A major difficulty in the fabrication of nanostructure based electronics is the lack of effective processes capable of precisely arranging nanostructures into predefined positions. Top-down approaches introduce increased complexity and a high cost for practical industrial use, while bottom-up approaches are probabilistic in nature and do not provide precise control of nanostructure properties (i.e., number, diameter), which influence device performance. Alternatively, nanomanipulation promises specificity, precision and programmed motion and its automation may facilitate the large-scale fabrication of nanostructure based devices. This study focuses on the development of an automated contact detection algorithm which positions an end-effector in contact with a target surface without the need for additional equipment, devices or sensors. We demonstrate this algorithm as an enabling feature for automated nano-FET biosensor construction with precise control over nanowire parameters thereby reducing device-to-device variability and also potentially allowing us to optimize individual device performance.

A major difficulty in the fabrication of nanostructure based electronics is the lack of effective processes capable of precisely arranging nanostructures into predefined positions. Top-down approaches introduce increased complexity and a high cost for practical industrial use, while bottom-up approaches are probabilistic in nature and do not provide precise control of nanostructure properties (i.e., number, diameter), which influence device performance. Alternatively, nanomanipulation promises specificity, precision and programmed motion and its automation may facilitate the large-scale fabrication of nanostructure based devices. This study focuses on the development of an automated contact detection algorithm which positions an end-effector in contact with a target surface without the need for additional equipment, devices or sensors. We demonstrate this algorithm as an enabling feature for automated nano-FET biosensor construction with precise control over nanowire parameters thereby reducing device-to-device variability and also potentially allowing us to optimize individual device performance.

Contact detection algorithms are needed in different areas of science and technology. From digital games and computer graphics to high-performance simulations and robotics. These algorithms require great computational effort and are prone to become the bottlenecks of its applications, even more when this computation must be done in real-time or large-scale systems. With the popularization of GPU cards use for both science and business, it is only natural that parallel implementations for this problem arise in the scientific community. In this work the main contact detection algorithms are analyzed and a numerical experiment is performed, with the goal of finding out which algorithm has better computational performance and memory use, or if they efficiency depends on different scenario features. For performing the experiment, a parallel Discrete ElementMethod application was developed using CUDA/C++ with the main algorithms presented in literature, besides these, the author proposes and implements the Sorting Contact Detection algorithm parallelization, that hadn’t been parallelized until now. The tests have found that the parallel Sorting Contact Detection algorithm is the most efficient in all studied scenarios, achieving a good performance and a superiormemory usage than its peers. / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Algoritmos de detecção de contatos são necessários em diferentes áreas da ciência e tecnologia, de jogos digitais e computação gráfica à simulações de alto desempenho e robótica. Esses algoritmos exigem grande esforço computacional e tendem a ser os gargalos das aplicação as quais fazem parte, principalmente em sistemas de grande escala ou em tempo real. Com a popularização das placas GPUs para uso científico e comercial, é natural que surjam implementações paralelas para esse problema. Nesse trabalho os principais algoritmos de detecção de contatos para GPU são analisados e é realizado umexperimento numérico, com objetivo de descobrir qual algoritmo é o melhor emtermos de desempenho computacional e uso de memória, ou se a eficiência de cada umdepende das diferentes características do cenários. Para a realização do experimento, foi implementado em CUDA/C++ uma aplicação paralela doMétodo dos Elementos Discretos comos principais algoritmos apresentados na literatura, além desses o autor propõe e implementa a paralelização do algoritmo de detecção com ordenação e busca binária que ainda não havia sido paralelizado. Após os testes é constatado que o algoritmo com ordenação e busca é o mais eficiente para todos os cenários estudados, obtendo nos resultados um bom desempenho em tempo de execução e com uso de memória muito superior aos outros.

Ögonkontakt-sensorer skapar möjligheten att tolka användarens uppmärksamhet, vilketkan användas av system på en mängd olika vis. Dessa inkluderar att skapa nya möjligheterför människa-dator-interaktion och mäta mönster i uppmärksamhet hos individer.I den här uppsatsen gör vi ett försök till att konstruera en ögonkontakt-sensor med hjälpav en Raspberry Pi, med målet att göra den praktisk i verkliga scenarion. För att fastställaatt den är praktisk satte vi upp ett antal kriterier baserat på tidigare användning avögonkontakt-sensorer. För att möta dessa kriterier valde vi att använda en maskininlärningsmetodför att träna en klassificerare med bilder för att lära systemet att upptäcka omen användare har ögonkontakt eller ej. Vårt mål var att undersöka hur god prestanda vikunde uppnå gällande precision, hastighet och avstånd. Efter att ha testat kombinationerav fyra olika metoder för feature extraction kunde vi fastslå att den bästa övergripandeprecisionen uppnåddes genom att använda LDA-komprimering på pixeldatan från varjebild, medan PCA-komprimering var bäst när input-bilderna liknande de från träningen.När vi undersökte systemets hastighet fann vi att nedskalning av bilder hade en stor effektpå hastigheten, men detta sänkte också både precision och maximalt avstånd. Vi lyckadesminska den negativa effekten som en minskad skala hos en bild hade på precisionen, mendet maximala avståndet som sensorn fungerade på var fortfarande relativ till skalan och iförlängningen hastigheten. / Eye contact detection sensors have the possibility of inferring user attention, which can beutilized by a system in a multitude of different ways, including supporting human-computerinteraction and measuring human attention patterns. In this thesis we attempt to builda versatile eye contact sensor using a Raspberry Pi that is suited for real world practicalusage. In order to ensure practicality, we constructed a set of criteria for the system basedon previous implementations. To meet these criteria, we opted to use an appearance-basedmachine learning method where we train a classifier with training images in order to inferif users look at the camera or not. Our aim was to investigate how well we could detecteye contacts on the Raspberry Pi in terms of accuracy, speed and range. After extensivetesting on combinations of four different feature extraction methods, we found that LinearDiscriminant Analysis compression of pixel data provided the best overall accuracy, butPrincipal Component Analysis compression performed the best when tested on imagesfrom the same dataset as the training data. When investigating the speed of the system,we found that down-scaling input images had a huge effect on the speed, but also loweredthe accuracy and range. While we managed to mitigate the effects the scale had on theaccuracy, the range of the system is still relative to the scale of input images and byextension speed.

Although several studies have proven the accuracy of using a non-contact, air-coupled receiver in nonlinear ultrasonic (NLU) Rayleigh wave measurements, inconsistent results have been observed when working with narrow specimens. The objectives of this research are first, to develop a 3D numerical finite element (FE) model which predicts nonlinear ultrasonic measurements and second, to apply the validated model on the narrow waveguide to determine causes of the previously observed experimental issues. The commercial FE-solver ABAQUS is used to perform these simulations. Constitutive law and excitation source properties are adjusted to match experiments conducted, considering inherent effects of the non-contact detection, such as frequency dependent pressure wave attenuation and signal averaging. Comparison of “infinite” and narrow width simulations outlines various influences which impair the nonlinear Rayleigh wave measurements. When the wave expansion is restricted, amplitudes of the fundamental and second harmonic components decrease more significantly and the Rayleigh wavefronts show an oscillating interaction with the boundary. Because of the air-coupled receiver’s finite width, it is sensitive to these edge effects which alter the observed signal. Thus, the narrow specimen adversely affects key factors needed for consistent measurement of material nonlinearity with an air-coupled, non-contact receiver.

The distinct element method (DEM) is a useful tool in rock engineering to model jointed rock masses. To simulate a jointed rock mass realistically, the main challenge is to be able to capture its complex geometry which consists of blocks with various shapes and sizes, and to model the interactions between these blocks. The main contribution of this thesis is the development of novel algorithms in the DEM to model jointed rock masses, namely rock slicing procedures for block generation, and algorithms for contact detection between polygonal blocks in 2-D or polyhedral blocks in 3-D. These algorithms make use of convex optimisation techniques, for which there exist efficient solution procedures. They do not rely on conventional vertex-edge-face hierarchical data structures and tedious housekeeping algorithms. The algorithms have been verified against analytical and numerical solutions, as well as validated against experimental results published in the literature. Among those, the results of DEM simulations were compared against the experimental model tests and numerical simulations of jointed beams carried out by Talesnick et al. (2007) and Tsesarsky & Talesnick (2007) respectively. Emphasis was placed on modelling the stiffness of the block interfaces accurately, and this was accomplished by reinterpreting the laboratory data published by the investigators. The capabilities of the numerical tools are also examined and demonstrated in areas for which the DEM has found practical application. A substantial fraction of this thesis is devoted to illustrating how these tools can assist the engineer in designing support systems; for example, designing the length and spacing of rock bolts and the lining thickness for a tunnel. Algorithms to model rock bolt and lining support were implemented for this purpose. Interesting comparisons with elastic solutions for supported openings were obtained. Further, it is shown that the relative benefit of introducing more rock bolts or thicker lining can be evaluated using the numerical tools with the aid of an interaction diagram. In the final part of this thesis, the case history of the 1963 Vaiont rock slide in Italy is studied. The 2-D analyses led to useful insights concerning the influence of the reservoir water level, the rock mass strength and deformability, and the slide surface shear stiffness. 3-D analyses were undertaken to investigate the influence of the eastern boundary of the slope, and interesting insights were obtained concerning the slope kinematics. Overall, the case study shows that the tools are capable of modelling problems with specific physical and geometrical detail in both 2-D and 3-D.

This thesis deals with the study of contactless and non-invasive methods for estimating heart and respiratory rate. Non-contact measurement involves sensing persons by using camera and the values of the physiological parameters are then assessed from the sets of image sequences by using suitable approaches. The theoretical part is devoted to description of the various methods and their implementation. The practical part describes the design and realization of the experiment for contactless detection of heart and respiratory rate. The experiment was carried out on 10 volunteers with a known heart and respiratory rate, which was covered by using of a sophisticated system BIOPAC. Processing and analysis of the measured data was conducted in software environment Matlab. Finally, results from contactless detection were compared with the reference from measurement system BIOPAC. Experiment results are statistically evaluated and discussed.

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