to improve a gradient-source (chemical/thermal) localization algorithm. The algorithm is implemented, and its performance is evaluated in diffusive and turbulent environments. We then show that sensor cross-correlation can be used in solving chemical localization in difficult turbulent scenarios. This leads into future techniques which can be designed for gradient source tracking. These techniques pave the way for use of biologically-inspired sensor networks in chemical localization.

This thesis focuses on two aspects of Quantum Information Processing (QIP) and contains experimental implementation by Nuclear Magnetic Resonance (NMR) spectroscopy. The two aspects are: (i) development of novel methodologies for improved or fault tolerant QIP using longer lived states and geometric phases and (ii) implementation of certain quantum algorithms and theorems by NMR. In the first chapter a general introduction to Quantum Information Processing and its implementation using NMR as well as a description of NMR Hamiltonians and NMR relaxation using Redfield theory and magnetization modes are given. The second chapter contains a study of relaxation of Pseudo Pure States (PPS). PPS are specially prepared initial states from where computation begins. These states, being non-equilibrium states, relax with time and hence introduce error in computation. In this chapter we have studied the role of Cross-Correlations in relaxation of PPS. The third and fourth chapters, respectively report observation of cyclic and non-cyclic geometric phases. When the state of a qubit is subjected to evolution either adiabatically or non-adiabatically along the surface of the Bloch sphere, the qubit sometimes gain a phase factor apart from the dynamic phase. This is known as the Geometric phase, as it depends only on the geometry of the path of evolution. Geometric phase is used in Fault tolerant QIP. In these two chapters we have demonstrated how geometric phases of a qubit can be measured using NMR. The fifth and sixth chapters contain the implementations of “No Deletion” and “No Cloning” (quantum triplicator for partially known states) theorems. No Cloning and No Deletion theorems are closely related. The former states that an unknown quantum states can not be copied perfectly while the later states that an unknown state can not be deleted perfectly either. In these two chapters we have discussed about experimental implementation of the two theorems. The last chapter contains implementation of “Deutsch-Jozsa” algorithm in strongly dipolar coupled spin systems. Dipolar couplings being larger than the scalar couplings provide better opportunity for scaling up to larger number of qubits. However, strongly coupled systems offer few experimental challenges as well. This chapter demonstrates how a strongly coupled system can be used in NMR QIP.

Abstract The focus of this thesis is to study direction of arrival (DoA) estimation algorithms for reconfigurable leaky-wave antennas and advanced antenna arrays. Directional antennas can greatly improve the spectrum reuse, interference avoidance, and object and people localization. DoA estimation algorithms have also been shown to be useful for applications such as positioning for user tracking and location-based services in wireless local area networks (WLANs). The main goal is to develop novel DoA estimation algorithms for both advanced antenna arrays and composite right/left-handed (CRLH) leaky-wave antennas (LWAs). The thesis introduces novel modifications to existing DoA estimation algorithms and shows how these can be modified for real-time DoA estimation using both antenna types. Three modified DoA estimation algorithms for CRLH-LWAs are presented: 1) modified multiple signal classification (MUSIC), 2) power pattern cross-correlation (PPCC), and 3) adjacent power pattern ratio (APPR). Additionally, the APPR algorithm is also applied to advanced antenna arrays. The thesis also presents improvements to the modified MUSIC and APPR algorithms. The complexity of the algorithms is reduced by selecting a smaller number of received signals from different directions. The results show that the selection of the radiation patterns is very important and that the proposed algorithms can successfully estimate the DoA, even in a real-world environment. Based on the results, this thesis provides a good starting point for future research of DoA estimation algorithms to enhance the performance of future-generation wireless networks and the accuracy of localization. / Tiivistelmä Tässä väitöskirjassa tutkitaan suunnanestimointialgoritmeja uudelleen konfiguroituville vuotoaaltoantenneille (LWA, leaky wave antenna) ja kehittyneille antenniryhmille. Suuntaavilla antenneilla voidaan parantaa huomattavasti spektrin uudelleen käyttöä ja esineiden ja ihmisten sijaintipaikannusta sekä pienentää häiriöitä. Suunnanestimointialgoritmit ovat myös osoittautuneet hyödylliseksi esimerkiksi seuranta- ja sijaintipaikannuspalvelusovelluksille langattomissa lähiverkoissa. Työn päätavoite on kehittää uusia suunnanestimointialgoritmeja sekä kehittyneille antenniryhmille että vuotoaaltoantenneille (composite right/left-handed (CRLH) LWA). Työssä osoitetaan, miten olemassa olevia suunnanestimointialgoritmeja voidaan muokata uudella tavalla, jotta ne soveltuisivat molemmille antennityypeille reaaliaikaiseen suunnanestimointiin. Vuotoaaltoantennille on kehitetty kolme erilaista suunnanestimointialgoritmia: 1) muunneltu MUSIC- (multiple signal classification), 2) säteilykyvioiden tehojen ristikorrelaatio- (PPCC, power pattern cross correlation) ja 3) vierekkäisten säteilykuvioiden tehosuhdealgoritmi (APPR, adjacent power pattern ratio). APPR-algoritmia on myös käytetty kehittyneelle antenniryhmälle. Työssä esitetään myös parannuksia muunnelluille MUSIC- ja APPR-algoritmeille. Algoritmien kompleksisuutta voidaan pienentää valitsemalla vähemmän vastaanotettuja signaaleja. Tulokset osoittavat, että signaalien valinta on hyvin tärkeää ja ehdotetut algoritmit estimoivat onnistuneesti saapuvan signaalin suunnan todellisessa mittausympäristössä. Yhteenvetona voidaan sanoa, että tämä väitöstyö on hyvä lähtökohta suunnanestimointialgoritmitutkimukselle, jonka tavoitteena on parantaa tulevien sukupolvien langattomien verkkojen suorituskykyä ja paikannuksen tarkkuutta.

L'évaluation de la démarche humaine est l'une des composantes essentielles dans les soins de santé. Les systèmes à base de marqueurs avec plusieurs caméras sont largement utilisés pour faire cette analyse. Cependant, ces systèmes nécessitent généralement des équipements spécifiques à prix élevé et/ou des moyens de calcul intensif. Afin de réduire le coût de ces dispositifs, nous nous concentrons sur un système d'analyse de la marche qui utilise une seule caméra de profondeur. Le principe de notre travail est similaire aux systèmes multi-caméras, mais l'ensemble de caméras est remplacé par un seul capteur de profondeur et des miroirs. Chaque miroir dans notre configuration joue le rôle d'une caméra qui capture la scène sous un point de vue différent. Puisque nous n'utilisons qu'une seule caméra, il est ainsi possible d'éviter l'étape de synchronisation et également de réduire le coût de l'appareillage. Notre thèse peut être divisée en deux sections: reconstruction 3D et analyse de la marche. Le résultat de la première section est utilisé comme entrée de la seconde. Notre système pour la reconstruction 3D est constitué d'une caméra de profondeur et deux miroirs. Deux types de capteurs de profondeur, qui se distinguent sur la base du mécanisme d'estimation de profondeur, ont été utilisés dans nos travaux. Avec la technique de lumière structurée (SL) intégrée dans le capteur Kinect 1, nous effectuons la reconstruction 3D à partir des principes de l'optique géométrique. Pour augmenter le niveau des détails du modèle reconstruit en 3D, la Kinect 2 qui estime la profondeur par temps de vol (ToF), est ensuite utilisée pour l'acquisition d'images. Cependant, en raison de réflections multiples sur les miroirs, il se produit une distorsion de la profondeur dans notre système. Nous proposons donc une approche simple pour réduire cette distorsion avant d'appliquer les techniques d'optique géométrique pour reconstruire un nuage de points de l'objet 3D. Pour l'analyse de la démarche, nous proposons diverses alternatives centrées sur la normalité de la marche et la mesure de sa symétrie. Cela devrait être utile lors de traitements cliniques pour évaluer, par exemple, la récupération du patient après une intervention chirurgicale. Ces méthodes se composent d'approches avec ou sans modèle qui ont des inconvénients et avantages différents. Dans cette thèse, nous présentons 3 méthodes qui traitent directement les nuages de points reconstruits dans la section précédente. La première utilise la corrélation croisée des demi-corps gauche et droit pour évaluer la symétrie de la démarche, tandis que les deux autres methodes utilisent des autoencodeurs issus de l'apprentissage profond pour mesurer la normalité de la démarche. / The problem of assessing human gaits has received a great attention in the literature since gait analysis is one of key components in healthcare. Marker-based and multi-camera systems are widely employed to deal with this problem. However, such systems usually require specific equipments with high price and/or high computational cost. In order to reduce the cost of devices, we focus on a system of gait analysis which employs only one depth sensor. The principle of our work is similar to multi-camera systems, but the collection of cameras is replaced by one depth sensor and mirrors. Each mirror in our setup plays the role of a camera which captures the scene at a different viewpoint. Since we use only one camera, the step of synchronization can thus be avoided and the cost of devices is also reduced. Our studies can be separated into two categories: 3D reconstruction and gait analysis. The result of the former category is used as the input of the latter one. Our system for 3D reconstruction is built with a depth camera and two mirrors. Two types of depth sensor, which are distinguished based on the scheme of depth estimation, have been employed in our works. With the structured light (SL) technique integrated into the Kinect 1, we perform the 3D reconstruction based on geometrical optics. In order to increase the level of details of the 3D reconstructed model, the Kinect 2 with time-of-flight (ToF) depth measurement is used for image acquisition instead of the previous generation. However, due to multiple reflections on the mirrors, depth distortion occurs in our setup. We thus propose a simple approach for reducing such distortion before applying geometrical optics to reconstruct a point cloud of the 3D object. For the task of gait analysis, we propose various alternative approaches focusing on the problem of gait normality/symmetry measurement. They are expected to be useful for clinical treatments such as monitoring patient's recovery after surgery. These methods consist of model-free and model-based approaches that have different cons and pros. In this dissertation, we present 3 methods that directly process point clouds reconstructed from the previous work. The first one uses cross-correlation of left and right half-bodies to assess gait symmetry while the other ones employ deep auto-encoders to measure gait normality.

Tato práce popisuje metodu analýzy translačního pohybu užitím křížové korelace. Ukazujeme, jakým způsobem se chová funkce křížové korelace obrazů s navzájem posunutými objekty, a jak nám to umožňuje nacházet jejich vektory posunu. Pro následnou implementaci je nalezena efektivní metoda pro hledání pouze požadovaného počtu lokálních maxim funkce.

Cílem mé diplomové práce bylo navrhnout metodu analýzy retinálních sekvencí, která bude hodnotit kvalitu jednotlivých snímků. V teoretické části se také zabývám vlastnostmi retinálních sekvencí a způsobem registrace snímků z fundus kamery. V praktické části je implementována metoda hodnocení kvality snímků, která je otestována na reálných retinálních sekvencích a vyhodnocena její úspěšnost. Práce hodnotí i vliv této metody na registraci retinálních snímků.

Fluorescence correlation spectroscopy (FCS) analyzes the fluctuations in the fluorescence intensity, which is emitted from a tiny excition volume, to obtain information about the concentration, the mobility, and the molecular interactions of labeled molecules. The more advanced fluorescence cross-correlation spectroscopy (FCCS) increases the precision in the determination of fl ow velocities and binding constants compared to standard FCS. The miniaturization in biomedical and chemical engineering has been developing rapidly, propelled by the vision of a fully functional laboratory on a single chip and its use in human therapeutics, for example, as implanted drug delivery system. A key requirement to fulfill this vision is the ability to handle small fl uid volumes. Handling liquids using the electrohydrodynamical principle circumvents many of the disadvantages of other systems. The complex flow pattern in the active region of such a pump could not be resolved by common tracking techniques. In this thesis, two-focus FCCS (2f-FCCS) was used to map the flow pro file inside a micropump. The high precision of 2f-FCCS in the determination of fl ow measurements even with small fluorescent particles allowed the measurement of the flow velocities induced by electrohydrodynamic forces acting on the solvent, while excluding the effects of dielectrophoretic forces acting on larger particles. Analysis of the fl ow data indicates a fl ow pattern that consists of two vortices of different size and opposite direction of rotation. The flow pattern derived by 2f-FCCS explains the observed complex particle trajectories in the force field and the accumulation of particles in well-de fined regions above the microelectrode array. In the second part of this thesis, the mechanism of RNA interference (RNAi) was studied by dual-color FCCS in vivo. RNAi is an evolutionary conserved gene silencing mechanism, which uses short double-stranded RNA molecules, called short interfering RNAs (siRNAs), as effector molecules. Due to its speci city and simplicity, RNAi yields a great potential for a widespread therapeutic use. To broaden the therapeutic applications, the in vivo stability of siRNAs has to be improved by chemical modi cations, but some of these modi fications inhibit the gene silencing mechanism. The presented FCCS assays are very well suited to investigate the individual assembly steps of RNAi machinery with very high specifi city and sensitivity in real time and to study the cleavage activity of the activated RNAi machinery. A direct correlation between activity of the RNAi machinery and the results from the FCCS measurements could be shown. The in fluence of several chemical modi cations on the assembly and activity of the RNAi machinery was investigated with these assays. / Fluoreszenz-Korrelations-Spektroskopie (FCS) analysiert die Fluktuationen im Fluoreszenzsignal eines kleinen angeregten Volumens, um Informationen über die Konzentration, die Bewegung und die Interaktionen der markierten Moleküle zu erhalten. Die Fluoreszenz-Kreuzkorrelations-Spektroskopie (FCCS) erhöht die Genauigkeit bei der Messung von Fließgeschwindigkeiten und Bindungskonstanten im Vergleich zur Standard-FCS. Die Miniaturisierung der Biomedizin und Chemie hat sich rapide entwickelt, angetrieben von der Vision eines kompletten Labors auf einem Chip und dem Einsatz dieses in der medizinischen Therapie, zum Beispiel als implantierter Medikamentenspender. Ein Schlüsselelement zur Erfüllung dieser Vision ist der Transport von kleinsten Flüssigkeitsmengen in diesen miniaturisierten Systemen. Der Transport von Flüssigkeiten mittels des elektrohydrodynamischen Prinzips umgeht viele Nachteile von anderen Systemen, allerdings zeigt eine solche Pumpe ein kompliziertes Strömungsbild in der aktiven Region, welches sich mit herkömmlichen Methoden wie Teilchenverfolgung nicht vermessen ließ. Hier wurde Zwei-Fokus-FCCS (2f-FCCS) genutzt, um das Strömungsbild in der Pumpe zu vermessen. Die hohe Genauigkeit der 2f-FCCS bei der Bestimmung von Fließgeschwindigkeiten auch mit kleinen fluoreszierenden Teilchen ermöglichte die Messung der Fließgeschwindigkeiten, aufgrund der auf das Lösungsmittel wirkenden elektrohydrodynamischen Kräfte, unter Ausschluss der auf größere Teilchen wirkenden dielektrophoretischen Kräfte. Die Analyse der Daten ergab, dass das Strömungsbild aus zwei entgegengesetzt rotierenden unterschiedlich großen Wirbeln besteht. Dieses Strömungsbild erklärt die komplizierten Teilchenbewegungsbahnen und die Anreicherung der Teilchen in klar abgegrenzten Bereichen über den Mikroelektroden. Im zweiten Teil dieser Arbeit wurde der RNAi-Mechanismus in lebenden Zellen mittels Zwei-Farben-FCCS untersucht. RNA Interferenz (RNAi) ist ein evolutionär erhaltener Geninaktivierungsmechanismus, der kurze doppelsträngige RNA Moleküle, so genannte kurze interferierende RNAs (siRNAs), als Effektormoleküle nutzt. Die Spezifi tät und Einfachheit der RNAi hat ihr ein weites Feld in der medikamentösen Therapie geöffnet. Zur Erweiterung dieses Feldes ist es nötig die Stabilität der siRNAs im Körper mittels chemischer Modi fikationen zu erhöhen. Einige dieser Modifikationen hemmen aber den RNAi-Mechanismus. Die hier vorgestellten FCCS Experimente sind sehr gut geeignet, um die einzelnen Schritte des Zusammenbaus der RNAi Maschinerie mit hoher Empfi ndlichkeit und Spezi fität in Echtzeit zu untersuchen und die Aktivität der RNAi Maschinerie zu studieren. Es konnte ein Zusammenhang zwischen der Aktivität der RNAi Maschinerie und den Ergebnissen der FCCS Messungen hergestellt werden. Der Einfluss von verschiedenen chemischen Modikationen auf den Zusammenbau und die Aktivität der RNAi Maschinerie wurde mit diesen neuartigen Methoden untersucht.

This thesis, structured in two parts, addresses a series of problems of relevance in the field of Spatial Geodesy. The first part delves into the application of satellite gravity data to enhance our understanding of water transport dynamics. Here, we present two significant contributions. Both are based on satellite gravity data but stem from different mission concepts with distinct objectives: time-variable gravity monitoring and high-resolution, accurate static geoid modelling. First, the fundamental notions about gravity are introduced and a brief summary is made of the different gravity satellite missions throughout history, with emphasis on the GRACE/GRACE-FO and GOCE missions, whose data are the basis of this work. The first application focuses on estimating water transport and geostrophic circulation in the Southern Ocean by leveraging a GOCE geoid and altimetry data. The Volume Transport across the Antartic Circumpolar Current is analyzed and the resulsts are validated validated using the in-situ data collected during the multiple campaigns in the DP. The second application uses time-variable gravity data from the GRACE and GRACE-FO missions to estimate the water cycle in the Mediterranean and Black Sea system, a critical region for regional climate and global ocean circulation. The analysis delves into the analysis of the different components of the hydrological cycle within this region, including the water flow across the Gibraltar Strait, examining their seasonal variations, climatic patterns, and their connection with the North Atlantic Oscillation Index. The second part of the thesis is more focused on data analysis, with the objective of developing mathematical methods to estimate the cross correlation function between two time series that are both unevenly spaced spaced (the sampling is not uniform over time) and observed at unequal time scales (the set of time points for the first series is not identical to the set of time points of the second series). Such time series are frequently encountered in geodetic surveys, especially when combining data from different sources. The estimation of the the cross correlation function for these time series presents unique challenges and requires the adaptation of traditional analysis methods designed for evenly spaced and synchronized time series. The two main contributions in this context are: (i) the study of the asymptotic properties of the Guassian Kernel estimator, that is the recommended estimator for the cross correlation function when the two time series are observed at unequal time scales; (ii) an extension of the stationary bootstrap that allows to construct bootstrap-based confidence intervals for the cross correlation function for unevenly spaced time series not sampled on identical time points.

Mit der Verwendung von Sensordaten aus mehreren Quellen entsteht oft die Notwendigkeit einer Synchronisierung der entstandenen Messreihen. Ein Standardverfahren dazu ist die Kreuzkorrelation, die jedoch übereinstimmende Zeitstempel voraussetzt und empfindlich gegenüber Ausreißern reagiert. In diesem Paper wird daher ein alternativer Algorithmus für die Synchronisierung von Ereignis-basierten Zeitreihendaten vorgestellt. / With the use of sensor data from multiple sources, the need for synchronization of the resulting measurement series often arises. A standard method for this is cross-correlation, but this requires matching timestamps and is sensitive to outliers. This paper therefore presents an alternative algorithm for the synchronization of event-based time series data.

Stålindustrierna Sandvik, Sandviken och SSAB, Borlänge tillverkar billets (kvadratiska ochlångsmala stålämnen). Vid tillverkningen av billets förflyttas stålämnena stegvis i ugnensamtidigt som de hettas upp. När stålämnena når slutet av ugnen lyfts de ur av en externmaskin. För att tids- och energieffektivisera den sista etappen krävs positionsbestämning avämnena då de når slutet av ugnen. Dessa aspekter är viktiga ur en ekonomisk såväl sommiljövänlig synpunkt då induktiva ugnar använder en stor mängd energi. Tillämpningen ärtänkt att användas av stålindustrin. UWB-radarns bredbandiga karakteristisk gör den till en lämplig ersättare till dagens sensorersom kräver håltagning i ugnens valv. Det breda frekvensspektrat hos en UWB-radarmöjliggör ytmonterade enheter i kontrast till de konventionella sensorer som används idag.Underhållsstopp för rengöring av sensorhålen kan då undvikas. Arbetet började med teoretisk studie rörande UWB-teknik och radar i allmänhet. Därefterutformades testscenarion för att studera radarvågen under varierande förhållanden. Denradaruppställning som användes under testscenariorna var framåtspridande radar. Deresulterande mätningarna signalbehandlades i Matlab. Resultatet visar att det är möjligt att detektera objekt av olika dimensioner och former på olikaavstånd, med hjälp av UWB-radar. Denna metod fungerar även som ett passagelarm, vilkenkan användas inom fler områden. / The steel industries Sandvik, Sandviken and SSAB, Borlänge, produces billets (quadratic,long steel units). Billets travelling through the furnace will heat up. At the end of the furnace,the billets will require precision measurements regarding its position, due to the extractingdevice. Sensors that are used today require an unobstructed view, which is achieved by holesin the furnace walls. Maintenance is needed in order to ensure that no impurities are cloggingthe holes. The goal with this thesis is to investigate whether it is possible to detect rectangular billets byusing an UWB-radar system. The broadband characteristics of an UWB-unit makes it asuitable successor, as free sight is not a requirement. This will decrease downtown due tomaintenance and optimize the time required for billets extraction.This involves economic and environmental aspects as well, due to lower energy consumption. This will be tested by collecting radar measurements for further signal processing. The usedradar system is forward scattering radar. The work started with a theoretical study aboutUWB-technique and basics about radar. Thereafter test scenarios were designed to study howthe radar wave is affected by changing environments. The resulting measurements were latersignal processed in Matlab. This work shows that it is possible to detect billets with various dimensions, using UWBradar.The algorithm can also be used as a passage alarm, which can be used in other areasthan furnaces.