The goal of this thesis is to demonstrate practical application of sparse data representation in the processing of sparse signals. For solving several example problems - denoising, dequantization, and sparse signal decomposition - convex optimization was used. The solutions were implemented in the Matlab environment. For each of the problems, there are two solutions - one for one-dimensional, and one for two-dimensional signal.

The design solution for angle selector attachment is developed and carry forward based on initial case study done by KTH Södertäjle students. This project is carried out to find the answers for few questions viz. potential concept design solution, considering the requirements given by Scania that needs to be fulfilled. The work is divided into sub-categories; Concept generation, Concept evaluation, Manufacturing of prototype and Testing. The existing tool solution data is used to compare results with new design while testing and analysing the results. The results show that with the help of new design, it is possible to achieve seamless rotation, locking with I/O signal, can hold torque up to 200 Nm and safety measures are also taken into account. So based on this, new proposition to change the way of tightening with angle selector is given in truck assembly line. / Konstruktionslösningen för ett rotationsvinkelfäste har tagits fram för ett koncept som tidigare har utvecklats i ett studentprojekt vid KTH Södertäjle. Detta projekt har undersökt potentialen hos det föreslagna konceptet och vidareutvecklat det i enlighet med Scanias krav. Arbetet har utförts enligt en vida accepterad systematisk konstruktionsprocess, bestående av följande arbetssekvens; Formulering av systemkrav, Konceptgenerering, Konceptutvärdering och –val, Dimensionering av valt koncept, Prototyptillverkning och Provning (verifiering). Den konstruktionslösning som utvecklats jämförs sedan med den lösning som används på dagens monteringslina. Resultatanalysen visar att den nya lösning, som tagits fram i detta project, möjliggör steglös rotation, och genom låsning med I/O-signal är det möjligt att hantera ett vridmoment på 200 Nm, med bibehållen säkerhet för operatören. Det framtagna rotationsvinkelfästet föreslås att införas på monteringslinan för lastbilar.

This thesis describes three readout formats for molecular analyses. A common feature in all works is probing techniques that upon specific target recognition ideally results in equimolar amounts of DNA circles. These are then specifically amplified and detected using any of the techniques presented herein. The first paper presents a method that enables homogeneous digital detection and enumeration of biomolecules, represented as fluorescence-labelled DNA macromolecules. This method offers precise measurements to be performed with a wide linear dynamic range. As an application, two closely related bacterial species were selectively detected. The second paper further investigates and optimizes the properties of the technique presented in paper one. The third paper demonstrates a platform that enables simultaneous quantitative analysis of large numbers of biomolecules. The array format and decoding scheme together propose a digital strategy for decoding of biomolecules. The array and the decoding procedure were characterized and evaluated for gene copy-number measurements. The fourth paper examines a new strategy for non-optical measurements of biomolecules. Characteristics of this technique are investigated, and compared to its optical equivalent, fluorescence polarization.

Various commercial software packages are available for simulating compressed air network operations. However, none of these software packages are able to dynamically prioritise compressor selection on large compressed air networks in the mining industry. In this dissertation, a dynamic compressor selector (DCS) will be developed that will actively and continuously monitor system demand. The software will ensure that the most suitable compressors, based on efficiency and position in the compressed air network, are always in operation. The study will be conducted at a platinum mine. Compressed air flow and pressure requirements will be maintained without compromising mine safety procedures. Significant energy savings will be realised. DCS will receive shaft pressure profiles from each of the shafts’ surface compressed air control valves. These parameters will be used to calculate and predict the compressed air demand. All pipe friction losses and leaks will be taken into account to determine the end-point pressure losses at different flow rates. DCS will then prioritise the compressors of the compressed air network based on the overall system requirement. This software combines the benefits of supply-side and demand-side management. Potential energy savings with DCS were proven and compressor cycling reduced. A DCS user-friendly interface was created to easily set up any mine’s compressed air network. / Thesis (MIng (Mechanical Engineering))--North-West University, Potchefstroom Campus, 2013

Various commercial software packages are available for simulating compressed air network operations. However, none of these software packages are able to dynamically prioritise compressor selection on large compressed air networks in the mining industry. In this dissertation, a dynamic compressor selector (DCS) will be developed that will actively and continuously monitor system demand. The software will ensure that the most suitable compressors, based on efficiency and position in the compressed air network, are always in operation. The study will be conducted at a platinum mine. Compressed air flow and pressure requirements will be maintained without compromising mine safety procedures. Significant energy savings will be realised. DCS will receive shaft pressure profiles from each of the shafts’ surface compressed air control valves. These parameters will be used to calculate and predict the compressed air demand. All pipe friction losses and leaks will be taken into account to determine the end-point pressure losses at different flow rates. DCS will then prioritise the compressors of the compressed air network based on the overall system requirement. This software combines the benefits of supply-side and demand-side management. Potential energy savings with DCS were proven and compressor cycling reduced. A DCS user-friendly interface was created to easily set up any mine’s compressed air network. / Thesis (MIng (Mechanical Engineering))--North-West University, Potchefstroom Campus, 2013

Les applications récentes telles que les bases de données forestières impliquent des observations de données spatiales associées à l'observation de nombreuses covariables spatiales. Nous considérons dans cette thèse le problème de l'estimation d'une forme paramétrique de la fonction d'intensité dans un tel contexte. Cette thèse développe les procédures de sélection des variables et donne des garanties quant à leur validité. En particulier, nous proposons deux approches différentes pour la sélection de variables : les méthodes de type lasso et les procédures de type Sélecteur de Dantzig. Pour les méthodes envisageant les techniques de type lasso, nous dérivons les propriétés asymptotiques des estimations obtenues par les fontions d'estimation dérivées par les vraisemblances de la Poisson et de la régression logistique pénalisées par une grande classe de pénalités. Nous prouvons que les estimations obtenues par de ces procédures satisfont la consistance, sparsité et la normalité asymptotique. Pour la partie sélecteur de Dantzig, nous développons une version modifiée du sélecteur de Dantzig, que nous appelons le sélecteur Dantzig linéaire adaptatif (ALDS), pour obtenir les estimations d'intensité. Plus précisément, les estimations ALDS sont définies comme la solution à un problème d'optimisation qui minimise la somme des coefficients des estimations soumises à une approximation linéaire du vecteur score comme une contrainte. Nous constatons que les estimations obtenues par de ces méthodes ont des propriétés asymptotiques semblables à celles proposées précédemment à l'aide de méthode régularisation du lasso adaptatif. Nous étudions les aspects computationnels des méthodes développées en utilisant les procédures de type lasso et de type Sélector Dantzig. Nous établissons des liens entre l'estimation de l'intensité des processus ponctuels spatiaux et les modèles linéaires généralisés (GLM), donc nous n'avons qu'à traiter les procédures de la sélection des variables pour les GLM. Ainsi, des procédures de calcul plus faciles sont implémentées et un algorithme informatique rapide est proposé. Des études de simulation sont menées pour évaluer les performances des échantillons finis des estimations de chacune des deux approches proposées. Enfin, nos méthodes sont appliquées pour modéliser les emplacements spatiaux, une espèce d'arbre dans la forêt observée avec un grand nombre de facteurs environnementaux. / Recent applications such as forestry datasets involve the observations of spatial point pattern data combined with the observation of many spatial covariates. We consider in this thesis the problem of estimating a parametric form of the intensity function in such a context. This thesis develops feature selection procedures and gives some guarantees on their validity. In particular, we propose two different feature selection approaches: the lasso-type methods and the Dantzig selector-type procedures. For the methods considering lasso-type techniques, we derive asymptotic properties of the estimates obtained from estimating functions derived from Poisson and logistic regression likelihoods penalized by a large class of penalties. We prove that the estimates obtained from such procedures satisfy consistency, sparsity, and asymptotic normality. For the Dantzig selector part, we develop a modified version of the Dantzig selector, which we call the adaptive linearized Dantzig selector (ALDS), to obtain the intensity estimates. More precisely, the ALDS estimates are defined as the solution to an optimization problem which minimizes the sum of coefficients of the estimates subject to linear approximation of the score vector as a constraint. We find that the estimates obtained from such methods have asymptotic properties similar to the ones proposed previously using an adaptive lasso regularization term. We investigate the computational aspects of the methods developped using either lasso-type procedures or the Dantzig selector-type approaches. We make links between spatial point processes intensity estimation and generalized linear models (GLMs), so we only have to deal with feature selection procedures for GLMs. Thus, easier computational procedures are implemented and computationally fast algorithm are proposed. Simulation experiments are conducted to highlight the finite sample performances of the estimates from each of two proposed approaches. Finally, our methods are applied to model the spatial locations a species of tree in the forest observed with a large number of environmental factors.

Chiral separation systems in capillary electrophoresis are in the scope of interest of many research groups all over the world. Therefore, the need to develop reliable theoretical models, which would help to explain phenomena connected with chiral separations or optimization of separation conditions, is obvious. In this thesis several mathematical models and approaches that can fulfill these requirements are presented. First part of the thesis deals with the determination of rate constants of interconversion of enantiomers by means of dynamic capillary electrophoresis. We focused on mixtures of chiral selectors and formulated a mathematical model, which enables to determine rate constants of interconversion in such systems. Mixtures of chiral selectors are very popular in separation practice due to their enhanced enantioselectivity. The theoretical model established in the thesis is able to explain the separation mechanisms of multi-chiral selector systems and to propose and verify possible ways of their optimization. In addition, the separation mechanism in systems with simultaneous cyclodextrin and borate complexation was revealed. Finally we present the complete mathematical model of electromigration in systems with complexation agents. The model is implemented into our simulation tool Simul 5...

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<div>Silicon based semiconductor technology is facing more and more challenges to continue the Moore's law due to its fundamental scaling limitations. To continue the pace of progress of device performance for both logic and memory devices, researchers are exploring new low-dimensional materials, e.g. nanowire, nanotube, graphene and hexagonal boron nitride. Transition metal dichalcogenides (TMDs) are attracted considerable attention due their atomically thin nature and proper bandgap at the initial study. Recently, more and more interesting properties are found in these materials, which will bring out more potential usefulness for electronic applications. Competing with the silicon device performance is not the only goal in the potential path finding of beyond silicon. Low-dimensional materials may have other outstanding performances as an alternative materials in many application realms. </div><div><br></div><div>This thesis explores the potential of TMD based devices in memory and logic applications. For the memory application, TMD based vertical devices are fully studied. Two-terminal vertical transition metal dichalcogenide (TMD) based memory selectors were firstly built and characterized, exhibiting better overall performance compared with some traditional selectors. Polymorphism is one of unique properties in TMD materials. 2D phase engineering in TMDs attracted great attention. While electric switching between semiconductor phase to metallic phase is the most desirable. In this thesis, electric field induced structural transition in MoTe₂ and Mo_1-xW_xTe₂ is firstly presented. Reproducible bipolar resistive random access (RRAM) behavior is observed in MoTe₂ and Mo_1-xW_xTe₂ based vertical devices. Direct confirmation of a phase transition from a 2H semiconductor to a distorted 2H_d metallic phase was obtained after applying an electric field. Set voltage is changed with flake thickness, and switching speed is less than 5 ns. Different from conventional RRAM devices based on ionic migration, the MoTe₂-based RRAMs offer intrinsically better reliability and control. In comparison to phase change memory (PCM)-based devices that operate based on a change between an amorphous and a crystalline structure, our MoTe₂-based RRAM devices allow faster switching due to a transition between two crystalline states. Moreover, utilization of atomically thin 2D materials allows for aggressive scaling and high-performance flexible electronics applications. Both of the studies shine lights on the new application in the memory field with two-dimensional materials.<br></div><div><br></div><div>For the logic application, the ultra thin body nature of TMDs allows for more aggressive scaling compared with bulk material - silicon. Two aspects of scaling properties in TMD based devices are discussed, channel length scaling and channel width scaling. A tunability of short channel effects in MoS₂ field effect transistor (FET) is reported. The electrical performance of MoS₂ flakes is governed by an unexpected dependence on the effective body thickness of the device which in turn depends on the amount of intercalated water molecules that exist in the layered structure. In particular, we observe that the doping stage of a MoS₂ FET strongly depends on the environment (air/vacuum). For the channel width scaling, the impact of edge states in three types of TMDs, metallic T_d-phase WTe₂ as well as semiconducting 2H-phase MoTe₂ and MoS₂ were explored, by patterning thin flakes into ribbons with varying channel widths. No obvious charge depletion at the edges is observed for any of these three materials, which is different from what has been observed in graphene nanoribbon devices. </div>

Nucleic acids are fundamental molecules of living organisms functioning essentially as the molecular information carriers of life. From how an organism is built to how it responds to external conditions, all of it, can be found in the form of nucleic acid sequences inside every single cell of every life form on earth. Therefore, accessing these sequences provides key information regarding the molecular identity and functional state of any living organism, this is very useful for areas like biomedicine, where accessing and understanding these molecular signatures is the key to develop strategies to understand, treat and diagnose diseases. Decades of research and technological advancements have led to the development of a number of molecular tools and engineering technologies that allow accessing the information contained in the nucleic acids. This thesis provides a general overview of the tools and technologies available for nucleic acid analysis, and proposes an illustrative concept on how molecular tools and emergent technologies can be combined in a modular fashion to design methods for addressing different biomedical questions. The studies included in this thesis, are focused on the particular use of the molecular tools named: padlock and selector probes, rolling circle amplification, and fluorescence detection of single molecules in combination with microfluidics and portable microscopy. By using this combination, it became possible to design and demonstrate novel approaches for integrated nucleic acid analysis, inexpensive digital quantification, mobile-phone based diagnostics and the description of viral infections. These studies represent a step forward towards the adoption of the selected group of tools and technologies, for the design and building of methods that can be used as powerful alternatives to conventional tools used in molecular diagnostics and virology. / <p>At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 1: Manuscript.</p>